(Stanford University) This repo provides access to our dataset of over 30,000 Human-AI interactions. We recruited crowdworkers and expert dermatologists and asked them to perform a variety of binary classification tasks. Participants gave two responses — their initial impression after seeing the task, and their response after being presented with some “advice.” This advice was presented as coming from either a human peer or an AI algorithm. Responses were recorded on a sliding scale, allowing users to indicate both label choice and confidence.
Link to Dataset
Human-AI Interactions Dataset
Date last updated: 2022