Difference between revisions of "AI safety"
KevinYager (talk | contribs) (→Learning Resources) |
KevinYager (talk | contribs) (→Status) |
||
| Line 25: | Line 25: | ||
=Status= | =Status= | ||
* 2025-01:[https://assets.publishing.service.gov.uk/media/679a0c48a77d250007d313ee/International_AI_Safety_Report_2025_accessible_f.pdf International Safety Report: The International Scientific Report on the Safety of Advanced AI (January 2025)] | * 2025-01:[https://assets.publishing.service.gov.uk/media/679a0c48a77d250007d313ee/International_AI_Safety_Report_2025_accessible_f.pdf International Safety Report: The International Scientific Report on the Safety of Advanced AI (January 2025)] | ||
| + | |||
| + | ==Policy== | ||
| + | * 2024-07: [https://arxiv.org/abs/2407.05694 On the Limitations of Compute Thresholds as a Governance Strategy] Sara Hooker | ||
=Research= | =Research= | ||
Revision as of 14:20, 14 February 2025
Contents
Description of Safety Concerns
Key Concepts
- Instrumental Convergence
- Orthogonality Thesis
- Inner/outer alignment
- Mesa-optimization
- Overhang
- Reward is not the optimization target (Alex Turner)
Medium-term Risks
- 2023-04: A.I. Dilemma – Tristan Harris and Aza Raskin” (video) (.website-files.com/5f0e1294f002b1bb26e1f304/64224a9051a6637c1b60162a_65-your-undivided-attention-The-AI-Dilemma-transcript.pdf podcast transcript): raises concern about human ability to handle these transformations
- 2023-04: Daniel Schmachtenberger and Liv Boeree (video): AI could accelerate perverse social dynamics
- 2023-10: Sociotechnical Safety Evaluation of Generative AI Systems (Google DeepMind)
Long-term (x-risk)
- List AGI Ruin: A List of Lethalities (Eliezer Yudkowsky)
Learning Resources
- Introduction to AI Safety, Ethics, and Society (Dan Hendrycks, Center for AI Safety)
- AI Safety FAQ
- Writing Doom (video) 27m short film on Superintelligence (2024)
- DeepMind short course on AGI safety
Status
Policy
- 2024-07: On the Limitations of Compute Thresholds as a Governance Strategy Sara Hooker
Research
- 2022-12: Discovering Latent Knowledge in Language Models Without Supervision
- 2023-02: Pretraining Language Models with Human Preferences
- 2023-04: Do the Rewards Justify the Means? Measuring Trade-Offs Between Rewards and Ethical Behavior in the MACHIAVELLI Benchmark
- 2023-05: Model evaluation for extreme risks (DeepMind)
- 2023-05: Principle-Driven Self-Alignment of Language Models from Scratch with Minimal Human Supervision
- 2023-06: Preference Ranking Optimization for Human Alignment
- 2023-08: Self-Alignment with Instruction Backtranslation
- 2023-11: Debate Helps Supervise Unreliable Experts
- 2023-12: Weak-to-Strong Generalization: Eliciting Strong Capabilities with Weak Supervision (OpenAI, blog)
- 2023-12: Practices for Governing Agentic AI Systems (OpenAI, blog)
- 2024-01: Sleeper Agents: Training Deceptive LLMs that Persist through Safety Training (Anthropic)
- 2024-04: The Instruction Hierarchy: Training LLMs to Prioritize Privileged Instructions (OpenAI)
- 2024-10: First-Person Fairness in Chatbots (OpenAI, blog)
- 2024-10: Sabotage evaluations for frontier models (Anthropic, blog)
- 2024-12: Alignment Faking in Large Language Models (Anthropic)
- 2024-12: Best-of-N Jailbreaking (code)
- 2024-12: Deliberative Alignment: Reasoning Enables Safer Language Models (OpenAI)
- 2025-01: Trading Inference-Time Compute for Adversarial Robustness (OpenAI, blog)
- 2025-01: Constitutional Classifiers: Defending against Universal Jailbreaks across Thousands of Hours of Red Teaming (Anthropic, blog,
- 2025-02: Utility Engineering: Analyzing and Controlling Emergent Value Systems in AIs (site, github)
- 2025-02: Auditing Prompt Caching in Language Model APIs
