Survey on intermediate goals in AI governance

It seems that a key bottleneck for the field of longtermism-aligned AI governance is limited strategic clarity (see Muehlhauser, 2020, 2021). As one effort to increase strategic clarity, in October-November 2022, we sent a survey to 229 people we had reason to believe are knowledgeable about longtermist AI governance, receiving 107 responses. We asked about:

  • respondentsā€™ ā€œtheory of victoryā€ for AI risk (which we defined as the main, high-level ā€œplanā€ theyā€™d propose for how humanity could plausibly manage the development and deployment of transformative AI such that we get long-lasting good outcomes),

  • how theyā€™d feel about funding going to each of 53 potential ā€œintermediate goalsā€ for AI governance,[1]

  • what other intermediate goals theyā€™d suggest,

  • how high they believe the risk of existential catastrophe from AI is, and

  • when they expect transformative AI (TAI) to be developed.

We hope the results will be useful to funders, policymakers, people at AI labs, researchers, field-builders, people orienting to longtermist AI governance, and perhaps other types of people. For example, the report could:

  • Broaden the range of options people can easily consider

  • Help people assess how much and in what way to focus on each potential ā€œtheory of victoryā€, ā€œintermediate goalā€, etc.

  • Target and improve further efforts to assess how much and in what way to focus on each potential theory of victory, intermediate goal, etc.

You can see a summary of the survey results here. Note that we will expect readers to abide by the policy articulated in ā€œAbout sharing information from this reportā€ (for the reasons explained there).

Acknowledgments

This report is a project of Rethink Prioritiesā€“a think tank dedicated to informing decisions made by high-impact organizations and funders across various cause areas. The project was commissioned by Open Philanthropy. Full acknowledgements can be found in the linked ā€œIntroduction & summaryā€ document.

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  1. ^

    Hereā€™s the definition of ā€œintermediate goalā€ that we stated in the survey itself:

    By an intermediate goal, we mean any goal for reducing extreme AI risk thatā€™s more specific and directly actionable than a high-level goal like ā€˜reduce existential AI accident riskā€™ but is less specific and directly actionable than a particular intervention. In another context (global health and development), examples of potential intermediate goals could include ā€˜develop better/ā€‹cheaper malaria vaccinesā€™ and ā€˜improve literacy rates in Sub-Saharan Africaā€™.