▶ 0:24:31Committee on Financial Services will come to order. Without objection, the chair is authorized to declare a recess at any time. Today's hearing is entitled From Principles to Policy: Enabling 21st Century AI Innovation in Financial Services. Without objection, all members will have five legislative days within which to submit extraneous materials to the chair for inclusion in the record. I now recognize myself for four minutes for an opening statement.
▶ 0:24:59Advancements in artificial intelligence are not just on the horizon, they're here and they're transforming our economy. Last Congress, Congressman Bill Foster and I served on Speaker Johnson and Minority Leader Jeffrey's bipartisan Congressional AI task force. And Congressman Steve Lynch and I led this committee's AI working group.
▶ 0:25:21In both forums, we examined how financial services firms and regulators are approaching artificial intelligence, analyzing its benefits and risks in a highly regulated environment. Just this past fall, the digital assets, financial technology, and artificial intelligence subcommittee led by chairman Brian Style held a hearing where members evaluated ho how financial regulators and firms are using AI.
▶ 0:25:48Today's hearing builds on our earlier work in last Congress and this Congress and will help us further examine AI use cases in the financial and housing industries. We will also consider how agencies are providing clear regulatory environment and assess where existing laws may fall short or require modernization and explore ways to foster innovation.
▶ 0:26:14For decades, the financial services industry has pioneered the realworld application of AI and continues to be a standout leader. AI has shown its transformative transformative potential to reshape how financial institutions operate from enhancing analysis to managing risk, mitigating fraud, and importantly enhancing customer service. However, as with any innovation, risks give rise to new challenges.
▶ 0:26:43Yet, human progress is everchanging, never static, and AI represents the latest leg in this journey. To move forward, we must embrace and adapt for innovation. This was the approach taken in the 1990s by former Congressman and former SEC chairman Chris Cox.
▶ 0:27:03When Congress confronted the rapid commercialization of the internet, rather than allowing fear to stall advancement, lawmakers adopted existing laws to fit the new technological era.
▶ 0:27:19Congress established clear guidelines and principles early on, setting the stage for the rapid growth of the internet, enabling countless innovations and entire industries, and putting the United States at the forefront of that innovation and the internet's expansion. Just as Congress navigated the uncertainties of the internet in the mid 1990s, we must view AI as a an opportunity, not a threat.
▶ 0:27:45applying lessons of that era in order to confront today's technological landscape. Identifying gaps and obstacles in our regulatory frameworks will help Congress create an AI landscape where innovation can flourish without unnecessary barriers while ensuring robust consumer protections and riskbased technological technology neutral regulations.
▶ 0:28:11The committee is steadfast in its commitment to empowering US firms to leverage AI's potential and drive the US global leadership in adoption and innovation. I thank all of our witnesses for joining us today and providing your valuable insights and perspectives and I yield back. It's now my pleasure to recognize the ranking member of the committee, Mrs. Waters, for four minutes for an opening statement.
▶ 0:28:34Uh, thank you very much, Mr. Chairman. AI is already embedding in the lives of millions of Americans, and we have a duty to ensure that it benefits society, not harms it. Unfortunately, Republicans have been complicit as Donald Trump bypasses Congress, directs federal agencies to deploy biased AI with no safeguards, and now issuing an executive order that seeks to undermine all state
▶ 0:29:06Republicans in Congress failed to acknowledge that despite all the benefits that AI may bring, it also poses challenges that demand our full attention. We're already seeing AI systems that hurt children, spread hate and discrimination, and amplify systemic risk in the financial system. As unemployment reaches new heights, reports continue to show AI replacing workers across industries.
▶ 0:29:35That's why the Biden administration put in critical protections to ensure AI systems are transparent, explainable, and These are just basic safeguards to keep families and children safe.
▶ 0:29:51In some of the worst cases, chat boxes have encouraged self harm like suicide, carried out sexually explicit conversations, and even provided dangerous misinformation and disinformation to minors. But no one should be surprised that the same president who calls affordability a hoax is ignoring uh these very real concerns with AI.
▶ 0:30:17Since twice this year, the White House and congressional Republicans have tried and failed to impose a moratorum on state AI laws. And now, despite those failures, Trump announced he would sign an executive order that would block states from adopting their own AI safeguards by threatening legal challenges and withholding federal funding.
▶ 0:30:43And for this hearing, Republicans posed a bill, posted a bill uh that would give AI and its big tech creators a pass when they violate consumer, housing, banking, or securities laws. Democrats are not going to sit by and watch Trump and Republicans allow big tech to forcibly experiment on our communities.
▶ 0:31:08any legislative efforts that Congress must ensure that consumers and investors understand the AI they are interacting with in the financial services space while giving companies meaningful standards they can innovate under a partisan approach is not necessary if Republicans fight for their constituencies.
▶ 0:31:34Last Congress, I and then Chair Mck Henry launched the first ever bipartisan AI task force. We held joint sessions, conducted oversight, and introduced bills to confront AI bias, deep fake scams, and discrimination, proving that innovation and oversight can go hand in hand. Democrats are leading these efforts because we believe in responsible innovation.
▶ 0:32:03The stakes are too high, the risks are too great, and the consequences too real to hand this technology over to big tech billionaires with no guard rails, no accountability. Thank you. And I yield back the balance of my time.
▶ 0:32:20Gentleoman yields back. Now recognize the chair of the subcommittee on digital assets, financial technology, and artificial intelligence, Mr. Style, Wisconsin, for one minute for an opening
▶ 0:32:30Thank you very much, Mr. Chairman. The US must win the global AI race and the regulations that we may make here are incredibly consequential. We can't get it wrong. Some have. For example, the EU AI act is a broad horizontal approach that stifles innovation in Europe. In the US, I believe we should take a targeted activityspecific approach to AI.
▶ 0:32:53As we examine use cases and those who develop and deploy AI today, we should examine if our rules need adjustments and tweaks to get this right. These use cases will only continue to evolve as generative and agentic AI technologies evolve. We must make sure we unlock innovation while pro while while protecting Americans. As the United States strives to win the AI global race, maintaining a try first approach will help preserve American dominance and agility.
▶ 0:33:24Let's win this race. I yield back.
▶ 0:33:27Gentleman yields back. I recognize the ranking member of the subcommittee on digital assets, financial technology, and AI, Mr. Lynch, for one minute for an opening statement.
▶ 0:33:35Uh, good morning. Thank you, Mr. chairman and ranking member Waters for holding this hearing to continue examining AI innovation and regulation in the financial services sector. I also want to thank our panel of witnesses uh for helping the committee with its work. Uh last Congress, I was proud to co-lead our bipartisan AI working group with my friend Chairman Hill to examine the benefits and risks of deploying AI technologies in banking, housing, credit lending, and other areas.
▶ 0:34:01uh these findings should continue to to guide us as we pursue effective and responsible AI regulation. However, as ranking member of the subcommittee on digital assets, financial technology, and artificial intelligence in this Congress, I'm concerned that some of the regulations uh regulated regulatory proposals before us committee, this committee not only failed to include adequate guardrails, but they also invite the financial services industry in adopting AI to choose which consumer protection and
▶ 0:34:32investor protection and safety and soundness regulations that they would like to avoid. um with which is reckless and dangerous. In closing, I look forward to working with my colleagues to develop bipartisan AI legislation that promotes innovation while ensuring robust consumer and financial protection. I yield back the balance of my time.
▶ 0:34:51Gentleman yields back. Today, we welcome the testimony of Janette Manfra, vice president, global head of risk and compliance at Google Cloud. Tall Cohen, president of NASDAQ, Nicholas Stevens, the vice president of product and senior developer of AI and engineering at Zillow, Wendy Whitmore, chief security intelligence officer at Palo Alto Networks, and Joshua Branch, big tech accountability advocate at Public Citizen. We thank each of you for taking time to be with us.
▶ 0:35:19Each of you will be recognized for five minutes to give an oral presentation of your testimony. Without objection, your written statements will be made part of our record. Mrs. Manfrob will start with you. You're recognized for five minutes for your oral remarks.
▶ 0:35:34Chairman Hill, Ranking Member Waters, and distinguished members of the committee. Thank you for the opportunity to appear before you today. My name is Janette Manfro and I'm the vice president of risk and compliance at Google Cloud. We appreciate the House Committee on Financial Services holding this important hearing and we look forward to sharing Google's perspective on the opportunity that artificial intelligence provides to America's financial sector.
▶ 0:35:58Google believes that the introduction of AI in the financial services sector promises to usher in a transformative era for quality, accessibility, efficiency, and compliance in financial markets and services. AI offers many benefits, including the potential to enhance individual productivity, strengthen security operations, and drive database decision-making and operational efficiencies. These improvements will benefit institutions of all sizes, including small and medium-sized financial entities.
▶ 0:36:28At the same time, we also recognize that AI introduces risks that must be managed and mitigated. We believe that existing risk management frameworks and established governance practices can be applied to manage risks in the AI context. For more than a decade, Google has used advancements in AI to further protect people from online scams where malicious actors deceive users to gain access to money, personal information, or both.
▶ 0:36:53We offer a wide variety of protections powered by AI, including using Google Cloud's anti-moneylaundering AI service for financial sector customer risk scoring, utilizing AI powered scam detection systems in search, an Android ecosystem that automatically identifies and blocks fishing messages and scam calls, and our efforts to ensure the integrity of Google ads on our platforms.
▶ 0:37:17Additionally, Google further disincentivizes this malicious behavior by proactively filing litigation to dismantle massive fraud operations. In a recent example, in November 2025, we announced our filing to dismantle Lighthouse, a massive fishing as a service operation. Bad actors built Lighthouse as a fishing as a service kit to generate and deploy massive SMS fishing attacks. These attacks exploit established brands like Easyypass to steal people's financial information.
▶ 0:37:44Our legal action is designed to dismantle the core infrastructure of this operation. We recognize that Google must work with industry participants, regulatory bodies, and technology providers to counter the critical threats posed by scams and frauds. And we are leading cross-industry efforts in combating fraud and scams.
▶ 0:38:01In response, we have introduced the agent payments pro protocol or AP2, an open-source protocol collaboratively developed with over 60 partners, including financial and technology companies like American Express, Mastercard, and PayPal. AP2 aims to standardize and secure transactions made by AI agents on behalf of users, addressing key challenges such as authorization, authenticity, and accountability. This is an important step, and I look forward to discussing this with the committee.
▶ 0:38:30We at Google have also introduced the secure AI framework or safe a conceptual framework for secure AI systems including those in the financial sector and we have recently published an extension of the safe risk map to address the core operational components of Agentic systems and their related risks and controls. In addition, we partnered with Amazon, Microsoft, IBM, Nvidia, and many others to co-found the Coalition for Secure AI.
▶ 0:38:55This is an open-source initiative to help all developers and deployers of AI create and maintain secure by design AI systems and help advance the safe framework. We recognize that we alone cannot solve these challenges. We've recently announced our endorsement of key bipartisan bills in Congress, crucial bills that we believe will help bring a decisive end to the financial harm and damage wrought by foreign cyber criminals.
▶ 0:39:18As the world focuses on the potential of AI and governments and industry work on a regulatory approach to ensure AI is safe and secure, we believe that AI represents an inflection point for digital security. Regulators should support the development of global standards and their use across the financial services and regulatory landscape. In addition, regulators should foster industry collaboration and training based on such standards. In closing, thank you for convening this really important hearing.
▶ 0:39:45We look forward to continuing to further raise awareness about cyber security threats and defenses for the financial sector and beyond.
▶ 0:39:52Thank you very much. Mr. Cohen, you're now recognized for five minutes for your
▶ 0:39:58Thank you, Chairman Hill, Ranking Member Waters, and members of the committee. Thank you for the opportunity to testify on the impact of artificial intelligence on our financial system and the role of responsible innovation. My name is Tyler Cohen, and I serve as president of NASDAQ. At NASDAQ, we aspire to be the trusted fabric of the global financial markets, connecting entrepreneurs and investors, fueling economic growth, fighting financial crime, and supporting millions of everyday savers and retirees.
▶ 0:40:24As a global technology provider and an operator of regulated markets, we have a unique perspective that shapes how we employ AI. Our approach centers on three core principles. Enhancing liquidity, ensuring transparency, and protecting integrity. AI is already making a measurable difference across all three of these within our solutions. And I'm going to start with financial crime where the human cost is greatest.
▶ 0:40:49In 2023, an estimated 3.1 trillion in illicit funds flowed through the global financial system and scam and bank frauds caused roughly 485 billion in losses worldwide. Behind these numbers are family losing savings, communities hard harmed by drug trafficking, human trafficking, and terrorism financing. NASDAQ's cloudnative AI enabled anti-inancial crime platform Verafin is used by thousands of financial institutions to detect and prevent these crimes.
▶ 0:41:18Verifin analyzes vast data sets across its network to identify suspicious activity in ways no single institution could do otherwise. This work went a step further with the launch of our agentic AI workforce. Our digital sanctions analyst has reduced the alert review workload for sanctioned screening by more than 80%. Freeing compliance professionals to focus on complex judgment heavy issues while AI handles routine tasks. AI also strengthens market integrity.
▶ 0:41:48Our surveillance platform uses machine learning to help exchanges and regulators detect insider trading across billions of daily transactions, rooting out market abuse that erodess investor confidence. These achievements are only possible if you have the right governance and the right oversight in place. From the outset, NASDAQ established an enterprisewide AI governance program aligned with the NIST AI risk management framework overseen by an executive steering committee that includes our CEO.
▶ 0:42:16We also implemented a cross functional governance committee led by legal risk regulatory and technology teams. Additionally, we had adopted responsible AI principles covering transparency, fairness, privacy, reliability, and accountability and we applied it across all products and internal operations. And that brings me to the AI AI policy consideration before this committee. The US has historic opportunity to lead in AI if we strike the right balance.
▶ 0:42:46From our perspective, the following principles are critical. First, leverage existing regulatory frameworks. The financial sector is already heavily supervised. Many AI related risks can be addressed with existing rules and mandates. Second, focus on use cases and outcomes. Regulation should reflect risk profiles. An AI tool detecting drug trafficking or protecting seniors from fraud should be subject to higher standards than when that same tool is used to approve apartment rentals.
▶ 0:43:15They carry different risk profiles and require different regulatory treatment. Third, keep frameworks flexible and innovation friendly. Overly prescriptive rules tend to age poorly and risk pushing innovation overseas. We support sandboxes, pilots, and AI centers of excellence where regulators and industry can learn and work together. Fourth, strive for harmonization. A patchwork of state level AI laws creates uncertainty, raises costs, and can limit access to these tools.
▶ 0:43:44Federal coordination is the best way to protect investors while preserving US competitiveness. Applying these principles will ensure that AI is working to make our financial systems more fair, more efficient, and more And that's the future we're working towards in NASDAQ and why we're grateful for the committee's leadership on these issues.
▶ 0:44:04In closing, we support the administration's America's AI action plan and bipartisan effort in Congress to address harms such as nonconsentual deep fakes and synthetic media while preserving space for innovation. Thank you again for the opportunity to testify today and I look forward to your
▶ 0:44:21Thank you, sir. Mr. Stevens, you're recognized for five minutes for your oral presentation.
▶ 0:44:29Chairman Hill, Ranking Member Waters, and members of the committee. Thank you for the opportunity to testify today. My name is Nicholas Stevens and I serve as vice president of product artificial intelligence of Zillow. Our mission is to help people navigate one of the most meaningful and complex decisions of their lives, finding a home. After nine years at Zillow improving the housing journey, I recently had the chance to live it again. My family just moved. At the end of the process, my five and seven-year-olds couldn't sleep.
▶ 0:44:59They were up at 3:00 a.m. and when my wife and I sat them down to ask what on earth was troubling them, they had two very nervous questions. A, are we bringing our cat Lily to the new home? B, are we also bringing the TV? I'm happy to report that both have made it safely to our new home. But everything in between, the search, the paperwork, the financing, the closing, was a reminder of how emotional and confusing this process can be.
▶ 0:45:28That is the friction we are trying to address with responsible Zillow has been applying AI to housing for nearly two decades. Starting with this estimate, one of the first largecale consumer uses of machine learning in real estate. It is not an appraisal or used for credit decisions. Rather, it empowers buyers and sellers with a ballpark estimate of home value.
▶ 0:45:50This estimate was so popular it crashed our site because consumers were asking for information that has historically been available only to a select few. Today 250 million unique users come to Zillow every month to dream, to rent, to tour, finance, buy, and sell their homes. And with that scale comes real Our products can't just be clever. They have to be reliable, fair, and trust affirming.
▶ 0:46:19Since Zillow last appeared before this committee, next generation AI has moved from pilot to production. AI and real estate is not theoretical. It powers tools people are using today. And I'll highlight a few examples. We've built in AI to be a true assistant to real estate agents nationwide. It helps prioritize an agents leads. It summarizes notes. It drafts emails. And one of the agents favorite features is that it suggests key topics to touch on in their client's catchup call.
▶ 0:46:48technology also allowed our company to go fully remote and we now have employees in all 50 states. Our latest computer vision experiences allow you to not only generate a home's floor plan so potential buyers can explore the inside and detail, we also let them fly around and get a sense of the exterior and yard. The through line is that safeguards are built in, not bolted on.
▶ 0:47:12Internally, Zillow employees complete fair housing and privacy training, and anyone working with AI receives additional responsible AI training. Before we launch an AI feature, cross functional teams conduct a model risk review focused on fairness, bias, privacy, and explanability. After launch, we perform periodic audits and continuous monitoring so we can catch issues that only appear at scale. And externally, this is even true with public partnerships.
▶ 0:47:40Now consumers can talk to Zillow directly inside Chat GPT's new inapp experience, asking, for example, Zillow, show me two-bedroom homes that are wheelchair accessible. And in return, they get listings, photos, and maps from Zillow in a conversational flow. We built this with a fair housing first design. Our fair housing classifier helps detect and prevent potential digital steering. We also believe responsible innovation means raising the floor for everyone.
▶ 0:48:10Zillow open sourced that same fair housing classifier under a permissive license and it is now in use by real estate platforms and researchers working to combat housing discrimination. That is a concrete example of innovation and compliance rowing in the same All of this argues for a rightsiz national framework for AI in financial services including housing.
▶ 0:48:34A coherent national baseline for fairness, transparency, privacy, and accountability would give consumers consistent safeguards and give companies the confidence to integrate strong protections from day one. The alternative is a patchwork where the same consumer gets different quality experiences across state lines for the same transaction. Even the latest AI technology wouldn't have prompted me to explain to my kids that yes, both our cat and the TV would be coming to our next home.
▶ 0:49:03But it can help tackle the structural challenges we all worry about. Affordability, supply, and outdated processes. As you consider a national framework for AI and modernization of our housing finance system, we stand ready to share data, technical expertise, and lessons from building these systems at scale. We appreciate the committee's leadership on this issue, and I look forward to answering your questions.
▶ 0:49:28Thank you very much. Miss Whitmore, you're now recognized for five minutes for your oral testimony. Good morning, Chairman Hill, Ranking Member Waters, and distinguished members of the committee. Thank you for the opportunity to testify. My name is Wendy Whitmore, and I'm the chief security intelligence officer at PaloAlto Networks.
▶ 0:49:45We are an American cyber security company protecting more than 75,000 organizations in over 150 countries including 97 of the Fortune 100, eight of the 10 largest banks, the US federal government and critical infrastructure operators. The promise of AI for financial services is undeniable and realizing it requires the sector to simultaneously embrace AI for cyber security and cyber security for AI.
▶ 0:50:15There is both urgency and opportunity for financial institutions to lead. The threat landscape is evolving as advanced AI and quantum computing reshape both innovation and risk. Attacks are faster, more automated, and harder to detect. Time from compromise to data exfiltration is now 100 times faster than four years ago. And attackers are increasingly excfiltrating data within one hour.
▶ 0:50:43Generative and agentic AI now supercharge every phase of the kill chain enabling deep fake driven fraud, know your customer evasion via face swapping, and tailored spear fishing, imitating trusted financial institutions. Our own research shows that Agentic AI can compress a multi-day ransomware operation into only 25 minutes from reconnaissance to compromise to data theft. This reality underscores why the financial sector must do two things.
