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Incident 396: Transgender Uber Drivers Mistakenly Kicked off App for Appearance Change during Gender Transitions

Description: Transgender Uber drivers reported being automatically deactivated from the app due to Real-Time ID Check failing to account for difference in appearance of people undergoing gender transitions.

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Alleged: Uber developed and deployed an AI system, which harmed transgender Uber drivers.

Incident Stats

Incident ID
396
Report Count
1
Incident Date
2018-07-04
Editors
Khoa Lam
Applied Taxonomies
CSETv1, MIT

MIT Taxonomy Classifications

Machine-Classified
Taxonomy Details

Risk Subdomain

A further 23 subdomains create an accessible and understandable classification of hazards and harms associated with AI
 

1.1. Unfair discrimination and misrepresentation

Risk Domain

The Domain Taxonomy of AI Risks classifies risks into seven AI risk domains: (1) Discrimination & toxicity, (2) Privacy & security, (3) Misinformation, (4) Malicious actors & misuse, (5) Human-computer interaction, (6) Socioeconomic & environmental harms, and (7) AI system safety, failures & limitations.
 
  1. Discrimination and Toxicity

Entity

Which, if any, entity is presented as the main cause of the risk
 

AI

Timing

The stage in the AI lifecycle at which the risk is presented as occurring
 

Post-deployment

Intent

Whether the risk is presented as occurring as an expected or unexpected outcome from pursuing a goal
 

Unintentional

Incident Reports

Reports Timeline

Incident OccurrenceSome transgender drivers are being kicked off Uber’s app
Some transgender drivers are being kicked off Uber’s app

Some transgender drivers are being kicked off Uber’s app

cnbc.com

Some transgender drivers are being kicked off Uber’s app
cnbc.com · 2018

Uber has revolutionized the taxi industry with its easy-to-use service, but its current features lack options for transgender drivers to identify themselves correctly, which get some of them kicked off the app.

Transgender drivers across th…

Variants

A "variant" is an incident that shares the same causative factors, produces similar harms, and involves the same intelligent systems as a known AI incident. Rather than index variants as entirely separate incidents, we list variations of incidents under the first similar incident submitted to the database. Unlike other submission types to the incident database, variants are not required to have reporting in evidence external to the Incident Database. Learn more from the research paper.

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