Description: Gates-Foundation-funded Intensive Partnerships for Effective Teaching Initiative’s algorithmic program to assess teacher performance reportedly failed to achieve its goals for student outcomes, particularly for minority students, and was criticized for potentially causing harm against teachers.
Entities
View all entitiesAlleged: Intensive Partnerships for Effective Teaching developed and deployed an AI system, which harmed students , low-income minority students and Teachers.
CSETv1 Taxonomy Classifications
Taxonomy DetailsIncident Number
The number of the incident in the AI Incident Database.
239
Risk Subdomain
A further 23 subdomains create an accessible and understandable classification of hazards and harms associated with AI
1.3. Unequal performance across groups
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
Unintentional
Incident Reports
Reports Timeline
The Gates Foundation’s big-data experiment wasn’t just a failure. It did real harm.
The Gates Foundation deserves credit for hiring an independent firm to assess its $575 million program to make public-school teachers more effective. Now th…
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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