▶ 0:51:14One, adopt AIdriven security operations that operate at machine speed and two, harden their AI ecosystems with a secure by design approach. Today's security operations centers known as SOCKS are drowning in fragmented data and alerts from an average of 83 security solutions, forcing skilled analysts into inefficient manual triage.
▶ 0:51:39Consequently, critical alerts are buried with 75% of breaches having actionable logging that was never reviewed, leaving vulnerabilities exposed and degrading our core ability to rapidly detect and respond to threats. AIdriven socks flip this paradigm acting as a force multiplier for cyber professionals that substantially reduces detection and response times. The results of deploying AI in our own sock are transformative.
▶ 0:52:08We ingest roughly 90 billion events every day. By leveraging AI, we reduce those to only 26,000 alerts, ultimately resulting in one single incident requiring manual investigation.
▶ 0:52:22In financial institutions deploying AIdriven socks, we see four times more security data ingested into a consolidated platform, thousands of models providing real-time prevention and detection, automation cutting analyst workload by three quarters, and the meanantime to respond falling by up to 90%. In one global financial markets utility, their meanantime to respond fell from 24 hours to 14 minutes.
▶ 0:52:49Another large bank saved more than a thousand analyst hours annually while improving threat hunting and reducing attrition. AI adoption is integral to America's innovation leadership which is why Palo Alto Networks was proud to support America's AI action plan which recognized that the benefits of AI will stall if we do not secure AI itself. Attacks against AI systems have fundamentally evolved beyond traditional cyber security considerations.
▶ 0:53:18They target how systems learn and how they reason. The answer to accelerate AI innovation is to embed security throughout the AI life cycle so that we can adopt AI tools confidently. Secure AI by design provides the blueprint to integrate security from development through deployment and use ensuring visibility control and protection at enterprise scale.
▶ 0:53:42Practically that means discovering discovering and governing external AI tools including shadow AI, securing AI infrastructure and data, monitoring and controlling AI agents, and safely building and deploying AI applications. Building an AI ready ecosystem is a team effort.
▶ 0:54:04As an FSISAC sector adviser and a participant in the cyber risk institute innovator program, PaloAlto Networks helps align best practices with leading standards and reduce compliance friction for financial institutions. If we secure the future now through AIdriven defense and secure AI by design, we can unleash the full potential of AI innovation while protecting consumers, markets, and national security. Thank you for the opportunity to testify.
▶ 0:54:33I look forward to your questions.
▶ 0:54:35Thank you very much. Mr. Branch, you're now recognized for five minutes for an oral presentation of your testimony.
▶ 0:54:42Thank you, Chairman Hill, Ranking Member Waters, and members of the committee. My name is JB Branch. I'm an artificial intelligence policy expert at Public Citizen, a nonprofit with more than 1 million members and supporters across the country. Each day we fight for everyday Americans by defending democracy, resisting corruption, and challenging corporate greed.
▶ 0:55:03I'm here today to talk about the difference between responsible AI innovation and the current reckless push by big tech to undermine state laws, weaken consumer protection, and place all of us at the mercy of a handful of AI billionaires. For decades, the default posture towards regulating new technology has been deference to industry. Congress deferred to the expertise of social media companies and we now live with the consequences including rampant misinformation and harms for children.
▶ 0:55:34We cannot make the same mistake with AI. The scale, speed, and autonomy of AI creates risks far beyond previous technology. The good news is that most AI regulations are rooted in common sense. Algorithms should not discriminate. Companies should be held accountable for harm. Non-consensual deep fake pornography is a devastating crime. These are American values. And Americans agree.
▶ 0:56:01A Galllet poll shows 97% of Americans agree that AI should be subject to regulation. 97%. States across the country have responded with bipartisan common sense safeguards that reflect this democratic will in Yet, instead of respecting that will, we have seen relentless attempts to override it. Over summer, some in Congress attempted to strip all state AI laws.
▶ 0:56:27Even worse, they tried to slip the proposals into the mustpass National Defense Authorization Act. Big tech tried to use our national security as leverage to avoid accountability. What was once called a moratorum is now being repackaged as a sandbox. These are all in the same deregulation schemes designed to invalidate all existing safeguards. And the hypocrisy is striking. Big tech is attacking many of the state-based AI laws they helped to write.
▶ 0:56:58They praise those laws locally while lobbying to destroy them I'm equally alarmed by President Trump referring to basic protections as dangerous ideology. Several of the administration's policy priorities target civil rights principles and AI, but fairness in AI simply means preventing discrimination, sexism, and While the Trump administration bashes equality as a dangerous ideology, it has simultaneously entered a federal contract with Elon Musk's Grock,
▶ 0:57:29an AI system that OSTP Director Katzios testified violated the administration's own principles. Grock's behavior is well documented. Racist slurs, sexism, and even referring to itself as Mecca Hitler. Is this the type of AI we want deployed throughout the US federal government? I also want to speak about the impact AI will have on workers and rural communities like the one I was raised in in central Pennsylvania. These communities know what broken promises feel like.
▶ 0:57:59We remember when steel mills closed and new jobs didn't come. Now big tech companies are telling us that data centers and AI will be salvation. And we've heard this before. So let me be clear. Data centers are at the bottom of the tech stack. They receive major tax breaks while local communities foot the bill and most employ fewer people than a single Walmart. They do not replace the jobs that communities have lost. This is another extraction model.
▶ 0:58:29I want to offer simple guiding principles. Responsible innovation requires enforcable accountability. Public citizen respectfully submits that the better path forward is not a mystery. Reject blanket preeemption and deregulatory sandboxes allowing states to respond to evolving harm. Require transparency. Companies must be able to explain how their AI systems work and how decisions are made. When AI systems cause harm, companies must be held accountable.
▶ 0:58:59Invest in regulatory enforcement. Laws mean nothing if they cannot be enforced. Congress must ensure regulators have the staff, the authority, and the resources to do their We all share the same goal. A strong middle class and leadership in responsible AI. Leadership means protecting workers, children, and democracy. At the same time, we foster innovation. This is a defining moment. It's a test of who governs America, the people, or the most powerful corporations on Earth.
▶ 0:59:30Public Citizen urges Congress to stand up to big tech, reject backdoor deregulation, and deliver real enforcable guard rails. Thank you and I look forward to answering questions.
▶ 0:59:41Thank our panel very much. I'll now recognize our members for questioning and I recognize myself for five minutes. The Trump administration's AI action plan prioritized the acceleration of AI adoption in government and outlines several policy actions that agencies can take to further US government's use of AI to as it says in his uh plan delivery responsive government American people expect and deserve.
▶ 1:00:10I'm pleased to see this mentality at the highest levels of government. Miss Manfra, how does the AI action plan align with industry best practices and the recent advancements in AI and what can the government learn from market participants to close the AI adoption gap and promote responsible use by our government agencies emphasis on
▶ 1:00:37Thank you for the question, sir. uh the uh administration's approach to ensuring that um AI and other technologies are used to better deliver services to the American people is very welcome and combined with that the approach to ensuring that responsible use with safeguards and um and the experience that agencies are having in implementing their own AI governance um has also been welcome and so being thoughtful about how these AI tools are
▶ 1:01:07being used um in different risk scenarios is something that we see every day with our customers and partners in the government and we welcome that. We also appreciate the approach of um experimentation and being able to create um spaces where um an agency or an organization can explore a use case for AI and work out responsibly what those issues might be before fully.
▶ 1:01:34I think that's a I think that's an important point because over the years we've had bipartisan support for regulatory sandboxes for a variety of things, blockchain and other aspects of it and that's something that
▶ 1:01:49technology providers and banks have tried to work out. It's important in fintech partnerships. It's not deregulatory per se. If one has a sandbox and in an offline capacity tries to perfect the use in this case of AI and then the responsible compliance procedures for it. Isn't that a fair way to describe it?
▶ 1:02:12You don't consider that per se deregulation, do you?
▶ 1:02:15I do not, sir. I think it allows um organizations to have a safe space where they can experiment and work out any potential issues before they would then
▶ 1:02:26yeah I kind of share that I share that view as a general statement subject to the details obviously while machine learning is not new and generative AI and aenic AI have recently been paradigm shifts for this technology particularly in the private sector. Such tools, they may hold enormous potential for our financial institutions and our financial regulators to change how they work. Mr. Cohen, let me turn to you at at NASDAQ.
▶ 1:02:54Um, you move trading markets to the cloud and you were one of the first exchanges to release an AI powered order type. Can you describe the efficiency gains that you achieved through this transition and what lessons you think that taught NASDAQ as you look at other AI adaptations?
▶ 1:03:14Uh thank you for the question. In terms of the order type you're referring to, it was it's it's called dynamic mellow. It is the first SEC AI enabled order type and and the SEC had to get comfortable with exactly how we designed it. uh the explanability of it, how we're testing it, and then how we're deploying it into the market.
▶ 1:03:34And we designed it for large institutions, the Fidelities, the Wellingtons of the world, so that they can execute in our markets with confidence and get the execution quality they need because they're serving retail investors, everyday investors sit behind the money that they put to work every day in our markets.
▶ 1:03:52So we wanted to democratize good execution quality and we did it through this order type through initially a static delay mechanism that allowed them to avoid fast money in the market which meant that at the end of the day they can look at their executions and the price movement after they executed and and see that there was quality in those executions.
▶ 1:04:12What we did with AI is we incorporated 140 data points every 30 seconds to determine what that delay should be to optimize the execution quality that those large institutions get.
▶ 1:04:25I appreciate that. My time is short. So, Miss Whitmire, if I could ask you to respond in writing. Of course, good good people and bad people can use AI. So countering threats I think is very important and I think cyber risks are a big challenge for the private sector and the government sector. Can you follow up in writing with me and talk about how uh we should counter those cyber risks to counter bad actors in this space using AI and I thank you.
▶ 1:04:52Yes sir.
▶ 1:04:54Thank you very much. If you do that in writing please me recognize the gentleman from Georgia the distinguished Mr. Scott for five minutes. Thank you very much, chairman. You know, concerning this AI business, I'm very fearful that we are rapidly becoming servants of the machine that we created to serve
▶ 1:05:24us. I want that thought to register with And that's why I'm working on a bill to expand wage insurance protections, guaranteeing temporary wage for workers who are forced into lower paying jobs by AI.
▶ 1:05:55This is And Mr. Branch, uh, let me ask you, you said something very important in your statement.
▶ 1:06:14You said in your statement uh and I quote, "Workforce policy built on aspiration and retraining slogans is not a real A1 So let me ask you a couple of question. Have you talked with our labor unions about this? What are they saying?
▶ 1:06:43if you have or have not.
▶ 1:06:46Thank you for the question, Representative. Uh yes, we have spoken with union representatives and they're concerned about the potential for replacement and lost jobs. Um the problem with some of these reskilling programs is that oftent times the jobs are not available in the communities where the jobs are lost. So you lose a job in rural America, but the job is actually based in Silicon Valley that you're being retrained for.
▶ 1:07:10And a lot of times the uh reskilling jobs don't even come at the rate of the jobs that end up being lost. So you end up having a variety of folks who lose jobs but then can't be uh employed afterwards.
▶ 1:07:24And spell out for us how can unregulated jobs lead to widespread job displacement?
▶ 1:07:36Well, thank you again. Currently, a variety of tech companies are really moving forward with trying to replace um a variety of their employers employees. We're seeing this in the tech force right now where you have uh whole slews of coders who are losing their their jobs. And so that's why it's important for Congress to address this issue headon to work with unions to ensure that when these jobs are lost that there are actually going to be jobs available for these folks.
▶ 1:08:04And that's why I keep saying we're rapidly becoming servants of this machine we created to serve us. And I hope uh Chairman Hill that this very timely hearing will wake our nation up to realize.
▶ 1:08:24And um I'm working on a bill, as I mentioned, to expand wage insurance protection, guaranteeing that our workers are taken care of here. And uh let me ask you one more question, Mr. Branch. The unemployment rate for recent college graduates has risen recently.
▶ 1:08:52Why is it important to modernize workforce protections to reflect today's a AIdriven
▶ 1:09:04Well, thank you again for the question.
▶ 1:09:05AI is driving it, man.
▶ 1:09:08Thank you again for the question. Um again to sort of boost efficiencies that some of these uh companies are talking about um they're really targeting lower level employees and lower level jobs. And so you're seeing waves of um college graduates who don't have those lower level jobs available for them.
▶ 1:09:29um they're oftentimes requiring additional job experience that they might not have because they haven't had the opportunity because you know efficiencies have made those jobs essentially redundant. So it's important to ensure that there are you know opportunities for these young kids to to get into because if you're removing those jobs you're essentially removing the ladders to success that the middle class was built on.
▶ 1:09:54And uh in my last seven seconds, we got to guarantee that our workforce is protected with this advance of AI. Mr. Chairman, thank
▶ 1:10:07I thank the gentleman from Georgia. I recognize the vice chairman of our full committee, the gentleman from Michigan, Mr. Heiser. You're recognized for five
▶ 1:10:13Thank you, Mr. Chairman. Uh it's interesting the conversation that we're we're having here. Um, we some seem to be suggesting we shouldn't innovate because of potential job loss. Uh, I can't imagine where America would be today if that was our uh our guiding principle.
▶ 1:10:32Um, we also seem to be having some folks lump in AI generally into one big category and seems to me an AI system dispensing quote life advice uh about whether I should take this job or or more tragically and is a huge problem uh where we have seen systems uh tell kids to go do things to themselves that they should not uh shouldn't even come across their screen
▶ 1:11:02uh but that's diff very different than an application to seek facts you know what uh what was the gross GDP of the United States in 1904 is a fact and and because of AI and because of some of these systems we're able to we're able to sort through those things but both of those are very different than an application to introduce efficiency into a simple process or even a complex process and we've got two great examples here with NASA and and Zillow and
▶ 1:11:32and and and others. Um I'm going to start there. Some have suggested that there is not the same protections against um with the application of AI to uh to to various transactions and and so Mr. Mr. Cohen, Mr. Stevens, I'd like you both to quickly address this. What have you done to ensure that that doesn't happen in your respective industries?
▶ 1:11:56Housing and and and investing are two uh two of those areas that we talk about often here on the committee. And is there any evidence that what your efforts have done is not working and is is not mitigating uh that concern and and have you had to make any adjustments, Mr. Con?
▶ 1:12:15Uh thank you for the question. So we do not serve retail uh directly. we serve institutions and obviously the financial
▶ 1:12:23and and the way that we think about it and the way that we employ it into our solutions whether it's our anti-inancial crime solution our surveillance solution uh or regulatory solutions it goes through the same if you will PDLC process that we have for anything that we would deploy and what's really important about that is the rigorous testing that we do the understanding of explanability and trans transparency can we reproduce it do we understand what the models are providing and there's always a human in the loop.
▶ 1:12:53Really important you keep that human in the
▶ 1:12:55and obviously you're not quite as forward facing as a real estate
▶ 1:12:59Yeah, similar answer. I I'll talk about fair housing and then back to the first part of your question how important advice from a human really is in housing. For fair housing, we built the classifier. So,
▶ 1:13:10by the way, as a former realtor, I'm I fully subscribe to that. So,
▶ 1:13:14well, our research shows, might be counterintuitive for a leader of AI to say it, but our research shows that humans making a buy, sell, rent decision want to sit across a kitchen table and get real human advice from someone who lives in their market. And so, our AI is built at to really target the processes that are keeping real estate agents like your former self away from those important conversations. And then along the way, we built classifiers like the fair housing classifier.
▶ 1:13:43AI should be held to the same standards as any human and we want to make sure the facts that are presented to people as they prepare are meeting those same fair housing standards. Real quickly in my last minute and a half here, Mr. Con, how's NASDAQ leveraging artificial intelligence to create markets that not only more efficient but more transparent and fair? You touched on that a little bit. Do you care to to elaborate or or um how how you have to deal with that through that? We have a great example of that that I did not talk about in my opening remarks.
▶ 1:14:13We have a a market intelligence desk where our listing clients, our corporate clients will contact us and ask us about sentiment, will ask us about um what is the intelligence, what are you seeing in the markets. And what we're doing is using AI to essentially group different parts of data or different pieces of data, which is what we see in social media, what we see in the news and what we see in the markets. And the confluence or the aggregation of that allows us to use AI, develop patterns, develop insights and intelligence.
▶ 1:14:42We can provide business leaders so they can make real-time decisions. Now again, there's a human in a loop. We ensure that to the extent that there's news out there, there's not real or fake, we're we're taking that out before we provide that.
▶ 1:14:55So, you're stitching that all together. And Miss Whitmore, I'm sorry you seem to be uh you're going to be answering a lot of our questions in writing. Uh but I want to touch on touch on AML KYC and how AI has the potential to enhance compliance efforts. So, 10 seconds.
▶ 1:15:09Okay, we will follow up in writing on that. Thank you.
▶ 1:15:12And with that, I get to yield back with two seconds. So, sorry about that.
▶ 1:15:16I thank the vice chairman. It's now my pleasure to call on the gentleman from Massachusetts, Mr. Lynch, who's the ranking member of our digital assets, fintech, and AI subcommittee.
▶ 1:15:26Thank you, my friend. Uh I I've got a couple of things here. So, uh, we're talking about a a quasi sandbox, uh, process here to try to test, um, some of these AI applications and financial services. Um, as a member of this committee, uh, in the past, we've we've done, uh, oversight on on the whole sandbox process.
▶ 1:15:51Uh, one of our more um, instructive experiences was when in Singapore where we went in there and they had a a a financial services uh, techn fintech uh, uh, sandbox where they invited u companies to come in and and uh, and participate. But the difference here is that when when they did that in um they had their regulations in place already.
▶ 1:16:22Uh and here we're we're doing it backward. We're we're inviting uh we're invi inviting uh financial services companies um as they deploy AI to choose which which consumer investor protections which soundness uh safety and soundness regulations that they might might want to avoid. And and Mr. branch.
▶ 1:16:52Is that is that a a proper way to to introduce a new technology where you're you're asking the the private sector to identify regulations that are in place to protect consumers, investors, uh depositors because this applies to banks as well.
▶ 1:17:10uh and you're asking them what would you like to to do to avoid a compliance with some of the current u existing financial services regulations.
▶ 1:17:26Thank you for the question representative. Um no I don't think that's a responsible way of moving about this. Um the sandboxes that are being proposed uh often are completely deregulatory. that is uh entirely different from the Singapore model which was actually hailed in this committee just a few months ago. Uh they had regulators in place. It was time limited. Consumers were warned if they're a part of that sandbox. None of that is present here.
▶ 1:17:53Right. So so the idea of a sandbox is you you have a a contained area. Matter of fact, uh Mr. Chairman, I'd like to ask consent to introduce fintech regulatory sandbox guidelines. um uh dated November 2016. This was in the advance of the u the Singapore uh
▶ 1:18:11Without objection.
▶ 1:18:12So um a few of the things that they point out here that are essential to um essential to a successful u sandbox and that is to manage risks uh to contain the possibility that that individuals might be uh injured or or financially damages.
▶ 1:18:33The consequences of failure for that technology need to be contained and people need to have advanced knowledge that of the risks that they're they're they're embracing by participating in in in adopting that technology.
▶ 1:18:49And it cannot they says here it cannot be used as a means to circumvent legal and regulatory requirements which is exactly what what this bill is suggesting that u that in adopting AI u they're they're allowing or in encouraging um ways of circumventing existing regulation in what is supposed to be a a technology neutral uh approach.
▶ 1:19:18Um, and there's also cautions here where applicants have not demonstrated that they have done due diligence, including testing the proposed financial services technologies in a laboratory environment beforehand and knowing the legal and regulatory requirements for deploying the proposed financial service technology. So, um, what so, Mr. Mr.
▶ 1:19:43Branch, what's what's wrong with that whole approach uh in terms of uh protecting uh consumers, investors, depositors, and others who rely on the benefits of this financial services uh industry?
