Incident 37: L'outil de recrutement expérimental d'Amazon aurait révélé des préjugés sexistes dans les classements des candidats.
Description: Entre 2014 et 2017, Amazon aurait développé un outil de recrutement basé sur l'IA pour noter les candidats, grâce à une décennie de CV prétendument composés en grande partie d'hommes. Selon les médias, le système aurait appris à privilégier les candidats masculins, pénalisant des termes comme « femmes » et les diplômées de certaines universités exclusivement féminines. Les efforts pour éliminer ces biais n'auraient pas garanti l'équité, et le projet a finalement été abandonné. Amazon aurait affirmé que les recruteurs ne se sont jamais fiés exclusivement à cet outil.
Outils
Nouveau rapportNouvelle RéponseDécouvrirVoir l'historique
Le Moniteur des incidents et risques liés à l'IA de l'OCDE (AIM) collecte et classe automatiquement les incidents et risques liés à l'IA en temps réel à partir de sources d'information réputées dans le monde entier.
Entités
Voir toutes les entitésPrésumé : Un système d'IA développé et mis en œuvre par Amazon , Amazon experimental AI resume scoring engine et Associated machine learning models trained on historical Amazon resume data, a endommagé Amazon applicants et Women applying to Amazon.
Systèmes d'IA présumés impliqués: Amazon experimental AI resume scoring engine et Associated machine learning models trained on historical Amazon resume data
Classifications de taxonomie CSETv0
Détails de la taxonomieProblem Nature
Indicates which, if any, of the following types of AI failure describe the incident: "Specification," i.e. the system's behavior did not align with the true intentions of its designer, operator, etc; "Robustness," i.e. the system operated unsafely because of features or changes in its environment, or in the inputs the system received; "Assurance," i.e. the system could not be adequately monitored or controlled during operation.
Specification
Physical System
Where relevant, indicates whether the AI system(s) was embedded into or tightly associated with specific types of hardware.
Software only
Level of Autonomy
The degree to which the AI system(s) functions independently from human intervention. "High" means there is no human involved in the system action execution; "Medium" means the system generates a decision and a human oversees the resulting action; "low" means the system generates decision-support output and a human makes a decision and executes an action.
Medium
Nature of End User
"Expert" if users with special training or technical expertise were the ones meant to benefit from the AI system(s)’ operation; "Amateur" if the AI systems were primarily meant to benefit the general public or untrained users.
Expert
Public Sector Deployment
"Yes" if the AI system(s) involved in the accident were being used by the public sector or for the administration of public goods (for example, public transportation). "No" if the system(s) were being used in the private sector or for commercial purposes (for example, a ride-sharing company), on the other.
No
Data Inputs
A brief description of the data that the AI system(s) used or were trained on.
Resumes
Classifications de taxonomie CSETv1
Détails de la taxonomieIncident Number
The number of the incident in the AI Incident Database.
37
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
Unintentional