Marion Korosec-Serfaty

Assistant Professor in IT - Human–AI Interaction & NeuroIS Researcher

Explainable AI in collaborative decision-making


Conference paper


Marion Korosec-Serfaty, Sylvain Sénécal, Pierre-Majorique Léger
5th International Neuroergonomics Conference, 2024, pp. 375-382

View PDF
Cite

Cite

APA   Click to copy
Korosec-Serfaty, M., Sénécal, S., & Léger, P.-M. (2024). Explainable AI in collaborative decision-making. In 5th International Neuroergonomics Conference (pp. 375–382).


Chicago/Turabian   Click to copy
Korosec-Serfaty, Marion, Sylvain Sénécal, and Pierre-Majorique Léger. “Explainable AI in Collaborative Decision-Making.” In 5th International Neuroergonomics Conference, 375–382, 2024.


MLA   Click to copy
Korosec-Serfaty, Marion, et al. “Explainable AI in Collaborative Decision-Making.” 5th International Neuroergonomics Conference, 2024, pp. 375–82.


BibTeX   Click to copy

@inproceedings{korosec-serfaty2024a,
  title = {Explainable AI in collaborative decision-making},
  year = {2024},
  pages = {375-382},
  author = {Korosec-Serfaty, Marion and Sénécal, Sylvain and Léger, Pierre-Majorique},
  booktitle = {5th International Neuroergonomics Conference}
}

Abstract


In deontologically-governed professional settings, human-AI collaborative decision-making must maintain human agency, confidence, and trust. However, AI’s opacity and interactivity may influence human cognitive performance and restrain oversight. This study investigates cognitive decision-making processes and neural dynamics driving the willingness to rely on AI for decision- making and the influence of AI’s explainability on professionals’ sense of agency, confidence, trust, and subsequent willingness to rely on AI for decision-making. We used neuropsychophysiological data triangulated with behavioral and self-report measures in an ecologically-valid, deontologically-governed task. Results suggest that low AI explainability increases human confidence in their judgments and AI reasoning and a greater sense of agency. Conversely, high AI explainability generates greater trust in AI’s recommendations and a greater willingness to rely on AI for decision-making.