Vend. 14 mai, de 12h00 à 13h30 – Présentation virtuelle. Pour plus d’infos : firstname.lastname@example.org
Conférencière invitée : Natalia Levina, Professor at the New York University Stern School of Business, and Director of the Fubon Center for Technology, Business and Innovation.
To incorporate or not to incorporate AI for critical judgments: How professionals deal with opacity using AI for medical diagnosis. Artificial intelligence (AI) technologies are promising to transform how professionals are conducting knowledge work, yet the opacity of AI tools is of growing concern, as it is difficult to understand or explain the results they produce. Organizational researchers are only starting to understand whether and how this transformation unfolds in practice. We conducted an in-depth field study in a major US hospital where AI tools were being used within three different radiology departments for forming critical judgments: breast cancer, lung cancer, and bone age. In all three departments, professionals experienced a surge in uncertainty due to the opacity of the AI tools’ results, which often conflicted with their initial diagnosis, yet provided no insight into its underlying reasoning or logic. We found that how professionals dealt with this opacity and its impact on their overall uncertainty were critical to whether and how they incorporated the AI results. Only in one department (of the three we studied), did professionals meaningfully and consistently incorporate AI results into their final judgments. This study reveals how only in this department did the AI tool’s results directly relate to professionals’ locus of uncertainty and led to developing rich interrogation practices of the opaque AI results; this way, using and incorporating the AI results reduced the overall uncertainty of forming their final judgments. Our study unpacks the challenges involved in “augmenting” professional judgment with powerful, yet opaque, technologies and contributes to literatures on opacity in AI, the adoption of new technologies, and the production of knowledge.