Difference between revisions of "AI safety"
KevinYager (talk | contribs) (→Research) |
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* 2024-04: [https://arxiv.org/abs/2404.13208 The Instruction Hierarchy: Training LLMs to Prioritize Privileged Instructions] (OpenAI) | * 2024-04: [https://arxiv.org/abs/2404.13208 The Instruction Hierarchy: Training LLMs to Prioritize Privileged Instructions] (OpenAI) | ||
| − | + | * 2025-01: [https://arxiv.org/abs/2501.18837 Constitutional Classifiers: Defending against Universal Jailbreaks across Thousands of Hours of Red Teaming] (Anthropic, [https://www.anthropic.com/research/constitutional-classifiers blog], | |
| + | * 2025-02: [https://drive.google.com/file/d/1QAzSj24Fp0O6GfkskmnULmI1Hmx7k_EJ/view Utility Engineering: Analyzing and Controlling Emergent Value Systems in AIs] ([https://www.emergent-values.ai/ site], [https://github.com/centerforaisafety/emergent-values github]) | ||
* 2025-02: [https://arxiv.org/abs/2502.07776 Auditing Prompt Caching in Language Model APIs] | * 2025-02: [https://arxiv.org/abs/2502.07776 Auditing Prompt Caching in Language Model APIs] | ||
Revision as of 14:10, 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
- DeepMind short course on AGI safety
- AI Safety FAQ
- Writing Doom (video) 27m short film on Superintelligence (2024)
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)
