Inaccuracy and poor predictive performance
The system fails to perform its intended task accurately or helpfully, producing erroneous, low-quality, or generic and homogenized results ('AI slop') that can erode content distinctiveness and organizational credibility, as distinct from fabricated content, brittleness to unusual inputs, and performance drift over time.
- Risk family
- Model & system behaviour
- MIT domain
- 7. AI System Safety, Failures, & Limitations
- MIT subdomain
- 7.3 > Lack of capability or robustness
- AI type
- GPAI, Classical_ML, Agentic
- Scope
- System
- Source standard
- MIT AI Risk Repository v4
Provenance
44 entries across 25 papers
- Abercrombie2024A Collaborative, Human-Centred Taxonomy of AI, Algorithmic, and Automation Harms58.07.12
- Bengio2024International Scientific Report on the Safety of Advanced AI49.02.00
- Critch2023TASRA: a Taxonomy and Analysis of Societal-Scale Risks from AI01.03.00
- Everitt2018AGI Safety Literature Review51.09.00
- Gipiškis2024Risk Sources and Risk Management Measures in Support of Standards for General-Purpose AI Systems62.15.02 62.16.03 62.18.02
- GOS2023Future Risks of Frontier AI56.11.00
- Habbal2024Artificial Intelligence Trust, Risk and Security Management (AI TRiSM): Frameworks, Applications, Challenges and Future Research Directions29.01.00
- Hagendorff2024Mapping the Ethics of Generative AI: A Comprehensive Scoping Review05.18.00
- IBM2025AI Risk Atlas65.13.01
- InfoComm2023Cataloguing LLM Evaluations43.01.00 43.01.04 43.02.00
- Leech2024Ten Hard Problems in Artificial Intelligence We Must Get Right54.03.00
- Li2025A Closer Look at the Existing Risks of Generative AI: Mapping the Who, What, and How of Real-World Incidents66.08.02
- Liu2024Trustworthy LLMs: A Survey and Guideline for Evaluating Large Language Models’ Alignment30.01.03 30.05.02 30.05.03 30.06.02
- Meek2016Managing the ethical and risk implications of rapid advances in artificial intelligence: A literature review09.02.04 09.02.05
- Nah2023Generative AI and ChatGPT: Applications, Challenges, and AI-Human Collaboration33.02.05
- Saghiri2022A Survey of Artificial Intelligence Challenges: Analyzing the Definitions, Relationships, and Evolutions39.12.00 39.27.00
- Schnitzer2024AI Hazard Management: A Framework for the Systematic Management of Root Causes for AI Risks59.03.00 59.16.00 59.21.00 59.26.03
- Steimers2022Sources of Risk of AI Systems14.04.00 14.07.00
- Tan2022The Risks of Machine Learning Systems15.01.04 15.01.06 15.01.07 15.01.08
- Tang2025Risks of AI Scientists: Prioritizing Safeguarding Over Autonomy71.02.03
- Teixeira2022An Exploratory Diagnosis of Artificial Intelligence Risks for a Responsible Governance42.03.00 42.15.00
- Uuk2025A Taxonomy of Systemic Risks from General-Purpose AI61.02.24 61.02.37
- Wirtz2022Governance of artificial intelligence: A risk and guideline-based integrative framework19.01.02 19.01.06
- Yampolskiy2016Taxonomy of Pathways to Dangerous Artificial Intelligence40.06.00
- Zhang2022Towards risk-aware artificial intelligence and machine learning systems: An overview21.02.02
Ev IDs of the entries consolidated into this risk in the MIT AI Risk Repository (V4); the source sheet row appears on hover.
Framework crosswalk
Every framework item mapped to this risk. Items marked partial overlap only in part; definitions appear on hover where the source licence permits.
2- A.4 ISO/IEC 23894 Annex A A.4
- A.9 ISO/IEC 23894 Annex A A.9
2- A.6.2.4 ISO/IEC 42001 Annex A A.6.2.4
- A.6.2.6 ISO/IEC 42001 Annex A A.6.2.6
1- Art. 15
1- ibm-poor-model-accuracy Poor model accuracy
More in Model & system behaviour
Part of the Deployer AI Risk Register, an open-source resource powered by MindXO. Version 1.0, 3 July 2026. Derived from the MIT AI Risk Repository (V4, December 2025) under CC BY 4.0; an independent derivative work, not endorsed by or affiliated with MIT. Sub-risk decomposition references MITRE ATLAS™ v5.6.0 (© 2021-2026 The MITRE Corporation, reproduced and distributed with permission). ISO/IEC and EU AI Act references are by number only. License: CC BY 4.0. Full attribution and licensing.