MIT AI Risk Repository · Risk Sub-Category · 59.26.02
Socio-technical
Category: Mode
Description
"In contrast to technical AI hazards, socio-technical hazards also require hu- man input related to social and cultural aspects [45]. Human judgment must be employed when deciding on quantification and treatment methods. For instance, AI hazards concerning discrimination and privacy, which are abstract concepts lacking a uniform technical definition, further complicate a clear quantification of the associated risks. Although quantitative methods exist to assess and treat these AI hazards, they require coordination with social and cultural values [27]."
From AI Hazard Management: A Framework for the Systematic Management of Root Causes for AI Risks (Schnitzer2024), as extracted by the MIT AI Risk Repository (CC BY 4.0).
Classification
Other entries from Schnitzer2024
- Inadequate specification of ODD
- Inappropriate degree of automation
- Inadequate planning of performance requirements
- Insufficient AI development documentation
- Inappropriate degree of transparency to end users
- Missing requirements for the implemented hardware
- Choice of untrustworthy data source
- Lack of data understanding
- Discriminative data bias
- Harming users’ data privacy
- Incorrect data labels
- Data poisoning