Difference between revisions of "AI predictions"
KevinYager (talk | contribs) (→Plans) |
KevinYager (talk | contribs) (→Strategic/Policy) |
||
| Line 224: | Line 224: | ||
* 2025-04: MIRI: [https://techgov.intelligence.org/research/ai-governance-to-avoid-extinction AI Governance to Avoid Extinction: The Strategic Landscape and Actionable Research Questions] | * 2025-04: MIRI: [https://techgov.intelligence.org/research/ai-governance-to-avoid-extinction AI Governance to Avoid Extinction: The Strategic Landscape and Actionable Research Questions] | ||
* 2025-05: [https://writing.antonleicht.me/p/the-new-ai-policy-frontier The New AI Policy Frontier]: Beyond the shortcomings of centralised control and alignment, a new school of thought on AI governance emerges. It still faces tricky politics. | * 2025-05: [https://writing.antonleicht.me/p/the-new-ai-policy-frontier The New AI Policy Frontier]: Beyond the shortcomings of centralised control and alignment, a new school of thought on AI governance emerges. It still faces tricky politics. | ||
| + | * 2025-05: [https://uncpga.world/agi-uncpga-report/ AGI UNCPGA Report]: Governance of the Transition to Artificial General Intelligence (AGI) Urgent Considerations for the UN General Assembly: Report for the Council of Presidents of the United Nations General Assembly (UNCPGA) | ||
=See Also= | =See Also= | ||
* [[AI safety]] | * [[AI safety]] | ||
Revision as of 11:09, 2 June 2025
Contents
Capability Scaling
- 2019-03: Rich Sutton: The Bitter Lesson
- 2020-09: Ajeya Cotra: Draft report on AI timelines
- 2022-01: gwern: The Scaling Hypothesis
- 2023-05: Richard Ngo: Clarifying and predicting AGI
- 2024-06: Aidan McLaughlin: AI Search: The Bitter-er Lesson
- 2025-03: Measuring AI Ability to Complete Long Tasks Measuring AI Ability to Complete Long Tasks
- 2025-04: Forecaster reacts: METR's bombshell paper about AI acceleration New data supports an exponential AI curve, but lots of uncertainty remains
- 2025-04: AI Digest: A new Moore's Law for AI agents
- 2025-04: Trends in AI Supercomputers
- The Road to AGI (timeline visualization)
AGI Achievable
- Yoshua Bengio: Managing extreme AI risks amid rapid progress
- Leopold Aschenbrenner: Situational Awareness: Counting the OOMs
- Richard Ngo: Visualizing the deep learning revolution
- Katja Grace: Survey of 2,778 AI authors: six parts in pictures
- Epoch AI: Machine Learning Trends
- AI Digest: How fast is AI improving?
AGI Definition
- 2023-11: Allan Dafoe, Shane Legg, et al.: Levels of AGI for Operationalizing Progress on the Path to AGI
- 2024-04: Bowen Xu: What is Meant by AGI? On the Definition of Artificial General Intelligence
Progress Models
Economic and Political
- 2019-11: The Impact of Artificial Intelligence on the Labor Market
- 2023-10: Marc Andreessen: The Techno-Optimist Manifesto
- 2023-12: My techno-optimism: "defensive acceleration" (Vitalik Buterin)
- 2024-03: Noah Smith: Plentiful, high-paying jobs in the age of AI: Comparative advantage is very subtle, but incredibly powerful. (video)
- 2024-03: Scenarios for the Transition to AGI (AGI leads to wage collapse)
- 2024-06: Situational Awareness (Leopold Aschenbrenner) - select quotes, podcast, text summary of podcast
- 2024-06: AI and Growth: Where Do We Stand?
- 2024-09: OpenAI Infrastructure is Destiny: Economic Returns on US Investment in Democratic AI
- 2024-12: By default, capital will matter more than ever after AGI (L Rudolf L)
- 2025-01: The Intelligence Curse: With AGI, powerful actors will lose their incentives to invest in people
- Updated 2025-04: The Intelligence Curse (Luke Drago and Rudolf Laine)
- 2025-01: Microsoft: The Golden Opportunity for American AI
- 2025-01: AGI Will Not Make Labor Worthless
- 2025-01: AI in America: OpenAI's Economic Blueprint (blog)
- 2025-01: How much economic growth from AI should we expect, how soon?
