We find that 1) acceptance of AI varies widely depending on use case context, 2) judgments differ between demographic groups, and 3) people use both cost-benefit AND rule-based reasoning to make their decisions where diverging strategies show higher disagreement.

To build consensus around AI use cases, it's imperative to understand how people, especially lay-users, reason about AI use cases. We asked 197 participants to make decisions on individual AI use cases and share their reasoning process.

We are accepting papers for the following two tracks!

🤖 ML track: algorithms, math, computation
📚 Socio-technical track: policy, ethics, human participant research

Website: solar-colm.github.io
With:
@usmananwar.bsky.social @liweijiang.bsky.social @valentinapy.bsky.social @sharonlevy.bsky.social Daniel Tan @akhilayerukola.bsky.social @jiminmun.bsky.social Ruth Appel @sumeetrm.bsky.social @davidskrueger.bsky.social Sheila McIlraith @maartensap.bsky.social