MIT AI Risk Repository · Risk Sub-Category · 47.01.05
Opacity (the black box problem)
Category: Technical and operational risks
Description
"Opacity surrounding the technical, internal decision-making processes of generative AI models is popularly known as the “black box problem.”277 Generative AI models, most ubiquitously built on deep neural networks with hundreds of billions of internal connections,278 have become so complex that their internal decision-making processes are no longer traceable or interpretable to even the most advanced expert observers. This means that, while the inputs and outputs of a system can be observed, developers cannot explain in detail why specific inputs correspond to specific outputs."
From Regulating under Uncertainty: Governance Options for Generative AI (G'sell2024), as extracted by the MIT AI Risk Repository (CC BY 4.0).
Classification
- Causal entity
- Other
- Intent
- Unintentional
- Timing
- Other
Subdomain definition: Challenges in understanding or explaining the decision-making processes of AI systems, which can lead to mistrust, difficulty in enforcing compliance standards or holding relevant actors accountable for harms, and the inability to identify and correct errors.
Real-world incidents in this subdomain
- Uber Launched Opaque Algorithm That Changes Drivers' Payments in the US
- Israeli Tax Authority Reportedly Used an Opaque Automated System to Issue a Fine, Declining to Explain or Disclose the Underlying Calculation
- Uber Allegedly Wrongfully Accused Drivers of Fraud via Automated Systems
- Houston ISD's EVAAS Teacher-Evaluation System Reportedly Put Teachers' Jobs at Risk Through Unverifiable Scores
- Dutch City Court Defended Home Value Generated by Black-Box Algorithm
How other frameworks describe this risk
- Intelligibility
- Attributing the responsibility for AI's failures
- General Evaluations (Difficulty of identification and measurement of capabilities)
- Lack of understanding of in-context learning in language models
- Model outputs inconsistent with chain-of-thought reasoning
- Model Evaluations (Interpretability/Explainability)
- Lack of transparency and interpretability
- Transparency - Explainability
Other entries from G'sell2024
- Technical and operational risks
- Technical vulnerabilities (Robustness - unexpected behaviour)
- Technical vulnerabilities (Robustness - unexpected behaviour)
- Technical vulnerabilities (Robustness - vulnerability to jailbreaking
- Technical vulnerabilities (Robustness - vulnerability to jailbreaking
- Technical vulnerabilities (The risk of misalignment)
- Technical vulnerabilities (The risk of misalignment)
- Factually incorrect content (inaccuracies and fabricated sources)
- Factually incorrect content (inaccuracies and fabricated sources)
- Opacity (industry opacity)
- Opacity (industry opacity)
- Ethical and social risks