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Anthropic 2024 paper
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This Wikipedia article serves as a broad introductory reference for AI safety; useful for orienting newcomers but lacks the depth and rigor of primary research papers or dedicated technical resources.
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Importance: 45/100wiki pagereference
Summary
A comprehensive Wikipedia overview of AI safety as an interdisciplinary field, covering its core components including AI alignment, risk monitoring, and robustness, as well as the policy landscape and institutional developments through 2023. The article surveys motivations ranging from near-term risks like bias and surveillance to speculative existential risks from AGI, and documents the field's rapid growth following generative AI advances.
Key Points
- •AI safety encompasses technical research (alignment, robustness, monitoring) and policy work (norms, regulations, government advocacy).
- •Risks range from near-term concerns (bias, surveillance, cyberattacks, bioterrorism) to speculative long-term risks (AGI loss of control, AI-enabled authoritarianism).
- •The field gained major momentum in 2023, leading to the creation of AI Safety Institutes in the US and UK following the AI Safety Summit.
- •Researchers warn that safety measures are not keeping pace with the rapid development of AI capabilities.
- •The field involves ongoing debate between those dismissing AGI risks (e.g., Andrew Ng) and those urging caution (e.g., Stuart Russell).
Cited by 2 pages
| Page | Type | Quality |
|---|---|---|
| Provable / Guaranteed Safe AI | Concept | 64.0 |
| Longterm Wiki | Project | 63.0 |
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AI safety - Wikipedia
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From Wikipedia, the free encyclopedia
Artificial intelligence field of study
Part of a series on Artificial intelligence (AI)
Major goals
Artificial general intelligence
Intelligent agent
Recursive self-improvement
Planning
Computer vision
General game playing
Knowledge representation
Natural language processing
Robotics
AI safety
Approaches
Machine learning
Symbolic
Deep learning
Bayesian networks
Evolutionary algorithms
Hybrid intelligent systems
Systems integration
Open-source
AI data centers
Applications
Bioinformatics
Deepfake
Earth sciences
Finance
Generative AI
Art
Audio
Music
Government
Healthcare
Mental health
Industry
Software development
Translation
Military
Physics
Projects
Philosophy
AI alignment
Artificial consciousness
The bitter lesson
Chinese room
Friendly AI
Ethics
Existential risk
Turing test
Uncanny valley
Human–AI interaction
History
Timeline
Progress
AI winter
AI boom
AI bubble
Controversies
Deepfake pornography
Taylor Swift deepfake pornography controversy
Grok sexual deepfake scandal
Google Gemini image generation controversy
It's the Most Terrible Time of the Year
Pause Giant AI Experiments
Removal of Sam Altman from OpenAI
Statement on AI Risk
Tay (chatbot)
Théâtre D'opéra Spatial
Voiceverse NFT plagiarism scandal
Glossary
Glossary
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AI safety is an interdisciplinary field focused on preventing accidents, misuse, or other harmful consequences arising from artificial intelligence (AI) systems. It encompasses AI alignment (which aims to ensure AI systems behave as intended), monitoring AI systems for risks, and enhancing their robustness. The field is particularly concerned with existential risks posed by advanced AI models. [ 1 ] [ 2 ]
Beyond technical research, AI safety involves developing norms and policies that promote safety, including advocacy for regulations at different levels of government. [ 3 ] [ 4 ] [ 5 ] The field gained significant popularity in 2023, with rapid progress in generative AI and public concerns voiced by researchers and CEOs about potential dangers. During the 2023 AI Safety Summit , the United States and the United Kingdom both established their own AI Safety Institute . However, researchers have expressed concern that AI safety measures are not keeping pace with the rapid development of AI capabilities. [ 6 ]
Motivations
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Scholars discuss current risks from critical systems failures, [ 7 ] bias , [ 8 ] and AI-enabled surveillance, [ 9 ] as well as emerging risks like technologica
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