13 citations · 38 across the 6 of their papers we have counts for
5 papers · 1 filter
Intersectional Inquiry, on the Ground and in the Algorithm
Shanthi Robertson, Liam Magee, Karen Soldatić
This article makes two key contributions to methodological debates in automation research. First, we argue for and demonstrate how methods in this field must account for intersecti…
Unmaking AI Imagemaking: A Methodological Toolkit for Critical Investigation
Luke Munn, Liam Magee, Vanicka Arora
AI image models are rapidly evolving, disrupting aesthetic production in many industries. However, understanding of their underlying archives, their logic of image reproduction, an…
Academic Institutions in Multilateral Data Governance: Emerging Arrangements for Negotiating Risk, Value and Ethics in the Big Data Economy
Tsvetelina Hristova, Liam Magee, Emma Kearney
Data sharing partnerships are increasingly an imperative for research institutions and, at the same time, a challenge for established models of data governance and ethical research…
Truth Machines: Synthesizing Veracity in AI Language Models
Luke Munn, Liam Magee, Vanicka Arora
As AI technologies are rolled out into healthcare, academia, human resources, law, and a multitude of other domains, they become de-facto arbiters of truth. But truth is highly con…
Structured Like a Language Model: Analysing AI as an Automated Subject
Liam Magee, Vanicka Arora, Luke Munn
Drawing from the resources of psychoanalysis and critical media studies, in this paper we develop an analysis of Large Language Models (LLMs) as automated subjects. We argue the in…