4 citations · 4 across the 6 of their papers we have counts for
4 papers · 1 filter
Moral Change or Noise? On Problems of Aligning AI With Temporally Unstable Human Feedback
Vijay Keswani, Cyrus Cousins, Breanna Nguyen +4
Alignment methods in moral domains seek to elicit moral preferences of human stakeholders and incorporate them into AI. This presupposes moral preferences as static targets, but su…
Why Do Decision Makers (Not) Use AI? A Cross-Domain Analysis of Factors Impacting AI Adoption
Rebecca Yu, Valerie Chen, Ameet Talwalkar +1
Growing excitement around deploying AI across various domains calls for a careful assessment of how human decision-makers interact with AI-powered systems. In particular, it is ess…
Can AI Model the Complexities of Human Moral Decision-Making? A Qualitative Study of Kidney Allocation Decisions
Vijay Keswani, Vincent Conitzer, Walter Sinnott-Armstrong +3
A growing body of work in Ethical AI attempts to capture human moral judgments through simple computational models. The key question we address in this work is whether such simple…
On the Pros and Cons of Active Learning for Moral Preference Elicitation
Vijay Keswani, Vincent Conitzer, Hoda Heidari +2
Computational preference elicitation methods are tools used to learn people's preferences quantitatively in a given context. Recent works on preference elicitation advocate for act…