Auburn University Launches AI-Café for Conversations About AI Without Panic and Tech Jargon

In Auburn, Alabama, university professors held open AI cafes — not as lectures about technology, but as honest conversations about concerns around AI. The format turned out to be simple, but it showed something important: people are willing to discuss artificial intelligence substantively if they're not talked down to.

How the AI cafe format was organized

The AI cafe took place in an ordinary coffee shop and bookstore. University professors, students, and city residents sat at tables, and the meeting lasted about 90 minutes. The organizers deliberately avoided an academic tone: less jargon, fewer attempts to "correct" other people's fears, more concrete stories from everyday life. Instead of debating superintelligence, participants were asked where exactly they already encounter AI — when job hunting, in studies, in social networks, in recommendation services, and in office tools.

According to the organizers, several simple rules worked most productively. They don't require a large budget, but they significantly change the quality of the conversation: people engage more quickly, share personal experiences more readily, and rarely venture into abstract debates about the distant future. Historical analogies also helped — printing press, electricity, smartphones. Through them, participants found it easier to understand their own reaction to new technology and avoid reducing the conversation to science fiction.

• Not an audience and stage, but circles around small tables
• Not abstract "AI in general," but specific tools and scenarios
• Not a debate about the future in 20 years, but a conversation about what's happening now
• Not an expert position from above, but a joint analysis of changes
• Not a one-time event, but a series of meetings to build trust

Another important conclusion turned out to be surprisingly practical: without a common definition of AI, people often discuss different things and quickly start talking past each other. For some, AI is ChatGPT and text generation; for others, it's feed algorithms, surveillance cameras, recommendation systems, or automatic resume screening. So the organizers asked participants to name not "AI in general," but specific tools and situations that concern them or, conversely, help in their work and studies.

What people heard

The strongest theme turned out to be not "fear of machines," but a sense of loss of control. Participants said that technologies are increasingly being implemented for companies' goals, not society's. Students feel this most acutely: if employers use AI screening, teams are being cut, and companies are pouring billions into infrastructure, then it becomes unclear what the labor market will look like by graduation. Against this backdrop, questions like "Will they interview me?" and "Will I be able to find a job after university?" sounded not like panic, but as a normal reaction to rapid change.

"Without considering public needs."

After people were given a chance to speak without condescension, the tone of the conversation noticeably changed. Instead of demanding "stop AI," a more mature position emerged: development will continue, but society wants to participate in choosing the rules. The meetings formulated quite practical priorities — fairness is more important than raw efficiency, dignity is more important than convenience, creativity is more important than blind automation, and community interests are more important than individualistic productivity racing.

For the organizers themselves, this also became a lesson: they saw how AI already affects work, children's education, and trust in information.

How to replicate the idea

The organizers believe that universities, professional communities, and public spaces should launch similar dialogues. The logic here is simple: the conversation about responsible AI shouldn't remain an internal affair of engineers or large tech companies. Ethical codes look good on paper, but without talking to those affected by new systems, they quickly become formalities. Moreover, there is no universal recipe: expectations about AI in one city, industry, or country can differ significantly from expectations elsewhere.

The practical conclusion from Auburn University's experience is this: you need to start not by explaining the model, but by talking about values. What kind of world do people want to preserve? Where does AI actually help? Where does it amplify inequality, pressure, or alienation? The role of moderation is also important: don't let the discussion drift into science fiction, bring it back to current experience, ask clarifying questions, and turn anxiety into a discussion of solutions. Otherwise, responsibility for the technology's trajectory imperceptibly passes to a narrow circle of specialists, and society again receives changes that happen to it, rather than with it.

What this means

The AI cafe story shows that the main deficit around AI today is not only technical but also social. People need not another pitch about a model's capabilities, but a space where they can name risks, agree on priorities, and reclaim their right to influence how technology enters their everyday lives.