Authors of linked report: Josh Rosenberg, Ezra Karger, Avital Morris, Molly Hickman, Rose Hadshar, Zachary Jacobs, Philip Tetlock[1] Today, the Forecasting Research Institute (FRI) released “Roots of Disagreement on AI Risk: Exploring the Potential and Pitfalls of Adversarial Collaboration,” which discusses the results of an adversarial collaboration focused on forecasting risks from AI. In this post, we provide a brief overview of the methods, findings, and directions for further research. For much more analysis and discussion, see the full report: https://forecastingresearch.org/s/AIcollaboration.pdf Abstract. We brought together generalist forecasters and domain experts (n=22) who disagreed about the risk AI poses to humanity in the next century. The “concerned” participants (all of whom were domain experts) predicted a 20% chance of an AI-caused existential catastrophe by 2100, while the “skeptical” group (mainly “superforecasters”) predicted a 0.12% chance. Participants worked together to find the strongest near-term cruxes: forecasting questions resolving by 2030 that [...] ---Outline:(02:13) Extended Executive Summary(02:44) Methods(03:53) Results: What drives (and doesn’t drive) disagreement over AI risk(04:32) Hypothesis #1 - Disagreements about AI risk persist due to lack of engagement among participants, low quality of participants, or because the skeptic and concerned groups did not understand each others arguments(05:11) Hypothesis #2 - Disagreements about AI risk are explained by different short-term expectations (e.g. about AI capabilities, AI policy, or other factors that could be observed by 2030)(07:53) Hypothesis #3 - Disagreements about AI risk are explained by different long-term expectations(10:35) Hypothesis #4 - These groups have fundamental worldview disagreements that go beyond the discussion about AI(11:31) Results: Forecasting methodology(12:15) Broader scientific implications(13:09) Directions for further researchThe original text contained 10 footnotes which were omitted from this narration. ---
First published:
March 11th, 2024

Source:
https://forum.effectivealtruism.org/posts/orhjaZ3AJMHzDzckZ/results-from-an-adversarial-collaboration-on-ai-risk-fri

Linkpost URL:https://forecastingresearch.org/s/AIcollaboration.pdf
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