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DTSTAMP:20260415T185235Z
DTSTART;TZID=Europe/London:20250523T090000
DTEND;TZID=Europe/London:20250523T100000
SUMMARY:A Plea for History and Philosophy of Statistics and Machine Learning—With a Little Story of Achievabilism
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DESCRIPTION:<p>Abstract: The integration of the history and philosophy of statistics was initiated at least by Hacking (1965) and advanced by Mayo (1996)\, but it has received little sustained follow-up. Yet such integration is more urgent than ever\, as the recent success of artificial intelligence has been driven largely by machine learning&mdash\;a field historically developed alongside statistics. Today\, the boundary between statistics and machine learning is increasingly blurred. What we now need is integration on two levels: an integrated history and philosophy of an integrated field&mdash\;statistics and machine learning. I present a case study of a philosophical idea in machine learning whose roots can be traced back to an often underappreciated insight in Neyman and Pearson&rsquo\;s work of the 1930s. This leads to the articulation of a foundational assumption&mdash\;largely implicit in\, but shared by\, the practices of frequentist statistics and machine learning&mdash\;which I call achievabilism. A third integration also emerges at the level of methodology: combining formal epistemology (FE) with history and philosophy of science (HPS).</p>\n<p><br></p>\n<p>Zoom Link:</p>\n<p>https://rutgers.zoom.us/j/99554502801?pwd=rXCCcpqG9LU TdvBDaZIOqnDbp0wFS9.1</p>
ORGANIZER;CN=Qiannan Li:
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