The Buffalo Statement for Public AI

The US AI Summit hosted by UB, in partnership with Times Higher Education and Inside Higher Ed, brought together nearly 200 participants from universities, government and industry organizations from across the nation and internationally for a two-day symposium to discuss and collaborate on the future of AI for the public good. 

The Buffalo Statement is the collective outcome of the US AI Summit’s dialogue on AI for the public good. Shaped by diverse perspectives from across sectors, this statement reflects a shared commitment to developing and governing AI in ways that benefit society.

There is no public agenda for AI.

Private interests have dominated the conversation and agenda for AI. Public involvement must help steer the development of AI to strengthen the fabric of society.

The US AI Summit at the University at Buffalo in June of 2026 focused on addressing the question of AI for the public good and the role of the university. This statement reflects the outcome of our meeting. AI is one of the defining features of our time, and universities must become convenors, translators, and stewards of a future that reflects human values and technological capability. Again and again, participants emphasized universities’ role in building human capabilities that cannot be automated: empathy, adaptability, ethical judgment. These are not peripheral qualities in an age of AI. They are central to it.

There is much at stake in the present moment for how we learn, work, create, organize our communities, and govern ourselves. Therefore, decisions we make now will shape the future of humanity perhaps more than at any point in human history.

AI will change how we create knowledge, educate, and develop as human beings. Yet technology is not new to education. It is commonplace.

As Mishra, Warr, and Islam write, “expecting technology to transform education is to give technological tools far more agency than they actually have … technologies have changed education profoundly by changing the world education functions in.”¹

We should expect a similar trajectory with AI. The levers of change for human development might come from the ways these new technologies first change the world around us.

We are excited about the promise of these new technologies as we monitor the impact on human cognitive and emotional development, on the importance of effort and practice in learning, and related issues of cognitive and emotional growth. It is clear that AIs can perform valuable tasks and can function, for some people and tasks, as a legitimate co-intelligence.²  Human capacity may be growing exponentially and degrading quickly.

In light of this context, meeting participants were more confident that the durable, human skills that have long been the source of higher education’s value will remain its essential contribution. Adaptable and confident graduates are the goal. Curiosity, sense-making, and discernment are required capabilities. We therefore must commit to the transferrable knowledge, skills, and dispositions of the liberal arts and sciences and university education more broadly as likely more valuable in the future.

The future of work will change, as many meeting participants detailed. New AI technologies will change the labor market, though how is currently unclear. Therefore, the value of higher education is in growing students’ capacity to offer employers something that AI cannot because universities do much more than prepare students for the labor market. They also cultivate judgement and dispositions that have market value and a public good.

With regard to research, as Venu Govindaraju argued at the meeting, the hard questions are not of capability but of consequence, and furthermore, that faster discovery does not mean better research. Failure is fundamental to discovery and creativity, and the unexpected and the outlier can be just as important as the norm and the pattern. 

We recommend ensuring durable, human skills and to ensure human experience, creativity, and failure remain part of our research and educational enterprises. This is the source of our humanity, creativity, and ability to discover.  

We need public AI infrastructure.

We tend to think of infrastructure as machines and wires and concrete. It is those things, but infrastructure is also, as Deb Chacra reminds us, “inherently collective, social, and spatial … [systems that] make manifest our ability to cooperate to meet universal needs and care for each other.” Our infrastructure tells a story about who we are as people.³

Empire AI is the best example of public infrastructure for AI. Made possible by a public-private collaboration in the State of New York, the initiative focuses on providing a consortium of universities with access to world-class, high-performance computing for AI research and development and AI innovation for the public good.

Currently AI is limited by infrastructure. In such a situation, infrastructure becomes strategy. 

Infrastructure creates possibilities. Public infrastructure enables access, and it also affords transparency and the possibility to safeguard AI systems and critical infrastructure, enable oversight and governance, and ensure accountability for inappropriate, illegal, and dangerous use. 

We recommend a commitment to universities as public infrastructure and not private goods, to build public AI infrastructure in partnership with universities to ensure transparency and sustainability, and to incentivize public-private partnerships with the mandate to support a broad view of economic and human development. 

The Center for Humane Technology notes that AI companies are in a race for the most powerful technology or the largest market share, and it is a race that deprioritizes safety and governance.⁴

At present, any friction is perceived by US policy makers as an impediment to innovation and competitiveness. There is, therefore, no center of gravity for governance conversations. We accelerate with little friction.

As developers of AI, universities can help build technical and ethical guardrails. The summit considered Institutional Review Board-style models where institutions create federal principles that are applied through local interpretation. These frameworks provide human accountability at the highest level while keeping shared standards intact. Meanwhile, public infrastructure models such as Empire AI center the principle of AI for good and therefore provide opportunity for AI governance development with transparency.

Trust, as was noted in Buffalo, is why we insist on humans in the loop. Not because humans are more capable or less error-prone than AI, but because we trust in our shared experiences and in the accountability of human communities. 

Universities are well-positioned to broker transparency and trust conversations.

We recommend positioning university expertise and engagement to develop and support policies to ensure mandatory transparency about AI use and training data and explicit human accountability in autonomous systems. We recognize as well that time-tested institutional review mechanisms that balance federal expectations with local context might serve us well in developing public AI governance. 

This statement has addressed AI but not the meaning of “the public.”

The task is to bring a public together around concerns that are shared. 

AI is concerning. It consumes millions of liters of water, electricity, and computing power and makes decisions at silicon, not human speeds. Against this backdrop, higher education is caught between the pressure to keep pace and our historical obligations to slow down in order to focus on creating and preserving knowledge. As the meeting conversation emphasized, we don’t need to feel the pressure to catch up. We can’t out infrastructure or outspend or outpace big tech or the technologies themselves. 

We need to out purpose them. Our mission is not their mission. 

Yet different purposes need not be competing purposes.

Universities have a central role because they sit at the intersection of knowledge, education, public trust, and democratic life. They prepare people to understand technological change, create spaces where competing interests can be examined, and help translate technical possibility into human consequence. Universities are essential democratic and public infrastructure when we bring people together to deliberate and act. We acknowledge that it is challenging to play this role at a moment of lower levels of public trust in universities. 

Still, we are uniquely positioned to gather, convene, host, and steward conversations about a future that reflects human values as we continue to design and develop technological capability. Again and again, participants in Buffalo emphasized universities’ role in building human capabilities that cannot be automated away: empathy, adaptability, ethical judgment. These are not peripheral qualities in the age of AI; they are central to it.

Public AI requires public institutions. 

Please give us a sense check on the statement and share your feedback by July 20, 2026.