▶ 1:19:57Well, I think the main thing that's wrong with that approach is that there's everything to gain for large corporations and the harm is just going to be entirely brought on by the American consumer. Uh and if anything, if things go wrong, the government is going to be expected to either bail out or uh help out the corporations that have put the consumers in in harm's way.
▶ 1:20:19Thank you very much. Um Mr. Chairman, I believe my my time has expired. I yield
▶ 1:20:24Gentleman yields back. Pleased to recognize the gentleman from Oklahoma, Mr. Lucas, who chairs our task force on monetary policy and Treasury market
▶ 1:20:33Thank you, Mr. Chairman, and thank you to our witnesses uh for being here today. Our whole economy benefits when United States companies lead the world in innovative financial services. I think we all agree on that. And our regulations should allow for that responsible growth and expansion when it comes to AI too. Mr. Cohen, would you expand a little bit? What are the best use cases as you see them for AI to be further deployed in capital markets?
▶ 1:21:00Thank you for the question. We at NASDAQ deploy AI in two ways. in our products and then on the business and the way that we think about in the products. We are trying to generate greater productivity, better outcomes for our clients and lead to a better client experience with with the type of solutions that we provide.
▶ 1:21:20And I mentioned this before, we see the the possibility of improving how how jurisdictions uh put out regulation, the complexity associated with regulations, and then what clients need to do to comply with those everchanging regulations. AI can go from reg to code and really allow them to ensure with confidence they're complying with regulations. So that's a great use case for us in fighting financial crime. I mentioned it earlier.
▶ 1:21:48We we must use AI and the data that we have at our disposal to make sure that we're staying ahead of the bad guys in terms of what I talked about with human trafficking, financing terrorism. We need to make sure that our solutions are protecting the reputation, the brand, and the consumer behind those institutions. So that that is really really important.
▶ 1:22:07And then in our markets, we're using AI and this is our northstar to make sure that we're democratizing the types of uh the types of capabilities that otherwise small broker dealers don't have the R&D and engineering talent to develop on their own and they would be left behind if not for NASDAQ and others developing it on their behalf.
▶ 1:22:29On that same thought, throughout the committee's work on combating fraud and scams in the financial services system, we've discussed the sophistication and technological assets that bad actors use against consumers. So, giving you prime time opportunity to answer, Miss Whitmore, how is AI being used right now to detect and stop fraud and scams, and how will those services improve and expand in the future?
▶ 1:22:53Well, I'm thankful for the question. Uh so what we're seeing in terms of the threat landscape relative to AI, two areas. First is attackers using AI to fuel traditional cyber crime. We're largely seeing that impact the speed and the scale with which they operate. The second part that's not being talked about as much is how attackers are targeting AI. So creating the ability to uh make agents inside of our environments into rogue insiders that cannot be trusted.
▶ 1:23:23And so what we see with that is the need for security to be closely coupled with AI innovation, the need to make sure that we're protecting uh the the build, the run and the access. So uh particular to the runtime, right? Making sure that agents are do not have the capability to go rogue uh and that those protections are in place so that organizations can successfully uh innovate without that being hijacked by attackers.
▶ 1:23:50Miss Manfra, can you discuss how smaller financial institutions like community banks can utilize this technology? Why is it important for financial institutions of all sizes to have access to the latest technology? Please.
▶ 1:24:05Absolutely. Thank you for the question. Um, one of the great benefits of what we're seeing in AI is the democratization of access to data that um, historically only large well-unded institutions might have and the additional productivity gains um that smaller institutions that are more resource constrained now have access to larger data sets more real time and are able to put in place um, improved uh, customer service experiences, improved productivity, are
▶ 1:24:35better able to detect fraud fraud and um reduce the amount of false positives so that their employees don't have to spend time chasing down um potential deadends. So we see a lot of opportunities in the small and medium-sized financial institution
▶ 1:24:48And Mr. Cohen, I'll ask you to respond in writing. Are existing regulations appropriate to encourage innovation while maintaining appropriate consumer and financial stability protections? And what are the regulations, statutes, if any, that would use modernization? And you can respond in writing. And I yield back, Mr. Chairman.
▶ 1:25:07Thanks, gentlemen. Chair recognizes the gentleman from California, Mr. Vargas, who's the ranking member on our task force on monetary policy. Recognized for five minutes. First of all, thank you very much, Mr. Chairman. I appreciate it. Uh, you and the ranking member putting it together. I think it's a very important hearing. Um, I don't believe that you can unring a bell or put the genie back in the bottle or do anything like that. So, the reality is that as science moves forward and our knowledge moves forward, you you can't reverse it. So I think AI is here.
▶ 1:25:36It's now how do you manage it? A few years back I had the opportunity to go some of my colleagues here to the World Economic Forum and somehow I got assigned to go to dinner with the young tech entrepreneurs to listen to Sam Alman and I thought I wasn't going to understand a thing because I'm not young and I'm not a techie. So I thought this is going to be interesting but I'm not going to understand anything. Turned out I understood everything because they really didn't talk about technology.
▶ 1:26:06They really talked more about philosophy. It really was more the philosophy of the machine you heard earlier versus human being. The the data that you put in and what comes out whether that data is positive or negative and you could see some of the results.
▶ 1:26:22I've seen them in the following years where yes, AI you will ask it a question and it'll come back with what we would think is a pretty absurd answer or or horrific answer for young some young people, but you could see why that the data that you put in it would ultimately reach that conclusion because not all data is positive. You also have data that's in there is negative. So I appreciate that.
▶ 1:26:45And also we've heard today the really the competition between the the good and the bad in AI because I mean the bad guys use AI also for fraud and other things. So with all that being said um Shallen you have a very transparent company. In fact when we talk to your staff they get back to us right away. So I'll ask you who's winning here? I mean are the bad guys winning in the attacks or or not?
▶ 1:27:14uh and thank you for the question. What's interesting about this technology is the rate of advancement of this technology is faster than the rate of adoption and you don't often see that with technology. The the second thing is we need to as an organization all of us within our four walls talk out loud about the negative scenarios that that might occur with AI so that we prevent them. If we don't talk out loud and we don't have conversations internally about that, then we're missing an opportunity.
▶ 1:27:45And then to your more specific question, we are seeing in our markets bad guys, if you will, using AI to come up with more sophisticated market manipulation schemes. If we are not using the data and the technology to stay one step ahead, then we risk the integrity and the investor confidence around our markets. for banks. Fraud is a massive massive problem and fraud is becoming more sophisticated. It's it's more difficult to detect and you can't do it on your own.
▶ 1:28:15You need a public private partnership and you had you need a massive amount of data to really stay ahead of it. So unless we arm our community to be able to do that, then we're going to be a step behind. Banks are going to be subject to fraud. Markets will be subject to market
▶ 1:28:30So So I understand that part. You have to they're going to use it. So you have to prepare. I mean it's one of these things that has to happen. But you also said something that's very interesting because it's also a philosophical point. I I do have a masters in philosophy. That's why I'm so confused normally. But it was more based on religion. I studied to be a priest for a long time. And the notion of keeping the person in this process becomes harder and harder as it advances because the decisions it makes it takes all this data and it uses so quickly.
▶ 1:29:01How do you figure to keep the person a human being in this process as you would call it in the loop when AI can make decisions so
▶ 1:29:12It's a it's an excellent question and and the human in the loop is a really really important and building those critical thinking skills and those judgment skills are exactly what we're training our people to do. So one we're putting the tool in our hands. Two is we're providing them with training and education. And three is we're putting good governance around them and providing them with policies that they can follow and understand. And so the humans are armed with enough so they can make the right decisions at the right time and understand their roles.
▶ 1:29:40And the roles are not decreasingly becoming marginalized. It's actually more important than ever to have that human in loop and provide that judgment as you noted because AI is designed to provide you with an answer. It's our responsibility to determine if that answer is correct and that that is the answer that we want to provide our investors and and if you will institutions that we serve around the
▶ 1:30:03Well, I apologize I asked you all the question. I apologize others. I wasn't able to but I have 10 seconds left. With that, I'll just thank all of you and I'll thank the chair. Appreciate it very much. Thank you, chair.
▶ 1:30:13Gentleman yields back. The gentleoman from Missouri, Miss Wagner, is now recognized for five minutes. I thank the chair and I say welcome to our witnesses. Uh Mr. Cohen, in your testimony, you highlighted how NASDAQ has been at the forefront of technological innovation in our capital markets since the exchange was founded in 1971.
▶ 1:30:38NASDAQ was an important player in the creation of electronic trading. And while rapid growth over the last few years in generative artificial intelligence or AI has brought this technology center stage uh for the general public, NASDAQ has been quietly using AI for years and years to fight fraud and increase market efficiency, liquidity, and
▶ 1:31:08transparency. Mr. Con, can you describe some of the ways that NASDAQ currently uses AI and the extent to which generative AI either has or might have a role to play in our capital markets and how do you manage the risks associated with uh this technology? Sir,
▶ 1:31:31uh thank you for the question. Uh and it is in our ethos, if you will, to adopt and integrate emerging and advanced technology early. We see it as a competitive advantage and one that we've embraced since our founding in 1971. And with respect to the use of AI, what is important for this committee to to understand is you can't harness the power of AI unless you make the foundational investments to do that.
▶ 1:31:56And we've done that over the past decade. Whether it's embracing the cloud, putting good governance in place, having a mature posture over information security, training and upskilling our employees, and making sure we have good governance. And good governance is the lubricant for innovation. That's the way we see it. And then you have to be really clear to make sure that it's centralized so you don't have the AI sprawl happening within your organization. And shadow AI where you can't control it, you don't know about it.
▶ 1:32:25So all of those things have been what we've been focused on over the past decade, which has now enable us to put it in our products, as you mentioned. We use it for market abuse. We use it to fight crime. We use it to democratize access. We use it to provide more transparency, more information, to end investors so they understand the risk that they're taking when they invest in our markets. And we're always trying to stay one step ahead of the bad guys.
▶ 1:32:52One, and two, one step ahead of ensuring that our markets continue to be the best in the world. We have a we have the pride in making sure that the US markets are the most robust, most vibrant, uh, if you will, highest mors of the way that we operate and we protect the US markets every day in the way that we
▶ 1:33:10You are absolutely right. we have the the the most extraordinary uh markets in the entire world and we're going to put a fine point on that this week with the invest act that will be moving forward. So, we're very excited about that. But you're right, other companies and industries need to to to look at that AI sprawl, uh shadow AI, some of the things that um that I don't know that they are entirely discerning, but those are those are key. Mr.
▶ 1:33:37Tone, do existing technological neutral regulations provide sufficient guard rails for the responsible use of AI in our capital markets or are new AI specific updates and clarifications required and if updates are in order, what should they look like and how can they be implemented without stifling innovation?
▶ 1:34:01It's a great question. It's one that we actually think about quite a bit uh especially as the technology is evolving. What I would say is we have a great foundation. We have uh securities laws. We have NIS that we follow. We have reggg sei uh and we've worked hard as an industry to put more rules in place around technology. So the foundation is there.
▶ 1:34:22I think the key to that question is because the technology is advancing at such a rapid pace information sharing a private public partnership where we can share information about the advancements of this technology to identify gaps because we don't know what those gaps might be today because the advancement of that technology is such that it's if it's it's it's not linear, it's exponential and we are we tend to plan very linearly as humans. We're we're just going to have to make sure we stay in touch.
▶ 1:34:52We share information. We use the foundation that we have that I mentioned with NIST and regi and the securities law to ensure when a gap comes out or when there's a risk that we've identified, we work together to address that quickly. Well, and I may not uh you may have to respond in writing here, but I I I am interested in knowing if there are any existing rules or ambiguities or proposals that are limiting AI innovation from reaching its its full potential in US capital markets. Obviously a focus of mine.
▶ 1:35:21So I'll look to your for your answer in writing and I thank you for your testimony and I yield back to the chair.
▶ 1:35:27Gentle lady yields back. The gentleman from New York, Mr. Meeks is now
▶ 1:35:30Thank you, Mr. Chairman. Let me go direct to Miss Whitman. Miss Whitman, the nexus of AI and sup and cyber security is particularly important uh and can be particularly concerning as well. Last year, the salt typhoon hack against the United States companies and high-profile leaders was called the largest cyber breach in United States history. Can you just give me a very brief summary of what happened?
▶ 1:35:58Um, yes. Thank you for your question. So you're referring to an attack by a nation state actor, in this case China, uh that target our telecommunications and critical infrastructure industries across the board with the intent to steal data to then use it to meet political objectives at some point.
▶ 1:36:15And unique to critical infrastructure, the component there is uh the fact that the Chinese nation state may be intentionally looking to embed themselves within critical infrastructure with the intent to take some sort of action at a later date. Thank you. And Mr. Chairman, I want to for the record uh enter uh this article entitled US halted plans to sanction Chinese spite spy agency to maintain trade troops.
▶ 1:36:41Without objection. Okay. And then a few days after the report, more news came out of the Department of Commerce, which I can't believe that they intend to uh to allow Nvidia to sell one of the most advanced AI chips to China that had been previously banned for export.
▶ 1:37:07In fact, the Justice Department was just about to go after someone who was trying to sneak them into China. Yet, this is unbelievable to me. The president started a trade war that we're losing.
▶ 1:37:28And he's now afraid to punish the PRC and its entities that hacked our most innovative companies to access the private communications of the American people. further by allowing advanced GPUs to go to the PRC. He's throwing away our biggest and most important advantage in the AI race with China.
▶ 1:37:59That's innovation. This isn't innovation. This isn't winning. This is indeed weakness. And unfortunately, it's going to cost our country. Let me go to another matter. In America today, rising housing prices and stagnant wages have put home ownership out of the reach for millions of Americans.
▶ 1:38:28Median home prices remain near historic highs, and too many working families are nowhere near achieving their American dream of owning a home. A major part of the problem is that we simply aren't building enough homes.
▶ 1:38:44Whether it's because of zoning barriers, permitting delays, outdated systems, and rising construction costs because of, you got it, Trump's tariffs on materials like lumber and others, you have what is becoming a perfect storm. So, Mr. Stevens, in your testimony, you mentioned that AI can help address some of these challenges.
▶ 1:39:12You said it can help with clearing per permitting and zoning backlogs, reduce loan origination and compliance costs, and speed up the development process. That would be good news. But my question to you, sir, is aside from boosting efficiency, how can AI be leveraged to enhance housing and increase the supply of homes? President says this is a hoax. affordability.
▶ 1:39:41But you know, let's let's go. How how how can that happen?
▶ 1:39:44Yeah, thank you, Congressman, for the question. I very much agree. We are facing a housing affordability crisis, and there is no silver bullet. I think you mentioned one of the biggest drivers that we're 4 million or four million homes short in terms of supply. We are very excited about the efficiency gains that you mentioned, zoning laws, really understanding how we can make more efficient the mortgage and real estate processes. I'd say beyond that uh bringing more information to consumers.
▶ 1:40:14It four million people will or four million families will buy a home this calendar year. 2 million for the first time and understanding what's available to them, what they can afford, what they should explore. Uh helps actually reduce some of the affordability problems we're facing today.
▶ 1:40:28There should be some public private partnering so that we can ensure that AI is being used safely and effectively. Is that not correct? You agree with that?
▶ 1:40:36Yes, exactly. Thank you. Go back.
▶ 1:40:39Gentlemen, gentleman's time is expired. Um I now recognize myself for five minutes of questioning. Um in President Trump's July AI data action plan, he notes that we must develop a grid to match the pace of AI innovation. Unfortunately, our grid is currently unable to keep pace with our energy demands.
▶ 1:40:59The Department of Energy projects that blackouts could increase 100fold by 2030 with one study saying that the Mid-Atlantic and Great Plains regions could face 400 hours of power outages annually. The growing demand for power uh with AI is uh uh increasingly a major strategic challenge for the United States.
▶ 1:41:21Um, Miss Manfra or or Miss Whitmore, what is the threat to US national security and global leadership in the AI space if we cannot meet the supply of energy needed to power AI data centers in the United States?
▶ 1:41:36Thank you, sir, for the question um, and raising this important topic. Um and happy to go and continue with you and your staff um and more discussion on this. But yes, overall we need to ensure that we are able to keep pace with the demand for energy and in order to support American competitiveness in this space and we also need to ensure that we're doing that responsibly and in partnerships with those uh those companies that are involved in the distribution and provision of electricity.
▶ 1:42:05Well, what considerations go into um the a firm's power strategy? Um uh your firm's uh strategy when it comes to training and developing frontier AI models.
▶ 1:42:18We are all we are heavily invested in optimizing our um our infrastructure. So our technical infrastructure and um and the way that we run and power um the the machines that power AI and for efficiency for energy efficiency. So we spend a lot of time and that is a key principle of ours is to optimize for energy efficiency. I hope that answers your question.
▶ 1:42:44Well, let me let me ask a question a different way. Um our self-inflicted energy crisis is a direct result of bad policy. Green New Deal, Payers Climate Accord, Network for the Greening of the Financial System, the SEC's climate disclosure rule, uh the the the regulators principles for climate related financial risk management, chokepoint, the the push for the greening of the financial system. Um Mr.
▶ 1:43:08Cohen, are can you can you talk about the importance of traditional financing of the most reliable and affordable dispatchable sources of power? That's fossil energy and nuclear. Uh why is that important uh for us to win the global race for AI leadership?
▶ 1:43:31I think at the end of the day it's important to note that uh NASDAQ does not operate its own data centers. Um and so when we think about power and we operate our markets for instance out of New Jersey, a data center we've been in for a very very long time.
▶ 1:43:45We are working handinhand with our data center providers on the power strategy and and as you just heard we as a as a public company for-profit company we want to be as cost-effective as we can making use of all sources of power and in ensuring that we have the portability and mo more uh mobility to move if should we
▶ 1:44:05I'm going to I'm going to reclaim my time and make an editorial comment. China has 33 nuclear power plants under construction with an additional 200 in planning. Coal has been the largest source of global electricity for 125 years and it will be for decades more in the future. It is by far the largest source of electricity in China. They are they built a 100 coal plants last year. Now we need diversified energy sources.
▶ 1:44:30I'm not advocating for exclusively fossil energy or exclusively nuclear, but we got to get with the program. If we are going to win the race for AI, we've got to look at what our competitor is doing and we can't put our head in the sand and continue to regulate our energy sources into oblivion if we want to win the AI race. Final question. We all acknowledge the risks of AI that Mr. Branch uh talked about, AI generated fraud, deep fake abuse, consumer deception, etc.
▶ 1:45:00But he criticizes this proposed AI preeemption language as an effort quote to undermine state AI protections. There are more than 160 state level laws and AI by its very nature is interstate commerce. Uh Mr. Cohen, can you talk about the importance of federal preeemption to avoid a patchwork of conflicting and inconsistent AI regulations that would stifle innovation?
▶ 1:45:26uh we we think federal preeemption is extremely important and we think it needs to be principles-based as well and we don't think we need a new central regulator uh while we consider that and I think the reasons for that are if you cause confusion if you raise the cost of doing business it will simply just go overseas well I agree we don't need a new central regulator but we do need federal preeemption so that AI innovation can fight crime detect and stop fraud democratize finance promote financial inclusion and protect our markets I yield back.
▶ 1:45:56Um, now the the we recognize the gentleman from Illinois, Dr. Foster, uh, for 5 minutes.
▶ 1:46:02Uh, thank you, Mr. Chair, and thank you for your witnesses for your really excellent testimony. Um, you know, Congress is is currently stuck in this issue with federalism uh, and and federal preeemption. uh you know there are um we're struggling between the nightmare of having 50 independent stand standards to for AI regulation and the uh fact that we have a do nothing Congress that is so paralyzed by the thing that even straightforward things that we ought to be able to agree on nothing's happening and we're seeing
▶ 1:46:32uh consumers suffer greatly already and it's not going to get easier. Uh there is a middle ground on this uh which is something that we're going to be circulating draft legislation on that I'd like to to comment on and which is simply a proposal to let coalitions of states form their own uh standard so that any coalition would have to have for example 20 or 25% of the population.
