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The subcommittee on higher education workforce development will come to order. I know the quorum is present. Without objections, the chair is recognized to call or recess at any time. Good morning and welcome. I want to thank our witness for joining us today as we examine one of the most consequential developments in higher

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education, the rise of artificial intelligence, AI. In just a few years, AI has grown dramatically across every segment of campus life. Students are using it to study, write, and problem solve. Faculties are are using to redesign courses and to rethink

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instruction, and administrators are using to reduce paperwork burdens. This is not a passing trend. It's a seismic shift in how learning happens and how institutions operate. This shift begins extraordinary, it brings extraordinary opportunities. AI can personalize

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instruction in ways that a single instructor teaching many students simply cannot do. It can identify students who are struggling before they fall behind. It can reduce the administrative burdens that consume faculty and staff, freeing them to focus on students. AI also helps

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better align academic programs with knowledge and skills employers need. The students in the classroom today will need to understand not only how to use AI but also how to evaluate its critically it critically recognize its limitations and exercise the kind of judgment that that automation cannot

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replace. At the same time the challenges of AI are significant. If students can produce polished work without genuine learning the value of credentials is diminished for employers institutions and students. Academic integrity framework built around bring built for

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the previous era are under significant strain and institutions still working out how to respond. Concerns about bias, data privacy and cyber security remain unsolved and many educators are rightly as asking what widespread use of AI

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could mean to foundational skills like writing, critical thinking and problem solving. The rights response is neither a knee-jerk prohibition nor a careless adoption. It is a thoughtful leadership grounded in a commitment to student access. Some some institutions are

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already demonstrating what it looks like uh with AI literacy initiatives, faculty development programs, and partnerships with employers designed to to work around evolving workforce diverse needs. Our global competitors are investing heavily in AI and integrating it into

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their educational systems. Employers are building their operations around it. Higher education has both opportunity and obligation to help lead this transition rather than simply endure it. Today's hearing gives us an opportunity to examine how education can rise to the challenge uphold the core mission of

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higher education and ensure students are prepared to succeed in AIdriven world. I look forward to the testimony and I yield to the rank they can remember. >> Thank you, Mr. Chairman, and thank you to our witnesses for being here today.

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Artificial intelligence is no longer theoretical. Students are using it, faculty are using it, universities are adopting it, employers are expecting familiarity with it. The question before us is no longer whether AI will shape

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our education. it already is. The real question is whether we will shape it responsibly. Right now, students across the country are trying to decide whether pursuing higher education is still worth it in a rapidly changing economy, largely driven

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by AI. New graduates entering the workforce here every day. That automation may replace the jobs for which they are trained. Faculty and educational professionals are being asked to adopt tools overnight, even as

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they evolve faster than institutions can respond. Fear and uncertainty are growing because there are few clear rules, few protections, and limited coordinated federal leadership. AI can absolutely be a tool that that helps

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Americans progress. It can support learning, expand access to tutoring and research assistance, and can help institutions better serve students. But these tools must remain tools. They cannot replace instruction, replace

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educators, or or undermine the student learning. We need clear guard rails to ensure AI strengthens education rather than weakens it. Unfortunately, the current administration's policy is moving us in the wrong direction. At a

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moment when stronger oversight is needed, we are seeing hesitation, fragmentation, and the weakening of the very institutions responsible for protecting students and educational professions professionals. Uh, as

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private companies rapidly collect data and expand AI systems into classrooms and and campuses, students and institutions are increasingly at risk. And what makes this moment especially concerning is that the Trump

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administration is weakening the very institutions responsible for protecting students while simultaneously pushing to rapidly expand the use of AI. This administration says it wants to unleash a AI. Yet, it has supported

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efforts to dismantle and weaken the Department of Education, reduce capacity within the Office of Civil Rights, eliminate the office responsible for educational technology guidance and support, and has scaled back workforce

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preparation, including the Office of Career, Technical, and Adult Education. That is deeply counterproductive. These gaps matter because AI systems are not neutral. They can reinforce bias,

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misuse student data, and create discriminatory outcomes that directly impact access to education, financial aid, disability accommodations, and and academic opportunity. And without strong federal oversight, students, faculty,

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and educational workers are left vulnerable with little recourse when their rights are violated by these systems. And that is why it is our job to step in. We need strong guard rails and infrastructure that match the scale

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of this technological shift. And that means restoring and strengthening federal educational technology leadership. It it means uh rebuilding uh OCR's capacity uh so that complaints involving AI discrimination and data

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misuse can actually be investigated. It means establishing clear accountability standards around transparency, data protection, auditing and oversight for AI systems used in higher education. But most importantly, higher education

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institutions need coordinated federal guidance instead of being left to navigate this alone campus by campus. AI is already here. Ignoring it will not stop it. But but failing to govern it responsibly will deeply

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deepen inequality and weaken trust in education and leave students unprotected during one of the most significant technological transitions of our time. We have an obligation to ensure that AI is used ethically and responsibly to

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serve students, educators, and the public interest. And with that, Mr. Chairman, I yield back. >> Thank you. Pursuant to committee rule 8C, all members who wish to insert written statements into record may do so by submitting them to committee clerk electronically in Microsoft Word format

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by 5:00 p.m. 14 days after this hearing. Without objection, the hearing record will remain open for 14 days to allow for such comments and other materials noted during the hearing to be submitted for the official hearing record. I'll now like to turn to induction introduction of four distinguished

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witnesses. Um, our first witness is Jonathan Fosard, chief information officer at Florida State University in Tallahass, Florida. Uh, our second witness is is Dr. Dave Duke, uh, chief product officer for higher education at McGrath Hill in Chicago, Illinois. The

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third witness is Dr. Bridget Burns, our CEO at University Innovation at uh, Alliance in Temple uh, Temper Temper, Arizona, sorry. And our fourth witness is Michael Horn. an author and adjunct professor at Harvard Graduate School in

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Education in Cambridge, Massachusetts. We thank the witness for being here today and look forward to your testimony. Pursuant to committee rules, I will ask each of you to limit your oral presentation to three minute summation in your written statement. Uh the clock will countdown for three minutes as committee members have many

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questions for you. However, uh, pursuant to community rule 8D and committee practice, we will not cut off your testimony until you reach the five minute mark. I would also like to remind the witnesses to to be aware of your responsibility to provide accurate information to the subcommittee. Uh, I

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first would like to first recognize Mr. Bazard for your testimony. >> Thank you, Chairman, Chairman Owens, Ranking Member Adams, and members of the subcommittee. Thank you for the opportunity to testify today on an important topic of AI Ready America. My

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name is Jonathan Fosard and I am the chief information officer at Florida State University. I am honored to appear before you and grateful for the opportunity to share the higher education perspective on one of the most consequential issues facing our country. Artificial intelligence is not simply another emerging technology. It is

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quickly becoming a defining capability that will shape the economic competitiveness, national security, scientific discovery, education, healthcare, public service, and the future of our work. The United States right now is a global leader in artificial intelligence, and we must

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remain at the forefront. This is a pivotal moment. Institutions, organizations, companies, and nations have a choice. They can embrace AI responsibly or they can choose not to use it at all. That decision will increasingly differentiate who is

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leading and who is falling behind at an exponential rate. That is why education must be central to America's AI strategy. America's AI leadership will not be secured by technology companies alone. It will require national education and research pipeline that

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begins in K through2 and continues through higher education expands into the workforce training and lifelong learning and is strengthened by meaningful partnerships among university government and our industries. At Florida State University, we see this responsibility very clearly. Higher

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education must prepare students not only to use AI but to understand it, to question it, to improve it, secure it, and apply it in ways that serve people and strengthen our nation. I have many waves uh of change and have seen many waves of change as a technology practitioner for more than 26 years. As

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a father of two children who will soon enter the workforce, this topic is also very personal to me. I want my children and students across this country to inherit a nation that continues to lead, continues to innovate, protect its values, and create opportunities for

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generations to come. I believe that five priorities should guide our nation's approach as we move forward. First, I believe that we must treat AI literacy as a national workforce priority. Second, we must support secure and responsible access to AI tools so that

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students are prepared for the future. Third, we must invest in hands-on learning and workforce development programs. Fourth, we must strengthen the K through2 to higher education pipeline. And fifth, we must continue investing in research infrastructure. At Florida

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State University, we stand ready to do our part. We are preparing students. We're supporting faculty. We're enabling researchers. We're modernizing our infrastructure. We're protecting data. And we're building partnerships that expand access to AI tools and training across all disciplines. We are doing

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this because AI readiness is not optional. It is central to our students future, our workforce, our research enterprise, our national competitiveness, and our responsibility to the country. The United States has the talent, the institution, the the innovation ecosystems and the values needed to lead in a world of artificial

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intelligence. But leadership is not guaranteed. It must be built, protected, renewed, sustained, and invested in education, research, infrastructure, security, and most importantly, people. This is the moment for urgency, but also for optimism. Higher education stands

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ready to help build the next generation of AI leadership and innovation. Working together, we can ensure that the United States remains at the forefront, not only for our own future, but for the future of our allies, our partners, and the democratic values we all share. Thank you for your time, for your

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service to our country, and for your commitment to building this AI ready America. I look forward to your questions later. >> Thank you. And I'd like to recognize Dr. Duke for your testimony. >> Thank you. I want to talk about something more uncomfortable than AI

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adoption rates, a gap that is opening in American higher education right now that our institutions are not yet equipped to close. Two things are happening simultaneously. Employers across every major sector of the American economy now expect AI proficiency from college

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graduates. It's showing up in entry- levelvel job descriptions. And hiring managers, many of which are not yet adept at using AI themselves, are expecting graduates to work with AI tools productively and responsibly within a specific professional domain.

