Description: The WHO's AI-powered health advisor, S.A.R.A.H. (Smart AI Resource Assistant for Health), is alleged to provide inconsistent and inadequate health information. The bot reportedly gives contradictory responses to the same queries, fails to offer specific contact details for healthcare providers, and inadequately handles severe mental health crises, often giving irrelevant or unhelpful advice.
Entités
Voir toutes les entitésAlleged: WHO developed an AI system deployed by WHO et S.A.R.A.H. (Smart AI Resource Assistant for Health), which harmed General public et People seeking medical advice.
Statistiques d'incidents
Risk Subdomain
A further 23 subdomains create an accessible and understandable classification of hazards and harms associated with AI
7.3. Lack of capability or robustness
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.
- AI system safety, failures, and limitations
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
For a cautionary tale on the dangers of health care by chatbot, look no further than the World Health Organization.
The WHO's bot, SARAH or Smart AI Resource Assistant for Health, is supposed to provide advice to the public on healthy livin…
Variantes
Une "Variante" est un incident de l'IA similaire à un cas connu—il a les mêmes causes, les mêmes dommages et le même système intelligent. Plutôt que de l'énumérer séparément, nous l'incluons sous le premier incident signalé. Contrairement aux autres incidents, les variantes n'ont pas besoin d'avoir été signalées en dehors de la base de données des incidents. En savoir plus sur le document de recherche.
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