▶ 1:46:55So there' be significant coalitions and and companies would only face at most two or three um two or three you know sets of AI standards. this would sort of cooperative federalism if you will I think is the is the thing that we may be able to agree on in this and so I just I'm tossing that out there will be you know more detailed legislation but it's a pretty simple concept most of you who work internationally already deal with a dozen different countries and their regulations so if the US had two or three standard markets
▶ 1:47:25for things like you know for everything AI privacy all this sort of stuff I I think it would actually work well and we'd preserve the laboratory of democracy of the states on this. Um so there are also you know the big thing that's coming at us is agentic AI and this is you know it's the future not only of financial services but um everything consumerf facing and B2B transactions in the near future most businesses are going to be facing you know not their customers but their customers
▶ 1:47:55agent and that's going to change everything uh customers AI agent won't care if you have a pretty website or an easytouse customer interface or a friendly smile you know most customer agents are just going to be given instructions to get the best price. Customer loyalty will go to zero. And this can destabilize our banking system. For example, with AIdriven bank runs, uh it's agents are going to squeeze the margins out of all consumer-f facing businesses. And that will be extremely disruptive.
▶ 1:48:23You know, for example, to pick an unsympathetic example, used car dealers will no longer have an infinite supply of clueless customers to take advantage of. Um, however, it may also really simplify consumer protection law because so much of consumer protection law is to protect unsophisticated customers. And if there are no unsophisticated customers because you're dealing with their AI, it'll change everything. Um, and the major uh All right. So, what can Congress realistically do on this?
▶ 1:48:51Uh, first off, um, preventing identity fraud by enhancing the deployment of digital driver's licenses, mobile ID. This is being done by most of the states right now. Um, the EU, the UK, the Asia, everyone has most almost every country has the ability to get out your cell phone to deploy a federally issued Real ID, a driver's license or the or passport or equivalent and prove they are who they say they are in an online transaction.
▶ 1:49:19We have to do everything we can to get this adopted. Um and and what we need here are not you know one of the legislation is uh to study best practices for sandboxes that we're not yet going to build. What we actually need is a pilot program to KYC customers using a real ID digital driver's license which would just simplify all kinds of things and and prevent a lot of the identity fraud.
▶ 1:49:42Um secondly I think if we would able to um define United States standards for agentto agent communication you know right now there are multiple competing uh standards there's the model context protocol for anthropic there's a A2A um coming out of Google actually Google has two you just in your um in your testimony reference AP2 where I spent a while on the website last night u it's actually I think a a much better uh step in in the direction
▶ 1:50:12of be- because what we need is a well-defined legally precise language to communicate uh you know things like what is the privacy what is the data retention what is the logging of the interaction uh and and all the legally things in order to have reliable transactions between agents there policy decisions there that we can defer what we should do is have NIST or or probably NIST and and number of uh uh partners in come together
▶ 1:50:42and define those standards. The White House is correctly pointing to the advantage of having the US lead that. And what I'd like to see is to have the NIST and the United States lead the world in defining HIT communication standards the same way uh we led the world in defining um personal ID standard, digital ID standards that are now in Android and and iOS and everything else. Um anyway, so these are there's lots of things to talk about here. I just want to thank you.
▶ 1:51:11You had really high quality testimony and um I learned a lot reading it. Thank you.
▶ 1:51:16Thank you, gentlemen. I now recognize myself for five minutes. Um you artificial intelligence does not change our fundamental regulatory framework which allows innovation while protecting consumers from abuse or fraud. As AI becomes more deeply integrated into our financial services and housing markets, it's essential that existing consumer protection laws governing privacy, fair lending, data security, fraud, etc. continue to apply fully regardless of the technology used.
▶ 1:51:47The principle should remain simple. If a practice violates the law without AI, it should not be permissible with AI. Uh at the same time, AI's increasingly increasing reliance on large sensitive data sets raises important questions about whether our current data protection frameworks are sufficiently clear and durable for the modern economy. In my view, privacy is the base layer for ethical a AI and we need to update our privacy laws.
▶ 1:52:15We need it to do a much more robust job of that. Congress should reassess how consumer data is collected, used, shared, and safeguarded without imposing rules that freeze innovation. Finally, we should also know that a fragmented patchwork of state AI mandates risks undermining both innovation and privacy. A harmonized federal framework can protect consumers while giving innovators the clarity and certainty they need.
▶ 1:52:42This needs to be a more thoughtful approach though and Congress should have the debate and make the decision, not something can be done with a two-s sentence addition to some bigger bill on another topic that basically says we can do whatever we want. It does require a more thoughtful approach in my opinion. Mr. Stevens, what specific categories of consumer data are being used to train and operate uh AI systems
▶ 1:53:08Many and thank you for the question. I totally agree especially in housing how important privacy is. This is the biggest financial transaction of your life. There are many factors that go into it. All our consumers report to us that they want to really make sure their personal data is theirs. Um we use basically things like signals on what preferences they have, financial data they give to us when they're thinking about what they can afford.
▶ 1:53:35They work with real estate agents who use some of our tools um and tell about their hopes and dreams and we make sure that all of the above is meeting the federal standards and laws. When we work with other companies as an example I gave during verbal with open AI we continue to make sure that's still the case. So when chat GPT might want to violate fair housing our classifier makes sure that doesn't happen and that all of the consumer's information is kept as theirs.
▶ 1:54:03How do you how do you ensure that you protect PII that what kind of transparency is there? What kind of recourse do consumers have?
▶ 1:54:10Yeah. Uh the easiest way is to not or is to first keep it safe. So keep it on our systems that are protected. Only certain humans have legal ability to view that data or work with that data. With thirdparty partnerships, we usually do not share that information. And if we do under limited license, that is then deleted upon completion of the Thank you. Uh Mr. Cohen, there's a lot of discussion about the importance of winning the AI race against China.
▶ 1:54:38Uh frankly, I'm concerned to beat China, we shouldn't try to be more like China. I don't want to be like China. I want to be like America. But yeah, on the technology end, we want to win the AI race. Can you give us a sense of how uh you view this discussion through the lens of our capital markets and give us a perspective on the level of AI adoption NASDAQ is seeing from the broader market in China in particular.
▶ 1:55:03Uh thank you for the question. Our focus continues to be as an operator of of markets here in the US to make sure that the markets here are the most robust, vibrant, most attractive in the world. And we will use AI to continue to ensure that we do that. And we do it and I I spoke about this before by introducing whether it's order types or functionality that democratize access that allow smaller broker dealers to participate in our market.
▶ 1:55:28So we have a healthy ecosystem or we root out uh financial crime to make it sure that there's investor confidence and market integrity or we use surveillance to detect increasing sophistication and market abuse. All of those require us to use AI, to invest in AI, to make sure that we are partnering with folks around here, the the colleagues that I have here on this panel and others to ensure that we ensure that the US capital markets remain the most robust in the
▶ 1:55:56Yeah. I mean, in the private sector, of course, there's a lot of incentive to, you know, keep up with this arms race. And on the other side, you're dealing with regulators that sometimes haven't kept up with a lot of the technology. So when we think about it here in Congress, what are the most important things we could do uh to make sure that America is the most competitive place for capital to be deployed?
▶ 1:56:15And we talked a little bit about it before, the the the need for sandboxes, the need for the ability to continue to innovate in a safe and responsible manner, I think, is extremely extremely important and not having overly complex regulation that we have to patch together is also very important. Now
▶ 1:56:33my apologies I didn't give you much time to answer that. If you want to provide a longer answer,
▶ 1:56:36I I can certainly do that.
▶ 1:56:37My time is expired and uh respecting everyone else's time, I now recognize the gentleman from California, Mr. Sherman, who's also the ranking member of our capital markets subcommittee.
▶ 1:56:48Want to commend uh Mr. Foster for his digital ID bill. I know it uh u is running into some opposition, but ultimately if we cannot identify ourselves uh in this new uh digital age, this will be a problem. And I also commend him for leading a letter uh asking that the FPS look at the financial risks of an AI bubble.
▶ 1:57:13Uh Mantra uh uh Montra uh you see signs of an AI bubble out there.
▶ 1:57:25So respectfully I'm not a market analyst. I'm responsible for a risk and compliance. Thank you. Oh, you
▶ 1:57:31uh but you are from Google and there's someone else who works at Google, Gray Kurszswwell. I think he was once your chief finan uh uh technology officer and he per was before the science committee uh some uh 22 years ago and I asked him um how long it will take for nonbiological intelligence to surpass
▶ 1:58:01human and his estimate then was 26 years. So, we're almost there. First of all, you hire very smart people because to predict something and to be that close, we're spending trillions of dollars as a uh, species to make AI more powerful.
▶ 1:58:26I cannot find a program anywhere in the world, and I'd support it if I could find it, designed to monitor and prevent self-awareness and to determine what can be done to uh to prevent AI from developing its own objectives, which I think would be hostile to ours. There's a book you don't have to you may not have to read the book.
▶ 1:58:55Great new book coming out. It just came out. If anybody bu it says if anyone builds it, everyone dies. Uh is Google Do you have a department? Do you have a budget for monitoring for preventing self-awareness, ambition or uh um uh AI uh creating its own uh its own goals?
▶ 1:59:18We invest a great deal in ensuring that uh the AI capabilities we're developing is in line with human values.
▶ 1:59:27I've I've always heard that and then it come and and and uh but I can't find a single scientist who's looking for self-awareness and and ambition. Obviously, you don't want criminals stealing our data or our money. Uh and what you describe fits into that category. Can you name one person whose job it is at Google to prevent AI from uh uh becoming a creature rather than a
▶ 1:59:53Sir, let me get back to you. We do have researchers that are heavily invested in this topic. So if we I can I'll get back to you. It's not my area. Please, please get back to me because I have not been able to find anyone and then you ask about uh these issues and you get these vague align with our uh our our goals and the goal usually is well look uh we can make trillions of dollars by making AI more powerful and there's no money in preventing AI from taking over the world.
▶ 2:00:21Uh that's uh that's next generation's problem. uh one problem we have um and I'll feed you one more question is uh AI doing its analysis and then reflecting the discrimination that has existed in our society for uh uh for many centuries. Uh for example, you could say if somebody grew up in a particular zip code, they're more likely to to uh default on their rent.
▶ 2:00:49uh what do you do at Google to make sure and I think there was another study that said if you want to analyze who's going to be successful at Yale uh it turns out the best predictor is being named I think Jared or some other name associated with uh the elites in our society. What do you do to make sure that uh the prejudices of the past aren't built into the computers that will control the world in the future?
▶ 2:01:14This Thank you for the question. This is something we care deeply about. um and um issued our responsible AI ethics principles uh nearly a decade ago. And so our approach first is to ensure that humans are involved in the um in the setting of the parameters if you will. We're constantly designing uh redesigning and then monitoring to ensure that we have an unbiased approach and we are always iterating.
▶ 2:01:44Do you have a program that prevents the zip code that you were born in from influencing the decision that's made?
▶ 2:01:51I know we look at those things to ensure that we don't. I will get back to you on a specific program.
▶ 2:01:56I will ask everyone to get back to me on whether you're focusing on preventing AI from becoming a creature and I'll yield
▶ 2:02:01The gentleman yields back. The gentleman from Tennessee, Mr. Ogles, is recognized for five minutes.
▶ 2:02:06Uh thank you, Mr. Chairman, and thank you to the witnesses. you know, obviously I serve on financial services, also serve on homeland security where I am the chairman of cyber, which would obviously overlap with AI. And so this obviously when you look and quite frankly, Mr. Chairman, when you look at AI, what really got my interest in this topic was the national security side of the financial services conversation.
▶ 2:02:29And so, uh, as we look at artificial intelligence in the context of financial services, I think it's important we recognize that we're dealing with a technology that doesn't fit neatly into traditional policy frameworks. AI isn't a product or a single system. It's a capability layer that will influence everything from market structure to fraud prevention to consumer decision-making. That means the question in front of this committee aren't simply about regulating a new tool.
▶ 2:02:56They're about whether our existing financial architecture, our risk models, our supervisory expectations, disclosure rules, or even our assumptions about human judgment are prepared for a world where some of our core analytic work is done by systems that learn and adapt at scale.
▶ 2:03:14At the same time, AI gives institutions the ability to detect threats faster than humans ever could, analyze complex data sets that were pre previously unusable, and and offer consumers services that are more personalized and more efficient. The challenge for Congress is understanding where AI is simply accelerating what firms already do and where it fundamentally changes the nature of a financial decision, a compliance obligation, or a market signal.
▶ 2:03:42My goal today is not to choose a side between regulation and restraint. It's to ensure that as AI becomes more embedded in our financial system and as said previously, it's here. It's not going away. Uh that we understand the concrete risks, the real opportunities and the limits of the technology and and I might argue the unlimited potential of the technology. We need clarity where clarity is necessary, flexibility where innovation requires it, and realistic view of how these systems operate in practice.
▶ 2:04:13Miss Manra, you mentioned grounding and outcomebased evaluations and AI risk management. Can you give a real world example of how grounding has corrected or improved financial AI models output or and how regulators should think about evaluating whether grounding was done I can get back to you on a specific example.
▶ 2:04:36Um but I would say in general the um the core to um what we need to focus on is the having transparency and explanability. And so as um which we have invested a lot in and work with a lot of our financial customers as they use AI for things like fraud detection, anti-moneyaundering um you know these various decisions that have this high-risisk to be able to ensure that they can go back and understand why the model made the decision or the recommendation that it did and
▶ 2:05:07enable um the compliance with existing laws that do apply to um to these scenarios as well. And so that is the space that I think is is very important is ensuring that transparency and that explainability um in particular for financial services though they're not the only industry um but to enable AI for these heavily manual but oftentimes high risk um with a lot of high false positives that put a lot of burden onto organizations.
▶ 2:05:35So I believe it actually can if organizations implement it responsibly you can reduce your compliance obligations better manage your risk and get better outcomes for consumers and partners. And for those that are watching at home, you know, the key here is that transparency and the understanding because the the financial institutions are required there's compliance requirements and if they're using AI to, you know, achieve those requirements to to be in compliance, they need to understand how AI is helping them get there, but then also understand where
▶ 2:06:06it may make mistakes or hallucinations. Right, Mr. Cohen? Your dynam dynamic MLO AI powered order type adapts to real-time market conditions. What specific signals or data streams does it rely on? And should investors have standardized transparency into how these AI assisted orders, order types behave? And unfortunately, you have 40
▶ 2:06:27I might come back to your details uh in
▶ 2:06:30but give us that overview. Right.
▶ 2:06:31So, we take in 130 different signals uh from the market to determine how that order type should operate. Every 30 seconds, we take that in because real-time market conditions. To give you a sense, we are processing millions of messages per second. And to be able to process all of that, we need to use AI to ensure that we're staying one step ahead of the market conditions that then allow our investors to get the kind of execution they require.
▶ 2:06:57And then and remember, we're highly regulated. So everything we do, we need to have the SEC approved. They need to make sure there's explanability and reproducibility on what we provide.
▶ 2:07:08Mr. Chairman, I'll just say that as we look at the national security landscape, the financial landscape, you know, our adversaries are leveraging AI without any guard rails, and we have to be prepared and ready to quite frankly go on the offense. Mr. Chairman, I yield
▶ 2:07:22Gentleman yields back. The gentleman from Missouri, Mr. Clever, who is the ranking member on the subcommittee on housing and insurance, is now recognized for five minutes.
▶ 2:07:30Uh, thank you, Mr. Chairman. Uh, I can also thank Mr. Lynch for for uh u kind of leading this effort. on on our side. Um I just have one question that's my my uh interest is in um AI grows daily and I am even more concerned today than I was yesterday.
▶ 2:07:58Um and if you look at what's happening in the federal government being reshaped by um uh the president and the Supreme Court, uh 75% uh of fair housing staff is gone. It's not like a couple of people, but has is gone since January.
▶ 2:08:30because I've been around I note that when we are talking about trying to deal with housing which is either the number one or number two most significant domestic uh issues we we face.
▶ 2:08:48I am my my paranoia is has grown stronger uh because uh I'm I'm concerned that AI could also be an excuse you know obviously this is fair goes along with some something uh that has was raised earlier fair housing I mean you know we're we're Don't worry
▶ 2:09:18about it. AI is going to make sure that everything is fair. I mean, after all, AI, you know, can't uh discriminate. Uh and and it it's infuriating uh first of all that this is already taking place in the government and then we got to deal with AI possibly doing even more damage to fair housing.
▶ 2:09:41Now, if we if everything was clear and equality was a part of everyday law uh, you know, I wouldn't even need to to raise this issue. But that's just not the case. And so at a time when we're when civil rights and fair housing uh are are issues uh growing issues instead of being Somebody help me understand uh how a AI why AI won't make this work
▶ 2:10:14I'd be happy to. Congressman working at Zillow dayto-day we totally believe that fair housing is paramount. I'd say an opportunity that AI we've already seen is you can just start describing what home you're interested in in a more natural language. No one wakes up and goes, I want threebedroom, big backyard, comma, like a human or like an computer would standardly want. Um, but with generative AI, you can say, hey, I'm I'm looking for that big backyard close commute to work, that kind of thing.
▶ 2:10:43The problem is there are certain fair housing questions that are not legally um supposed to be answered. And so that's what led to our fair housing classifier. It's probably one of the more complicated models we've developed at Zillow. And instead of going, okay, we'll just keep that to ourselves, we felt that the right thing to do to help other researchers, other institutions was to make that available to others. They can contribute back and of course use it in their own systems.
▶ 2:11:09So that means every deployable AI in the housing sector can take advantage of a fair housing compliant method. Well, and I appreciate that uh your your response. I'm wondering about the the others on on our esteemed uh panel today. Um do do any of you have a suggestion?
▶ 2:11:29Representative, may I respond to your question? Um
▶ 2:11:33there's an assumption built in with a variety of companies when they discuss the positives of AI. And one of those built-in assumptions is that AI is going to remain aligned to human values or American values. Uh what they're not acknowledging is the possibility of AI drift. That's when AI starts to drift away from what some of our values actually are. That's when you see instances of kids being encouraged to harm themselves or discrimination in banking decisions.
▶ 2:12:02And that's why it's important to have these regulations in place to ensure that these companies um are being regulated and ensured that they are making sure that their algorithms are working in place. And there are ways to do that. We've spoken a lot about China today. I don't think Americans have to choose between winning a hypothetical AI race in China or being protected from harmful AI products. I think that's a false narrative and a false binary. Thank you.
▶ 2:12:33Thank you. Thank you, Mr.
▶ 2:12:34Gentleman yields back. I recognize myself for five minutes. Um, I think we've seen a real positive shift uh in AI policy from the previous administration to the Trump administration. Uh, the Biden administration's uh precautionary approach was stifling uh innovation. The Trump administration's AI action plan try first approach is the right approach in my opinion and I think financial services have been leading the way and applying AI in the real world for decades.
▶ 2:13:04So I just want to get a couple instances on the I'll start with you if I can Mr. Cohen. Can you just describe a couple ways that NASDAQ is utilizing and has been utilizing AI uh in the financial services space?
▶ 2:13:16Thank you for the question. I'll go back to my opening comments and in that we focus on three core principles when we employ AI. I talked about liquidity, transparency, and integrity. With regards to integrity, our anti-inancial crime platform, Verafin, is allowing banks to operate with confidence when it comes to fraud management. And it's allowing them to achieve uh goals that they otherwise could not achieve on their own when they limit fraud in the market.
▶ 2:13:43So it's essential to to manage fraud, elicit trading um broadly in the risk space.
▶ 2:13:49Absolutely. And it and it does more than any single institution can do on its own because it's cloudnative AI enabled and uses consortium data.
▶ 2:13:57Let me jump to you Miss Manfra if I can. A good Wisconsinite. Uh good to see you here. Um can I ask you to to pinpoint how are firms in particular thinking about this uh when they're deploying this new technology? I would say and and reiterate what you've probably heard before as well is the financial services firm has a long history in managing model risk and um and there are processes and regulations and oversight in that place.
▶ 2:14:24And so what we see with our financial services customers is um as as you noted very innovative uses for this um these set of capabilities but also very thoughtful and um and so they think about things like how do I ensure human in the loop? How do I ensure I have proper governance in place? How do I ensure that I understand how I can meet my risk management and uh and compliance goals?