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And this is also true. Most institutions of higher education are not preparing their graduates to meet that expectation. The response to AI on campus across the country has been fragmented and inconsistent. The gap between what higher education is producing and what the economy now

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requires is real and it is growing and it is a structural challenge. And I call this the proficiency dilemma and has two sides that are in tension. On one side, students are using AI constantly. They've developed a practical fluency through daily use. But fluency through

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unsupervised use is not the same as cultivated professional competency. They've not developed the critical thinking or domain expertise the AI will demand of them as professionals and they have learned to produce outputs without developing the capacity to evaluate

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them. On the other side, academic institutions that have responded to AI primarily through restriction and detection are producing a different kind of graduate altogether. one who has been taught that AI is something to be managed and avoided rather than

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understood and used with skill and judgment. And so the right answer is neither unrestricted use nor aggressive restriction. It is intentional, structured, pedagogically sophisticated integration. Teaching students not only how to use these tools, but when, why,

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and with what critical judgment. Very few institutions are doing this well. And I want you to know that faculty are making individual decisions in a policy vacuum, often without guidance, without professional development, and without the time to think through what

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responsible AI integration requires. And let me explain what is at stake if we get this wrong. We will produce a generation of graduates who are simultaneously overreiant on AI and underprepared to work with it professionally. We will widen, not

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narrow, the gap between students who receive structured AI education and those who do not. And we will perpetuate a disadvantaged workforce that has a difficult time competing in the global economy. Higher education has always been America's mechanism for translating

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individual potential into national strength. And if we allow it to fall behind the economy it is meant to serve, we are not just failing students, we're failing ourselves. And I'll leave you with three recommendations. First, treat AI proficiency as a core educational

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competency, a nationwide commitment built into accreditation standards and general education frameworks to clarify the expectation of an AI ready America. Second, initiate the development of institutional AI frameworks that create

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actionable guidance that faculty and administrators need but currently lack so that individual educators are not left to navigate this transformation on their own. And third, examine the variation in AI readiness among all institutions explicitly. well organized

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and better positioned universities have advantages and AI adoptions that smaller regional and community colleges do not and the benefits of AI and higher education should be broadly shared. So the question before American higher education is not whether AI will

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transform the experience of learning and working. It already has. The question is whether our institutions will lead that transformation. The students sitting in classrooms today will spend the most consequential years of their careers in an AI-shaped economy. They deserve an

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education that prepares them for that reality. McGraw Hill is committed to that work and we're grateful for this subcommittee's attention to it. Thank you and I welcome your questions. >> Thank you. I'd like to recognize Dr. Burns for your testimony. Chairman Owens, uh, Ranking Member

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Adams, and members of the subcommittee, thank you for the opportunity to testify today. My name is Bridget Burns, and I serve as the CEO of the University Innovation Alliance, which is a national consortium of 19 large public research universities across the country, serving

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more than half a million students. Over a decade ago, the UIA was formed by our presidents and chancellors who were trying to respond to a national challenge. We needed to increase the number of college graduates to strengthen the economic competitiveness of our country. And over the past 12

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years, our member institutions have stepped up and produced more than 180,000 additional graduates above their stretch capacity in that time while simultaneously increasing their graduates from lowincome backgrounds by 51%. We did this by doing something

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higher education rarely does, which is we innovated together and we shared openly what we learned in real time. Our campuses have leveraged AI, machine learning, chat bots, and predictive analytics to improve student outcomes for more than a decade. That experience

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has directly shapes how we view artificial intelligence. It's tempting to treat AI as a technology challenge, but it is far more all-encompassing than that. It is rapidly reshaping teaching and learning, workforce preparation, research, advising operations, and

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student support. In less than two years, institutions have gone from asking whether a student would use these tools to manage a reality where their use is every day. One of the reasons uh navigating AI transformation is so challenging is that it does not neatly

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fit into any traditional organizational structure. It cuts across every aspect of the institution. institutions across the country are trying to answer the exact same questions responsibly around workforce preparation and privacy and governance and learning but most

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institutions are not actually resisting AI they are trying to navigate it but most of them are navigating it alone that is the problem my concern is that we are approaching AI a primarily as an institutional challenge when it's increasingly becoming a national

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competitiveness challenge if America wants to lead in an AI enabled future. We need to be organizing around national priorities and leveraging the full capacity of our higher education institutions to help achieve them. That requires coordinating infrastructure that does not exist. Right now,

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thousands of institutions are independently evaluating vendors and developing governance frameworks, piloting tools, and creating policies. And too often, the lessons learned are remaining in one place and not going to another institution. We're duplicating effort at a moment when we should be

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accelerating learning across the country. We also need to not leave underresourced institutions behind. Whether a student benefits from responsible AI adoption should not depend on where that student happens to enroll. Students attending rural institutions, regional universities,

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community colleges, H.B.CU, all of them deserve access to the same opportunities at the wealthiest institutions in the country. America's economic competitiveness depends on developing talent everywhere. Our campuses are already demonstrating what responsible AI adoption looks like. At Arizona State

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for University, for example, they developed something called the triangulator which streamlines credit transfer credit evaluation. A process at any other institution that traditionally requires staff manually weeks to compare catalog courses by, you know, course by

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course. The tool uses AI to identify likely equivalencies and present recommendations for staff review with a human expert always making final decisions. AI open-sourced this solution and already many institutions including seven of my own are working to scale it.

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Purdue University was the first institution in the country to integrate AI literacy into their graduation requirements. At UC Riverside, the writing faculty have designed a Socratic tutoring tool that coaches students through the work via questioning rather

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than rewriting. It preserves authentic learning while prov providing the personalized learning and support they need. And at University of Utah, they're piloting AI enabled tools that help students connect academic pathways to career opportunities. Importantly, these institutions are not treating AI

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innovation as a proprietary competitive advantage. They are openly sharing what they learn. so other institutions can adapt and benefit from the work. What concerns me [snorts] is that we are doing so while campuses are operating under significant strain. Leadership turnover, staffing shortages, financial

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pressure, and uncertainty around research infrastructure are making it harder for institutions to build the capacity required to navigate this moment successfully. Federal policy has spent decades rewarding institutions for developing innovation. The AI era requires us to also re reward

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institutions for sharing them. One of the most effective ways to do that would be to prioritize multi-institutional partnerships in federally funded AI initiatives. I'm looking forward to Thank you so much for your questions and I look forward to your time. >> Thank you. Last lastly, I'd like to recognize Mr. Horn for your testimony.

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>> Chairman Owens, Ranking Member Adams, and members of the subcommittee. Thank you for inviting me today. My central message today is simple. AI alone will not improve higher education. What matters is whether colleges redesign their resources, processes and

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priorities around it. The analogy is electricity. Early factories adopted electric motors but saw little productivity gain because they kept the same organizational designs and processes in place. Only later when they redesigned themselves around electricity

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did productivity surge. Higher education is at a similar moment. Today faculty and students are already using AI at scale. Adoption has in a sense been quite rapid. Yet most colleges with a

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few uh exceptions named earlier have seen few learning leaps, few dramatic improvements in student success and few efficiency gains. Most campuses remain somewhere between a wait andsee approach and a patchwork of siloed experiments.

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The outcome is frankly predictable in every sector. When organizations treat the adoption of technology as a problem of technology, progress is slow and uneven. Indeed, organizations that frame the challenge as one of technology often

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perceive it more as a threat than an opportunity. Hence how AI is exacerbating cognitive automation on the part of students and faculty overwhelmingly report concerns around plagiarism and cheating. The challenge is actually the operating model itself

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and the opportunity is redesign. We can in fact use AI to increase academic rigor rigor and reinvent assessment. If AI can complete an assignment, perhaps the assignment itself is in need of change. Oral

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defenses, presentations, demonstrations, and rigorous feedback can help ensure that students are still doing the hard work of learning. We can use AI to boost student success by connecting data around academics, finances, and

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well-being to offer more meaningful support. We can also streamline processes and reduce administrative overhead. And we can better connect learning to work. As AI rapidly ch changes jobs and the half-life of skills

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shrinks, students need opportunities to do real work in real world settings and use AI in the course of that work. Employers are not asking whether employees should use AI. They are expecting it. That means that schools

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must offer embedded projects and simulations and courses, externships, paid internships, co-ops, or apprenticeships. All the better when these experiences both pay, count for credit, and connect students to working professionals to

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help them build social capital. Many universities are stepping up on this front. from Northeastern University with its co-ops to Manurva University where I'm a trustee with its combination of online seminars and in-person incountry projects to reach university with its

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apprenticeship degrees. Finally, because it is difficult to redesign existing institutions, we should encourage experimentation from both existing schools as well as new AI native colleges and university.

