MIT AI Risk Repository · Risk Sub-Category · 62.07.02

Operational harms (financial markets)

Category: Direct Harm Domains (system and operational)

Open the MIT Risk Navigator All entries from Gipiškis2024

Description

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From Risk Sources and Risk Management Measures in Support of Standards for General-Purpose AI Systems (Gipiškis2024), as extracted by the MIT AI Risk Repository (CC BY 4.0).

Classification

Domain: 7. AI system safety, failures, & limitations
Subdomain: 7.0
Causal entity: Not coded
Intent: Not coded
Timing: Not coded

How other frameworks describe this risk

Risks from Malfunctions
International Scientific Report on the Safety of Advanced AI (Bengio2024)
Safety & Trustworthiness
Cataloguing LLM Evaluations (InfoComm2023)
Extreme Risks
Cataloguing LLM Evaluations (InfoComm2023)
Limitations of Human Feedback
AI Alignment: A Comprehensive Survey (Ji2023)
Uncertainty concerns
AI Hazard Management: A Framework for the Systematic Management of Root Causes for AI Risks (Schnitzer2024)
Inappropriate data splitting
AI Hazard Management: A Framework for the Systematic Management of Root Causes for AI Risks (Schnitzer2024)
Choice of untrustworthy data source
AI Hazard Management: A Framework for the Systematic Management of Root Causes for AI Risks (Schnitzer2024)
Lack of data understanding
AI Hazard Management: A Framework for the Systematic Management of Root Causes for AI Risks (Schnitzer2024)

Other entries from Gipiškis2024

Dimension - Intent Risk Category
Intentional Risk Sub-Category
Unintentional Risk Sub-Category
Partially intentional Risk Sub-Category
Dimension - Entity Risk Category
Human Risk Sub-Category
AI Risk Sub-Category
Combination of humans and AI Risk Sub-Category
Dimension - Failure dynamics Risk Category
Isolated (non-normal) failures Risk Sub-Category
System (normal) failures Risk Sub-Category
System (normal) failures Additional evidence