AI Community Engagement Through “AI Cafés”

“Can I get an interview?” “Can I get a job when I graduate?” Those questions came from students during a candid discussion about artificial intelligence, capturing the anxiety many young people feel today. As companies adopt AI-driven interview screeners, restructure their workforces, and redirect billions of dollars toward AI infrastructure, students are increasingly unsure of what the future of work will look like.

We had gathered people together at a coffee shop in Auburn, Alabama, for what we called an AI Café. The event was designed to confront concerns about AI directly, demystifying the technology while pushing back against the growing narrative of technological doom.

AI is reshaping society at breathtaking speed. Yet the trajectory of this transformation is being charted primarily by for-profit tech companies, whose priorities revolve around market dominance rather than public welfare. Many people feel that AI is something being done to them rather than developed with them.

As computer science and liberal arts faculty at Auburn University, we believe there is another path forward: one where scholars engage their communities in genuine dialogue about AI. Not to lecture about technical capabilities, but to listen, learn, and co-create a vision for AI that serves the public interest.

The AI Café Model

Last November, we ran two public AI Cafés in Auburn. These were informal, 90-minute conversations between faculty, students, and community members about their experiences with AI. In these conversational forums, participants sat in clusters, questions flowed in multiple directions, and lived experience carried as much weight as technical expertise.

We avoided jargon and resisted attempts to “correct” misconceptions, welcoming whatever emotions emerged. One ground rule proved crucial: keeping discussions in the present, asking participants where they encounter AI today. Without that focus, conversations could easily drift to sci-fi speculation. Historical analogies—to the printing press, electricity, and smartphones—helped people contextualize their reactions. And we found that without shared definitions of AI, people talked past each other; we learned to ask participants to name specific tools they were concerned about.

Organizers Xaq Frohlich, Cheryl Seals, and Joan Harrell (right) held their first AI Café in a welcoming coffee shop and bookstore. Well Red

Most important, we approached these events not as experts enlightening the masses, but as community members navigating complex change together.

What We Learned by Listening

Participants arrived with significant frustration. They felt that commercial interests were driving AI development “without consideration of public needs,” as one attendee put it. This echoed deeper anxieties about technology, from social media algorithms that amplify division to devices that profit from “engagement” and replace meaningful face-to-face connection. People aren’t simply “afraid of AI.” They’re weary of a pattern where powerful technologies reshape their lives while they have little say.

Yet when given space to voice concerns without dismissal, something shifted. Participants didn’t want to stop AI development; they wanted to have a voice in it. When we asked “What would a human-centered AI future look like?” the conversation became constructive. People articulated priorities: fairness over efficiency, creativity over automation, dignity over convenience, community over individualism.

The three organizers, all professors at Alabama’s Auburn University, say that including people from the liberal arts fields brought new perspectives to the discussions about AI. Well Red

For us as organizers, the experience was transformative. Hearing how AI affected people’s work, their children’s education, and their trust in information prompted us to consider dimensions we hadn’t fully grasped. Perhaps most striking was the gratitude participants expressed for being heard. It wasn’t about filling knowledge deficits; it was about mutual learning. The trust generated created a spillover effect, renewing faith that AI could serve the public interest if shaped through inclusive processes.

How to Start Your Own AI Café

The “deficit model” of science communication—where experts transmit knowledge to an uninformed public—has been discredited. Public resistance to emerging technologies reflects legitimate concerns about values, risks, and who controls decision-making. Our events point toward a better model.

We urge engineering and liberal arts departments, professional societies, and community organizations worldwide to organize dialogues similar to our AI Cafés.

We found that a few simple design choices made these conversations far more productive. Informal and welcoming spaces such as coffee shops, libraries, and community centers helped participants feel comfortable (and serving food and drinks helped too!). Starting with small-group discussions, where people talked with neighbors, produced more honest thinking and greater participation. Partnering with colleagues in the liberal arts brought additional perspectives on technology’s social dimensions. And by making a commitment to an ongoing series of events, we built trust.

Facilitation also matters. Rather than leading with technical expertise, we began with values: We asked what kind of world participants wanted, and how AI might help or hinder that vision. We used analogies to earlier technologies to help people situate their reactions and grounded discussions in present realities, asking participants where they have encountered AI in their daily lives. We welcomed emotions constructively, transforming worry into problem solving by asking questions like: “What would you do about that?”

Why Engineers Should Engage the Public

Professional ethics codes remain abstract unless grounded in dialogue with affected communities. Conversations about what “responsible AI” means will look different in São Paulo than in Seoul, in Vienna than in Nairobi. What makes the AI Café model portable is its general principles: informal settings, values-first questions, present-tense focus, genuine listening.

Without such engagement, ethical accountability quietly shifts to technical experts rather than remaining a shared public concern. If we let commercial interests define AI’s trajectory with minimal public input, it will only deepen divides and entrench inequities.

AI will continue advancing whether or not we have public trust. But AI shaped through dialogue with communities will look fundamentally different from AI developed solely to pursue what’s technically possible or commercially profitable.

The tools for this work aren’t technical; they’re social, requiring humility, patience, and genuine curiosity. The question isn’t whether AI will transform society. It’s whether that transformation will be done to people or with them. We believe scholars must choose the latter, and that starts with showing up in coffee shops and community centers to have conversations where we do less talking and more listening.

The future of AI depends on it.