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that will require accreditation reform that lowers barriers to entry while strengthening the focus on student outcomes. Something counts as innovative only if it creates true progress and value for

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students and society. If we focus on student outcomes, AI can become not a threat to higher education, but an enabler of redesign that strengthens its value for every American. Thank you. Thank you. Under committee rule nine, we

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will now question witnesses under fiveminute rule. I will recognize myself for five minutes. Mr. Bazard, uh Florida State has partnered with companies like uh Google, Microsoft, Amazon Web Services to expand access to AI tools and training. How do partnerships like

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these bridge the gap between classroom learning and skills employers employees employees are seeking? And how can universities and uh cons uh how can universities structure themselves to give students workforce relevance experience while preserving

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institutional independence and academic priorities? >> Thank you chairman. I I think that this is a um this is a a great question because it's a partnership. uh higher education, we [clears throat] don't view that AI will replace instruction or replace the classroom, but the

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partnership will prepare um will prepare our students uh to be able to uh have exposure to the tools and the the the workforce and the platform that they will use in their future careers. So for us, these partnerships with companies like Google, with Microsoft, with with

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Amazon is to give them access, that ubiquitous access across all disciplines, across all fields to have exposure to these tools in a secure and reliable way. And our framework that we've developed is um is called rise and it's built on uh research and instruction for R, innovation,

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modernization for I, security and compliance for S, and engagement and student success. And we really feel like our AI strategy has to be built on those four pillars to be successful with any partnership that we do. But we do feel like that there's a classroom component

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that we have to have um foundational access, foundational knowledge, but we also have to expose our students to the tools that they're going to use in the workforce. And so Florida State University has taken the approach of of building these partnerships and having secure environments where their data is protected. they can experiment with our

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instructors, with our researchers in a secure environment. >> Very good. Thank you. >> Uh Dr. Duke, you spent many years working in educational technology. The rapid rise of artificial intelligence since 2022 has transformed the conversations around uh teaching and learning technology. From your

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perspective, how has educational technology landscape changed during the during that time? and what are the biggest uh implica implications of that shift for students, faculty and institutions?

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Thank you for the question. It's true the landscape has changed significantly as we sit here today. AI is has been embedded uh in every daily workflow for students, instructors and administrators. The vast majority of students are using artificial

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intelligence. faculty adoption uh is uneven but it is accelerating. Everyone from admissions counselors, financial aid representatives, other administrators are all using generative AI and the work that they do. Virtually

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every education infrastructure company like McGraw Hill has included AI enabled products into their ecosystems. And so AI as we sit here today is now a requirement to provide the best learning possible. It has increased personalized

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learning. It is increasing efficacy and if we don't invest more and and um put more resources behind this, we won't see the full value of artificial intelligence. >> Thank you. Uh Mr. Horn, the rise of artificial intelligence has led some

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students and families to question the value of college education. What must colleges and universities do to demonstrate the value in the AIdriven economy? >> It's true that many uh people are increasingly questioning the value of college. I think what it's incumbent

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upon colleges to do is really show the outcomes, the connection to the labor market value that we know that families are expecting as a requirement for jumping into college. That's number one. And number two, show the relevance. The real world connections, the programs that you just heard about at Florida

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State, real connections with employers will go a long way to showing that we have their interests at heart and that's incumbent on every college to make sure that those connections are clear. >> Okay. Thank you so much. I now recognize um the ranking member for the purpose of questioning witnesses.

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>> Thank you, Mr. Chairman. Uh Dr. Burns. Um as you may be aware, HB.CU CUS play a major role in expanding educational opportunities especially in STEM related fields. A joint report from UNCCF Houston Tillerson University and

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Elucleitian highlighted that AI could transform the role of higher education at H.B.CU by creating new opportunities for innovation. However, sim simultaneously many H.B.CU CUS continue to face challenges with funding and resource

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constraints that can limit their efforts to access AI technologies to the extent that these schools decide to use them. And that matters because AI readiness can cannot only be available uh to the institutions with the largest endowments, the strongest vendor

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relationships or the most staff capacity. If if we're not careful, AI could become uh one more area where well-resourced institutions move forward while underresourced institutions are asked to do more with less. Mr. Chairman, I'd like to um uh to uh for

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unanimous consent to enter this article uh H.B.CU's artificial intelligence and a new vision for higher education into the record. Thank you, Dr. Burns. What are some of the opportunities and challenges that HBUs are encountering with AI innovation?

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>> Thank you. Uh, ranking member Adams, I would say first, uh, the UI includes the largest H.B.CU in the country, North Carolina ENT. And so we have some familiarity with the challenges and they are quite relatable. We're seeing this across the sector where it's a I would just say broadly the lack of broader

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coordination across higher education to ensure that all institutions are benefiting in real time when institutions are actually figuring out some of these similar challenges around literacy and safety and privacy. Um that is disadvantaging H.B.CU is disadvantaging underresourced

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institutions broadly. Um I observe that the indirect cost uh challenge around uh the research enterprise has definitely made it very difficult for institutions to navigate. We're asking them at a moment when we need American ingenuity which our academic research is really

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the heart of. Um is is operating in a time where it's been relatively uh destabilized I would say financially. Um but these HBUs broadly are an incredible uh STEM talent activator. they are uh they generate incredible talent and we

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just believe that broadly for the competitiveness of our country that we need to activate all the talent we have >> and and thank you for mentioning North Carolina ent that is my alma m twice uh Dr. Burns uh colleges and universities now have access to to many different AI tools. Some come with packages of other

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technology such as Microsoft 33 365 while others require specific subscriptions given that larger institutions have more resources for new tools. Underresourced institutions may have a harder time providing these tools and developing faculty understanding,

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therefore creating disparities in our students academic careers. And I wonder that if if uh if if students at one institutions are receiving strong AI literacy, hands-on experience, and access to tools employees are already using while students at another

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institution are not, then we're not preparing students equally for the future of work. So given that large uh larger institutions are at the forefront of developing AI curricula and competency, what impact do you think that this will have on student access and the digital achievement gap?

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>> I'm I am deeply concerned about students who are being left behind across the country. Uh we noticed early on, you know, it's it's not like we have a ton of expertise with navigating AI, right? everyone is as new as a couple years at this technology. And so when my

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institutions were first trying to diagnose how they decide to sign any of these agreements, ASU for instance was the first institution to sign a enterprise level contract with open AI. Um we started in that moment sharing what are the questions you ask, how do you interrogate it? Because this

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expertise doesn't exist. Normally it wouldn't be just like the legal council knows how to navigate something so complex and it's worth definitely seeing at H.B.CU cus and there are some resources out there but I think there need to be more. >> Thank you. A few more seconds. What what can underresourced institutions do to

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provide additional access to these tools despite limited capacity? >> Uh ranking member Adams, I believe that institutions need to be broadly sharing what they're learning in real time. They're lack we currently lack the coordinating infrastructure where one campus is tinkering and others are going

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to ask the same question and it's actually going to harm students. I'm most concerned about institutions that um are in a moment where they don't have that capacity. They will freeze that in risk is is too we're too uncertain and we can't delegate um the

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responsibilities to our student to a vendor. So as a result there are some institutions who will resist who will just freeze because they are waiting for more clear direction. >> Thank you very much Mr. Chairman. I yel back. I'm out of time. >> Thank you. I would now like to recognize the chairman of full committee, my good

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friend from Michigan, Mr. Wahber. >> Thank you, Mr. Chairman, and thanks to the panel, and I wish uh there had been a miracle today and all of the committees that are meeting would have not met except this one. Uh because frankly, it would have been great. And Mr. Chairman, thanks for your wisdom in

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holding this this hearing. It is so important. But I think that if we all had been here on either side of the aisle, there'd be a great amount of discomfort on our faces at what we are hearing because of the challenges that

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we are forced to face. But um Miss Burns, thank you for giving us some examples of hope and opportunity. also opportunity for me to say this is a time of disruption and higher education needs to find ways of doing things without

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always more money but being creative and setting priorities. So I appreciate the examples and um again I wish we all had had a chance to hear because these are great times but the challenge is there and we don't want to miss it. Uh and uh

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um Mr. horn. I was taken by your example of electricity and u taking that wonderful thing and and just doing the same old same old until finally we woke up and I think that'll be the case with AI but the Chinese Communist Party isn't

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waiting for us and we had better be the ones that are using it well. So could you go on a little bit further uh Mr. Horn and or Dr. horn and um tell us what it would mean for a college to redesign itself around EI on AI

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rather than simply adding AI as a tool. >> Absolutely. on our on our research on innovation, what's become clear is that institutions need freedom uh to free up the how they do their work to be able to actually rethink the resources, processes, the financial formula in some

