This post is a part of Rethink Priorities’ Worldview Investigations Team's CURVE Sequence: “Causes and Uncertainty: Rethinking Value in Expectation.” The aim of this sequence is twofold: first, to consider alternatives to expected value maximization for cause prioritization; second, to evaluate the claim that a commitment to expected value maximization robustly supports the conclusion that we ought to prioritize existential risk mitigation over all else. This post presents a software tool we're developing to better understand risk and effectiveness.
Executive Summary
The cross-cause cost-effectiveness model (CCM) is a software tool under development by Rethink Priorities to produce cost-effectiveness evaluations in different cause areas.
- The CCM enables evaluations of interventions in global health and development, animal welfare, and existential risk mitigation.
- The CCM also includes functionality for evaluating research projects aimed at improving existing interventions or discovering more effective alternatives.
The CCM follows a Monte Carlo approach to assessing probabilities.
- The CCM accepts user-supplied distributions as parameter [...]
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Outline:
(00:43) Executive Summary
(04:24) Purpose
(05:36) Key Features
(05:52) We model uncertainty with simulations
(06:38) We incorporate user-specified parameter distributions
(07:17) Our results capture outcome ineffectiveness
(08:42) We enable users to specify the probability of extinction for different future eras
(09:28) Structure
(10:08) Intervention module
(10:40) Global Health and Development
(11:14) Animal Welfare
(12:00) Existential Risk Mitigation
(13:59) Research projects module
(14:56) Limitations
(15:12) It is geared towards specific kinds of interventions
(16:24) Distributions are a questionable way of handling deep uncertainty
(17:13) The model doesn’t handle model uncertainty
(18:01) The model assumes parameter independence
(18:59) Lessons
(19:06) The expected value of existential risk mitigation interventions depends on future population dynamics
(20:15) The value of existential risk mitigation is extremely variable
(21:38) Tail-end results can capture a huge amount of expected value
(22:22) Unrepresented correlations may be decisive
(23:43) Future Plans
(24:49) Acknowledgements
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