Project 1: Intersectional Harms in Workplace Incidents

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Harms from AI used in workplaces can be worse for people with intersecting identities, such as young women and lower-income people of color.

Prior work has not closely studied how intersecting identities within one person shape the causes and effects of workplace AI incidents.

We address this gap by:

• collecting workplace AI incident reports;
• coding how intersecting identity factors relate to each incident’s context, mechanism, and harm, following the procedure in [1]; and
• releasing a dataset and analysis code so others can reproduce our results.

References

1. [1] Why AI Harms Can’t Be Fixed One Identity at a Time: What 5,300 Incident Reports Reveal About Intersectionality.