Statistics, philosophy, and health: the SMAC 2021 webconference

Savy Nicolas (), Moodie Erica Em (), Drouet Isabelle (), Chambaz Antoine (), Falissard Bruno (), Kosorok Michael R. (), Krakow Elizabeth F. (), Mayo Deborah G. (), Senn Stephen () and Mark Van der Laan ()
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Savy Nicolas: Toulouse Institute of Mathematics, University of Toulouse III and IFERISS FED 4142, University of Toulouse, Toulouse, France
Moodie Erica Em: Department of Epidemiology & Biostatistics, McGill University, Montréal, Québec, Canada
Drouet Isabelle: SND (UMR CNRS 8011), Sorbonne Université, Paris, France
Chambaz Antoine: MAP5 (UMR CNRS 8145), Université de Paris, Paris, France
Falissard Bruno: CESP, INSERM U1018, Université Paris-Saclay, Villejuif, France
Kosorok Michael R.: Department of Biostatistics and Department of Statistics and Operations Research, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
Krakow Elizabeth F.: Fred Hutchinson Cancer Research Center and University of Washington, Seattle, WA, USA
Mayo Deborah G.: Department of Philosophy, Virginia Tech, Blacksburg, VA, USA
Senn Stephen: Consultant Statistician, Edinburgh, UK
Mark Van der Laan: Division of Biostatistics, School of Public Health, University of California, Berkeley, USA

The International Journal of Biostatistics, 2023, vol. 19, issue 2, 261-270

Abstract: SMAC 2021 was a webconference organized in June 2021. The aim of this conference was to bring together data scientists, (bio)statisticians, philosophers, and any person interested in the questions of causality and Bayesian statistics, ranging from technical to philosophical aspects. This webconference consisted of keynote speakers and contributed speakers, and closed with a round-table organized in an unusual fashion. Indeed, organisers asked world renowned scientists to prepare two videos: a short video presenting a question of interest to them and a longer one presenting their point of view on the question. The first video served as a “teaser” for the conference and the second were presented during the conference as an introduction to the round-table. These videos and this round-table generated original scientific insights and discussion worthy of being shared with the community which we do by means of this paper.

Keywords: artificial intelligence; Bayesian statistics; biostatistics; causality; health; philosophy (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1515/ijb-2022-0017

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