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Emmanuel Didier

As seen in: Nature, Memory Studies, The Conversation, Issues in Science and Technology
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Articles by Emmanuel Didier

Ce que les données numériques disent de nous et du monde

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By Emmanuel Didier
| The Conversation Verified
Loin de permettre l’omniscience quant à la vie des individus, les données numériques n’offrent qu’un point de vue sur le social. Elles ressemblent en cela aux méthodes statistiques qui les ont précédées, et s’inscrivent dans une histoire longue de la collecte de connaissances sur les populations. Les traces que nous laissons lorsque nous naviguons sur Internet – nos données numériques – disent beaucoup de nous.
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The Question Isn’t Asset or Threat; It’s Oversight

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By Emmanuel Didier, Kelsey Schoenberg
| Issues in Science and Technology Verified
As part of a research group studying generative AI with France’s Académie Nationale de Médecine, I was surprised by some clinicians’ technological determinism—their immediate assumption that this technology would, on its own, act against humans’ wishes. The anxiety is not limited to physicians.
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The new watchdogs’ vision of science: A roundtable with Ivan Oransky (Retraction Watch) and Brandon Stell (PubPeer)

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By Emmanuel Didier, Catherine Guaspare-Cartron
| Memory Studies
On March 3rd, 2016, the authors of this note hosted a conference entitled ‘Destabilized Science’ at the University of California, Los Angeles, to which we invited two representatives of core actors within the new science watchdog pack: Ivan Oransky, co-founder in 2010 of Retraction Watch, and Brandon Stell, co-founder in 2012 of PubPeer. After the formal conference, we organized a roundtable to discuss these invitees’ experience and their vision of contemporary science.
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Five ways to ensure that models serve society: a manifesto

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By Andrea Saltelli, Gabriele Bammer, Erica Charters, Monica Di Fiore, Emmanuel Didier, Wendy Espeland, John Kay, Samuele Lo Piano, Deborah Mayo, Roger Pielke Jr, Theodore M. Porter, Arnald Puy, Ismael Ràfols, Jerome Ravetz, Erik Reinert, Daniel Sarewitz, Philip Stark, Andrew Stirling, Paolo Vineis Verified, Tommaso Portaluri
| Nature Verified
The COVID-19 pandemic illustrates perfectly how the operation of science changes when questions of urgency, stakes, values and uncertainty collide — in the ‘post-normal’ regime. Well before the coronavirus pandemic, statisticians were debating how to prevent malpractice such as p-hacking, particularly when it could influence policy1. Now, computer modelling is in the limelight, with politicians presenting their policies as dictated by ‘science’2.
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