Description: Amazon and Uber were alleged in a multiyear ethnographic study using algorithmic systems based on gig workers' data to vary pay, such as by offering them lower wages for the same amount of work.
Entities
View all entitiesAlleged: Uber and Amazon developed and deployed an AI system, which harmed Uber drivers , gig workers and Amazon delivery workers.
Incident Stats
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.
- 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
Intentional
Incident Reports
Reports Timeline
Recent technological developments related to the extraction and processing of data have given rise to widespread concerns about a reduction of privacy in the workplace. For a growing number of low-income and subordinated racial minority wor…
Gig workers are doing the same jobs for different pay, and this model could come to your workplace someday.
That's according to new research from Veena Dubal, a law professor at University of California Hastings, who drew upon six years an…
Variants
A "variant" is an AI incident similar to a known case—it has the same causes, harms, and AI system. Instead of listing it separately, we group it under the first reported incident. Unlike other incidents, variants do not need to have been reported outside the AIID. Learn more from the research paper.
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