Implicit Bias in Humans and Machines

Implicit biases are automatic evaluative attitudes that influence perception, judgment, and behaviour. They affect everything from quick social evaluations to the outputs of machine-learning systems trained on biased data. The current widespread use of AI embeds these biases ever more deeply in our social lives, implying that the problem must be tackled from multiple perspectives that bridge human social cognition and algorithmic design. The workshop is meant to create a welcoming and informal forum where researchers across disciplines, who study or are interested in implicit bias, can connect, share their latest findings, and reflect on the topic together. 

This is the second edition of the workshop, where the first took place at DTU in 2024. 

Organizers: 

Gaia Belardinelli, Stanford University

Thomas Bolander, Technical University of Denmark

Vedran Sekara, IT University of Copenhagen