Performative Ethics From Within the Ivory Tower: How CSPractitioners Uphold Systems of Oppression (Abstract Reprint)
Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence. Journal Track. Pages 8483-8483.
https://doi.org/10.24963/ijcai.2024/955
Keywords
- Journal Track: Journal Track
Abstract
This paper analyzes where Artificial Intelligence (AI) Ethics research fails and breaks down the dangers of well-intentioned, but ultimately performative ethics research. A large majority of AI ethics research is critiqued for lacking a comprehensive analysis of how AI is interconnected with sociological systems of oppression and power. Our work contributes to the handful of research that presents intersectional, Western systems of oppression and power as a framework for examining AI ethics work and the complexities of building less harmful technology; directly connecting technology to named systems such as capitalism and classism, colonialism, racism and white supremacy, patriarchy, and ableism. We then explore current AI ethics rhetoric's effect on the AI ethics domain and AI regulation. In conclusion, we provide an applied example to contextualize intersectional systems of oppression and AI interventions in the U.S. justice system and present actionable steps for AI practitioners to participate in a less performative, critical analysis of AI.
- [McFadden and Alvarez, 2024] Zari McFadden and Lauren Alvarez. Performative ethics from within the ivory tower: How CS practitioners uphold systems of oppression. J. Artif. Intell. Res., 79:777-799, 2024.
References were extracted automatically from the PDF and may contain errors.
Full text extracted automatically from the PDF; figures, tables and equations may differ. The PDF is the version of record.
Performative Ethics From Within the Ivory Tower: How CSPractitioners Uphold Systems of Oppression (Abstract Reprint)
Zari McFadden and Lauren Alvarez
North Carolina State University zmcfadd@ncsu.edu, lalvare@ncsu.edu
Abstract Reprint. This is an abstract reprint of a journal by [McFadden and Alvarez, 2024].
Abstract
This paper analyzes where Artificial Intelligence (AI) ethics research fails and breaks down the dangers of wellintentioned but ultimately performative ethics research. A large majority of AI ethics research is criticized for not providing a comprehensive analysis of how AI is interconnected with sociological systems of oppression and power. Our work contributes to the handful of research that presents intersectional, Western systems of oppression and power as a framework for examining AI ethics work and the complexities of building less harmful technology; directly connecting technology to named systems such as capitalism and classism, colonialism, racism and white supremacy, patriarchy, and ableism.We then explore current AI ethics rhetoric's effect on the AI ethics domain. We conclude by providing an applied example to contextualize intersectional systems of oppression and AI interventions in the US justice system and present actionable steps for AI practitioners to participate in a less performative, critical analysis of AI.
@inproceedings{ijcai2024p955,
title = {Performative Ethics From Within the Ivory Tower: How CSPractitioners Uphold Systems of Oppression (Abstract Reprint)},
author = {McFadden, Zari and Alvarez, Lauren},
booktitle = {Proceedings of the Thirty-Third International Joint Conference on
Artificial Intelligence, {IJCAI-24}},
publisher = {International Joint Conferences on Artificial Intelligence Organization},
editor = {Kate Larson},
pages = {8483--8483},
year = {2024},
month = {8},
note = {Journal Track},
doi = {10.24963/ijcai.2024/955},
url = {https://doi.org/10.24963/ijcai.2024/955},
}
TY - CPAPER TI - Performative Ethics From Within the Ivory Tower: How CSPractitioners Uphold Systems of Oppression (Abstract Reprint) AU - McFadden, Zari AU - Alvarez, Lauren T2 - Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, IJCAI-24 PB - International Joint Conferences on Artificial Intelligence Organization PY - 2024 SP - 8483 EP - 8483 DO - 10.24963/ijcai.2024/955 UR - https://doi.org/10.24963/ijcai.2024/955 ER -Copied
Machine-readable versions of this paper, for tools and AI agents:
Welcome
Future Conferences
AI Journal Division
IJCAI Proceedings
About IJCAI
IJCAI Awards