COMPAIN PROJECT

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Online Lecture Series

The COMPAIN research group invites scholars and the wider public to join a conversation on the complexity of pain and its ethical dimensions. To foster this exchange, we are launching the COMPAIN Lecture Series for the winter semester of 2025, featuring talks dedicated to pain-related themes from philosophical, medical, and interdisciplinary perspectives.

To participate in the lecture series, use the following Zoom link:
https://uni-ms.zoom-x.de/j/2720643197?omn=62804254235

20 November 2025 (12:00-13:30 CET / 19:00-20:30 CST)
Saulius Geniusas (The Chinese University of Hong Kong)
Title: Pain and the life-world: Somatization and psychologization

27 November 2025 (12:00-13:30 CET / 19:00-20:30 CST)
Hadeel Naeem (FAU Erlangen-Nürnberg)
Title: Pain, epistemic injustice, and AI

12 December 2025 (08:30-10:20 CET / 15:30-17:20 CST)
Philip Gerrans (The University of Adelaide)
Title: Pain, suffering, and the self

15 January 2025 (12:00-13:30 CET / 19:00-20:30 CST)
Dieter Birnbacher (Heinrich Heine University Düsseldorf)
Title: Pain, suffering, and the will

29 January 2026 (12:00-13:30 CET / 19:00-20:30 CST)
Kevin Reuter (University of Gothenburg)
Title: The complexity of the concept of pain

12 February 2026 (12:00-13:30 CET / 19:00-20:30 CST)
Noelia Bueno-Gómez (University of Oviedo)
Title: The pathologization of suffering and pain

Everyone’s welcome to attend.
If you have any questions, feel free to contact Dominik Koesling.
[email protected]

Newly Published Research Article

AI and the Complexity of Pain
(Philosophy & Technology)

Hadeel Naeem

Abstract
Pain is a complex, multidimensional phenomenon. Pain research documents cases where our disregard of diverse pain experiences leads to epistemic injustices against those who suffer from pain. Automated pain detection technologies use limited behavioural and physiological indicators and are trained on insufficiently diverse datasets. These technologies can potentially exacerbate existing epistemic harms against pain sufferers, particularly marginalised groups. I argue that we must carefully consider the diverse presentations of pain and their neurological, biological, psychological, and social dimensions when implementing AI-based pain assessment tools. To prevent deepening epistemic injustices in pain care, we must develop AI systems by collecting diverse datasets, implementing explainable algorithms, maintaining transparency in data and algorithms, and incorporating flexibility for ongoing improvements. Preserving pain’s complexity when developing these technologies helps prevent further marginalising those who experience pain, particularly vulnerable populations.

Click here to access.