Events
Event

5th Luxembourg Workshop on AI & Epistemology

  • Location

    Maison du Nombre, room 1.010

    6, avenue de la Fonte

    4364, Esch-sur-Alzette, Luxembourg

  • Topic(s)
    Humanities
  • Type(s)
    Conferences, In-person event

The purpose of this workshop is to explore how recent advances in AI technology intersect with issues in epistemology and adjacent fields.

The workshop is organized as part of the project The Epistemology of AI Systems, generously funded by the Luxembourg National Research Fund (FNR).

To register for the workshop, please send an email at aleks.knoks@uni.lu by 20 June 2026.

Programme

Thursday, 2 July 2026

  • 09.45-11.00

    Kate Vredenburgh (LSE): Collaborating with A.I. Agents

  • 11.00-11.20

    Coffee break

  • 11.20-12.35

    Eliot du Sordet (Neuchatel): Neither World nor Text: On the Representational Targets of Preference-tuned LLMs

  • 12.35-14.00

    Lunch break

  • 14.00-15.15

    Juan Durán (Delft): Can algorithms participate in scientific knowledge? Epistemic Opacity, Algorithmic Luck, and the Orthogonality Problem in the Epistemology of Algorithms

  • 15.15-15.30

    Coffee break

  • 15.30-16.45

    Annika Schuster (Dortmund): Illusions of Objectivity in XAI

  • 16.45-17.00

    Coffee break

  • 17.00-18.15

    Alex Grzankowski (KCL): Benchmarking Intelligence Better

Friday, 3 July 2026

  • 09.45-11.00

    Johan Largo (Luxembourg): Mental Representation in LLMs?

  • 11.00-11.20

    Coffee break

  • 11.20-12.35

    Alessandro Corona Mendozza (Copenhagen): Can Sheer Stubborness Mitigate Knowledge Collapse?

  • 12.35-14.00

    Lunch break

  • 14.00-15.15

    Nina Poth (Radboud): A.I. as a Contrast Class to Human and Other Forms of Biological Cognition

  • 15.15-15.30

    Coffee break

  • 15.30-16.45

    Donal Khosrowi (Hannover): What Kind of Thing are Machine Learning Systems Like AlphaFold? And What Kinds of Things do they Produce?

  • 16.45-17.00

    Coffee break

  • 17.00-18.15

    Matthieu Queloz (Bern): How Should we Think about Machine Understanding?

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