Abstract 

The growing importance of 'explainable AI' frameworks has recently sparked a debate about the meaning of the concepts of explanation and understanding in artificial intelligence. Although xAI was initially intended to increase user confidence, ensure regulatory compliance and promote a fair use of AI by making models more transparent, many critics have argued that intelligibility cannot be reduced to algorithmic traceability.

This workshop proposes shifting the focus from explainable AI to understandable AI, which is understood as a broader, more contextualised epistemic, ethical and social process. Bringing together researchers from philosophy, cognitive science, AI ethics and management science, the workshop will examine the conditions under which AI systems can truly be understood by their designers, users and the institutions that regulate them.

Critically, the workshop aims to provide interdisciplinary insights into key questions related to AI intelligibility. What forms of understanding are at play in human–AI interaction? How do organisational, institutional and regulatory contexts shape the production of so-called ‘understandable’ systems? Is transparency sufficient for understanding AI? Through a combination of normative and empirical approaches, the workshop will highlight the limitations of technical transparency and emphasise the importance of considering understanding as a critical, relational and contextualised relationship with artificial intelligence technologies.

Organising Committee: : Lou Safra & Léa Antonicelli (CEVIPOF)

• Date: 5 december 2025 (14h30) 
• Venue: Sciences Po, 1 place Saint-Thomas d’Aquin, 75007 Paris (K008)
• Format: Hybrid (in person and online) 

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Zoom access

Program 

• Christophe Denis, Sorbonne Université | Institut de recherche pour le développement ;
  Unité Mixte internationale de Modélisation Mathématique et Informatique de Systèmes Complexes
  From explainability to meaning-making: towards a hybrid and semiotic intelligibility of AI
• Thomas Souverain, CEA-Saclay, ENS Ulm & Sorbonne Paris XIII
  Explaining AI in Three Dimensions: A Philosopher’s Perspective
• Léa Antonicelli, CEVIPOF - Sciences Po
  Leveraging psychology to promote responsible AI: the case of information about training set
• Ahmad Aidar, Institut Louis Bachelier.
  Responsible AI is not only good governance, it is good business!
• Théophile Pénigaud de Mourgues, CEVIPOF (Sciences Po), Yale's Institution for
  Social and Policy Studies
  How Generative AI Threatens Public Reason and Accountability