Data Ethics Emergency Drill: A Toolbox for Discussing Responsible AI for Industry Teams

要旨

Researchers urge technology practitioners such as data scientists to consider the impacts and ethical implications of algorithmic decisions. However, unlike programming, statistics, and data management, discussion of ethical implications is rarely included in standard data science training. To begin to address this gap, we designed and tested a toolbox called the data ethics emergency drill (DEED) to help data science teams discuss and reflect on the ethical implications of their work. The DEED is a roleplay of a fictional ethical emergency scenario that is contextually situated in the team’s specific workplace and applications. This paper outlines the DEED toolbox and describes three studies carried out with two different data science teams that iteratively shaped its design. Our findings show that practitioners can apply lessons learnt from the roleplay to real-life situations, and how the DEED opened up conversations around ethics and values.

著者
Vanessa Aisyahsari Hanschke
University of Bristol, Bristol, United Kingdom
Dylan Rees
LV= General Insurance, London, United Kingdom
Merve Alanyali
LV= General Insurance, London, United Kingdom
David Hopkinson
LV= General Insurance, London, United Kingdom
Paul Marshall
University of Bristol, Bristol, United Kingdom
論文URL

https://doi.org/10.1145/3613904.3642402

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: Remote Presentations: Highlight on AI

Remote Sessions
14 件の発表
2024-05-13 18:00:00
2024-05-14 02:20:00