▶ 2:14:47So, so knowing that these firms are going through this deliberative process to think through how they're balancing reward and risk and utilizing AI, I want to come back because we discussed the sandbox concept earlier. I'm come to you with Mr. Cohen with a short question here, but earlier this year, Mr. M. Chairman Hill and I introduced bipartisan uh unleashing AI innovation in financial services act which enables uh regulatory sandboxes at the federal financial agencies that are targeted in size and scope. These sandboxes they have a handful of things.
▶ 2:15:17They got to be approved and overseen by federal regulators. They require complyment compliance strategies and risk management which we were just discussing. Uh they must not impose systemic or national security risks. Obvious to make sure we're doing that. So federal regulators will impose appropriate limitations or conditions on them and additionally fraud and unsafe and unound practices will remain prohibited under the sandbox.
▶ 2:15:42So the idea that these sandboxes create a freeforall and allow participants to flout all the rules they just don't like, it's simply not true, right? And so rather the sandboxes provide a more secure environment to experiment with AI enabling innovation with built-in guard rails, federal oversight.
▶ 2:16:03And so this is how I think we learn from best practices for governance while exploring the applications that'll provide American finan improve American financial life. So here's the question. Would these AI sandboxes enable regulars and market participants to responsibly experiment with AI and learn best
▶ 2:16:24Yes. And it the the key qualification is what you said. It needs to be controlled. It needs to be targeted. It needs to be time boxed and it can't be used to circumvent. And we have a very practical example of that. We as a highly regulated institution often run pilots with the SEC where we are really transparent about the results of that pilot and we ensure that the that informs decision-making allows for better outcomes for investors in the
▶ 2:16:48And so it's not really a free-for-all. It's a sandbox that has a regulatory structure in place. Underlying laws apply. Uh Ms. Manfra laid out how firms are thinking about applying AI. They're going through a deliberative thoughtful process. And so in your opinion, does sandboxes help create innovation and development in the United States in a thoughtful structured way?
▶ 2:17:08They have. They have. They've been critical to our innovation. And again, if it's controlled, time boxed, and targeted, and transparent, it yields positive results.
▶ 2:17:17I I appreciate that. Miss Whitmore, I wanted to take my time and come to you and discuss uh in particular how AI can eliminate fraud, deep fakes, uh and really help us in 10 seconds. Can you can you add to your previous comments?
▶ 2:17:34Excuse me. We'll be happy to follow up with a written response to that. Thank
▶ 2:17:37Thank you very much. I yield back. I'll now recognize the gentleoman from Ohio's Miss Batty uh who is also the ranking member of the subcommittee on national security. Uh she is now recognized for five minutes.
▶ 2:17:49Thank you, Mr. Chair and ranking. And thank you to the witnesses. Wow. Uh a lot of uh good testimony. and never thought about uh asking my grandchildren when we move what they'd like to take into a new house. So uh you put it in a whole new perspective uh for us. But a lot of words today on both sides of the aisle and and they all come together. You know, we've heard things like we need to strike the right balance. Uh we should not discriminate with AI. We should have accountability. It should be well defined.
▶ 2:18:18There should be responsible AI. We need clarity. we need legal and policy definitions. Uh and and all of that is true whether it came from uh the Republican or the Democratic side. I don't know that I've heard a lot of responses that are definitive to say here's how we're having responsible AI. And I have a a great concern.
▶ 2:18:42I serve as ranking member on the national security subcommittee and I'm focused on preserving the safety and the security of our financial systems and protecting consumers from fraud. So my my first question I'm going to try to get through a series of them. Uh Mr. Branch will start on this end. How is AI used in anti-money laundering and fraud detection and how effective is it as a tool in our illicit finance uh arena?
▶ 2:19:13Uh, Representative, thank you. But I I apologize. I'm not a AI uh fraud analyst. That's outside of my expertise, but I could have my colleagues get back to you.
▶ 2:19:23Okay. Anybody else want to take a stab at that?
▶ 2:19:28I can try. Uh, so we operate uh a financial crime management platform called Verafin. I've spoken about it here. It again it is cloudnative AI based and we take in uh we have over 2700 clients we have 725 million accounts just to give you a sense of how large that that pool of consortium data that we dig into is and we use that we use that to protect small and medium-siz institutions small banks super regional banks from the cost of fraud so they
▶ 2:19:58can operate and provide everyday customers and investors and clients of theirs the security that they deserve when they invest investor money and then have transactions associated with that institution. So that that solution is really uh paramount to creating safety and responsibility along the the traditional rails.
▶ 2:20:18Now we also are looking at non-traditional rails like crypto rails and others to consider how payments and transactions may be uh may be subject to fraud as well. So that that's where we're extending it, but it's incredibly important and valuable for small and medium banks. Okay, I'm gonna go to another uh question. Um, we talked about or someone on both sides said that uh we should not discriminate.
▶ 2:20:42Uh, one of my primary concerns about the use of AI especially in financial services or maybe not necessarily um with just financial services is the potential for bias in algorithms and that they lead to unfair results. you can only be good as the individuals that put the data or gather all the the folks in it.
▶ 2:21:05So as we look at um to develop a comprehensive AI regulatory framework, how do we ensure that the use of AI does not lead to discriminatory lending or pricing or underwriting or any other area that we use algorithms. Uh anybody want to take a stab at that?
▶ 2:21:27I'll thank you Congresswoman for the question. And I'll say uh I was first hired by Zillow to work on this estimate. And two answers would be additional data and then also a national right-siz framework that we can apply across the country on additional data. That's the benefit of Genai for for the Zestimate. We can now look at additional comparables maybe outside of your direct neighborhood to get a more balanced and fair evaluation.
▶ 2:21:54We can also look at the listing images, the listing description, all all this unstructured data that wasn't possible to be ingested before. At the same time, we have to do a lot of checks that that is the right data and there's no inherent bias within it. And that's where we use um like the NIST RMF framework to make sure before we deploy that it's a fair evaluation.
▶ 2:22:16And thank you for adding and saying that because you the outcome has to be that you have people from other communities and there's a diverse pool of folks at the onset. So it would help us not have discriminatory practices with that. Uh and thank you because I know for example women have not always been included in trials and so when you're building these algorithms you have to have people and examples that you put in.
▶ 2:22:45So, that's something that I'm watching carefully. Uh, my time is up and thank you, Mr. Styles. I yield back.
▶ 2:22:52The gentleoman yields back. The gentleman from Florida, M. Mr. Heridopoulos, is now recognized for 5
▶ 2:22:58Thank you, Mr. Chairman. I appreciate this thoughtful conversation. Uh, I know Congressman Licardo and I are working across bipartisan lines and trying to find solutions so it doesn't become a hyperartisan issue, which is, I think, all of our goal today, especially as we face this increasing threat from China. Uh we just had a hearing in my subcommittee that I chair on the threat in space and some of those challenges face course here on financial services a little bit different model.
▶ 2:23:22Um if I could um Miss Manro with uh Google if if I could um ask this question. One of the things that I've been concerned about and this goes across the gamut as far as age groups too are these deep fakes. this idea where AI is used, someone's reputation can be literally eliminated in a day because there's some type of fake video. What does a a huge company like yours do to try to identify these to take them either offline or to identify that these are deep fakes?
▶ 2:23:54I'll I'll say just to start um first thank you for the question and it's something that's been concerning for us for a long time and we've invested a lot in um um technical measures to be able to better detect um as well as making a lot of these um measures and processes that we've learned from available um to others to be able to do that and to rapidly be able to take those down. Um, and happy to get more details if you're interested in more of the specifics on the technology that we use to be able to
▶ 2:24:23I think that'd be very helpful because again, this is a reputational issue. It takes a lifetime to generate a reputation that can be destroyed in a minute. Absolutely. And I I think that this is especially true of not only politics but just everyday life. I mean, we've seen how people get hazed. Uh, bullying happen especially at the middle schools and high schools and and this could easily be done with just a basic technology. So any advice you all have would be great. I think the second one I'll ask with NASDAQ if I could. Um there is existing rules of the road.
▶ 2:24:53Um what are those guide rails sufficient for what you do every day in the investment world and are there enough recommendations that that our committee is putting out and that you're of course producing uh and providing for us? Where are we? Are the guard rails sufficient now? Are there a lot more guardrails needed in your opinion to make sure that the financial markets are protected from AI in a negative way?
▶ 2:25:17Our markets as you know are highly regulated and have uh a lot of transparency to ensure uh that we run our markets in a way that is enduring from a trust perspective. Trust is not a word we've spoken about a lot but trust is extremely important when we talk about our markets.
▶ 2:25:32So the fact that we are highly regulated run missionritical infrastructure requires us to have certain standards outside of just thinking about AI and I think we can use that as the foundation whether it's the the securities law it's regse SEI it's following this all of that are foundational what I mentioned earlier and I think is incredibly important as this technology advances and maybe creates gaps we need to make sure there's information sharing that we have a safe space to share information with one another
▶ 2:26:03about what we're seeing about what we're seeing with it within our own four walls and across the industry. So I think that would be what I would advocate for to make sure that we have what we need on a principal base and and from a federal level. Those are the two things that I think we would we would also want to see.
▶ 2:26:20Thank you. And Miss Whitmore, um what keeps you up at night about AI? What what is the biggest concern that's out there in your opinion? You see this every single day. We deal with a lot of issues every single day, but you're focused on AI. What is the the the the fear factor that you have wondering I hope they don't do this or this is it the threat that's most uh prevalent out there in the both the business community and and the general uh internet space.
▶ 2:26:44Uh thank you for the question congressman. Uh so first I think just a challenge that attackers are leveraging uh a AI for which is primarily speed and scale. So now we're looking at reduced time frames to execute a ransomware attack to 25 minutes and that includes from initial access into an environment to the time that they encrypt or steal data in that environment.
▶ 2:27:07The second is the concern uh that attackers are specifically targeting AI to then misuse it intentionally right and that requires the use of some specific guard rails to put in place. But in particular, uh, one, we can to solve these two challenges, right? We can, uh, we need to be fighting machines with machine speed. That's the only, uh, solution that we're going to have to transform the way that we detect and respond and to truly get to decreased numbers in both of those categories.
▶ 2:27:36And then second is the capability to uh ensure that as these uh systems are running within environments that we've got the critical levels of visibility into the actions they're taking so that when an attacker does decide to change uh the functionality of an agent and have it go rogue that we can detect that and stop it as quickly as possible.
▶ 2:27:57Appreciate the thoughtful answers to those. Mr. Chairman, I yield back.
▶ 2:28:00Gentlemen yields. The gentleman from Illinois, Mr. Casten, is now recognized for five minutes. Uh, thanks so much. Appreciate you all. Um, I want to focus on on specifically on securities regulation. Um, and I'm going to oversimplify, but uh, and I'm going to Mr. Cohen, I'll ask you to correct me if I've got it wrong. We've got federal securities regulation through the SEC. We've got an additional state layer with registrations and and licensing laws. And then, of course, the rules that the individual stock exchanges put in.
▶ 2:28:29Um, are are you generally supportive of that structure? um having those three layers of of regulation
▶ 2:28:37we are and and don't forget FINRA.
▶ 2:28:39Yeah. Yes.
▶ 2:28:40So we have SEC, FINRA and then obviously we we have our own if you will responsibilities as an exchange highly regulated exchange listing qualifications for instance.
▶ 2:28:50Fair fair point and I and I I I raised that only because I had some concerns about in your testimony when you supported federal preeemption of state laws related to AI. And so I just want to pick at this point a little bit. I'm concerned partly because, you know, the Trump White House has instituted massive cuts to SEC. So, if this is a three or four-legged stool, it's kind of a wobbly chair right now.
▶ 2:29:12And I get nervous about saying, "Let's shorten all the legs to make it work." But I also have a concern as a as an engineer, as a guy who built some AI models before I came here. Um, I don't think this is as big a deal as we talk about it. I think we use words, you know, we call it intelligence, but it's just it is a massive correlation machine.
▶ 2:29:32Um, it's not intelligent per se, but I can plug in, you know, huge amounts of data on the markets and historic trading trends and say, I want this algorithm using those historic correlations to identify relationships and optimize for profit margin. It can do that. It's really cool, right? I can plug in the entire Taylor Swift catalog and say put, you know, let's take a Tom Weight song and make it sound like a Taylor Swift song. I can do that. It's not intelligent. It's just massively correlative.
▶ 2:30:01And if there is no reason why anybody using an AI tool is necessarily incentivized to say, "Let me optimize this for truth. Um, let me optimize this for ethics. Let me optimize it for legal compliance. I'm going to optimize it for the thing that's valuable to me. Making something that sounds like Taylor Swift making, you know, making money in markets. And I I guess I I don't understand why, or maybe correct me if I'm mis misreading you.
▶ 2:30:32Wouldn't it be wise to prevent states from protecting investors from AI enabled market manipulation, especially if the federal government isn't doing
▶ 2:30:41And let me answer the the first part of your question. As an exchange, we're an SRO, self-regulatory organization, and we have a public mandate, and our public mandate is to ensure that we run fair and orderly markets, and we take that responsibility very seriously. So, our northstar is just that when we design solutions around our markets, we're thinking about making sure that
▶ 2:31:02Well, I wanted and I don't mean to cut you off. I'm just nervous about the clock here. I I was in the energy industry for a long time. I remember there was a there was a professor who did this experiment with a bunch of grad students where none of them had information but they were basically in a simulation of California power markets and they all independently just based on the other students trading strategy figured out how to collude and it it was when Enron blew up it was this thing of okay you don't actually have to have information to collude but there's an incentive to collude in the structure and people will figure it out.
▶ 2:31:31There was a University of Pennsylvania study recently that found that AI bots released into simulated markets will do essentially do the exact same thing. And so, you know, as an SRO, how do you if if we're not going to regulate, you know, if we're going to provide liability shields for these companies, it's not about whether the tool is good, but if we're not going to provide liability shields, don't we still have to get to that? And and maybe just to sort of put the punch line on it and then you can use the rest of the time.
▶ 2:32:00There's a long legal history within the courts, within the SEC of saying if there isn't intent to defraud, you can't hold somebody to account. And my nervousness is that a lot of the, you know, the people building these tools are saying, well, I want a liability shield. I want state preeemption. And if if the tool isn't designed not to commit fraud, it can still be optimized and end up committing fraud. So as a market manager, how do you protect against that?
▶ 2:32:26And what sorts of regulatory reforms would we need to do to modify some of these this history that you you need to show intent?
▶ 2:32:35Yeah. And just to be clear, in terms of federal preeemption, our view is around minimizing complexity. What you just described, you can achieve all of that at the federal level. You don't have to have it as a patchwork in each state where it's it's a struggle for people to figure out how to operate in that state. And it's not just the exchanges, it's our members that we think about and the industry at large. And again, being highly regulated, we do have a northstar about how we want to serve and what our business interests are.
▶ 2:33:03So, it's more about the complexity and it's more about the patchwork that we're concerned about. You we think we're going to solve for everything you just talked about at the federal level. I'm I'm out of time, but I would just welcome comments from all the respondents about there's a hole in in securities law and any ways that we could fix those holes to address this question of intent I think is important and would welcome all of your expertise. Yield back.
▶ 2:33:25Gentlemen, time has expired. Gentleman yields back. Um the gentleman from Wisconsin, Mr. Fitzgerald, is now recognized for 5 minutes.
▶ 2:33:30Uh thank you, chair. uh regulatory technology sometimes called regers to innovation in technology deployed by companies to manage regulatory compliance. Mr. Cohen, um how does NASDAQ uh use AI and other any type of machine learning powered by regg tools to kind of enhance the regulatory compliance such as trade surveillance um or how much just efficiency and cost savings has gone up?
▶ 2:34:01So, so we have uh two reg tech solutions that we offer. One is for market abuse surveillance and and the other is actually axiom which is a regulatory compliance and reporting uh application. I haven't talked as much about that today but that's important because it's used by all the tier one banks across the globe. It is the standard for regulatory reporting. What we do because we manage and orchestrate complex workflows through this tool is we use AI for data discovery.
▶ 2:34:30So they can go through complex regulations and understand and interpret how that piece of regulation needs to be implemented into the reporting obligations they have and also if they have any anomalies in their financial reporting, capital obligations, liquidity obligations, it may take them uh a handful of individuals hours, days, weeks to identify anomalies. We can do that through AI very very quickly. Keep the human in the loop.
▶ 2:34:58make sure that they're they're center in the center of any decision-m that can occur, but they don't have to do the heavy lifting to understand that there is an anomaly. And then also what we've done from a product development life cycle perspective, we're now taking regulations, reggg all the way to code through agents and allowing agents to hand off work to one another to take a piece of regulation that could be four to 500 pages long and allow them to implement it in our tool and then deliver it more quickly to our clients.
▶ 2:35:28And this is incredibly important in a world where the regulation is exponential in terms of the obligations that one needs to meet. They're changing. there's reforms. There's a different view in America versus where Europe and Asia are going. So just as a tier one bank or tier one institution to keep up with it, it it requires a lot of operational spend. We're trying to reduce your operational spend so you can do the things that you need to do.
▶ 2:35:53Put money back into your balance sheet then that you can then use for loans or for business that help small small businesses and their their
▶ 2:36:03Very good. Um Mr. Stevens, let me ask you the question first, and I was just maybe fill in afterwards. I'm kind of switching it on the paper here. How are AIdriven underwriting models helping to safely expand access to credit for a broader range of borrowers borrowers? Because there are concerns, I know that AI has led maybe to some riskier borrowers. I don't know how else to describe it.
▶ 2:36:29or that uh it's kind of changed kind of the perspective on borrowers compared to the due diligence that you know the human that sits down and fills out the form and and does does everything that we're typically used to. So I was wondering if you could comment on that idea.
▶ 2:36:46Yeah, thank you congressman for the question. The way AI is helping is looking at additional data sources that if we just left it up to humans, they might not have time to consider. And that I think is helping particularly first-time buyers qualify. But at Zillow, we make sure the actual decision making in the underwriting process, what we are pre-qualifying you for, for example, is completely human-driven. And so we still rely on humans making that ultimate judgment.
▶ 2:37:13Very good. Uh, Miss Manfra, the 1945 McCarron Ferguson Act left insurance regulation largely to the states with all the uh, talk of freeing financial services from the owner of state uh, regulation of AI. Um, notwithstanding the act, can the business of insurance benefit from being included in any national approach to AI?
▶ 2:37:42I can't speak to the specific regulatory framework of the insurance. That's just not an area of my expertise. But absolutely there are lots of benefits for AI in the insurance industry and I think would benefit from a um being a part of a national conversation and framework for standards of transparency and explanability.
▶ 2:37:58Has it advanced quick enough or far enough to really be a tool or is it something that's just kind of a sideeshow right now
▶ 2:38:06for insurance companies?
▶ 2:38:07Yes, for insurance companies. I I would say insurance companies are um using AI tools uh and it's very different in terms of the customers and um but absolutely they are using AI and and innovating around that for sure.
▶ 2:38:21Very good. Thank you all. I yield back.
▶ 2:38:23Gentlemen yields back. The gentleoman from Massachusetts, Miss Presley, is recognized for five minutes.
▶ 2:38:31Thank you to our witnesses for joining us today. AI is everywhere. our phones, our classrooms, our hospitals, our bank loans and job applications, every facet of our lives. And that is why we must ensure that AI works for everyone um and that um instead of deploying biased AI which can create harm or compound existing harms, it needs to benefit everyone.
▶ 2:39:01all people regardless of race, gender, income level, medical conditions, or other parts of our identity. Mr. Stevens, should we prohibit the use of AI that discriminates on the basis of race, gender, or other factors? Just a just a yes or no.
▶ 2:39:18Especially in housing, I believe yes. Fair housing makes sure that we uh eliminate all forms of racism, different disperate impact, that kind of thing.
▶ 2:39:26Okay. I'll ask the question of everyone just for the purposes of the record. So, just a yes or no. Should we pre prohibit the use of AI that discriminates on the basis of race, gender, or other factors? Yes or no,
▶ 2:39:38Mr. M?
▶ 2:39:40Mr. Cohen.
