Algorithmic Allocation of Resources in Healthcare for Disabled and Elderly Care Services Allegedly Harmed Patients
Description
A healthcare algorithm designed to equitably distribute caregiving resources is alleged to have drastically cut care hours for the disabled and elderly, purportedly leading to significant hardships and harm. Initially developed for fair resource allocation, the system reportedly faced legal challenges for its inability to accurately assess individual needs, resulting in allegedly reduced essential care.
Actors
Alleged Deployers
- washington-dc-government
- state-governments
- pennsylvania-state-government
- missouri-state-government
- iowa-state-government
- idaho-state-government
- arkansas-state-government
Alleged Developers
- state-governments
- brant-fries
Harmed Parties
- tammy-dobbs
- larkin-seiler
- economically-vulnerable-people
- economically-vulnerable-patients
- elderly-individuals
- people-with-disabilities
Classification
Risk Domain
AI Safety & FailuresRisk Subdomain
7.3. Lack of capability or robustness
MIT Risk Profile
Topics
Source
Related Incidents (AI Safety & Failures)
View all →Research Papers on This Topic
View all →Concrete Problems in AI Safety
A Survey on Explainable Artificial Intelligence (XAI): Towards Medical XAI
Representation Engineering: A Top-Down Approach to AI Transparency
Explainable artificial intelligence (XAI) in deep learning-based medical image analysis
Mitigation Tools
Tools related to this risk domain, via shared responsible AI topics.