- 2025-02: Morgan Stanley: The Humanoid 100: Mapping the Humanoid Robot Value Chain
- 2025-02: The Anthropic Economic Index: Which Economic Tasks are Performed with AI? Evidence from Millions of Claude Conversations
- 2025-02: Strategic Wealth Accumulation Under Transformative AI Expectations
- 2025-02: Tyler Cowen: Why I think AI take-off is relatively slow
- 2025-03: Epoch AI: Most AI value will come from broad automation, not from R&D
- The primary economic impact of AI will be its ability to broadly automate labor
- Automating AI R&D alone likely won’t dramatically accelerate AI progress
- Fully automating R&D requires a very broad set of abilities
- AI takeoff will likely be diffuse and salient
- 2025-03: Anthropic Economic Index: Insights from Claude 3.7 Sonnet
- 2025-04: Will there be extreme inequality from AI?
- 2025-04: Anthropic Economic Index: AI’s Impact on Software Development
- 2025-05: Better at everything: how AI could make human beings irrelevant
Job Loss
- 2023-03: GPTs are GPTs: An Early Look at the Labor Market Impact Potential of Large Language Models
- 2023-08: The Short-Term Effects of Generative Artificial Intelligence on Employment: Evidence from an Online Labor Market
- 2023-09: What drives UK firms to adopt AI and robotics, and what are the consequences for jobs?
- 2023-11: New Analysis Shows Over 20% of US Jobs Significantly Exposed to AI Automation In the Near Future
- 2024-01: Duolingo cuts 10% of its contractor workforce as the company embraces AI
- 2024-02: Gen AI is a tool for growth, not just efficiency: Tech CEOs are investing to build their workforce and capitalise on new opportunities from generative AI. That’s a sharp contrast to how their peers view it.
- 2024-04: AI is Poised to Replace the Entry-Level Grunt Work of a Wall Street Career
- 2024-07: AI Is Already Taking Jobs in the Video Game Industry: A WIRED investigation finds that major players like Activision Blizzard, which recently laid off scores of workers, are using generative AI for game development
- 2024-08: Klarna: AI lets us cut thousands of jobs - but pay more
- 2025-01: AI and Freelancers: Has the Inflection Point Arrived?
- 2025-01: Yes, you're going to be replaced: So much cope about AI
- 2025-03: Will AI Automate Away Your Job? The time-horizon model explains the future of the technology
- 2025-05: It’s Time To Get Concerned, Klarna, UPS, Duolingo, Cisco, And Many Other Companies Are Replacing Workers With AI
- 2025-05: What Happens When AI Replaces Workers?
- 2025-05: Educated but unemployed, a rising reality for US college grads Structural shifts in tech hiring and the growing impact of AI are driving higher unemployment among recent college graduates
- 2025-05: NY Times: For Some Recent Graduates, the A.I. Job Apocalypse May Already Be Here The unemployment rate for recent college graduates has jumped as companies try to replace entry-level workers with artificial intelligence
National Security
- 2025-04: Jeremie Harris and Edouard Harris: America’s Superintelligence Project
Near-term
- 2021-08: Daniel Kokotajlo: What 2026 looks like
- 2025-02: Sam Altman: Three Observations
- The intelligence of an AI model roughly equals the log of the resources used to train and run it.
- The cost to use a given level of AI falls about 10x every 12 months, and lower prices lead to much more use
- The socioeconomic value of linearly increasing intelligence is super-exponential in nature
- 2025-03: Glimpses of AI Progress: Mental models for fast times
- 2025-04: Daniel Kokotajlo, Scott Alexander, Thomas Larsen, Eli Lifland, Romeo Dean: AI 2027 (pdf)
- 2025-04: Stanford HAI: Artificial Intelligence Index Report 2025
- 2025-04: Arvind Narayananand Sayash Kapoor: AI as Normal Technology
- 2025-04: Dwarkesh Patel: Questions about the Future of AI
- 2025-05: Trends – Artificial Intelligence
Overall
- 2025-03: Kevin Roose (New York Times): Powerful A.I. Is Coming. We’re Not Ready. Three arguments for taking progress toward artificial general intelligence, or A.G.I., more seriously — whether you’re an optimist or a pessimist.
- 2025-03: Nicholas Carlini: My Thoughts on the Future of "AI": "I have very wide error bars on the potential future of large language models, and I think you should too."
Surveys of Opinions/Predictions
- 2016-06: 2016 Expert Survey on Progress in AI
- 2023-08: 2023 Expert Survey on Progress in AI
- 2024-01: Thousands of AI Authors on the Future of AI
- 2025-02: Why do Experts Disagree on Existential Risk and P(doom)? A Survey of AI Experts
- 2025-02: Nicholas Carlini: AI forecasting retrospective: you're (probably) over-confident
- 2025-04: Helen Toner: "Long" timelines to advanced AI have gotten crazy short
- 2025-05: AI 2025 Forecasts - May Update
Bad Outcomes
- List of p(doom) values
- 2019-03: What failure looks like
- 2023-03: gwern: It Looks Like You’re Trying To Take Over The World
- 2025-01: Gradual Disempowerment: Systemic Existential Risks from Incremental AI Development (web version)
- 2025-04: Daniel Kokotajlo, Scott Alexander, Thomas Larsen, Eli Lifland, Romeo Dean: AI 2027 (pdf)
- 2025-04: AI-Enabled Coups: How a Small Group Could Use AI to Seize Power
Intelligence Explosion
- 2023-06: What a Compute-Centric Framework Says About Takeoff Speeds
- 2025-02: Three Types of Intelligence Explosion
- 2025-03: Future of Life Institute: Are we close to an intelligence explosion? AIs are inching ever-closer to a critical threshold. Beyond this threshold lie great risks—but crossing it is not inevitable.