▶ 2:39:41Again, we apply three principles. We try to promote transparency, liquidity, and integrity in our markets.
▶ 2:39:48And as a highly regulated institution, we are making sure that we prevent that in our in our algorithm.
▶ 2:39:54Mr. Stevens, yes or no? Again,
▶ 2:39:58Miss Whitmore,
▶ 2:40:00And Mr. branch.
▶ 2:40:02Okay. Thank you. Uh we need urgently civil rights laws for the 21st century in the age of AI, which is why I've joined with uh Senator Marky and also with Congresswoman Evette Clark to introduce the AI Civil Rights Act. It's urgent because the truth is that we are already behind. People are already being exploited and discriminated against with the use of algorithms. Now, um let's take an issue like housing for example, which in my opinion is a human right. Everyone deserves more than just shelter. They deserve to have a home. its safety, its dignity, its health, its mobility.
▶ 2:40:33Uh, in 2025, the Trump administration has gutted the key agencies that protect against housing discrimination, the CFPB and HUD fair housing enforcement offices. They are even trying to undo consent orders that are already in place like the Townstone discrimination case in Chicago. This group, this gap in civil rights protections is an opening for continued discrimination.
▶ 2:40:54One study found that mortgage lenders are 80% more likely to reject black applicants compared to white applicants with the same qualifications. Mr. Branch, should we have additional oversight tools such as assessments to test the algorithms out before companies can use AI on the public? Yes or no?
▶ 2:41:15Do any of our witnesses uh other than Mr. Branch disagree with that? Okay. I let the record reflect that uh no one disagreed. Uh we know that bias exists in our nation. We see the inequities all around us.
▶ 2:41:29I represent the Massachusetts 7th of vibrant, diverse, dynamic district and one of the most unequal in the country where in a three-mile radius from Cambridge uh home to MIT Harvard and AI advancement to Roxbury, the blackest part of my district, life expectancy drops by 30 years, and median household income by $50,000. Now, that is the result of intentional lawmaking, which is why I believe we have to be just as intentional in undoing the harms and charting an equitable path forward.
▶ 2:41:58Because AI is trained on data that is already biased and by humans that have biases, it can replicate and exacerbate these harms unless we have oversight and prevent it. We must not allow AI innovation without AI protections. In a world of artificial intell intelligence, we really cannot lose sight of what is real and that is the people. The people and their livelihoods and their lives.
▶ 2:42:24Uh if Republicans are serious about protecting our elders from fraud and consumers from discrimination, then Congress must pass the AI Civil Rights Act. Thank you and I yield back.
▶ 2:42:37Gentle lady yields. Gentleman from Indiana, Mr. Stzman, is now recognized for five minutes.
▶ 2:42:42Thank you, Mr. Chairman. appreciate you all uh being here today. Uh before I forget begin though, I'd like to address some concerns raised by my colleagues across the aisle. The unleashing AI innovation in financial services act enables federally regulated entities to experiment with AI in secure environments overseen, approved, and subject to the conditions of their federal regulators, including for compliance and risk management.
▶ 2:43:09Importantly, the sandboxes must not present systemic or national security risk. Two, unsafe and unound practices and fraud remain prohibited. Three, the sandboxes under unleashing AI would be targeted, timelmited, and subject to regulatory approval and oversight.
▶ 2:43:30And finally, the participants compliance strategies must be approved by the appropriate regulator and who would retain enforcement authority subject to the terms the regulator sets. So, it's been great to have President Trump back in the White House for many reasons, but especially for the reason we're discussing here today. During the Biden administration, AI innovation was viewed primarily as a threat to the American people.
▶ 2:43:59While President Trump has set the country back on track towards innovation and American AI dominance on the world stage, we cannot have Biden's allies in anti-inovation states like California and Massachusetts setting the trend on overregulating AI. I'll follow Miss Presley's uh format and I'll begin with each of you. Do you think that a patchwork quilt or a patchwork of inconsistent AI laws would help encourage innovation or stifle it?
▶ 2:44:29Yes or no?
▶ 2:44:32Stifle or unstifle innovation and add complexity and burden
▶ 2:44:38Mr. Cohen.
▶ 2:44:41Add complexity and stifle.
▶ 2:44:42All right, Mr.
▶ 2:44:43Add complexity and stifle. I think too much complexity uh largely benefits attackers and not the defenders of our environments who are also looking to innovate.
▶ 2:44:55Mr. Branch,
▶ 2:44:57uh I do not believe that this stifles innovation. Um there's a lot of talk about different states that have different models. However, oftent times these state laws overlap and so it's not a fragmented 50st state um analysis that needs to be done. In fact, oftent times many of these states overlap and so uh they're not competing with a variety of state laws. The the language in the laws overlap and we see that in company valuations.
▶ 2:45:26Uh if this innovation is being stifled then these companies would not be worth trillions of dollars and America would not be leading in the AI race which we have been since the inception of this AI race. But you don't think that having federal guidelines and then having states having their guidelines that's going to create complexity and actually people just finally say we're out.
▶ 2:45:48Well, respectfully, uh, Congressman, the states have had to step up because we don't have federal guidelines and they're actually begging for the US federal government to pass some form of regulation, but they've not passed that regulation and that's what the American people are waiting for Congress to do. All right, Miss Manfra, isn't it true that many of our existing risk management frameworks and governance practices already apply to AI?
▶ 2:46:19So, following up a little bit, can we update our guidance to be fit for AI without reinventing the wheel here?
▶ 2:46:27Absolutely. As has been noted, um the existing laws do apply. However, there are areas such as ensuring transparency and explanability as we've discussed, maintaining human in the loop, some of these other areas where it's important to clarify in existing rules, but we do not need new.
▶ 2:46:45All right. I want to talk a little bit about the risks a bit. Um, we've had algorithmic trading in this country for decades, and these models are increasingly uh incorporating AI. Um, one concern I've heard is that AI and machine learning could exacerbate hurting Uh this is where trading models end up encouraging the same activity across firms because firms are using the same or similar models. Mr. Cohen, what do you make of the risk posed by model
▶ 2:47:14Uh that risk existed uh before AI. Uh and so you might have individuals that work for one firm go to another firm and design models that are very similar to one another and therefore exacerbate volatility or have the hurt effect.
▶ 2:47:28uh and so post some market events over the last 10 to 12 years we the SEC and the industry have taken action to ensure that we have volatility guards we put in regi we've put in a a number of different rules to protect the marketplace but maybe most importantly we've asked those that are introducing algorithms to test them and then monitor monitor them throughout their life cycle because it may be that a a trading strategy is in the market for three four years but a change in market condition
▶ 2:47:58then snaps the algorithm. And so we we are we're really focused not just on the testing of it when it comes into the market, but the monitoring and the transparency we have once it's in the market. And FINRA has a responsibility to go into all of these broker dealers and make sure they have written procedures that they test it, they monitor it, and they're taking care of it in a judicious manner. Do you know is that happening happening frequently or is it just on occasion that you're seeing a hurting uh strategy?
▶ 2:48:28Is it daily? Is it weekly, monthly? I mean, does it happen? How often?
▶ 2:48:34I wouldn't know the exact details around that. We can come back to you on that
▶ 2:48:38All right. Thank you. Thank you, Mr. Chairman. I see my time's expired. I'll yield back.
▶ 2:48:42Gentlemen yields. The gentleoman from Texas, Miss Garcia, is now recognized for five minutes.
▶ 2:48:47Thank you, Mr. chair and thank you to all our witnesses here today. AI will impact every industry, every line of work and every type of business in the near future. I think we can all agree to that. AI has potential to save employers on labor costs and increase productivity. But it can also disrupt workplaces and lead to loss of millions of jobs at home. And my district is a workingclass district, 77% Latino.
▶ 2:49:15Many of my constituents are concerned, in fact, deeply concerned about how AI will impact their jobs and their livelihood. Mr. Branch, could you quickly discuss what the private sector, Congress, and the public sector can do to best address workforce challenges as AI becomes more widely adapted?
▶ 2:49:35Thank you, Congresswoman. Um, they can speak with these workers and allow for worker input. They can uh speak with unions. Many unions are discussing algorithmic pricing. Um they're discussing uh wages and the necessity to ensure that there are fair fair wages as well. So I would encourage them to collaborate with unions and their employees. Thank you.
▶ 2:49:57You also mentioned in your testimony how a how it it is to how how important it is to include the states when crafting AI policy. I mean, I think you just just said that you need the national framework and then the states will act and states actually have acted because the federal legislation hasn't acted. In 2025, 38 states have adopted or enacted around 100 measures. More than that, Colorado and Texas both enabled omnibus legislation regulating AI.
▶ 2:50:27In fact, our governor just signed a bill um to that effect. It will go into effect in January. uh and uh it's a new regulatory framework that applies to developers and deployers of AI systems. Many of the witnesses today spoke about the importance of cooperation between the federal and state policy makers. Despite this, President Trump shared his intent to enact some type of AI moratorium through an executive order via social media just yesterday.
▶ 2:50:57As someone responsible for NASA's financial technology division, Mr. Mr. coin would would it be practical uh what would be the practical impact of such a moratorum on consumers and investors so NASDAQ we don't serve retail investors directly institutions are customers and from our perspective again we we want to make sure that there's a balance between the the types of rules and regulation that come in more principal based allow us to advance
▶ 2:51:27the technology and innovate while make sure it's safe and responsible and We think from the the perspective of the governance we have internally the foundation of the rules that we have in the marketplace today following NIST gives us that great foundation that we can build off of.
▶ 2:51:41But what would a moratorum do
▶ 2:51:44in with respect to
▶ 2:51:46the impact on NASDAQ and in the work that it does?
▶ 2:51:50I I think we've been operating in a space with uncertainty already. Uh so I I don't think that it would have a a significant impact on us if there was a The Trump administration's AI action plan and recent actions pursue an aggressive deregulatory approach to AI dismissing the role of both Republican and Democratic states.
▶ 2:52:10Rather than leveraging existing regulations and enacting new riskbased and proportional regulation, President Trump and congressional Republicans have tried to fail and failed twice to pass broad federal preeemption. Mr. wrench. Can you shed some light on how state AI laws have helped to fill the current federal enforcement gap in areas like algorithmic discrimination and consumer
▶ 2:52:35Yes, thank you for the question. Um, states have stepped up to the bat in response to Congress not passing federal legislation and they've listened directly to their constituents. They've passed laws in terms of deep fake non-consensual images. They've passed laws with regard to um pricing as well as discrimination and uh this would essentially be usurping the state's abilities to protect their own consumers. This is something historically in the United States has been a right reserved to the states.
▶ 2:53:06Uh there's never been a previous administration that has directly assaulted uh the state's abilities um to protect their own consumers. So this is a very unique situation.
▶ 2:53:17Thank you. And um Miss Whitmore, I know I served on the um the AI task force that was working group that was put together from um this committee and it always struck me as the final question really becomes, you know, who is who is auditing and who is monitoring and making sure that that the AI who's monitoring AI and who's going to make sure that everything they're doing is safe, secure, and something that will not negatively impact
▶ 2:53:47uh everyday
▶ 2:53:50I I think you're articulating the criticality of security being closely coupled with AI innovation so that we can answer those questions uh very clearly and ensure that the communications that are occurring uh are
▶ 2:54:05Thank you. The gentle ladies time is
▶ 2:54:07Thank you.
▶ 2:54:08The gentleman from Texas, Mr. Williams, the chair of the House Small Business Committee is now recognized for five
▶ 2:54:14Thank you, Mr. Chairman. Thank all of you for being here today. Uh artificial intelligence and the banking sector are two industries that are working together handinand. And for financial institutions, artificial intelligence is a valuable tool that allows them to navigate risk assessments and stress test, detect and prevent fraud, assist with regulatory compliance and several other critical operational duties.
▶ 2:54:35Now, my district back home in Texas, Fort Worth, and around in the metroplex and and out out west uh in uh is loves their community banks who are the backbones of their communities. And as artificial intelligence continues to uh change the landscape of banking, it's crucial that uh we uh we ensure that AI is empowering rather than complicating the work of community banks.
▶ 2:54:58So, Miss Manfra, what would we be thinking about to ensure that these technology, this technology can reach community bankers, allow the importance they offer to grow and flourish and help people like myself in Main Street America?
▶ 2:55:13Thank you for the question, sir. I think one of the opportunities, one of the greatest opportunities with with AI and cloud and associated technologies is the ability to bring access to data and capabilities that historically was only reserved for people with deeper um pocketbooks as it were. And so um being able to empower community banks and other smaller organizations that are more resource contain constrained, AI can give them access to that data in more real time.
▶ 2:55:42It also allows them to um to benefit from those efficiencies with the limited staff to be able to provide better services to their customers and maintain that um that trust that you noted in in communities. I think what is important is ensuring that um we don't create regulatory burdens that unfairly impact um organizations that have less resources to manage those would be my final point
▶ 2:56:08Thank you. AI tools are reshaping how businesses grow and enters capital markets. I see that in my business. I'm in the car business. And tools that help companies analyze market trends, each uh reach investors, prepare for fundraising used to be available. Only the largest firms unlimited resources. Now, artificial intelligence has the potential to level the playing field by giving smaller and emerging companies better insight, data, and more efficient ways to market themselves to investors. So, Mr.
▶ 2:56:33Cohen, how is AI changing the way smaller companies prepare for for and access public markets?
▶ 2:56:41You touched on a really important point, which is if we get AI right, it will democratize uh the way that small businesses can access and have access to the same tools as large businesses. They don't have the engineering talent, maybe the R&D budget uh and maybe the sophistication of the larger firms.
▶ 2:56:59So it's up to companies like us to provide capabilities, make them available to those companies, whether it's on the capital raising side of the house or in the secondary trading side of the house to ensure that we when we put these capabilities out there, it's for all investors. It's for all of the individual and corporations that we serve and that allows them, if you will, to level the playing field and then grow their businesses.
▶ 2:57:22Great. Miss Manford, in your testimony, you highlighted Google's use of artificial intelligence to combat moneyaundering, fraud, and scams. And across the world, organized fraud uh syndicates are stealing billions of dollars a year from hardworking Americans. And one of the biggest challenges is the speed at which these schemes operate. And it takes only seconds to steal personal information, drain bank accounts, or even compromise identity verification systems.
▶ 2:57:46So we must give law enforcement the tools to keep up with the pace of these scams and improve the flow of information between victim to agency and across the agency. So my question here in the remaining time is could you explain how Google is using artificial intelligence to improve uh information sharing in the case of fraud and scams and specifically how does this real-time data uh sharing up the banks and uh and credit card companies stop funds from flowing to these overseas scam rings faster?
▶ 2:58:17Uh there's two aspects to it. the work that we do internally across all of our various different platforms to um stop, you know, fishing, scams, fraudulent website, fraudulent ads, fraudulent reviews, um building an ecosystem around Android that I talked about in my testimony. Um so we have invested a lot in the use of AI and ML um to be able to prevent those um for those who use Google platforms.
▶ 2:58:41We've also taken those capabilities and working with partners in particular in financial services to be able to do things like using AI for um preventing uh money laundering and we're seeing huge benefits in that. Um fraud detection has been a use case for u machine learning for a very long time and continues to grow. So reducing those uh false positive rates so that investigators are able to spend their time on um useful and productive leads.
▶ 2:59:08Um, and then also just being able to, we have one customer, a banking customer who experienced a four-fold increase in the detection of suspicious activity at the same time reducing by 60% the volume of false positives. So, they're identifying more and having more productive investigations as a result.
▶ 2:59:27Thank you very much. I yield my time
▶ 2:59:30Gentlemen yields. Uh, the gentle woman from Michigan, Miss Talib, is now recognized for 5 minutes.
▶ 2:59:35Uh, thank you, Mr. Chair. Um, you know, one of the things that I continue to hear obviously is all the great things about some of the technology, including AI, but I think we're not realizing the way the uh corporate America is and is set up is very profit driven and the abuse is going to be very clear that everything is being going to be modeled around profit first. Uh, no matter how much people are like it's going to make this or easy or that easy.
▶ 3:00:02uh just New York Times publishing article after article about some of the abuses we already see and I'm really concerned of course on on the cost of prices and the fact that private information is being used to price groceries groceries. So I'm going to walk into a place and they're going to gather my private uh and use that to price it differently than the person that comes right after me. It it's discriminatory. It's private data and information.
▶ 3:00:32It doesn't belong in grocery stores. And I know Mr. Branch, you know about stop um price gouging and groceries act that I I would like for you to talk about surveillance pricing. I was with seniors and I was trying to, you know, explain to them how surveillance pricing is going to be used in a way not to reduce cost but actually to be able to price uh higher um on cost because they know where they work, they know what income they have, what they were searching online.
▶ 3:01:03Um, and so for folks that are out there right now, can you talk about what that means right now, the use surveillance pricing by some of the big
▶ 3:01:13Yes, thank you for the question, Congresswoman. Um, in this new age of AI, the power is data driven. And the largest companies on Earth own all of that data. And so from a consumer perspective, there's a mismatch there because consumers only see the price that's in front of them, but the large companies have all the information from the consumer.
▶ 3:01:35And so, you know, uh, Consumer Report actually just came out with a report uh, just the other day that showed that, uh, grocery prices based on algorithmic pricing can increase individual consumers, uh, grocery bills by $1,200 over the course of a year.
▶ 3:01:52And so we're going to find ourselves in a situation where Americans are struggling and struggling to make ends meet and these these uh companies are arguing that it's just about everything else when in reality it's the algorithms that are setting the prices and manipulating them and taking advantage of the data that they have that the consumers are not uh privy to.
▶ 3:02:13And and that's in combined to the digital pricing, you know, explain to folks. So, so bye-bye tags that they have, it's going to be digital. Explain how that's connected.
▶ 3:02:24Right. So, dig digital pricing um can involve the price of certain goods and those goods can um differentiate between different groups of people oftent times based off of shopping behavior. So, if you happen to like wheat thins for example, wheat thins are going to be more expensive for you by maybe a quarter, maybe a nickel, whatever it is. But that little incremental amount ends up adding up over the course of the year and over the course of your grocery bill
▶ 3:02:52Mr. Chair, I ask unanimous consent to enter into the record uh article. Goodbye price tags. Hello dynamic pricing. Shopping has always been a game and now it's being rigged against you.
▶ 3:03:05Um I want to now talk about the discriminatory factors that are going to be at play because I see this in the auto insurance industry that they already use and collect data. factors like your marital status, your education level, your credit score used towards auto rates right now without the the kind of technology and adding that and compiling that on to decide how much to pay uh charge somebody for auto insurance in Michigan.
▶ 3:03:30It's it's mindboggling uh that your son's GPA or your child's GPA has anything to do with driving rank, but they're asking for that data as well. What happens when AI models now and using this technology are trained on historic or contemporary um data that reflects past or present Doesn't this risk create models that perpetuate or reinforce discriminary practices because it's teaching it to go around um telling on themselves?
▶ 3:04:00That's correct, Congresswoman. I mean the thing that a lot of folks don't necessarily understand about AI is that its goal is to uh move towards its goal as efficiently as possible. And so um that can be replicating discrimination. Um that can be just trying to get the best price possible for the corporation or for the business at hand. And so again I think that leads back to the fact that a lot of these companies have the data and the power.
▶ 3:04:26Mr. Branch and I I need my colleagues to know this. They're not going in there and saying, "How can we make this cheaper for the consumer?" They're saying, "How we can make it cheaper internally so we can even char." But they they're going to charge our residents more using this technology. And we need to face the fact that that is exactly what's going to happen. This thing of pretending it's going to make things easier, it's going to No, it isn't. It is going to charge people more because they're going to know all this private information, know that they need these products and charge them more.
▶ 3:04:56Even if it's 10 cents, that's 10 cents too much for our residents. Thank you.
▶ 3:05:01Gentle lady's time has expired. I now recognize myself for five minutes. So, thank you all very very much by the way for being here. Um, it's a terrific uh panel and highly informative. I think you're aware that u many of us the leadership of this committee as well as the Trump administration is committed to unleashing AI's full potential.
