Incidente 645: translated-es-Seeming Pattern of Gemini Bias and Sociotechnical Training Failures Harm Google's Reputation
Descripción: translated-es-Google's Gemini chatbot faced many reported bias issues upon release, leading to a variety of problematic outputs like racial inaccuracies and political biases, including regarding Chinese and Indian politics. It also reportedly over-corrected racial diversity in historical contexts and advanced controversial perspectives, prompting a temporary halt and an apology from Google.
Editor Notes: This incident ID archives various reports following Gemini's release. The documented cases, while distinct, suggest that further refinement in training may have been beneficial. The primary impact appears to be on Google's reputation.
Entidades
Ver todas las entidadesRisk 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