- 2025-03: Forethought: Will AI R&D Automation Cause a Software Intelligence Explosion?
- 2025-05: The Last Invention Why Humanity’s Final Creation Changes Everything
- 2025-06:
Superintelligence
- 2024-10: How Smart will ASI be?
- 2024-11: Concise Argument for ASI Risk
- 2025-03: Limits of smart
- 2025-05: The Limits of Superintelligence
Long-range/Philosophy
- 2023-03: Dan Hendrycks: Natural Selection Favors AIs over Humans
Psychology
Science & Technology Improvements
- 2024-09: Sam Altman: The Intelligence Age
- 2024-10: Dario Amodei: Machines of Loving Grace
- 2024-11: Google DeepMind: A new golden age of discovery
- 2025-03: Fin Moorhouse, Will MacAskill: Preparing for the Intelligence Explosion
Plans
- A Narrow Path: How to Secure our Future
- Marius Hobbhahn: What’s the short timeline plan?
- Building CERN for AI: An institutional blueprint
- AGI, Governments, and Free Societies
- Control AI: The Direct Institutional Plan
- Luke Drago and L Rudolf L: The use of knowledge in (AGI) society: How to build to break the intelligence curse
- AGI Social Contract
- Yoshua Bengio: A Potential Path to Safer AI Development
Philosophy
- Dan Faggella:
- Joe Carlsmith: 2024: Otherness and control in the age of AGI
- Anthony Aguirre:
- 2025-04: Scott Alexander (Astral Codex Ten): The Colors Of Her Coat (response to semantic apocalypse and semantic satiation)
- 2025-05: Helen Toner: We’re Arguing About AI Safety Wrong: Dynamism vs. stasis is a clearer lens for criticizing controversial AI safety prescriptions
Research
Alignment
- 2023-03: Leopold Aschenbrenner: Nobody’s on the ball on AGI alignment
- 2024-03: What are human values, and how do we align AI to them? (blog)
- 2025: Joe Carlsmith: How do we solve the alignment problem? Introduction to an essay series on paths to safe, useful superintelligence
- What is it to solve the alignment problem? Also: to avoid it? Handle it? Solve it forever? Solve it completely? (audio version)
- When should we worry about AI power-seeking? (audio version)
- Paths and waystations in AI safety (audio version)
- AI for AI safety (audio version)
- Can we safely automate alignment research? (audio version, video version)
- The stakes of AI moral status
- 2025-04: Dario Amodei: The Urgency of Interpretability
Strategic/Technical
Strategic/Policy
- 2015-03: Sam Altman: Machine intelligence, part 2
- 2019-07: Amanda Askell, Miles Brundage, Gillian Hadfield: The Role of Cooperation in Responsible AI Development
- 2025-03: Dan Hendrycks, Eric Schmidt, Alexandr Wang: Superintelligence Strategy
- Anthony Aguirre: Keep The Future Human (essay)
- The 4 Rules That Could Stop AI Before It’s Too Late (video) (2025)
- Oversight: Registration required for training >1025 FLOP and inference >1019 FLOP/s (~1,000 B200 GPUs @ $25M). Build cryptographic licensing into hardware.
- Computation Limits: Ban on training models >1027 FLOP or inference >1020 FLOP/s.
- Strict Liability: Hold AI companies responsible for outcomes.
- Tiered Regulation: Low regulation on tool-AI, strictest regulation on AGI (general, capable, autonomous systems).
- The 4 Rules That Could Stop AI Before It’s Too Late (video) (2025)
- 2025-04: Helen Toner: Nonproliferation is the wrong approach to AI misuse
- 2025-04: MIRI: AI Governance to Avoid Extinction: The Strategic Landscape and Actionable Research Questions
- 2025-05: The New AI Policy Frontier: Beyond the shortcomings of centralised control and alignment, a new school of thought on AI governance emerges. It still faces tricky politics.
- 2025-05: AGI UNCPGA Report: Governance of the Transition to Artificial General Intelligence (AGI) Urgent Considerations for the UN General Assembly: Report for the Council of Presidents of the United Nations General Assembly (UNCPGA)