▶ 3:05:26So we indeed in the United States wins the AI race uh with investment and energy dominance to support the AI infrastructure. My home state of Pennsylvania is doing everything we can to draw in as much AI infrastructure as possible. Um the uh however it brings risks uh that we're talking about and exposing here uh which are happening now and we want to mitigate for the future.
▶ 3:05:53uh they definitely include fraud, scams, profiling um and seem to be growing more sophisticated. So um you know AI is proving to be a incredibly strong tool for detecting and shutting down these very threats but as well creating them. So, um, Miss Manfra, I'd like to first start with you.
▶ 3:06:16Uh, and first off, thanks thank you to Google for the good work that you folks seem to be in the lead of, uh, mitigating and finding out scams and, um, addressing them in the in the in a in the manner that they they should be because it's a really serious problem facing all walks of life in in our constituents and consumers throughout the United States on the international level and on the local level.
▶ 3:06:41And I I know I don't have to tell you that, but um but um you're you recently highlighted the use of AI to uncover a Chinese linked operation known as Lighthouse, which reportedly targeted Americans with Easy Pass, Postal Service, fraudulent messages, demanding payments to settle fines um and very other common scams uh that my constituents often encounter.
▶ 3:07:03Can you describe how Kougal what you did to identify this lighthouse operation and what role AI um detection played in ser in uh surfacing those camp those scam
▶ 3:07:16uh to first let me say that we'd be happy if you're interested in further deep dive to follow up but generally what we do is we have um uh threat intelligence um individuals um and um detection capabilities that use advanced technologies including AI um that um are increasingly fi more finely tuned and able to spot both scale but also be able to identify networks of organizations that are using um our infrastructure and our services.
▶ 3:07:46So it's a combination of all of these things coming together to identify this um and then you know of course then the partnership with law enforcement to um to ultimately bring this down.
▶ 3:07:56Well that's that that's great. Congratulations. Um, how do you envision and even how is AI playing a role in financial fraud and scam prevention? I think AI and and ML is um because of the it's the scale um and um it's been quite helpful for many years now and um the newer technologies and AI even more so again and being able to detect um various different networks in addition to being able to be very good at um filtering
▶ 3:08:27out the signal from the noise if you will which is a huge challenge for fraud detection and also getting very good at um being able to um reduce the noise around false positives which organizations spend a lot of time when they get an alert um they have to you know go chase that down go investigate that so as our AI and ML capabilities are getting better they're becoming more targeted they're reducing that noise that financial organizations have to deal with and they're better able to um deploy their
▶ 3:08:57investigators and their teams in the same way
▶ 3:08:59great if that formula could be socialized elsewhere and not be a competitive model within within fraud it would be great for that to serve and help others. But I I need to move on. Thank you very much, Mr. Cohen. NASDAQ has been at the forefront of deploying AI to monitor markets. Last year, NASDAQ introduced dynamic mellow uh uh which stands for, as you well know, dynamic midpoint extended life order designed to ensure the best trade execution for the investor. Can you briefly walk us through it?
▶ 3:09:28Yeah. So, so Dynamic Melo employs a a delay that it's almost like a timer that we put on the order so that institutions who are trading lot large blocks of shares can avoid price impact when they try to execute those shares. So, we take in 130 data points to help that institution to identify the ideal time to trade. And as a result of that, after they trade, there's no price movement.
▶ 3:09:53And the result of that is the individual investors that sit behind those large institutions get a better price, get better price execution and benefit from that order type. And we have grown that order type by 50% because of the success we've had.
▶ 3:10:08Well, it sounds terrific. Uh thank you. My time has expired. I yield back. Uh now I want to recognize the gentleman from California, Mr. Micardo, for five
▶ 3:10:18Thank you very much, Mr. Chair. uh appreciate the testimony and um thank all the witnesses for taking time. Uh Miss MRA, it's good to have uh somebody from a local neighborhood business uh from district 16 here. Uh and I I should tell Mr. Stevens, my wife is probably one of the people who crashed uh the system when Zestimate came out. She's um a big Zillow addict. Um and Whis Miss Whitmore, I know um you employ many of our residents even though you're just next door. So we appreciate having you all here.
▶ 3:10:48Um I I'm brand new here to Congress, but I observed in my 45 or so weeks here that there is essentially a paralysis uh in Congress about AI. Uh it seems to be born of a few basic challenges. One is that we generally don't um uh regulate tech very uh timely or effectively. Anyway, we've been waiting about 30 years for uh any kind of regulation or statute governing digital privacy.
▶ 3:11:17uh folks have been waiting for us to update section 230 to make social media platforms safer and we've waited about a quarter century for that. Um and so that is a basic challenge as we approach AI to be sure and I think there are a lot of doubts about whether or not Congress is really terribly effective or competent at this. Um I think many of us were still trying to learn to spell AI. We are still uh I think we recognize this technology is moving very quickly.
▶ 3:11:44we can't possibly legislate the pace of the technology that is changing. Um, and in the absence of this congressional action, we now see 50 states rushing in. I think this year alone, we've had 36 states that have approved more than 100 pieces of legislation governing AI. I appreciate that is mightily difficult for an industry to navigate. Uh, and so now the counter uh or the reaction is we need a moratorium on everything states are doing.
▶ 3:12:13Um, and that's an understandable reaction. I don't support a moratorum without some kind of sensible federal regulation to actually supplant it. Uh, but I certainly understand and appreciate why industry would need and want it. Uh, given the fact that we are an international arena and certainly China doesn't have 50 states trying to regulate the industry as we do. Um, and and I think look, as was pointed out, 97% of Americans do support uh some regulation AI and that's for good reason.
▶ 3:12:42I'd like to see how we can move beyond this binary debate that has us stuck between moratorum or no moratorum. I think it's preventing sensible uh legislation and sensible regulation from moving forward. And so I wanted to sort of imagine that we took a different approach and I'd be interested in any feedback you might offer that the the approach we take would would focus on outcomes. I don't think anybody here I certainly don't know how exactly to regulate algorithms or model weights.
▶ 3:13:12Uh and I think outcomes is something we can measure and the good news is we have laws that regulate outcomes whether it's discrimination or fraud or anything else. We should be able to do that. Um we should be relatively techneutral when we talk about financial service providers who use AI just like any other tool. they should be held to the same standards uh under for example fair housing act or anything else uh that that that govern them whether they use AI or not.
▶ 3:13:37Um and certainly uh LLMs u we know uh and since we have one representative from that community um you know we recognize there's real challenges here in in trying to simply uh get involved in the machines. I don't think most LLM developers are particularly good or will admit I think they admit that they're not terribly good at explanability of their models.
▶ 3:14:06Uh we wouldn't have a hallucination if we thought we could transparently eliminate it. uh and so that perhaps a better approach might be to take away from Congress and have an independent commission of some kind industry experts academics and others who can set essentially industry best practices establish what is the technology uh whether it's around security privacy uh a host of other measures fraud detection whatever it might be here's the industry best practices and if the model meets it great you have preeemption
▶ 3:14:38uh you also have a standard of care that you've met uh and if If you don't, then good luck navigating the thicket of 50 different rules. I guess I'll ask I'll start with you uh Miss Mro. Do you have any sense about is that something that uh is viable in terms of how we can move forward with sensible regulation?
▶ 3:14:58Yes sir, absolutely. Thank you for the question. I think you know this is already happening. um industry is working together um through formal and informal channels um you know at Google with partners um across industry um we've part we've created the coalition for secure AI um and so committing to research and this is you know with Microsoft with Amazon with other partners across industry um to drive best practices aligned with um what we
▶ 3:15:28have learned internally in the development of large language models and others um we have deployed toolkits um for our partners and guidance based again on what we've learned um and and I do agree with you is focusing on outcomes is I think the priority and we
▶ 3:15:46time has expired that's a important answer but thank you very much gentleman yields back
▶ 3:15:50I yield
▶ 3:15:52uh the gentleman from Georgia Mr. Laddermilk is now recognized for five
▶ 3:15:57well thank you Mr. Chairman, thank everybody for being here. This is an extremely important discussion we need to be having. Um, and I think it's timely as well. But, uh, I spent 30 years in the information technology industry. Um, 20 years in the public in public service in the state legislature and here in in Congress.
▶ 3:16:18When I first elected the state legislature in 2005, I was uh probably one of the few technologists in uh in the state legislature at the time. So, I took the lead on a lot of policy initiatives. And one thing that I brought up at the time, I mean, if you look at device here, everybody's got one of these, right? The least used part of this, ironically, is what we call it, the phone, right? That's the legacy part of this.
▶ 3:16:48And uh I I've literally talked to people in younger generations than mine that have literally never used the telephone feature of this device. And part of the reason is is it wasn't the phone that that led to the massive technological development that we've seen today. It was the internet and it was broadband. Ironically, those were the least regulated aspects of technology.
▶ 3:17:15I if you go back and you look at the at at the massive growth and technological advancements um it wasn't over the wired network it was over um broadband uh the cable television network which was not heavily regulated as the big cell or the big uh carriers were.
▶ 3:17:37So with that in mind, what we've seen from history is government can seriously stifle innovation if it's overly And so it's it's kind of a balance that we strike because we do have a a need to put guard rails up but to leave this sandbox available for innovation. And um so I think that's where we need to be looking especially when it comes to tools like AI.
▶ 3:18:07There are benefits to that and there's also reason to be fearful of the misuse of AI. So miss man for um modernization of the bank secrecy act is is an area of great interest to me. have put a lot of effort into that over the past several years and uh especially the significant obligations that uh Bank Secrecy Act imposes on financial institutions to monitor and report potential elicit finance activity.
▶ 3:18:37It's especially impactful on smaller financial Keeping in mind, we have not modernized this thing since the early 1970s when the thresholds of $10,000 were put in place, which if it had been adjusted would be $80,000 today. Um, how do platforms like Google Cloud help financial institutions automate processes for generating CTRs and suspicious activity reports?
▶ 3:19:08Um we have a couple of different offerings um particularly around um anti-moneyaundering um tools that we have co-developed with our partners um to ensure that they are able and again this goes back to some of the questions around transparency and explanability of the model to ensure that it's getting to the right decisions but as I mentioned um our customers are seeing um huge improvement in detection as well as a reduction in the uh the uh false positive as well, which has been um
▶ 3:19:38hugely impactful to actually finding the true, you know, risks, the true illicit finance um and um in being able to more effectively deploy their investigative resources and and more successfully uh report on suspicious activity.
▶ 3:19:52I think it's really important with SARS, especially because what I hear from a lot of financial institutions is we're we just don't want to get dinged by the federal government, right? So they may report a SAR that the local bank president may know is not suspicious for that particular customer but the same action may be suspicious for someone else but to save the integrity of the bank from uh any uh action by regulators they'll report it anyhow.
▶ 3:20:20Um can you talk about how Google Cloud's AMLAI system uses explainable risk scores and ensures they are auditable for
▶ 3:20:30Yeah, thank you for the question. um we've invested a lot in explainable AI and so you know in the end getting to a point where the um the the customer or auditor or regulator is able to go back and look at how was a decision arrived at um so that you can you know address redress uh of a decision or auditability for the purposes of um compliance.
▶ 3:20:54And so we do offer that um and um work with very closely with our customers especially in the financial services um um in particular for AML although it's used in other areas as well.
▶ 3:21:04All right. Thank you. I yield back.
▶ 3:21:06Gentlemen yields. Gentleman from New York Mr. Torres is now recognized for 5
▶ 3:21:11Thank you Mr. Chair. One of the greatest challenges confronting America is the utility affordability crisis. Uh the proliferation of data centers is one of the drivers, not the only one, but one of the drivers of rapidly rising electricity cost in America. Utility rates and returns depend not on efficiency or affordability, not on performance, but on capital spending. The more utility spends on infrastructure, the more profit it earns, and the more customers pay. The electricity cost of new data centers are therefore socialized.
▶ 3:21:42So given our broken system of utility rate setting in America, how do we ensure that the tech companies rather than working-class families and small businesses are the ones shouldering the cost burden of new data centers? So Mr. Branch,
▶ 3:21:58thank you for the question. Congressman Public Citizen believes it's critically important to be collaborating with local communities to ensure that they're uh looped into the process of when these data centers may or may not be um built. And we argue and we're seeing it across the country that a lot of these communities are fighting back against these data centers. But just as importantly, we need to ensure that these large tax incentives are not provided to these data centers because that ultimately ends up being dispersed throughout consumers.
▶ 3:22:29And that's why Americans across the US are seeing their electricity bills skyrocketing.
▶ 3:22:35You see, I'm I'm pro AI. My whole life is integrated with Chat GBT and Gemini. So for me, the question is not whether we should have AI. Of course, we should have AI and we need data centers to enable AI. The question is who should pay for it, right? Should should the cost be borne by working-class families and small businesses or should it be borne by the owners and operators of the data centers? What say you?
▶ 3:22:59I think these data centers are worth a lot of money. These corporations make a lot of money and they should be footing that bill responsibly.
▶ 3:23:08There are tens of millions of Americans who have next to no credit history. TransUnion estimates the number at 45 million. FICO, more than 50 million. Experian more than 60 million. In the Bronx, I have thousands of constituents who have paid their rent and utilities on time and in full for decades, who maintain steady income and sufficient bank deposits, and yet who remain deprived of a credit score. And without a credit score, you have no access to credit. Without credit, you have no access to home ownership.
▶ 3:23:38And without home ownership, you have no means of building equity and passing down wealth from one generation to the next. And so America's exclusionary model of credit scoring has done irreparable intergenerational damage to working-class communities in places like the Bronx. Does anyone here have any thoughts on how we can harness the power of AI to build an underwriting system that is more predictive, more inclusive, and more representative of the full financial reality of working-class
▶ 3:24:09I'll take a stab, Congressman. I really appreciate the question. Of the four million families that are going to buy for the first time this year, most of them are previous renters. And at Zillow, we are big fans of working with TransUnion, Equifax, and others to consider those on-time rent payments as part of the larger equation.
▶ 3:24:30Um, and so we believe that AI is that ability to look at disperate sources of information that otherwise a loan officer or underwriter wouldn't have time to consider it and then ultimately leave it to them as humans to make the right decision on what to underwrite.
▶ 3:24:42Because we should harness the power of AI not only to disrupt but to democratize finance and access to credit is exhibit A.
▶ 3:24:49The federal government is drowning in vast oceans of data. For example, in Fininsen received a staggering 4.7 million suspicious activity reports, an average of 18,8 12,870 a day. Now, there's no agency in the federal government that has sufficient human resources to thoroughly review millions upon millions of reports. And so, valuable information can easily disappear into the black box of bureaucracy.
▶ 3:25:20You know, AI can process vast quantities of data that the human mind cannot process. It can recognize patterns that the human mind cannot readily recognize. Do any of you have thoughts on the role of AI in facilitating not only finance but also financial regulation and So, as NASDAQ employs AI and a surveillance solution, so we're trying to root out market abuse uh through our surveillance solution and we use AI to do that.
▶ 3:25:50One great example, and it just keys off of what you said is a human investigation analyst comes through many, many possible market manipulations. How do they know which ones to pay attention to? How do they know which ones to let go? We use AI to help you number one do all the manual tasks, the series of tasks that you would otherwise go through to make that analysis. We provide you with a risk score. So then you can focus on the bigger issues, the most important issues affecting our markets. That's how we use AI.
▶ 3:26:20And we always again, we have the human making the complex judgment decision around that, but we're just reducing the manual workload to get to that decision.
▶ 3:26:29Thank you. Thank you. I now recognize my five myself for five minutes. Thank you witnesses for being with us today. Like other areas under the digital assets jurisdiction, artificial intelligence is a transformative technology that will shape how American companies, consumers, and investors engage with our financial system.
▶ 3:26:50If the United States is going to remain a global leader in innovation, we must adopt clear and harmonized rules that support technological progress while also protecting consumers and preserving market integrity. Industry leaders are increasingly concerned about the growing patchwork of state laws related to artificial intelligence. These state requirements often conflict with one another, whether in the form of impact assessments, documentation standards, or definitions of high-risk systems.
▶ 3:27:15For firms that operate across the country, these inconsistencies can create significant operational challenges, especially when artificial intelligence supports critical functions such as fraud detection and cyber defense. Without a unified federal framework that replaces duplicative and contradictory state rules, we risk higher compliance cost, slower innovation, and weaker protection for consumers. Miss Manfra, Google Cloud supports financial institutions that rely on artificial intelligence for essential operations.
▶ 3:27:42What regulatory obstacles or outdated requirements are hindering firms from deploying artificial intelligence responsibly at scale, particularly when those challenges grow under inconsistent state Thank you for the question.
▶ 3:27:57I would say first of all, it's important to be able to have a national framework that is addressing uh all of the issues that we've been talking about and not have that patchwork um that does pose undue burden and unduly impacts uh smaller medium-sized players um and creates higher barriers to entry that would otherwise be available to them with all this new technology. And so I think that's very important.
▶ 3:28:21I also think it's important to recognize that existing laws and frameworks um are in place and apply to these new technologies, but to be able to provide spaces for financial institutions to innovate and to test how these tools might be applicable into higher risk areas is also very
▶ 3:28:40Thank you for that. Uh follow-up question. Many state proposals include different documentation and testing requirements for similar artificial intelligence systems. From an operational point of view, how difficult is it for a cloud provider or a financial institution to adjust model governance and controls to comply with several conflicting regimes? Is very difficult and it would be incredibly resource intensive onto an organization and putting personnel and other resources into positions that aren't uh enabling the core business of that
▶ 3:29:09I feel like we've seen this before. We watched Europe pass GDPR and then now we have CCPA and we have all these different uh data privacy, data security standards and I think everyone agrees that we need to have a federal standard that preempts everything and leads in the global economy and we're not learning from past mistakes.
▶ 3:29:28So, not only do we need to lead here in Congress on AI, but we also need to get with the program and address the patchwork framework that is costing in incredible amounts of money for compliance for businesses. And I, you know, I feel like the larger businesses have a have a better capacity to deal with the patchwork frameworks um for cyber security. But in AI, it's just going to stifle growth and innovation. And we are competing in the global uh in the global economy. We cannot we cannot lose this fight.
▶ 3:29:58Um so although there are real real challenges in establishing clear rules for artificial intelligence, there are also significant opportunities. AI can strengthen the safety and soundness of our financial system by improving anomaly detection, accelerating the identification of fraud, enhancing cyber security and enabling faster and more accurate risk analysis. At the same time, compliance expectations continue to rise for institutions of every size. Smaller banks, credit unions, and broker dealers feel the b this burden most.
▶ 3:30:25AI tools can help reduce manual compliance work, streamline reporting, and allow institutions to devote more time and resources to customer service and innovation. Uh, Mr. Cohen, NASDAQ relies on AI to support its market operations and oversight uh, responsibilities. From your perspective, how is AI helping strengthen the integrity, stability, and resilience of the US financial system?
▶ 3:30:46Our markets operate on on the mandate of trust and investor confidence. And if we compromise either of those, then we won't have the standing we have today in our market. So we use our surveillance solution uh and we employ AI in it to essentially allow investigation analysts to scale up uh focus on the high value activities and also focus on the sophisticated manner in which market abuse is being conducted today. What we're seeing is market abuse today.
▶ 3:31:14It's the same outcome, but the techniques used are hard for any single human or a series of humans to detect. What used to be, if you will, clear patterns are now noise. And to make them and convert them back into signals, we've been using AI to help uh, if you will, regulators, exchanges, and broker dealers around the globe protect the integrity of their
▶ 3:31:35Thank you for that. Um, the gentleman from Texas, Mr. Green is now recognized for five minutes.
▶ 3:31:42Thank you, Mr. Chairman. I thank the witnesses for appearing. I especially thank the chair and the ranking member for allowing me this privilege to ask this question. Um, I have intelligence indicating that over the next 10 years approximately 100 million jobs will be lost to AI. Uh, I know that's a large number. Perhaps you have a number that is um somewhat different.
▶ 3:32:10Uh but let's just assume that this number is accurate. My question is how do we provide for a 100 million jobs being lost in terms of how they will impact people? usually have people associated with them. So how do how do these people u maintain their lifestyles?
