Till startsida
Webbkarta
Till innehåll Läs mer om hur kakor används på gu.se

Kalendarium


FLOV och SOCAV STS seminarium: The Politics of Algorithms: The rise of digital risk prediction

Seminarium


With this development algorithms, machine learning, and computerized statistics become tools not only to assess risks on the population level, but also bring these calculated risk assessments to bear on individuals. Algorithmic systems thus increasingly produce social facts: and people are compelled to accept, challenge, account for, or in other ways relate to these algorithmic classifications.

This paper discusses these developments as challenges for sociological inquiry. How should sociology approach the increasing encroachment of algorithms and big data into the making of social facts? How do we do sociology where we are increasingly becoming quantified, classified, and valued by algorithmic systems? Departing from a few examples of algorithmic risk prediction the paper discusses theoretical and methodological consequences of the algorithmization of society for sociological inquiry.

Francis Lee is Associate Professor in Technology and Social Change currently hosted by the Department of History of Science and Ideas and affiliated with the Department of Sociology at Uppsala University. Together with Shai Mulinari, he was newly awarded SEK 6 million within the Wallenberg AI, Autonomous Systems and Software Program - Humanities and Society (WASP-HS).

For more information on Francis see:
https://wasp-hs.org/people/francis-lee
http://francislee.org"/>

Today, algorithms and so-called "Big Data" systems are increasingly producing a plethora of social facts that shape our social lives in profound ways. For instance algorithms are increasingly used to identify risks in society. Today, they are used for things ranging from predicting natural catastrophes, like earthquakes or pandemics, to predict who is a risky person, such as a gambling addict, a loan applicant, a tax-cheater, an AIDS patient, or indeed a migrant suspected of lying about their age.

With this development algorithms, machine learning, and computerized statistics become tools not only to assess risks on the population level, but also bring these calculated risk assessments to bear on individuals. Algorithmic systems thus increasingly produce social facts: and people are compelled to accept, challenge, account for, or in other ways relate to these algorithmic classifications.

This paper discusses these developments as challenges for sociological inquiry. How should sociology approach the increasing encroachment of algorithms and big data into the making of social facts? How do we do sociology where we are increasingly becoming quantified, classified, and valued by algorithmic systems? Departing from a few examples of algorithmic risk prediction the paper discusses theoretical and methodological consequences of the algorithmization of society for sociological inquiry.

Francis Lee is Associate Professor in Technology and Social Change currently hosted by the Department of History of Science and Ideas and affiliated with the Department of Sociology at Uppsala University. Together with Shai Mulinari, he was newly awarded SEK 6 million within the Wallenberg AI, Autonomous Systems and Software Program - Humanities and Society (WASP-HS).

For more information on Francis see:
https://wasp-hs.org/people/francis-lee
http://francislee.org

Föreläsare: Francis Lee, History of Science & Ideas, Uppsala University

Datum: 2019-10-18

Tid: 13:15 - 15:00

Kategorier: Samhällsvetenskap

Plats: F 417

Kontaktperson: Elena Bogdanova

Sidansvarig: Lars-Olof Karlsson|Sidan uppdaterades: 2011-12-21
Dela:

På Göteborgs universitet använder vi kakor (cookies) för att webbplatsen ska fungera på ett bra sätt för dig. Genom att surfa vidare godkänner du att vi använder kakor.  Vad är kakor?