Reference class forecasting on human achievements argument for AI timelines

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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.