MIT AI Risk Repository · Risk Category · 59.26.00
Mode
On this page 3 sections
Description
"The second axis of the taxonomy pertains to the mode of an AI hazard, which determines with what methods to assess and treat AI hazards. We distinguish among three distinct classes: technological, socio-technological, and procedural."
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