Alienating social groups
when an image tagging system does not acknowledge the relevance of someone’s membership in a specific social group to what is depicted in one or more images
ENTITY
2 - AI
INTENT
2 - Unintentional
TIMING
2 - Post-deployment
Risk ID
mit137
Domain lineage
1. Discrimination & Toxicity
1.1 > Unfair discrimination and misrepresentation
Mitigation strategy
- Implement rigorous data curation protocols to ensure training datasets are diverse and statistically representative of all target social groups, thereby counteracting the foundational cause of underrepresentation and subsequent alienation (Source 2, 13). - Establish a continuous monitoring and auditing framework for post-deployment systems to actively detect and measure representational harms, utilizing distribution-based metrics to identify skewed or inaccurate depictions of social groups in image tags (Source 2, 5). - Mandate collaborative human oversight and iterative engagement with affected social groups and ethicists to inform the definition of fairness, validate the social and cultural appropriateness of tagging outputs, and address the subjective experience of alienation (Source 2, 8).
ADDITIONAL EVIDENCE
[Lack of representation] further promotes the idea that you don't belong and perpetuates the sense of alienation