Assessing Potential Future AI Risks, Benefits, and Policy Imperatives is a 69-page report published as OECD AI Papers No. 27 in November 2024 by the OECD's AI and Emerging Digital Technologies Division and Strategic Foresight Unit. It was produced by the OECD's Expert Group on AI Futures, co-chaired by Stuart Russell (UC Berkeley / CHAI), Francesca Rossi (IBM), and Michael Schönstein (Federal Chancellery of Germany). It reviews potential future AI risks, including loss of human control, alongside potential benefits and policy actions.
Provenance and development
The report was reviewed by member state representatives and formally approved by the OECD Digital Policy Committee. It reviews published research and expert perspectives rather than generating new empirical findings. OECD membership covers 38 major economies, and OECD guidance documents are influential with national policymakers.
The report was developed through the OECD AI-WIPS programme (AI in Work, Innovation, Productivity and Skills), funded by the German Federal Ministry of Labour and Social Affairs, which accounts for its emphasis on workforce and economic disruption alongside technical safety.
The document states its prospective and tentative character: "many of the future-oriented aspects of its contents are necessarily speculative." It is among the first documents from a major multilateral governance body to engage with frontier AI risk scenarios, including potential loss of human control, while maintaining the diplomatic constraints of OECD publication. This prospective orientation departs from the OECD's typical empirical policy documents, which focus on near-term economic and social impacts.
Summary of analysis
Potential future benefits
The report identifies productivity gains and economic growth; scientific acceleration in medicine, climate, and materials science; enhancement of human capabilities; and democratization of expertise.
Potential future risks
The risk analysis distinguishes near-term, higher-confidence risks from longer-term, more speculative ones.
Near-term, higher-confidence risks: labor market disruption and inequality; concentration of AI economic power; erosion of privacy and surveillance expansion; algorithmic discrimination at scale; and information ecosystem degradation (misinformation).
Longer-term, more speculative risks: loss of human oversight and control over AI systems; autonomous AI pursuing misaligned goals; concentration of AI-enabled political and military power; and societal dependency and skill atrophy.
Policy imperatives
The policy recommendations span three levels. At the national level, the report points to risk assessment frameworks, safety research investment, and workforce transition programs. At the multilateral / OECD level, it points to shared definitions, cross-border incident reporting, and coordination on standards. On AI governance architecture, the report argues for building governance capacity before frontier risks materialize.
Relation to other frameworks
Russell's participation, as a UC Berkeley AI safety researcher, signals that AI safety research is influencing OECD-level policy deliberations. The report's engagement with loss-of-control scenarios departs from the OECD's traditional focus on near-term economic and social impacts.
The report contrasts with the NIST AI RMF: NIST provides a voluntary technical framework for managing current AI risks within organizations, while the OECD report is oriented toward prospective international governance of systemic risks that have not yet materialized.
Relative to the Eight Worlds Framework, the OECD report supplies an international governance dimension largely absent from Sullivan and Feldman's US-centric analysis; both grapple with the same uncertainties. It is one of the few multilateral documents to engage with loss-of-control scenarios, the subject of AI Autonomy Risk. Its workforce focus provides international comparative material alongside US-centric labor analyses in AI Labor Disruption. The OECD report and the academic Taxonomy of Systemic Risks operate at the same level of abstraction, the OECD providing policy framing and the taxonomy academic rigor. The report's prospective framing is consistent with Ord's argument in Broad Timelines for broad probability distributions rather than short- or long-timeline camps. The OECD governance framework is being operationalized through the standards-body process documented in Jeon (2025), discussed in Standardization Trends.