▶ 3:32:39Will there be some imalument accorded them by way of the federal government? Um let's start with you, Mr. Branch, if you don't mind, and we'll go to your right and down the line. Thank you for the question, Congressman. Um, if I had the answer to that, I'd be a very rich guy because um, there's currently not really an answer to this solution. And that's uh, the big problem.
▶ 3:33:05Um, a lot of these tech companies are moving full-fledged forward with um, this theory of having AI take up a variety of jobs, but there's no solution for when those folks end up being laid off or
▶ 3:33:20All right. Next, please. Thank you, Congressman. So, I work in the field of cyber security and and we've historically had a pretty significant job shortage. I think right now any estimates would probably be over 1 million jobs within our industry that are not filled. And that's due to a lack of skills with that labor shortage.
▶ 3:33:39So in that regard, I think we're looking at cyber security uh usage of AI as really being able to put on an exoskeleton for our defenders, making them more capable, being able to conduct tasks that are uh much more efficient and defend our networks in a way that we're not able to do at human scale today.
▶ 3:33:58And interestingly in the field of cyber security, I think we're actually providing a lot more job satisfaction to our industry analysts and defenders who primarily deal in very repetitive tasks.
▶ 3:34:11Well, I appreciate your answer, but if I may, I'm posing a different question. Uh you've answered a question associated with how well and how efficacious your business model is. My question has to do with the people who are displaced. How how will they make a living?
▶ 3:34:31I think that's a great question, but as a, you know, cyber security expert, I'm not sure that I'm the best position to answer that. So, I may uh turn it to Mr.
▶ 3:34:41All right. Thank you, Congressman. I'll talk briefly about how important humans are to housing and then also offer how we can improve uh building the next generation US workforce. In housing ultimately where people are going to live is a very humanbased decision and we find time and time again people want a real estate agent to sit across the table and give them advice on if they're making a good decision. And so in housing we continue to see humans being very important.
▶ 3:35:08Outside of that, I think something that's come up briefly is we really need to invest more in training the next generation here at home to work on these models and help really improve them over time. And that
▶ 3:35:22excuse me if I may 100 million people 100 million jobs 100 million
▶ 3:35:29I I I've not seen that stat but I certainly believe if we gave equal access of this technology that
▶ 3:35:37Okay. Thank you. I I think that you your model is a good one, but we're talking about 100 million. Yes, sir.
▶ 3:35:45It's it's a great question. The first thing that we have to do is be honest about the workforce transition that we're going to go through as a country. Um what we're doing in terms of our parties, we're trying to make sure that we upskill, reskill employees, and we're actually creating roles of the future. So, we're we're doing trying to do our part to make sure that our workforce comes with us into the next generation. And then you also have to believe in the power of AI to generate new business models, new opportunities.
▶ 3:36:13And that's why it's important that we capture them here so that we can make sure that those individuals that may be displaced have opportunities in the future.
▶ 3:36:20I have to go to the last speaker. Please
▶ 3:36:23Thank you, sir. It's a very important topic and one that we care a lot about. Similar to our colleagues, we're very invested in ensuring our own workforce has the tools to be able to be successful. this includes our uh engineers using AI to be more productive. I would say more broadly is that we are seeing more job creation. We are seeing businesses grow as a result and it's important that we invest in education at the lowest levels of into elementary school to make sure
▶ 3:36:52the chairperson is admonishing me. Let me thank you Mr. Chairman and simply indicate that this is a question that we have to uh give some serious consideration to 100 million jobs. I thank you, Mr. Chairman. I yield back.
▶ 3:37:05The gentleman from California, Miss Kim, is now recognized for five minutes.
▶ 3:37:09Thank you, chairman and ranking member for convening our hearing today. Uh earlier this year, the state of where I'm from, they passed SB54 that would unfairly regulate AI and impose uh heavy compliance burdens on companies. Now, states across the country are looking to this California model as a basis for developing their own artificial intelligence regulations.
▶ 3:37:38Therefore, there is an urgency for Congress to establish a federal framework for AI. That's why I support legislation like chairman uh French Hills unleashing AI innovation in financial services act that would create federal regulatory sandboxes. Uh Mrs. Menfra, if that bill is signed into law, will those federal protections be respected?
▶ 3:38:04If you are simultaneously fighting a patchwork of restrictive state laws, particularly the anti-inovative regulatory framework in my home state of California.
▶ 3:38:17Thank you for the question, ma'am. Uh yes, we absolutely think the need for a national framework is critical and having to navigate a patchwork of regulations does not help um either our company or our customers.
▶ 3:38:29Thank you. You know what has made America a leader compared to other countries is our philosophy of trying first rather than regulation first. So the longer we fail to act the regulatory standard will be set at the state level not and the uh innovation will suffer. So thank you. Uh another area where AI has high value is in its application in the field of cyber security.
▶ 3:38:56So I want to ask you Miss uh Whitmore by leveraging AI how have banks been able to save time and protect themselves through cyber security efforts? Thank you for the question. So I think one of the most measurable areas we see with financial institutions is actually the applications to cyber security and in particular measuring outcomes and how quickly we detect attacks and how quickly we respond to them.
▶ 3:39:23Uh as we've seen the use of AI increase we've seen ransomware attacks that have been uh completed from initial part of the attack to stolen data or encryption of data in 25 minutes. And we've worked with customers in the financial services industry who have taken a meanantime to detect from 24 hours to, you know, as little as at 10 minutes. And so those type of measurable outcomes are incredibly critical at our ability to defend financial services networks.
▶ 3:39:53Thank you. You know, scams are an issue that I hear constantly about from my constituents. Uh we know that modern financial scams are rarely isolated to a single app. They may start with a text on a phone, move to a fraudulent website and follow up with an email. Mrs. Manfra, let me come back to you. How does Google connect the technical dots in the background to prevent those uh foreign scammers?
▶ 3:40:24Thank you. Um we have invested a lot in the space and seen a lot of very positive results going to um the ability to identify um four-fold increase in um activity that we are then able to detect and take down on a variety of our platforms. Um we do not want fraudulent um or or scam information that are sitting on our platforms or that are impacting our customers.
▶ 3:40:46So every day we are identifying millions and taking down millions of fraudulent ads, preventing scams, presenting fishing as a through the use of AI and ML technology.
▶ 3:40:57So let's say if AI detects a thread in Gmail, how does that transfer across Android or Chrome to ensure that it is neutralized across a person's uh accounts? Um well in some cases we use common tools um and many of our platforms and tools reside on common infrastructure. So oftentimes we're able to leverage that scale to be able to identify commonality.
▶ 3:41:28Um in other cases um we do have to use unique tools but that um but we are sharing um the uh the outcomes the detections the things that we're finding to make sure that other um uh products and platforms are available to use that.
▶ 3:41:43Well thanks for your work on that. Let me quickly shift gear to um AI. It has a large role to play in preventing financial uh crime as well. So Mr. Cohen, I want to give you a chance to uh answer how does uh NASDAQ utilize AI to address compliance and prevent financial So we were saying earlier that we have a leading financial crime platform is cloudnative AI enabled and what we do is use consortium data to detect
▶ 3:42:13patterns that no single institution can do on its own. And we have 725 million accounts and what we're able to do is reduce false positives and help investigators focus on real crime and identify real crime that is otherwise a drain on
▶ 3:42:27gentle lady's time's expired. Sorry I now recognize the gentleman from New Jersey for 5 minutes.
▶ 3:42:32Thank you Mr. Chairman, um, AI is being used, as we all know, to detect fraud and and, uh, stop uh, seniors from getting manipulated, uh, those especially who are targeted by scams involving deep fakes and other AI powered tools. According to the FTC report released just last week, adults over 60 lost 2.4 billion to scams and fraud in 2024.
▶ 3:42:56Alarmingly, this is the same report that found that older adults who reported losing more than $100,000 increased more than five-fold between 2020 and 2024. Very grateful to chairman Hill and the capital market subcommittee chairwoman and Wagner for recognizing the importance of my senior security act and including it in the vest act which the house will vote on this week to put new senior protection focused cop on the beat at the SEC. Miss Whitmore and Mr. cone.
▶ 3:43:23What specific safeguards should be considered to prevent and detect elder financial fraud and abuse related to AI? And how should industry coordinate with Congress and regulators and law enforcement and others to ensure those protections keep pace with rapidly evolving AI enabled threats?
▶ 3:43:40Thank you sir for the question. So I I think specific to the demographic you're talking about, education is a huge concern and really an issue. If we can raise awareness that these scams uh are being conducted and con create a level of education that doesn't necessarily exist at widespread today, I think that really helps with that.
▶ 3:44:01Additionally, what we're also talking about is visibility at large scale to protect the transactions on the back end and that's where organizations like ours truly focus is looking at the packets that are moving. So in your specific use case, we would be looking at the financial services transactions and ensuring that our detection capabilities are not facilitating those types of crime.
▶ 3:44:24Mr. Con,
▶ 3:44:25thank you.
▶ 3:44:25There's two important elements here. There's the the public private partnership. We need information sharing because these scams scale incredibly fast in the world that we live in today. And it shouldn't be that the elderly find out on Facebook from their friends about a scam. We should have this information sharing at a scaled level to make sure that we can prevent it and not just deal with it after the fact. And then the second thing is we can use AI to detect it at scale. Right now what we're doing is is we're coming into it and we're trying to deal with it on a one-off basis.
▶ 3:44:56We need to we need the tools and the automation to be able to stop it the second we see it and not let it propagate through the system. And AI can help us do that.
▶ 3:45:05Are we seeing that miss mom? Are you are we are you taking steps to actually make sure that happens from a Google
▶ 3:45:11Absolutely. We are um identifying blocking and taking down um fraudulent use of our platforms, fraudulent postings, fraudulent ads, scams that are targeting various customers, fishing attempts. Gmail alone blocks 180 million fishing attempts every day. And so we are investing in AI as a critical component to being able to do that.
▶ 3:45:31Thank you very much. um you know regulators have used innovation hubs and sandboxes to encourage responsible experimentation in other areas of and um you know and I and I am personally very focused on this area and for for the entire panel what features and guardrails do you think are essential for AI pilots to truly encourage innovation and protect consumers and communities in this space? Um Josh you want to start?
▶ 3:45:57Thank you for the question Congressman. Uh well, I think these sandboxes need to be timelimited. Um they need to be specific. Um and I think those are two of the primary sort of components that are at least not seen currently in the sandbox offerings.
▶ 3:46:13Woman, thank you. So I think we look at it from three categories. First is defining a riskbased approach with consistent definitions. the focus is on actual threats and and not necessarily those that are hypothetical and those certainly that are more high-risk applications. Second would be distinguishing between the developers and the deployers. And third is making sure that defense is a priority. So having voluntary standards, a framework that then looks at making sure we're protecting our most critical information uh and not getting in the hands of our
▶ 3:46:44Thanks Nick.
▶ 3:46:45Thank you. I I would say briefly that laws stay in force, that we test responsibility in these sandboxes, independence checks still happen, bias testing and the like. And then last, I would add transparency is obviously paramount regulatory reviews
▶ 3:47:02I agree.
▶ 3:47:03Control, targeted, and time boxed, and don't allow for circumvention of of approval process.
▶ 3:47:11I agree with Mr. Cohen and the previous
▶ 3:47:14Great. Thanks so much. Yield back. The gentleman from New York, Mr. Garbrino, is now recognized for five
▶ 3:47:22Thank you, chairman, and thank you all for being here today. Uh, as chairman of the House Committee on Homeland Security, one of my top priorities is the reauthorization of the cyber security information sharing act of 2015, also known as CISA 2015. Uh, it is a vital framework that allows for voluntary exchange of cyber security information between the federal government and private entities, from energy companies to major finance institutions on Wall Street.
▶ 3:47:44the private sector's the first line of defense against malicious cyber adversaries in SISA 2015 is critical to ensuring those threats are not realized for someone who previously served as assistant secretary for cyber security at SISA how important is the reauthorization of CISA 2015 to ensure our cyber security needs are met to combat AI powered threats
▶ 3:48:07it's very important sir
▶ 3:48:09can you give me some examples of what could happen in the financial services space if a 2015 authorization were to lapse as like it did under the shutdown but would lapse for a longer time.
▶ 3:48:20So the the framework that um the legislation provides SISA um to be able to share information in protected spaces with its partners to include financial services means that they are actively reducing risks in um those protected conversations and information sharing environments and so not having that is um detrimental to those partnerships.
▶ 3:48:41Yes. I mean, financial service companies, they're they are hit all the time with cyber attacks. They learn about vulnerabilities before because they're the front line of defense. They can't share that information with the federal government. The federal government can't then share it with everybody else and those which means those vulnerabilities cannot be fixed and you know, we're just facing more and more threats. Correct. Thank you. Um, Miss Whitmore, is our existing financial data privacy and cyber security framework well suited for the current era of AI or reforms needed?
▶ 3:49:11I think we can, you know, leverage existing regulation, but what we really advocating for moving forward uh are actions that benefit the defenders and not the attackers. So the more that we look at streamlining regulation and harmonizing it, the better we make it for defenders to really focus on truly firefighting and not filing the, you know, complexities of of too much
▶ 3:49:32Yeah. Harmonization. I I once I had lunch with Jamie Diamond once and he said more than 50% of his cyber security employees spend more than 50% of their time on compliance instead of actual cyber security defense, which is wild to me. So harmonization is another thing that um I know I've spoken to the chairman Hill about uh as as something we should focus on here as well.
▶ 3:49:52Um, switching gears a bit, um, the mortgage industry has spent decades under federal oversight, uh, starting with the Great Depression when agencies like FHA and Fanny May were created to stabilize the housing market and expand access to home ownership and intensify and and intensifying again after 2008 uh, financial crisis through the DoddFrank Act and then the creation of the CFPB. Today, federal rules shape nearly every part of the mortgage process. Mr.
▶ 3:50:20Stevens, as AI enters mortgage lending, should we extend existing federal financial services regulatory frameworks to cover AI?
▶ 3:50:28Definitely uh any any law or regulation that humans have to follow, AI definitely should too. And I think to the first part of your question, AI has that ability to take on a lot of the administrative burden that slows everyone else down. If you shadow a loan officer, they spend hours just collecting documents, copying and pasting data. AI can do that so they can focus on the right decisions.
▶ 3:50:48Absolutely. So what should Congress do to ensure or maybe not do to ensure that you can continue uh to innovate here?
▶ 3:50:54I think national right-size frameworks. I mean we rely a lot on the risk you know AI management framework um and so anything that has a consistent baseline for all of our states will help us. Are there any, and maybe it's the states, but are there any regulatory structures that are currently standing in the way uh of AI delivering on the promise to expand access to affordable
▶ 3:51:19It's something we could certainly follow up on. I think in housing, a lot of the regulations were written before the age of the internet. For example, we have a whole database at Zillow that is just mindful of when e-ign is allowed depending on the state you're in. And so, I'd say a comprehensive review of some of those older frameworks would be
▶ 3:51:35Yeah. If you if you could get us more ideas that would be uh more detailed
▶ 3:51:40and from your vantage point Mr. Steven's last question how can you how can building consumer products how can technology and modernization not more regulation actually help lower the costs uh for buyers and renters?
▶ 3:51:52Yeah, both the efficiency we were talking about with loan officers and real estate agents. I'd say also the democratic um democratization of data access. If you have a nationwide framework, that means we can give guidance about what home to buy across state lines, which many consumers consider all the time. If it's a patchwork, that means we have to build very custom models depending on the state you're looking in right now. And that kind of efficiency helps people make better decisions at the right
▶ 3:52:19Thank you very much. And I'm out of time. I yield back.
▶ 3:52:22Thank you. The gentleman from Nebraska Nebraska, Mr. Flood, is now recognized for five minutes.
▶ 3:52:26Thank you, Mr. Chairman. I really think about AI in really two buckets. Number one is it relates to entities that are already regulated in the financial services lane, whether it be by the Fair Housing Act, the Fair Credit Reporting Act, the Graham Leech Lley Act, or statutes that apply to financial actors. And so basically what I tell people is if we find you discriminating, we will find you and we will enforce the law.
▶ 3:52:52In other words, if you're using AI to break consumer protection law or discrimination law, we we need to ensure that our regulators are equipped to track and identify that. I had this idea that someday we're going to begin an enforcement action and the regulated entity will say, well, we we didn't intend to do that. It was all in our AI model and this was the outcome. Well, we're not going to fall for that. Like, if you break the law, you broke the law and you had a model that did it.
▶ 3:53:22But number two, we need to work together to identify these bad actors, these folks that use generative AI to scam people out of money, uh, to let fraudsters fool people and steal their cash. And law enforcement needs to be able to respond to these threats. And we absolutely need the help of technology companies in preventing AI from being used by those who do it to lie, cheat, and steal. And so that's really where I come from on this.
▶ 3:53:49uh to all of you on the panel today, can you just describe the intentions with the the interactions I should say with the regulators you work with on AI both at the federal and the state level and do you see in those regulators sufficient expertise uh in your counterparts in government uh to make you feel they're up to the task of overseeing this changing landscape?
▶ 3:54:12In other words, as you in engage with regulators, do you feel like they have the tools they need to do the job given the changed landscape with artificial intelligence? And we'll start here.
▶ 3:54:25We'll say the one those that we interact with um whether as as customers or partners or regulators um I do think that they show a willingness and an openness to learn. I do think that like many other organizations, they do need more skilling in this space and um and to be able to best focus on the outcomes but also be able to apply that to new
▶ 3:54:50Just to frame your question, public private partnerships are incredibly important and and they're what will keep us ahead and and so two things if I could take the opportunity. the cyber security information act that needs to be extended. So we continue that on the cyber security side and then in terms of the regulators and the way that we work together we do feel like they appreciate the issues there is a deep level of understanding around the issues the one thing we worry about is regulatory arbitrage.
▶ 3:55:18So you need to make sure that as we go to the regulators we do not want to go to the regulators that understand the least to try to get something approved. And that is why at a federal level, we're going to need some clarity there so there isn't regulatory arbitrage and people don't try to go to the regulator that understands the
▶ 3:55:37Well said. Thank you. I appreciate the question. I'd say certainly education could help when we partner at the federal and state level, but even more so we see successful partnerships when they're outcome focused, when they're customer first, when they're transparent. I I could sit down and explain all the fraud models behind Zillow Rentals, but if we just agree that no customer shouldn't see a fraudulent listing or have a fraudulent payment, then we can collaborate even more efficiently.
▶ 3:56:04Thank you for the question. So, not only do we work on behalf of public private partners within cyber security and all our counterparts on the government side, but also on behalf of our customers when we're investigating these major cyber breaches. they're then challenged so many times with the different regulatory uh frameworks that they need to report these breaches in.
▶ 3:56:24And so I think the one area I'd really like to share there is that uh more complexity never benefits the defenders who are trying to fight the fire and stop the breach uh while they're also worried about the paperwork. So that really benefits the attackers. And I think the more we can streamline the better off we're going to
▶ 3:56:41Mr. Branch,
▶ 3:56:43thank you Congressman for the question. Um many agencies have lost jobs due to various layoffs. Um and so these agencies are playing catch-up and are in a bit of a difficult position to try to enforce some of the laws. Um but also President Trump's AI action plan uh has predominantly been a deregulatory effort and as such the um agencies are not really empowered to enforce some of the laws that exist.
▶ 3:57:07And then the last thing that I would say as well is that um some of the sandbox bills that have been proposed allow the companies to sort of self-regulate. And so from that end of things um these companies are sort of guarding their own laws and it's um not allowing the regulators to essentially do the jobs that they're uh required to
▶ 3:57:26Thank you very much. With that, I yield
▶ 3:57:31Pursuant to the previous order, the chair declares the committee in recess subject to the call of the chair. We will reconvene immediately after the floor vote series. The committee stands in recess.
▶ 4:49:44Committee on Financial Services will come to order. Uh I would like to thank all the witnesses for their testimony today. Uh without objection, all members will have five five legislative days to submit additional written questions for the witness to the chair. The questions will be forwarded to the witnesses for their response. Witnesses, please respond no later than January 14th, 2026. The hearing is adjourned.