{"slug": "new-paper-prioritizing-risks-from-ai-a-delphi-study-of-272-experts", "title": "[New Paper] Prioritizing Risks from AI: A Delphi Study of 272 Experts", "summary": "A new Delphi study of 272 international AI experts found that 18 out of 24 AI risk domains have a more than 10% chance of causing catastrophic outcomes—including over one million deaths or $100 billion in losses—by 2030 under a business-as-usual scenario. The study identified a responsibility gap: general-purpose AI developers and governance actors are seen as most responsible for reducing risks, while AI users and affected stakeholders are most vulnerable. This misalignment of incentives, the researchers warn, undermines effective risk mitigation across the most vulnerable sectors, including information, finance, and national security.", "body_md": "TL;DR: We ran a Delphi study with 272 international AI experts to prioritize 24 AI risk domains from the [MIT AI Risk Domain Taxonomy](https://airisk.mit.edu/risks). In a business-as-usual scenario, experts judged a more than 10% chance of catastrophic outcomes (i.e., ‘more than 1 million human deaths or more than a USD 100B in financial loss or civilizational-scale intangible impacts’) from 18 of our 24 AI risk domains over the next five years.\n\nThey also identified a responsibility gap: AI users and affected stakeholders are most vulnerable, while general-purpose AI developers and governance actors are seen as most responsible for reducing the risks.\n\nBelow are three of the key findings and related visualizations.\n\n18 of 24 risks were judged to have a more than a 10% chance of causing catastrophic outcomes (which could include more than one million deaths, more than $100 billion in financial losses, or other harms) by 2030 under a business as usual scenario.\n\nAccording to experts, general-purpose AI developers and governance actors such as governments, regulators, and standards bodies hold primary responsibility for addressing AI risks. In contrast, AI system users and affected stakeholders such as members of the public are most vulnerable to AI risks.\n\nThis mismatch means that those who are most responsible for addressing AI risks are not those who are most vulnerable, leading to misaligned incentives in addressing the most important AI risks.\n\nAcross most risks, experts identify information, finance & insurance, and national security as the most vulnerable sectors. The results also show how vulnerability differs across sectors and risk categories.\n\nRead our paper and explore the interactive results [here](https://airisk.mit.edu/priorities).\n\nDisclosure: I used an LLM to help generate the first draft of content in this post. I then rewrote and reviewed the text, and I endorse the final version. We also used LLMs as part of the research and communication, for instance, in generating the images and interactives.", "url": "https://wpnews.pro/news/new-paper-prioritizing-risks-from-ai-a-delphi-study-of-272-experts", "canonical_source": "https://forum.effectivealtruism.org/posts/oaap7qYBwtEHEkyo3/new-paper-prioritizing-risks-from-ai-a-delphi-study-of-272", "published_at": "2026-06-11 20:56:58+00:00", "updated_at": "2026-06-11 21:18:01.765600+00:00", "lang": "en", "topics": ["ai-safety", "ai-policy", "ai-ethics", "ai-research", "artificial-intelligence"], "entities": ["MIT"], "alternates": {"html": "https://wpnews.pro/news/new-paper-prioritizing-risks-from-ai-a-delphi-study-of-272-experts", "markdown": "https://wpnews.pro/news/new-paper-prioritizing-risks-from-ai-a-delphi-study-of-272-experts.md", "text": "https://wpnews.pro/news/new-paper-prioritizing-risks-from-ai-a-delphi-study-of-272-experts.txt", "jsonld": "https://wpnews.pro/news/new-paper-prioritizing-risks-from-ai-a-delphi-study-of-272-experts.jsonld"}}