The Illusion of Artificial Inclusion

要旨

Human participants play a central role in the development of modern artificial intelligence (AI) technology, in psychological science, and in user research. Recent advances in generative AI have attracted growing interest to the possibility of replacing human participants in these domains with AI surrogates. We survey several such "substitution proposals" to better understand the arguments for and against substituting human participants with modern generative AI. Our scoping review indicates that the recent wave of these proposals is motivated by goals such as reducing the costs of research and development work and increasing the diversity of collected data. However, these proposals ignore and ultimately conflict with foundational values of work with human participants: representation, inclusion, and understanding. This paper critically examines the principles and goals underlying human participation to help chart out paths for future work that truly centers and empowers participants.

著者
William Agnew
CMU, Pittsburgh, Pennsylvania, United States
Stevie Bergman
Google DeepMind, London, United Kingdom
Jennifer Chien
University of California, San Diego, San Diego, California, United States
Mark Diaz
Google Research, New York City, New York, United States
Seliem El-Sayed
Google DeepMind, London, United Kingdom
Jaylen Pittman
Stanford University, Stanford, California, United States
Shakir Mohamed
Google DeepMind, London, United Kingdom
Kevin McKee
Google DeepMind, London, United Kingdom
論文URL

https://doi.org/10.1145/3613904.3642703

動画

会議: CHI 2024

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2024.acm.org/)

セッション: Ethics of AI

314
5 件の発表
2024-05-14 01:00:00
2024-05-14 02:20:00