Click the star to add/remove an item to/from your individual schedule.
You need to be logged in to avail of this functionality.

P228


Rebooting the STS programme for AI: emerging controversies and methods for studying 21st-century artificial intelligence 
Convenors:
Nicolas Chartier-Edwards (Institut National de la Recherche Scientifique)
Valentin Goujon (Sciences Po)
Jonathan Roberge (National Institute of Scientific Research, Canada)
Etienne Grenier (Institut national de la recherche scientifique)
Send message to Convenors
Discussants:
Nicolas Chartier-Edwards (Institut National de la Recherche Scientifique)
Michael Castelle (University of Warwick)
Valentin Goujon (Sciences Po)
Etienne Grenier (Institut national de la recherche scientifique)
Format:
Traditional Open Panel

Short Abstract:

The hype around neural networks reorganised the field of AI research in terms of both epistemic culture and political economy. What are the emergent controversies of the contemporary AI paradigm and how newly developed STS methodologies can benefit the rising field of critical AI studies?

Long Abstract:

There exists, in Science and Technology Studies (STS), what could be qualified as a first wave corpus of work on research in artificial intelligence (Woolgar, 1985; Collins, 1992; Forsythe, 1993; Suchman & Trigg, 1993). However, the paradigm shift from symbolic to connectionist AI — and in turn to multibillion-parameter large language models (LLMs) — has reorganized the field in terms of both epistemic culture and political economy, each of which has strongly transformed AI research practices in different and/or overlapping ways.

As new trends in synthetic data and automated dataset labeling jeopardizes the very idea of “ground truth” so crucial to traditional supervised machine learning, the dominant contemporary AI discourse is one which seeks to monopolize resources within corporations and depends on an industry-dominated gatekeeping system that redefines what is valuable in terms of research. However, this gives rise to controversies as non-profits, minority actors, and other independent research communities try to make their own statements in the field. How can we understand the alternative discourses unfortunately submerged by the narrative of the major AI research institutions?

This reactivates the need for a “strong” STS programme that studies the mutations of research practices in the field of AI: Where are contemporary AI models made, how do they come into existence and come to be deployed and dwell in societies? The recent Shaping AI international research consortium in Canada and UK/Europe has studied the connectionist paradigm through the lens of controversy analysis, but in a context of controversy attenuation, how can both classical STS methods and new digital methods open the supposed black box of neural network research? Is it possible to foster public engagement while marginalized and/or dissonant technoscientific narratives are buried so deeply that they appear resistant to classical controversy analysis?

This two-part panel will open with a conversation involving four presenters about both old and emergent controversies of the contemporary AI paradigm, followed by a second discussion on how newly developed STS methodologies can benefit the rising field of critical AI studies.

Accepted papers:

Session 1
Session 2