Description: A study published in JAMA Network Open reveals that racial bias built into a commonly used medical diagnostic algorithm for lung function may be leading to underdiagnoses of breathing problems in Black men. The study suggests that as many as 40% more Black male patients might have been accurately diagnosed if the software were not racially biased. The software algorithm adjusts diagnostic thresholds based on race, affecting medical treatments and interventions.
Entités
Voir toutes les entitésAlleged: unknown developed an AI system deployed by University of Pennsylvania Health System, which harmed Black men who underwent lung function tests between 2010 and 2020 and potentially received inaccurate or delayed diagnoses and medical interventions due to the biased algorithm.
Statistiques d'incidents
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
Rapports d'incidents
Chronologie du rapport
NEW YORK (AP) – Les préjugés raciaux intégrés dans un test médical courant pour la fonction pulmonaire conduisent probablement à une diminution du nombre de patients noirs recevant des soins pour des problèmes respiratoires, suggère une étu…
Variantes
Une "Variante" est un incident qui partage les mêmes facteurs de causalité, produit des dommages similaires et implique les mêmes systèmes intelligents qu'un incident d'IA connu. Plutôt que d'indexer les variantes comme des incidents entièrement distincts, nous listons les variations d'incidents sous le premier incident similaire soumis à la base de données. Contrairement aux autres types de soumission à la base de données des incidents, les variantes ne sont pas tenues d'avoir des rapports en preuve externes à la base de données des incidents. En savoir plus sur le document de recherche.