"Collective Intelligence as Infrastructure for Reducing Broad Global Catastrophic Risks"

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Abstract/Contents

Abstract: Academic and philanthropic communities have grown increasingly concerned with global catastrophic risks (GCRs), including artificial intelligence safety, pandemics, biosecurity, and nuclear war. Outcomes of many, if not all, risk situations hinge on the performance of human groups, such as whether governments or scientific communities can work effectively. We propose to think about these issues as Collective Intelligence (CI) problems—of how to process distributed information effectively. CI is a transdisciplinary research area, whose application involves human and animal groups, markets, robotic swarms, collections of neurons, and other distributed systems. In this article, we argue that improving CI in human groups can improve general resilience against a wide variety of risks. We summarize findings from the CI literature on conditions that improve human group performance, and discuss ways existing CI findings may be applied to GCR mitigation. We also suggest several directions for future research at the exciting intersection of these two emerging fields.

Author	Yang, Vicky Chuqiao
Author	Sandberg, Anders

DOI	https://doi.org/10.25740/mf606ht6373
Location	https://purl.stanford.edu/mf606ht6373

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License: This work is licensed under a Creative Commons Attribution Non Commercial No Derivatives 4.0 International license (CC BY-NC-ND).

Preferred citation: Yang, V. and Sandberg, A. (2023). "Collective Intelligence as Infrastructure for Reducing Broad Global Catastrophic Risks" in Intersections, Reinforcements, Cascades: Proceedings of the 2023 Stanford Existential Risks Conference. The Stanford Existential Risks Initiative. Stanford Digital Repository. Available at https://purl.stanford.edu/mf606ht6373. https://doi.org/10.25740/mf606ht6373.

Intersections, Reinforcements, Cascades: The Proceedings of the 3rd Annual Stanford Existential Risks Conference

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