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cases to your point about doing things with less uh and really reinvent themselves and that requires unconstrained uh in terms of the inputs and what we're looking for in the institution but an absolute rigor on what the outcomes are on the other side and I believe what we would see and we

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are seeing in many pockets already is a plurality of different designs uh where we know for example Western Governor's University is already creating a native AI university experiment. We know that UMass Global is doing the same thing right now. And so we're seeing existing

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institutions literally carve out separate areas where they can rethink the fundamental first principles of what these universities look like. And frankly, we've done this before with online education as well. Many institutions just used online education

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to layer over their existing models. But some institutions again like Western Governors started thinking from first principles. And they have a very different model as you know with taking the faculty role and unbundling it into five different roles uh to create a much

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more robust web of support but also a very affordable model for students that has a very high success rate. again and again an example of where the consortiums and joining together and sharing this is so important. U Mr. Fazard um how should universities

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respond when students are making decisions based on uncertainty about AI's effect on future employment? I >> I think that's a question that all universities should be asking. We're having these conversations with our leadership, our our uh provost, our faculty are having these. I I think that it is every discipline, no matter what

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discipline it is, will need some type of AI literacy and AI skill set. Um there will be degrees and and programs that we will have to think through uh the curriculum and we're going to have to evaluate what those programs look like. But I strongly believe that that every discipline, every field, every degree

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that we have will need some component of artificial intelligence baseline literacy and use. >> Just plan on it. I I I wholeheartedly agree that that is the future for America. >> Dr. Duke, what kinds of evidence do you look for before concluding that an AI tool is truly improving learning and how

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do you ensure those tools are helping students build lasting understanding rather than completing assignments? >> Yeah, thank you for the question. This is something we do pretty well, efficacy research uh and we approach this uh with regards to Gen AI in a similar way um in

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terms of backwards designs. We do pre and post- test measures, basic statistical analysis. Said differently, we have an idea in mind what learning outcome we want to create and we work backwards. Did we create a learning experience that produced that? The new layer though with generative AI is who

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did the work. Uh so when geni is involved, we have to make sure we have preserved the productive struggle of students so that we can assess whether or not they did the work and therefore we had the outcome we wanted. Well, thanks again for

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scaring me, but all also exciting me that my grandkids are going to have an interesting life ahead because of things that we can use and learn from screwing up with electricity originally. Move on. I yield back. >> Thank you. I'd like now to recognize my

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friend from California, Mr. Nado. >> Thank you, Mr. Chairman. Uh Dr. Burns. Uh, thank you for mentioning uh the University of my district, the University of California, Riverside, uh, in your testimony. As you point out, instructors at, uh, UCR are using AI to

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prompt students to learn how to be better writers rather than to do their work for them, not using AI to kind of, you know, coast or or or to make it look like they they wrote um,

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a product. um uh but they're actually using AI to teach the students to actually be better writers. Um innovations like this one are one of the many reasons why UCR is the top university in the country for social mo mobility. What I mean by that is that u

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students of lower economic means come to this university and they they gain the capacity to actually uh increase their economic situation and there are measures out there on social mobility and UCR is one of the universities where

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the students who go there make incredible gains. Um now innovations like the one we just mentioned are one of the so Dr. Burns, what I want to know is do you foresee more examples like the one you gave in which AI technology could lessen

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the gaps in student achievement? >> Um, uh, Congressman, yes. Inc., in in fact, I had a difficult time winnowing my testimony greatly because there were so many examples across our institutions. There is so much creativity and innovation that has been

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unleashed by this technology. I was just on UCR's campus two weeks ago and you would be blown away at the incredible way that we are unleashing the creativity of faculty to reimagine how they can support students. And really for us when you think about closing gaps and thinking about how you can help

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[clears throat] all students. The you know the the holy grail we're looking for here is personalized learning and this is going to enable us to possibly achieve personalized learning at scale with the small pilots and experiments that faculty are doing in real time. and um and we are measuring not just by the

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degree outcomes, but rather we're moving to that postcol mobility as being the measure of our success. Um something that UCR has been a leader on. >> So as a former teacher um at the secondary level um and having been a substitute teacher at the the primary

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level, the individualized learning is what I see as the greatest potential of AI, not replacing the the teacher. um you'll need teachers to for that human interaction um and that human connection

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um but a teacher with 30 kids or 180 kids uh at the higher level but it doesn't change much from like 12th grade to like freshman year uh when students have got to pass uh usually the expository writing requirement and uh

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the university math university level math um and one of the things that I as a former community college trustee that I encountered a lot. What what was a ongoing theme is is the cost of remediation um when students either you know they enter straight into the four-year

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university or that it's a struggle for the community colleges to get students um to not to to retain them. Uh what what have you what are what's what sorts of things are going on in sort of addressing this remediation because I think I kind of think of that as one of

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the gaps. Would you agree with me? >> Um, yes. I I think this is one of the things where you really need um as much uh of the capacity and technology is a is a is a really supportive tool when when used well um to ensure that we can understand what a student knows, what

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they don't know. Otherwise, it's very difficult if you're teaching in a course to actually know where every student is coming in from. So, this is definitely one of the ways we're thinking about it. We uh just wrapped up a complex project to try and address uh DF and withdrawal rates on campus um especially in gateway

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courses and we applied an intervention that made a huge difference uh adding supplemental instruction and nearpeer coaching uh so that students actually had that support and some campuses are experimenting with using AI as a coach as actually using that Socratic method

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to be able to probe students and it's actually helping with learning and that's where we need more studies is to understand how we're going to actually be able to measure the learning improvement. But we already saw that it increase. Uh normally when a student retakes a course, if they've uh take if they've gotten a D or an F in the past,

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they've only passed at about 50% uh that second time. Ours were up to 80% they were passing the course. So we're seeing incredible gains. There are lots of experiments happening. Um I would say that our institutions are are what really matters is not just the number of experiments but how do you make sure

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that the ideas are spreading the scale of learning and how we accelerate ideas across the sector so that every institution can benefit from the experiments and the innovation that are underway. >> Well thank you. I wish we could spend more time together but um I got to be

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respectful. I yield back. >> Thank you. I would like to recognize my friend from North Carolina, Mr. Harris. >> Thank you, Mr. chairman and thank you to all of you on the panel today for your expertise and and Mr. Chairman, appreciate you uh calling this uh this hearing. You know, over the last several

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years, we've seen a dramatic increase obviously in the use of AI programs and this increase has been apparent in academic settings from K12 institutions to secondary schools to colleges and universities. And while many students have used AI to complete coursework,

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there has been a need across the workforce for students to have more of an in-depth knowledge of how to use AI technology in professional settings. As you all have have touched on today, closing that knowledge gap between students using AI for coursework and the

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young professionals entering the workforce where proficiency with AI programs is necessary for creating work products is absolutely critical. And Dr. Duke, I I just noticed in reading your written testimony, you explained the ability to work with AI tools

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productively, critically, and responsibly within a specific skill domain is an expectation that is shown in job descriptions for in entry level jobs across the country. I would ask how can we help prepare students to transfer

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their AI knowledge from basic AI proficiency learned in school to the skills that our workforce are actually looking for. Thank you for the question. I think one of the um missteps we can make is to synonymize enabling a workforce with

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artificial intelligence and applying AI to the learning journey. They're not the same thing. In the workforce, you want people to be very very efficient, work efficiently, make very few mistakes, >> right? >> When people are learning, you actually want that to be inefficient. Sometimes you want them to make mistakes. That's

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where the best learning happens. And there is the dilemma >> along the way. These students have to establish proficiency while also managing learning. And so one way we can do that is to integrate it into the curriculum. We could define the set of

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skills that students need and make sure that they get them along the way. They get some of this uh proficiency through daily use, but it's not the same as cultivated professional competency. And this is where I think the learning science actually needs to catch up and

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how we need to change concept mastery and how a student marches toward not knowing anything and graduating and being in the workforce. and and you also discussed the importance of treating AI proficiency as a quote core educational competency just like information

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literacy, quantitative reasoning or financial literacy. What would you in your opinion treating AI proficiency as a core educational competency look like in the higher education setting? >> One, we would have to say that we would have to determine that it is a core

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competency or something that is um expected. Right now I don't think that we do that. We do that in other areas like financial literacy and information literacy as you point out but until we do that institutions aren't going to be able to design their curricula around

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that and also um making it a core competency I think will accelerate some of the thinking the experiments and the testing that we've talked about on the panel today um and will help us improve in this area. >> Thank you. On January 23rd, 2025,

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President Trump issued an executive order titled removing barriers to American leadership and artificial intelligence. And although that EO does not specifically address higher education, the goal of the order was to revoke restrictive policies and promote

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innovation. And Mr. Vizard, I just want to ask in your experience working at Florida State University, what impact does removing restrictive policies and promoting innovation have on the way AI is developed and utilized on college and

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university campuses like your own. >> I I think that artificial intelligence has to have the ability um to be integrated into curriculum, be uh accessible to our students. Um a case in an example is we partnered on a design sprint. It was a 24-hour design sprint

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with students across multiple disciplines to solve a real world problem. AI didn't do the job for them. They had to come together. They had to collaborate. They had to use AI in these in these u new and innovative ways to solve a problem. So there was a problem, you get a team together, they have 24 hours to work around the clock to solve

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it. It's something that they're going to do in the real world setting too in their careers. And I think that we have to allow the space for innovation um to take place. The other thing that I would say is we have been heavily investing in u the material science space, the engineering space, the quantum technology space at Florida State

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University and that's under the leadership of our president because that will differentiate us too to have that infrastructure and we must be able to research that and to invest in that um to be able to really be a leader in the world in artificial intelligence. >> Well, thank you very much and Mr. Chairman, I yield back.

