The evidence shelf
Read the argument. Check the forecast.
Primary sources beside criticism; conceptual arguments separated from dated predictions; videos selected for clarity rather than heat.
Forecast audit
14 April 2026
Before he wrote AI 2027, he predicted the world in 2026. How did he do?
Clara Collier and Daniel Kokotajlo
A retrospective audit of Kokotajlo’s earlier forecast, including misses and partial hits.
Response
2025-12
Response to the critique of the AI 2027 timelines model
Daniel Kokotajlo and Eli Lifland
The authors answer the timeline critique and clarify where they agree and disagree.
Review
18 September 2025
If someone builds it, will everyone die?
Kelsey Piper
A safety-informed but critical examination of the book’s strongest claims.
Book
16 September 2025
If Anyone Builds It, Everyone Dies
Eliezer Yudkowsky and Nate Soares
A forceful argument that sufficiently capable misaligned superintelligence would cause human extinction; it is an argument, not a dated forecast.
Book
2025-09
If Anyone Builds It, Everyone Dies
Eliezer Yudkowsky & Nate Soares
The strongest-form case that building superintelligence with current methods leads to human extinction, and a call to stop.
Critique
19 June 2025
A deep critique of AI 2027’s timeline models
titotal
A detailed challenge to assumptions and mathematics beneath the scenario’s compressed timeline.
Scenario
3 April 2025
AI 2027
Daniel Kokotajlo, Scott Alexander, Thomas Larsen, Eli Lifland and Romeo Dean
The primary interactive scenario, including its race and slowdown branches and supporting model.
Essay
3 April 2025
Our first project: AI 2027
Daniel Kokotajlo
The creators introduce the project, its purpose and how they want it read.
Paper
3 April 2025
Essay
2025-04
AI 2027
Daniel Kokotajlo, Scott Alexander, Thomas Larsen, Eli Lifland, Romeo Dean
A month-by-month scenario of how a race to superhuman AI could unfold by 2027, with two endings.
Report
2025 (updated 2026)
International AI Safety Report
Yoshua Bengio (chair) and ~100 experts, commissioned by 30+ governments
The closest thing to an IPCC-style consensus review of what advanced AI can do and what the risks are.
Video
2025
AI 2027: Daniel Kokotajlo and Scott Alexander
Dwarkesh Podcast
A long-form walkthrough with two of the scenario’s authors.
Paper
2025
Subjective-probability forecasts of existential risk
Ezra Karger and collaborators
A peer-reviewed comparison of domain experts’ and superforecasters’ estimates of existential risk.
Podcast
2025
AI 2027 report
Lawfare Daily
Daniel Kokotajlo and Eli Lifland explain the scenario in a policy-focused interview.
Essay
26 July 2024
AI existential-risk probabilities are too unreliable to inform policy
Arvind Narayanan and Sayash Kapoor
A critique of treating highly uncertain extinction estimates as policy-grade measurements.
Forecast
2024-06
Situational Awareness: The Decade Ahead
Leopold Aschenbrenner
A compute- and geopolitics-driven case for very rapid progress and an international race.
Research
11 March 2024
Roots of Disagreement on AI Risk
Forecasting Research Institute
A structured investigation of why informed people remain far apart on A.I. risk.
Video
2024
Intro to AI Safety, Remastered
Robert Miles
A clear, non-alarmist introduction to the mechanics behind the safety argument.
Report
30 May 2023
Statement on AI Risk
Center for AI Safety (signed by Hinton, Bengio, Altman, Amodei, Hassabis and hundreds more)
One sentence: mitigating the risk of extinction from AI should be a global priority alongside pandemics and nuclear war.
Report
22 March 2023
Pause Giant AI Experiments: An Open Letter
Future of Life Institute
Calls for a six-month pause on training systems more powerful than GPT-4 while shared safety protocols are developed.
Book
2023
The Coming Wave
Mustafa Suleyman (with Michael Bhaskar)
A lab co-founder argues the wave of AI and synthetic biology cannot be stopped, only contained, and lays out ten steps toward containment.
Forecast
6 August 2021
What 2026 Looks Like
Daniel Kokotajlo
An earlier dated scenario whose near-term claims can now be compared with events.
Book
2021
Atlas of AI: Power, Politics, and the Planetary Costs of Artificial Intelligence
Kate Crawford
Maps AI as an extractive industry — minerals, energy, labour, data — rather than a disembodied intelligence.
Book
2020
The Alignment Problem: Machine Learning and Human Values
Brian Christian
A reported, historical account of how machine-learning systems come to encode values, and how researchers try to keep them aligned with ours.
Book
2020
The Precipice
Toby Ord
Places A.I. alongside other existential risks and explains how numerical risk estimates are used.
Book
2019
Human Compatible: AI and the Problem of Control
Stuart Russell
Argues that the standard model of AI (optimize a fixed objective) is the root of the control problem, and proposes machines that are uncertain about human preferences.
Book
2019
Human Compatible
Stuart Russell
A control-problem account that also develops a more solutions-oriented model of beneficial A.I.
Video
2018
The Orthogonality Thesis
Robert Miles
An accessible explanation of why intelligence alone does not guarantee human-compatible goals.
Book
2014
Superintelligence: Paths, Dangers, Strategies
Nick Bostrom
The foundational modern account of orthogonality, instrumental convergence and loss of control.
Book
2014
Superintelligence: Paths, Dangers, Strategies
Nick Bostrom
The book that framed the modern debate: why a superintelligent system might be hard to control and what strategies might help.