Artificial intelligence and the affective labour of understanding: the intimate moderation of a language model

Carlo Perrotta, Neil Selwyn, Carrie Ewin

Research output: Contribution to journalArticleResearchpeer-review

11 Citations (Scopus)


Interest in artificial intelligence (AI) language models has grown considerably following the release of ‘generative pre-trained transformer’ (GPT). Framing AI as an extractive technology, this article details how GPT harnesses human labour and sensemaking at two stages: (1) during training when the algorithm ‘learns’ biased communicative patterns extracted from the Internet and (2) during usage when humans write alongside the AI. This second phase is framed critically as a form of unequal ‘affective labour’ where the AI imposes narrow and biased conditions for the interaction to unfold, and then exploits the resulting affective turbulence to sustain its simulation of autonomous performance. Empirically, this article draws on an in-depth case study where a human engaged with an AI writing tool, while the researchers recorded the interactions and collected qualitative data about perceptions, frictions and emotions.

Original languageEnglish
Number of pages25
JournalNew Media and Society
Publication statusAccepted/In press - 2022


  • Affect
  • artificial intelligence
  • digital literacy
  • labour
  • language models

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