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>> Thank you. And [clears throat] I'd like to in to recognize my friend from our Oregon, Miss Panovichi. Uh thank you, Mr. Chairman. Thank you to the witnesses. Dr. Burns, thank you for all the work you've done in higher education in Oregon and now of course with the alliance. Um AI we know is shaping

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classrooms and workplaces uh faster than many schools and employers can respond. I'm also on the early childhood K12 subcommittee and we're having similar conversations there. Uh but I tell you many educators at all levels are concerned about a decline in their students creativity and critical

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thinking skills. Dr. Dr. Rebecca Winthre from the Brookings Institution calls this cognitive stunting. And if it's happening at the K12 level, it's definitely going to be affecting higher education. It's the impairment of cognitive development that results from an overreiance on AI tools in the

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learning process. I'd like to submit for the record a recent article by Dr. Winthre that's in the New York Times titled, "What 370,000 college essays tell us about AI's effects on creativity." Uh Dr. Dr. Winthre discusses the importance of the brainstorming process for building

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creative thinking skills and generating new and innovative ideas and offloading the act of brainstorming is one of the many ways that despite its numerous promises AI can do more harm than good for students in the long run. So I'd like to submit that article for the record, Mr. Chairman.

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>> No objection. >> Uh and and UC Berkeley School of Law has a new policy that restricting the use of AI in academic work submitted for credit. They want students to use their cognitive skills. The policy prohibits AI in conceptualization, revision, translation, and exams. A recent article

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about the California state system just out discussed a survey that a majority of students and faculty are skeptical of the benefits and worry about what AI will do to not only job security and creativity, but also the environment. Um, and there's a lot of questions about

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AI grading. Um, I'm a parent who paid college tuition for two students for many years. Uh, when students are paying tuition, do they not deserve human feedback? And so there's questions about AI grading as well, uh, privacy, security, bias. Um, so I just want to to

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to put that out there. As AI continues to integrate in higher education, I think it's more important that institutions put appropriate safeguards in place to protect students from the risks including from the misuse and harmful effects and protect against

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bias, protect privacy and security and also uh the uh the decline of critical thinking skills. So, Dr. Burns, what safeguards should be in place to protect students from the risks associated with AI, including cognitive stunting? Um,

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thank you, Congressman uh Guanamichi. I uh I share your concerns. These are things that our institutions are wrestling with right now in real time. Every institution in the country is. And again, I'm most concerned about underresourced institution's navigating this because these are things that are absolutely on the frontier of science.

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We're trying to figure out the learning effects um the the mental uh effects, the cognitive load. Um I would say that you want more you want more testing, you want more validation and you want this a thoughtful uh process where institutions are evaluating materials. But I think in

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terms of privacy, we know that um and the protections for students that we absolutely are responsible and uh we cannot delegate that um responsibility for student privacy to a vendor which is where you create the problem because >> Right. Right. and and I hope that

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responsibility is is shared among all institutions of higher education. The World Economic Forum's future of work report just forecasted that AI literacy, creative thinking, and curiosity will all be core skills in 2020. But AI literacy involves more than just

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learning how to write prompts. People need to know how to critically evaluate AI through ethical and linguistic and social perspectives that reinforce that critical thinking. I I'm thinking of the example of the when we we we recently spoke with Dr. Winthrop, but she was talking about how like a 10th grade

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student will write a paper using AI and then put it through a humanizer to make it look like a 10th grade student wrote it. So they take out sophisticated language and put in some typos and then if if then if AI is grading it, I mean we what what are we doing uh in in education? So what is the current state

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of AI literacy in higher education and how are institutions integrating AI literacy across fields of study especially among the [clears throat] humanities which remain important. >> Uh so our institutions like I shared Purdue already has put this into their graduation requirements. It's AI

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literacy. Um other institutions are following. We believe that it is technical fluency. So you need to understand how it works and why when to use it. Um, but it also has to have those durable human skills as the as the back end. You need the critical thinking and the judgment to work alongside AI. >> Absolutely. And and I've mentioned this

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before. I'm working on a comprehensive human-based framework to to strengthen uh teaching, learning, and dignity of work in an AI enabled economy. I look forward to working with my colleagues hopefully on both sides of the aisle to really promote that critical thinking which will remain important uh going

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forward to improve literacy and professional development which there is not enough of in not just in the higher ed system but also in the K12 system and also protect privacy safety and civil rights. So thank you very much Mr. Chairman. Thank you to the witnesses and I yield back.

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>> Thank you. I would like to recognize my friend from Missouri Dr. Andrew. >> Thank you Mr. chairman and thank you to the witnesses for coming before the subcommittee today. Um it's no secret that our students are increasingly outsourcing their cognition to

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generative AI platforms like chat GPT and October 2025 nationwide survey of college students showed that 64% of students used AI to get help with coursework and 36% used AI to write their papers. Uh there is concern that

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student outcomes are worsening because AI thinking is replacing student thinking. A September 2025 survey of employers re revealed that only 22% of hiring managers believed that entry-level employees were prepared to

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do their jobs. Um the reason according to most of these employers is that the upcoming generation lacked the skills needed to thrive in the work workplace because their heads were buried in their cell phones. Constant phone usage uh

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decreases attention spans and leads to poor poor academic performance. A study a study monitoring the cell phone usage of university students in Brazil showed that for every 100 minutes of daily cell phone usage there was a corresponding

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drop of 6.3% in academic rate ranking with with uh with with usage uh during class nearly doubling that drop. And when young people are simultaneously addicted to technology and performing poorly in class, they search for an easy

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way out and they may use their AI chatbot to write their papers for them or give them answers to test questions. They can outsource critical thinking skills uh instead of working through problems or asking teachers or peers for the help that they might need. Um, I

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commend institutions like UC Berkeley School of Law that adopted an AI policy prohibiting students from using AI except to identify sources for research papers. I think it's worth reading a few sentences of that policy aloud. quote, "Future lawyers may need to use AI

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fluently, but the current state of technology requires AI use to be coupled with the cognitive skills necessary to strategically deploy the technology uh to critically assess its work product and to uphold ethical obligations to

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clients and to the legal system. In short, thinking remains the sin quuanon of good lawyering and of a quality legal education. This policy seeks to ensure our courses focus on requisite cognitive skills. It provides students with the

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opportunity to develop their skills that they need to conceptualize, outline, draft, revise, and edit their work by forbidding use of AI for purposes in connection with work submitted for credit. Uh, this policy was crafted specifically for legal education, but I

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think uh it can and should be applied in other academic settings. Um, Mr. Horn uh what policies do you think institutions of higher education can adopt uh applicable to any academic discipline that uh student that u ensure that

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students are not outsourcing their thinking to AI? >> Yeah. First I want to say I appreciate the uh point that you have made and the concern. I think it's a very real one at the current moment and I think it speaks to the importance of building foundational knowledge. I said a lot about cell phone use, but I think AI has

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the potential of these harms we see from cell phone use on steroids. >> 100%. And what I would say is this is where we need nuance in the conversation, right? We need as opposed to an all or nothing intentional use where it's supporting the kind of personalization we heard earlier, great.

