AI predictions

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 (preprint)
• 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?
• 2025-06: The case for AGI by 2030

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)
    • Pyramid Replacement
    • Capital, AGI, and Human Ambition
    • Defining the Intelligence Curse
    • Shaping the Social Contract
    • Breaking the Intelligence Curse
    • History is Yours to Write
• 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
  • 2023-03: These jobs are most at risk due to ChatGPT, as per OpenAI study
• 2023-08: The Short-Term Effects of Generative Artificial Intelligence on Employment: Evidence from an Online Labor Market
  • Freelancer sector shrinking

• 2023-09: What drives UK firms to adopt AI and robotics, and what are the consequences for jobs?
  • 78% of Companies Say AI Created More 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
• 2025-06: How not to lose your job to AI The skills AI will make more valuable (and how to learn them)
• 2025-06: Future of Work with AI Agents: Auditing Automation and Augmentation Potential across the U.S. Workforce

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
  1. The intelligence of an AI model roughly equals the log of the resources used to train and run it.
  2. The cost to use a given level of AI falls about 10x every 12 months, and lower prices lead to much more use
  3. 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
• 2025-06: IdeaFoundry: Evolution vs. Extinction: The Choice is Ours The next 18 months will decide whether AI ends us or evolves us

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."
• 2025-06: Sam Altman: The Gentle Singularity

Surveys of Opinions/Predictions

• 2016-06: 2016 Expert Survey on Progress in AI
  • 2023-03: Scoring forecasts from the 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)
  • 2025-02: The Risk of Gradual Disempowerment from AI
  • 2025-05: Gradual Disempowerment: Concrete Research Projects
• 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
  • takeoffspeeds.com simulator
• 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

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

• 2025-01: A defence of slowness at the end of the world

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
  • Forging A New AGI Social Contract
• Yoshua Bengio: A Potential Path to Safer AI Development
  • 2025-02: Superintelligent Agents Pose Catastrophic Risks: Can Scientist AI Offer a Safer Path?

Philosophy

• Dan Faggella:
  • 2018-07: Moral Singularity – Unpredictable Values Bodes Poorly for Humanity
  • 2025-02: There is No Pause – We Must Bend the Posthuman Trajectory
• Joe Carlsmith: 2024: Otherness and control in the age of AGI
  1. Gentleness and the artificial Other
  2. Deep atheism and AI risk
  3. When “yang” goes wrong
  4. Does AI risk “other” the AIs?
  5. An even deeper atheism
  6. Being nicer than Clippy
  7. On the abolition of man
  8. On green
  9. On attunement
  10. Loving a world you don’t trust
• Anthony Aguirre:
  • 2025-03: Keep The Future Human

• 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
• 2025-05: Joe Carlsmith: The stakes of AI moral status

Research

• 2025-05: Gradual Disempowerment: Concrete Research Projects

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
  1. What is it to solve the alignment problem? Also: to avoid it? Handle it? Solve it forever? Solve it completely? (audio version)
  2. When should we worry about AI power-seeking? (audio version)
  3. Paths and waystations in AI safety (audio version)
  4. AI for AI safety (audio version)
  5. Can we safely automate alignment research? (audio version, video version)
• 2025-04: Dario Amodei: The Urgency of Interpretability

Strategic/Technical

• 2025-03: AI Dominance Requires Interpretability and Standards for Transparency and Security

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
  • Executive Summary
  • Introduction
  • AI Is Pivotal for National Security
  • Deterrence with Mutual Assured AI Malfunction (MAIM)
  • Nonproliferation
  • Competitiveness
  • Conclusion
  • Appendix FAQs
• Anthony Aguirre: Keep The Future Human (essay)
  • The 4 Rules That Could Stop AI Before It’s Too Late (video) (2025)
    1. Oversight: Registration required for training >10²⁵ FLOP and inference >10¹⁹ FLOP/s (~1,000 B200 GPUs @ $25M). Build cryptographic licensing into hardware.
    2. Computation Limits: Ban on training models >10²⁷ FLOP or inference >10²⁰ FLOP/s.
    3. Strict Liability: Hold AI companies responsible for outcomes.
    4. Tiered Regulation: Low regulation on tool-AI, strictest regulation on AGI (general, capable, autonomous systems).
• 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)
• 2025-06: AI & Jobs: Politics without Policy Political support mounts - for a policy platform that does not yet exist
• 2025-06: Sarah Hastings-Woodhouse: Safety Features for a Centralized AGI Project

See Also

• AI safety