Difference between revisions of "Reference class forecasting on human achievements argument for AI timelines"

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'''Reference class forecasting on human achievements''' uses various [[reference class]]es like "ambitious STEM technology" or "notable mathematical conjectures" to get an [[outside view]] probability of [[AI timelines]]. The [[Open Philanthropy]] report on semi-informative priors is an example of this type of forecasting.<ref>https://www.openphilanthropy.org/blog/report-semi-informative-priors</ref>
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'''Reference class forecasting on human achievements''' uses various [[reference class]]es like "ambitious STEM technology" or "notable mathematical conjectures" to get an [[outside view]] probability of [[AI timelines]]. The [[Open Philanthropy]] report on semi-informative priors is an example of this type of forecasting.<ref>https://www.openphilanthropy.org/blog/report-semi-informative-priors</ref> This estimate might then further be adjusted according to the inputs going into AGI creation (e.g. number of researchers and amount spent on computation), as is done in the Open Philanthropy report.
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[[MTAIR project]]'s paths to HLMI module also analogizes HLMI creation to radically transformative events and other technologies.
  
 
==References==
 
==References==

Latest revision as of 00:14, 12 July 2021

Reference class forecasting on human achievements uses various reference classes like "ambitious STEM technology" or "notable mathematical conjectures" to get an outside view probability of AI timelines. The Open Philanthropy report on semi-informative priors is an example of this type of forecasting.[1] This estimate might then further be adjusted according to the inputs going into AGI creation (e.g. number of researchers and amount spent on computation), as is done in the Open Philanthropy report.

MTAIR project's paths to HLMI module also analogizes HLMI creation to radically transformative events and other technologies.

References