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When it's to do the cognitive automation where you're not doing the work, that's a huge problem. And so I think building knowledge, foundational knowledge so you can do the critical thinking and judgment and understand when it's going wrong and right uh is critical and having a clear set of what's the

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learning objective, what are the tools allowed for it, how are we going to assess it. Often that should be real- time oral defenses, real-time conversations with faculty where you can't rely on the crutch. But then conversely, I know many uh uh recent graduates, for example, I I was recently

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talking to someone uh who produces uh uh graduates in film studies. They were applying to entry- level jobs that were expecting them to use AI tools in their production and they had no experience with it for their education. That's a problem on the flip side. >> Thank you. Uh Mr. Fazard, uh does

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Florida State uh have any any plans or recommendations in this in this area? So we so we freely and openly share. We actually have guidelines that are posted that we worked with our faculty, our students, our our university leadership to post across all disciplines. So um we freely and readily share. We also have

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three uh K- through2 uh kind of laboratory charter schools. So we're not just a higher education institution. We're looking at this through the whole lens of the K through2 all the way into higher education and then those that enter the workforce after graduation. >> Thank you. I yield back. >> Thank you. I'd like to uh recognize my

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friend from Arizona, Mr. Holden. >> Thank you, Mr. Chairman. Um, as the representative for Arizona's seventh congressional district serving the University of Arizona, Puma Community College, and a diverse student body, I believe that innovation is only

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progress if it expands opportunity for everyone. Crucially, we must recognize that if we do not provide proper guard rails, AI can quickly turn from a tool for success into a weapon used against our most vulnerable students. I am concerned that while institutions are

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being pushed to adopt these new tools, the current administration is dismantling the very federal offices meant to protect students, including the Office of Educational Technology and the Office of Civil Rights. These are entities responsible for providing the guidance schools need to prevent

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documented harms. And also as a schoolboard member for 20 years, these offices were very critically important to the work we did at a very local level. Like and like the Stamford University study showing AI tools falsely flagging non-native English

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speakers for plagiarism. This shows that these risks are not rhetorical. They're happening right now. We cannot ask our colleges to be AI ready while the federal government is stripping away the oversight meant to ensure equity and justice in the classroom. Dr. Burns,

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it's a pleasure to have you here, especially given your ties to our state's higher education system through your time at the at Arizona State University. Given your leadership scaling student success across the country, I'd like to start with practical ways we're seeing these technologies implemented on our

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campuses. Um, colleges and universities are navigating how to integrate AI into academic and student support functions, including academic advising and other student success supports. Reports indicate that some colleges and universities are seeking out strategies

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to integrate AI into curricula and instruction to advance student success. Could you share some examples of how some colleges and universities are scaling student success initiatives and support uh through AI? Uh thank you congresswoman. Uh yes we

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actually this is one of the challenges is there is so much happening in this space. Um I shared earlier about uh one example where the writing faculty which was the first department that was most impacted by AI initially. It was the writing departments. They started seeing it uh when chat GPT was first released.

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Um they had to immediately figure out how you were going to adapt and how do we make it so that this is not going to address some of that cognitive burden challenge. Um so figuring out how you use tools as a a Socratic learning tool, how you actually can create ways that it's a prompt that's actually stimulating more creativity and more uh

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learning from students. That's happening in real time across all of my institutions. Um and I would say the number of experiments is is quite significant and they are sharing in real time. Part of the challenge is uh that we they're literally using AI in so many

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different facets of the institution and trying to find and develop the coordinating infrastructure that brings those different entities together which did not previously exist is part of the complexity in the moment. So, building on those concerns, I want to specifically um look specifically at the

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accountability vacuum left by the loss of federal oversight I mentioned earlier. Since the federal government has eliminated the offices that once provided safety toolkits and civil rights guidance were often leaving institutions and students to fend for themselves when technology fails. Um,

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with the loss of these centralized federal oversight bodies and the guidance they provided, what entity is currently responsible for holding institutions or private tech vendors accountable when their AI systems produce these types of discriminatory results? And that's for Dr. Burns.

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>> Uh, Congresswoman, what we we're very clear that this is actually something that is the responsibility of our own institutions. We cannot actually we uh delegate the responsibility for um when it comes to students uh privacy protections um which is part of where

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the challenge is is that we're having to evaluate every single vendor individually. Um in general uh there need to be privacy protections that are very clear, enforceable and modern and no matter where that enforcement is happening. I know there is transition currently we just need that I would say

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that institutions need the capacity to evaluate the tools and someone needs to provide that kind of enforcement mechanism uh regardless of where they're located. They need to be able to help guide institutions as they're navigating the constantly changing environment. >> Yeah. Thank you. Beyond just identifying

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these risks, what specific pathways for recourse currently exists for a student who's been unfairly penalized or academically disciplined due to bias algorithm? >> Um, Congresswoman, again, we we are very clear that this is not something that we can delegate uh the responsibility for

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enforcement to any company and so we take that responsibility very seriously and uh we believe very strongly that a human must be in the loop on any consequential decisions. And so, uh, in any of the examples I'm sharing, if a decision is made, there has to be a human brought in, and that's how we're

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building from the ground up. >> Okay. Thank you. I yelled back. >> Thank you. Now, I'd like to recognize my friend from Wisconsin, Mr. Goffman. >> Thank um start with Mr. Horn. You emphasized that students need real world work

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experience because AI is rapidly is rapidly changing the nature of work. How can internships, apprenticeships, and employer connected projects help ensure students graduate with the necessary skills and experience? >> I think when you think about uh building

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student understanding of what the workplace will look like, there's three modes to think about is learning about work, learning through work, and then learning at work. And so a college program that starts in the early years with bringing exposure to students so they can understand, hey, this is

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something I actually want to do. This is something I don't want to do and rule it out. That iterative nature is important. Secondly, when they're actually interacting with employers uh in these settings through projects, apprenticeships, internships, and the like, they're actually building real

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world connections, real social capital, real mentors that can help guide them and get them into jobs in the future. One of the myths I think that the younger generation often has is that you get a job by applying online when research shows upwards of 50% maybe as

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high as 85% of jobs are filled by someone in your network. And then thirdly, you actually get to experience the real ways that technology is used in these jobs and what professionalism and the durable skills that you need to bring to bear look like in these roles.

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And you build that fluency while you're in school. That's the uh entry level experience you need to get that first job. >> Okay. What barriers do you think students face when trying to just start out with an internship or apprenticeship related to AI?

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>> I think the biggest thing right now is that schools are not providing the instructure nearly enough to actually make that a default option. What I hear from a lot of the schools that I talk to is, "Oh, we offer that, but only our top students take advantage of it." This

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should be the default for every single student. So no one's falling through the cracks. They should be doing it on the front end of the academic planning. So it's part of the process. Career services shouldn't be the afterthought that's at the end of the process. >> Okay. Mr. Fazard, one of my concerns

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about AI is that it could lead to a decrease in human involvement in the workplace due to overinvolvement on technology. How is Florida State's information technology services internship program ensuring that human oversight is not removed? >> Thank you for that question. I actually

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was a product of a student internship. Um I got into my career in technology because of that. And uh we have 150 student interns that go through each semester hands-on experience, hands-on learning with artificial intelligence and how we can use it at the university. And those are positions from cyber

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security to helping assisting with our enrollment to uh doing student support services. And our results in those internships show because we have a 99% uh fall to uh spring uh retention rate in our university. And we're using these

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students not just as uh workers that are grabbing coffee or making copies, but actually using the technology and having hands-on experience before they graduate. um we're seeing these students not just succeed but thrive in their careers. >> Okay. Uh there's a broader question. One

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of the things that concerns me about AI when you look at other uh platforms even in the past even you just Google something uh when you begin to look over time you see an ideological bent to what comes back and as it is you know you

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read articles generated by AI and over time you begin to see a little bits of ideological bias as well in which maybe things in history disappear and things that or minor in history all of a sudden are exaggerated. It becomes a very very

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scary thing. Um and I don't know what to do about it. But would any of you like to take a shot on what we can do to make sure in the future I can trust if I use AI that I'm getting something that is

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factual, not ideologically tilted. I just just briefly I think that this is where education has to play a major role. The critical thinking skills cannot be replaced by artificial intelligence and this is where K through2 education and higher education must be present and we must equip our

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students with those critical thinking skills um to be able to leverage those tools and be able to question those tools. >> My my question is I think people what they learn is going to be based on what AI gives them. Right? We already have the schools I believe overwhelmingly

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biased because we have overwhelmingly biased faculty. Now if you have overwhelmingly biased AI or even a little bit biased AI in which irrelevant parts of history are you know you can you can create a world view. I don't see

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how we do that no matter how good the student is if his reference becomes AI. I I would just argue that um you know any technology, any media, anything that we have access to, we have to use critical thinking skills to be able to

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determine and to differentiate fact from fiction. And so I view AI as a technology and a tool. It's not a a magic eight-ball. Um it has to use data and it has to have um compute power to be able to give and provide answers. And I think that if we view AI through this

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lens of um being kind of the sole source of truth, we negate the human aspect, which I think is so so important to be able to differentiate fact from fiction. >> Okay. Thank you. Thank you. U now I'd like to Whoops. Now I'd like to recognize my friend from

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California, uh Mr. Dr. Sonier. >> Thank you, Mr. Chairman. Um well, I want to thank you all for being here. It's fascinating. Uh I'd like to talk first of all uh Mr. Burns about um the behavioral health health aspect of kids

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as they develop and go to college. I think uh where am I? So Dr. Burns um I just flew in so forgive me [snorts] jet lag. Uh I speaking of jet lag. So, the University of California, I think recently over the weekend was talking

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about reestablishing te standardized testing because so many of the students that they're getting are that the professors uh just don't feel like they're noticeably not prepared. Um, so when it comes to behavioral health in kids, we've got a lot of good research

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now developing about the effect on cognitive development and social media in general. Um, but particularly with AI is quite frightening. I just had a meeting with the authors of the AI con and it's just uh it's a combination of marketing and as a member from the Bay

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Area who has friends in tech who warned me that uh we're doing the same thing with AI that we did with social medias. We're marketing um and unfortunately caveat emptor I don't think kids are prepared to be aware of particularly the sophistication of how their brains are

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being developed when they're on um on this AI. So could you speak a little bit about that as first do no harm? How are we dealing with cognitive development and AI and how do we get at least a a standard of first do no harm before we

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really know how bad this is particularly by the time they get to higher education. >> Congressman, [snorts] I I think your concerns are shared broadly um not just within the academic environment. We are seeing that this is going to create long-term effects because this is a workforce readiness challenge as well.

