Explore a thought-provoking conference talk that delves into future developers' perceptions of fairness in algorithmic decision-making. Presented at the FAccT 2021 virtual conference, this 18-minute research track presentation by S. Kleanthous, M. Kasinidou, P. Barlas, and J. Otterbacher examines the complex relationship between agreement with algorithmic decisions and the perceived fairness of those outcomes. Gain insights into how the next generation of developers views the ethical implications of AI-driven decision processes and the potential impact on system design and implementation. Discover the nuances of fairness perception and its relevance to the development of responsible AI systems.
I Agree with the Decision, but They Didn't Deserve This - Future Developers' Perception of Fairness
Association for Computing Machinery (ACM) via YouTube
Overview
Syllabus
"I agree with the decision, but they didn't deserve this": Future Developers' Perception of Fairness
Taught by
ACM FAccT Conference
Related Courses
-
Fairness, Equality, and Power in Algorithmic Decision-Making
-
Bridging Machine Learning and Mechanism Design towards Algorithmic Fairness
-
Evaluating Fairness of Machine Learning Models Under Uncertain and Incomplete Information
-
Translation Tutorial - Fairness and Friends
-
Re-imagining Algorithmic Fairness in India and Beyond
-
On the Moral Justification of Statistical Parity
