mlsanityData to 14 Oct 2026

TASRA: a Taxonomy and Analysis of Societal-Scale Risks from AI

arXiv 2306.06924 ↗First posted 12 Jun 2023cs.AI cs.CR cs.CYcited by 26

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Abstract (arXiv)

While several recent works have identified societal-scale and extinction-level risks to humanity arising from artificial intelligence, few have attempted an em exhaustive taxonomy of such risks. Many exhaustive taxonomies are possible, and some are useful -- particularly if they reveal new risks or practical approaches to safety. This paper explores a taxonomy based on accountability: whose actions lead to the risk, are the actors unified, and are they deliberate? We also provide stories to illustrate how the various risk types could each play out, including risks arising from unanticipated interactions of many AI systems, as well as risks from deliberate misuse, for which combined technical and policy solutions are indicated.

Key facts. Cited by 26 papers in the map (data through 14 Oct 2026). Builds on 13 of its 64 references that are in the map. First posted on arXiv 12 Jun 2023.

Builds on

13 of 64 references.

References · 13

  1. 2016Concrete Problems in AI Safetycited by 1,642
  2. 2020Closing the AI Accountability Gap: Defining an End-to-End Framework for Internal Algorithmic Auditingcited by 384
  3. 2016Cooperative Inverse Reinforcement Learningcited by 300
  4. 2013The Complexity of Decentralized Control of Markov Decision Processescited by 231
  5. 2019Conservative Agency via Attainable Utility Preservationcited by 35
  6. 2019Preferences Implicit in the State of the Worldcited by 34
  7. 2019Learning Gentle Object Manipulation with Curiosity-Driven Deep Reinforcement Learningcited by 26
  8. 2019Literal or Pedagogic Human? Analyzing Human Model Misspecification in Objective Learningcited by 15
  9. 2017Low Impact Artificial Intelligencescited by 11
  10. 2017Incorrigibility in the CIRL Frameworkcited by 9
  11. 2015Taxonomy of Pathways to Dangerous AIcited by 4
  12. 2017Servant of Many Masters: Shifting priorities in Pareto-optimal sequential decision-makingcited by 2
1 more
  1. 2017Toward negotiable reinforcement learning: shifting priorities in Pareto optimal sequential decision-makingcited by 1

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 5; 2024: 8; 2025: 9; 2026: 4.

26 papers.

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  1. 2023Can LLM-Generated Misinformation Be Detected?cited by 177
  2. 2023Taken out of context: On measuring situational awareness in LLMscited by 143
  3. 2024Visibility into AI Agentscited by 79
  4. 2024Sabotage Evaluations for Frontier Modelscited by 52
  5. 2023From task structures to world models: What do LLMs know?cited by 46
  6. 2024A Collaborative, Human-Centred Taxonomy of AI, Algorithmic, and Automation Harmscited by 19
  7. 2024Not My Voice! A Taxonomy of Ethical and Safety Harms of Speech Generatorscited by 18
  8. 2024The AI risk repository: A meta-review, database, and taxonomy of risks from artificial intelligencecited by 16
  9. 2023An International Consortium for Evaluations of Societal-Scale Risks from Advanced AIcited by 5
  10. 2025A Framework for Responsible AI Systems: Building Societal Trust through Domain Definition, Trustworthy AI Design, Auditability, Accountability, and Governancecited by 5
  11. 2024Avoiding Catastrophe in Online Learning by Asking for Helpcited by 4
  12. 2025Misalignment or misuse? The AGI alignment tradeoffcited by 4
14 more
  1. 2026Overview of Risk Assessment and Management for Intelligent Systems under the AI Act and Beyondcited by 4
  2. 2024Strategic Insights from Simulation Gaming of AI Race Dynamicscited by 3
  3. 2025TechOps: Technical Documentation Templates for the AI Actcited by 3
  4. 2026AI Finds A Waycited by 3
  5. 2025The Economics of p(doom): Scenarios of Existential Risk and Economic Growth in the Age of Transformative AIcited by 2
  6. 2025Against racing to AGI: Cooperation, deterrence, and catastrophic riskscited by 2
  7. 2023General Purpose Artificial Intelligence Systems (GPAIS): Properties, Definition, Taxonomy, Societal Implications and Responsible Governancecited by 1
  8. 2024Taxonomy to Regulation: A (Geo)Political Taxonomy for AI Risks and Regulatory Measures in the EU AI Actcited by 1
  9. 2025Safe Learning Under Irreversible Dynamics via Asking for Helpcited by 1
  10. 2025Dimensional Characterization and Pathway Modeling for Catastrophic AI Riskscited by 1
  11. 2025A Taxonomy of Omnicidal Futures Involving Artificial Intelligencecited by 0
  12. 2025AI Consciousness and Existential Riskcited by 0
  13. 2026Relative Principals, Pluralistic Alignment, and the Structural Value Alignment Problemcited by 0
  14. 2026Culturally Situated AI Safety for Youth: Saudi Arabian Perspectives of Youth, Parents and Teacherscited by 0