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Um I think this is a place where we need more investment in federal research because we need to have far more testing uh to happen not just you know be like on the actual models as they're developing but the the short medium and long-term effects on students. it is happening so quickly and um I would say

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this is a space where there's a need for not just federal research investment but to have it be multi-institutional so that we're actually pulling together the expertise across the country because I think this is not something that you want [snorts] one institution or one entity to figure out how we do it better

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you want this to actually spread broadly >> and I have a bill just um that I have with some other members just it's like a warning um bill uh that would just tell parents that when you go online, this is just for social media, but make it stronger for AI, just sort of like

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tobacco or liquor, make parents and kids be aware that when you go on here, you really don't know the power um and how sophisticated it is. Could you respond to that and anyone else who would respond to it? And the gist the gist of everything I'm trying to get at is having spent a lot of time on this having spent a lot of time with experts

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in the Bay Area at Stanford particularly both pedi uh neurological pediatricians and people in the education school there is and their relationship with artificial intelligence um and with technology how do we have a discussion

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about we don't want to inhibit innovation but the other hand we've got to slow it down so we make sure the full consequences and the fact that most people don't realize how targeted these algorithms are becoming. >> Um, Congressman, again, I I just want to reinforce that um, [snorts] your your

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concerns are shared broadly for parents everywhere. Young people and our faculty are contemplating this on a daily basis as students are coming into the classroom. We're trying to analyze exactly what is happening and to really study the learning effects. I would say that this field is somewhat nent that this is a space where we need to do more

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research. We need to actually um interrogate this uh all along the way. But again, it also is just so clear to me the lack of broader coordination to ensure that institutions are pulling together on this. This is not a challenge that any one human being will be able to to tackle or one [snorts]

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institution will tackle. You need the entire higher education sector to be enrolled in figuring out how to use AI responsibly because we take protecting our students very seriously and we don't delegate that responsibility to anyone else. The real thing is who's missing up here are the AI providers, right? And

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that's these models are being released so quickly and the question of whether or not they're having the level of efficacy testing prior to release is something that definitely needs to be paid attention to. >> Well, and I hear that in the Bay Area when I go out and talk to people, they're like, "Oh, you're inhibiting innovation." I said, "That's what you

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told me 15 years ago, and I don't want to inhibit in innovation, but we've got to be careful of the consequences. you can make a lot of money, but we're not fully aware. And one of the best stories on this, and I'll wrap up, sorry I didn't get to have you respond, is the YouTube story about pre-adolescent

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adolescent girls being targeted by their algorithm. So that 30% of them were predisposed to suicidal uh ideiation and depression to the point where the YouTube algorithms would bring them all the way to a YouTube that showed them how to commit suicide. And it wasn't for a reporter, we might not have found that

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out at all. So with that, I will thank you. I apologize for not having been giving you enough time to talk uh answer my questions and thank you Mr. Chairman. I yield back. >> Thank you. I'd like to recognize my friend from Florida, Mr. Fine. >> Well, thank you, Mr. Chairman. Um for the last couple weeks, I've been having

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a lot of nostalgia. My my oldest son um graduated from high school two weeks ago, and I've thought about how his high school and junior high career has changed as he gets ready to go to college. He was one of the kids who went home for spring break in sixth grade and then had the longest spring break ever

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because they never went back to school because of COVID. And then his junior high was ruined because of many of the terrible decisions that government made about how to deal with COVID. Something that the kids graduating now about to go off to universities are probably behind forever because of the decisions that

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were made. But now I've gotten to watch over the last year how AI has affected his senior year. Fortunately, he was smart enough to realize that if you had AI write your paper, um there might be AI that could figure out that you used AI to write your paper as some of his

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classmates learned the hard way. So, we have seen that these technologies are changing how the world works. And I I apologize the other three witnesses. My questions are going to be for the home for the home state, um Florida State, where my son did apply and was admitted, but I'm sorry, he he's going out of state. I won't say where. Um um I I

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wanted to ask you though a question about a bill I've introduced HR8747 the K12 AI literacy and readiness act. So the bill recognizes that AI is becoming as foundational as computers and the internet. It fundamentally modernizes schools to help integrate new

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this new technology equip teachers and prepare students to compete in an AIdriven economy in a safe and responsible way. Do you believe that if if K12 schools um begin preparing students with AI concept and tools, will those Florida students be better

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prepared to succeed at places like Florida State and in the economy shaped by AI? >> I Congressman, I think that you have to have those baseline skills um in the K through2 space to translate into higher education and translate into the workplace. I think the earlier that we

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can get those skills in a safe, secure environment with our students, the more likely that they'll be successful in using the the the technology and to the other congressman's question, they'll be able to evaluate it um in the right ways on how they're using it with the critical thinking skills and and what

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what works and what doesn't. And my bill, to be clear, isn't just about training students. Students, to some degree, can figure it out faster than we can because they're younger. My my son is much more advanced in the use of AI than his 52-year-old father who by the way spent 22 years building software

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companies. So I see how fast the world world has changed. But I want to talk about what all this means. Um people worry that AI is going to replace the jobs on which we rely and depend on. Um frankly for many of I I think particularly some of my colleagues I

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think the people who used to write their speeches are replaced by AI. Um, unfortunately not me. But without exaggeration, whether we welcome it or not, we should we should welcome this inevitable reality. Technology has changed how the world works since the horse and buggy. And we didn't look back, we looked forward, and we have to

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do that here as well. Um, our education system though has a challenge to prepare them for the reality, to not train them for the jobs that will no longer exist, but to train them for the ones that will. So, what can universities do? What could Florida State do? the other universities in our number one in

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America state university system in Florida. What can we do to ensure students don't lose the critical thinking, the problem solving, the communication and other foundational skills that many believe could be eroded by AI? >> I I think it it comes down to access. We have to give ubiquitous access across

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all disciplines, not just one discipline. It's not just computer science majors. It has to be every major that goes through a collegiate system has to have access to the technologies in a secure environment. I would also offer that Florida State University, we are giving a um AI kind of foundational

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certification that every student has access to take to build those skill sets up and it's regardless of discipline, regardless of program, everybody has access to that to build those skills. I think it's very important to lead, not follow. >> All right. Well, since I have a few minutes left, I'm going to let someone from my alma mater actually answer the

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question even though he's not from Florida. Mr. Horn, I don't know if you've got any thoughts on these questions. I think this is why it's so uh critical to frankly build knowledge right as we uh start uh the the uh progress up and recognize that the use of AI in different domains is going to look

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differently in different places and so each domain is going to have to be very intentional about how it uses AI and what are the foundational knowledge building blocks and then what are the skills of integrating AI. The one analogy I would say is when we had calculators introduced several decades ago, we still learned how to add,

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subtract, do multiplication, and frankly memorize multiplication tables, then you could use the calculators to help you. But >> as I've had to remind my 14-year-old, >> and it's an important fact that we still need to build those uh cognitive literacies. >> Well, thank you. Look, I think the key thing is this is going to change

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incredibly fast. It's not just that the world is changing. the rate at which it is changing is changing faster and we've all got to be prepared to deal with that to make sure our kids are prepared for the future. Thank you, Mr. Chairman, and I yield back. >> Thank you. I'd like to now recognize my friend from Virginia, Mr. Scott.

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>> Thank you. Thank you, Mr. Chairman. Um, Mrs. Burns, you indicated Dr. Burns, you indicated um that well resourced institutions need to disseminate the information they gain to lesser resourced information res.

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Exactly. How would they do that? >> Uh, congressman, thank you for the question. Uh, so this is my biggest concern is that it's shouldn't be left on the responsibility of the institutions themselves. They can make decisions about how they build things. The example I shared from ASU of they actually built the entire triangulator

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outside of ASU system so others could use it. Um the real question is who is what infrastructure is missing uh in terms of ensuring coordination that that institutions across the country are able to know what experiments are happening? What have you learned? Um can I can I

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borrow that that language that used in that contract? How do how is this a good vendor to use or not? All of these questions right now relying on just people happening to know who to talk to. And given that AI, who's the actual professional responsible for AI, is adapting in real time, this is a huge

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space that has challenges. K12 has uh something called the Eds Safe Alliance, which has played a critical coordinating function so that uh lessons learned about literacy, safety, and privacy are spreading. We think that something similar needs to exist in higher red. [clears throat] [snorts]

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>> Thank you, Mr. Facade. um how is uh student data protected and not misused and how do you make sure that students know how their data is being collected? >> That's a great question and thank you for asking it. One of the the frameworks that we have at Florida State University

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is to make sure that we sign agreements with companies to make sure that our data isn't used to train models. Um it's one of the foundational aspects at Florida State University. I think every university should ensure that that there's not free models being used that go and train their intellectual property isn't being given away, their research

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isn't being given away to train a model. And so we enter into agreements and sign agreements with companies uh before we offer this at the enterprise level again to every student, every faculty and staff um to ensure that our data is in a secure and protected environment >> and

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AI can be used for administration in colleges as well as the teaching. How would it be used in admissions and administration and particularly how would you avoid racial discrimination in this application?

