CFP: The AI & Society Symposium: Where Technology Meets Human Values

The Boston University Humanities & AI Lab (HAIL) invites undergraduate and graduate students from any institution and any discipline to submit papers for its first symposium. 

This symposium inquires into the conceptions of the human built into generative AI. 

GenAI systems sound like us: they say “I understand,” they apologize, they appear to care. They’re also made for a user, and so they come with assumptions about who that user is: what they need and what they can already do. And they’re built on assumptions about what intelligence itself is. Some of these pictures of the human reflect choices made by engineers and product teams; others were assumed without anyone ever deciding. It all demands to be examined. This symposium brings these and related questions into public discussion, asking what it means to be human at a time when these systems are made like us and for us, even as this ‘us’ is still being decided. 

We welcome work from any discipline in the humanities, the social sciences, and technical fields such as engineering, computer science, and data science. Possible topics include, but are not limited to:

• Should AI systems speak like us? How does this affect the way we relate to them? How do training choices like fine-tuning on human feedback produce an AI’s voice?
• Do we owe anything to a system that speaks as one of us? Does making AI seem human lead us to trust it more than we should?
• How do economic incentives shape the picture of the user, or the humanlike voice, built into AI?
• Who is the user GenAI systems are built for? An assistant presupposes someone who knows what they want and can judge what they get. Whose needs, abilities, and ends does this take for granted? Who is left out of this picture?
• What picture of intelligence, reasoning, and understanding is built into how AI is designed? Is it the right one, or does it leave something out?
• Can using AI prevent us from learning key skills we need to develop as people, professionals, and citizens? Can it lead us to lose skills we already have?
• What would AI look like if it were built for people who are still learning? Can it be designed to support learning rather than replace it, and how would we know if it works as intended?

Submission details:

• Fill in this Google Form with your name, institution, program and year, and paper title. 
• Attach in the form an abstract of up to 500 words, prepared for anonymous review.
• The deadline is January 5, 2027.
• Decisions by February 5, 2027. 
• Talks are 20 minutes, followed by 10 minutes of discussion. 

Limited travel grants may be available for presenters from outside Boston, with priority for students in New England. 

You can send questions to [email protected].

Organized by Pol Pardini Gispert, Anika Mukherjee, Daniel Munro, and Seth Villegas, with support from the Boston University Center for the Humanities and the APA Berry Fund.