LLMs Draft Report on AGI Forecasting Amid Deep Uncertainty
A new report on forecasting artificial general intelligence (AGI) was published, primarily drafted by large language models—GPT 5.1, Gemini 3 Pro, and Claude 4.5 Opus—with human researchers providing direction, peer review, fact-checking, and revision. The report reviews methodologies for predicting AGI arrival, assesses their reliability, and analyzes strategic and policy implications. It synthesizes diverse forecasting approaches, documents significant limitations, and proposes a research agenda for more-robust forecasting infrastructure. The authors do not endorse any specific forecast or scenario but offer a framework for interpreting forecasts under deep uncertainty. The report is available on arXiv under the category Computer Science > Computers and Society.
Key facts
- Report titled 'Artificial General Intelligence Forecasting and Scenario Analysis: State of the Field, Methodological Gaps, and Strategic Implications'
- Primary drafting by GPT 5.1, Gemini 3 Pro, and Claude 4.5 Opus
- Human researchers provided direction, peer review, fact-checking, and revision
- Reviews current state of AGI forecasting methodologies
- Assesses reliability of existing forecasting methods
- Documents significant limitations in current approaches
- Proposes research agenda for robust forecasting infrastructure
- Does not endorse any specific forecast or scenario
- Provides framework for interpreting forecasts under deep uncertainty
- Published on arXiv under Computer Science > Computers and Society
Entities
Institutions
- arXiv