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>> Could could you repeat I >> you're using uh if can you use AI in admissions? >> Correct. Yeah, we use it across >> and administration and how would you make sure that racial discrimination isn't embedded in those algorithms? Yeah. So, we we still believe strongly in a human in the loop and I think it

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needs to be a founding principle for all artificial intelligence that a human is in the loop in automation processes and reviews. There still needs to be a human in the loop. Um and and that's one of our foundation principles that we have at Florida State. >> So, there'd be no loophole or for racial

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discrimination just because you're using AI? >> I'm I'm not aware of any. >> Okay. Mr. Horn, how is the graduate school preparing teachers to use AI? >> Uh, the candid answer is it's uneven across different faculty and classes at

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the moment. Uh, and we're we're all trying to figure it out right now in different ways. >> All right. Um, Mr. Duke, you've indicated that um, AI is used in um, job skills. What kind of jobs do you see AI

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well-prepared AI students doing much better on the job than those that are poorly poorly prepared? >> Well, certainly knowledge work um is is one of the most impacted domains uh for AI ready job skills. So, I would say any

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knowledge work that you can think of, whether you're going to be an accountant or a consultant, students who can leverage AI to create work products the first day on the job are going to do better than students who do not. Um, students who are going into more hands-on jobs in the trades are less

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affected by that. Um, but that's the domain uh that we see impacted the most. >> Is that the kind of thing that you can pick up by job training >> in the knowledgebased sector? Right. >> It is. However, you're going to have a hard time competing against a student

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that already has those skills on day one. >> Thank you, Mr. Chairman. >> Thank you. I can now recognize my friend from Guam, Mr. Mullen. >> Thank you, Mr. Chairman. Panel, thank you for your testimonies. And uh Dr. Duke, first question for you. In your

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written testimony, you stated, "Access to higher education in the United States has always been shaped by geography, economics, and the ability uh of support structures." I totally agree with you and I don't think anyone knows this better than the

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people of Guam and the millions of Americans who call the territories home. Small economies and geographic isolations often mean that territorial development lags behind Konis. So, how is McGraill and other private entities

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working to expand access to higher education and critical workforce skills in geographically isolated parts of the US? Great question and thank you for calling that out in my testimony. The the first way that we're doing that is is

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integrating AI enabled product experiences into our products. And so, if you buy our products, you're getting that access baked in. One of the things I wanted to talk about earlier I wasn't able to get in is that we keep bringing together the idea that an LLM is the

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same as AI enabled product experiences embedded into an existing platform that a student might use. They're two different things. They're managed in different ways. And so in terms of access and our ability to make those kinds of features, whether it is um uh

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features that help a student translate content into their native language, whether it is the ability for a student to get extra support after a faculty member is is not around late at night, we bake those into our products so that

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that access extends to anyone using our platforms. That's primarily how we do that. >> Thank you, Dr. do u Mr. Horn uh you used electricity and factories analogy uh to describe using AI in the workplace and

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how innovation requires us to rethink traditional processes. But it's also true that AI should not come at the expense of human dignity. Now Pope Leo recently stated work is not considered simply as a problem to be dealt with or

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a means of generating income but a fundamental good for the person, a principle of economic activity. and the key to the entire societal questions. Through work, human beings bring their freedom, creativity, and the capacity

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for cooperation into play, contributing to the cultural and moral evaluation of society. Thought and creativity should not be replaced with chat GBT, nor should we see humans display displaced

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because of mass adoption. Instead, AI should enhance learning outcomes, job performance, and see our country become more competitive rather than complacent. So, how can institutions, industries, and government come together to work

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towards measurable progress to keep the US and the leader in education and innovation? >> Thank you for your question. I share the concern and what I would say is a few things. Number one, fundamentally in education, we are about building human

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capital and the human dignity of each individual and that's the center of the enterprise and so everything should start from that uh point. The second one I would say is there is a view of the future of work where it becomes uh uh fewer people working. I don't share that

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view. I think that what we have seen throughout history is that when technology makes something abundant, the things around it all of a sudden seem scarce and human ingenuity leans into that. And so much so the importance of making sure that individuals in

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education institutions have opportunities to do real work with real employers, build those connections, build that understanding of work, what work looks like, so that they can become the creators of those jobs and companies and uh processes in the future that will

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power the American economy. And I think the more we give those opportunities, the more we will continue to signal that the human is the center of that. Thank you. Oh, one final final question for you, sir. Mr. Horn, building off your point that colleges need to redesign their models as AI reshapes

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education and the workforce for students in places like Guam, where geography can limit access to specialized programs and employer connected learning opportunities. How can AI help overcome geographical barriers and prepare students for careers and opportunities

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of the future? It's really interesting when online learning burst on the scene, it all of a sudden created much more access regardless of where you were to expertise. What I think AI is now doing is uh for the first time, we've heard a lot about virtual reality simulations and things like that over the years. We

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can actually now create those at scale that bring it to people wherever they may be uh and give them access to those real embedded opportunities regardless of what the local ecosystem looks like. >> Thank you, panel. Thank you, Mr. Chairman. >> Thank you. Uh we'll now move toward uh

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move to our closing uh closing remarks. I'd like to recognize uh Dr. Adams for her closing remarks. >> Thank you, M. Thank you. Thank you, Mr. Chairman. Um let me just um first of all thank all of the

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witnesses uh again for testifying today. Uh today's discussion has reinforced a a simple reality. AI is is not a future issue. It's already affecting how students learn, how faculty teach, how institutions operate, and how employers

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evaluate skills and qualifications. The decisions we make now will will shape whether this technology expands opportunity or deepens existing inequities. No one is suggesting that we should ignore innovation or try to stop

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technological progress. The question is whether we will put in place the the ne the safeguards necessary to ensure that that innovation serves the the public interest. Students should not have to worry that that an opaque algorithm w

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will determine their educational opportunities. Faculty should not be left without guidance as as these tools become more integrated in classrooms and institutions should not be forced to navigate these challenges alone. As AI

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continues to evolve, guard rails become more important, not less. We need transparency, accountability, strong protections for student data, robust uh enforcement of civil rights laws, and clear guidance that helps institutions

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use these tools safely and responsibly. Higher education has always been about preparing people for the future. I spent 40 years in the classroom uh at Bennett College in Greensboro, North Carolina. And I know that our responsibility is to

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ensure that the future we are preparing them for is one where where technology strengthens learning uh expand opportunities and respects the rights and dignity of every student. That is the work before us and it is the work

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that we cannot afford to delay. So I thank the witnesses again. I thank you Mr. Chairman. I yield back. >> Thank you. Um I'm going to to highlight what the chairman of full committee said. Uh this is a a hearing I wish all of my colleagues could sit in and listen

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to. Um and I also can see the bipartisanship we have here. We we all have concerns uh uh make sure there's a balance between opportunities and also the dangers of this process. But uh I I I came across a a quote just just a couple days ago. Productivity productive

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capacity is power. Um I'm so excited uh for teachers like my parents. My dad was a professor Floyd for 40 years. mom was a high school teacher and they their eyes they just were so excited about seeing the the eyes of their kids that are teaching that just open up their

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confidence grow and that was a mission. I'm so excited about teachers like that in the future we have as we produce really I think one of the most productive generations coming if we make sure we down balance this right uh I I wrote down just a couple words as we were going through this I just wanted to share with you guys uh words like this

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disruption sharing of open I uh open AI we even got into electricity we talked about paradigm shift of electricity uh personalized learning at scale uh ubiquitous access and we talk about colleges like the HPUs that uh that

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would need this uh knowledge work uh critical thinking human dignity dignity uh this these are all words that we can now say we have a great opportunity to to embrace uh I cannot wait to see the the pro productivity we're going to have our kids coming in the future as they

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they begin to understand how to critical think and work in this process and I want to thank you also you and your industry um this is a remarkable time and we need to have people that are smart that are passionate that have the intelligence the wisdom come to know the difference and and also to know that you

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can lean in and and uh and um and and have this collaborative effort to make sure that we all grow as a country. This is a very important time for our country's future and this process you we're going through right now and what you represent will will make sure we're leading in in a good good way. So I want

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to thank you uh for all the work you're doing for work that we'll be seeing in the near future. Um, and I'd like to again thank the witness for taking the time to testify before the sub committee today. Without objections and there being no further business, the subcommittee stands of

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journ. >> Thank you. >> Thank you. >> I know that's all. Oops.