Presentation

The achievements of modern machine learning (ML) methods highlight the enormous potential of integrating artificial intelligence systems in various areas of medicine, from diagnostic image analysis in radiology and dermatology to increasingly complex applications such as predictions in intensive care units or diagnosis of psychiatric disorders.

However, many medical professionals are still skeptical about integrating machine learning tools into their practices. The reasons are mainly related to the problem of opacity, or the "black box," which refers to the difficulty for humans to understand the reasoning behind the results of Machine Learning models and ultimately decide whether or not to trust them.

In recent years, efforts have been made to overcome this difficulty both from policy and ethical perspectives and from engineering and design perspectives.

The purpose of the meeting, organized in Lugano on Nov. 2 and 3, 2023 by the Dalle Molle Institute for Artificial Intelligence (IDSIA USI-SUPSI) in collaboration with EPFL's College of Humanities and University of Zurich's Digital Society Initiative, is to bring together experts from different disciplines such as philosophy, bioethics, AI ethics, XAI, and human-computer interaction to discuss whether, how, and to what extent proposed solutions to the black box problem are effective in supporting the successful integration and appropriation of artificial intelligence systems into medical practice.

The event is funded by the Swiss National Science Foundation (SNSF).

Information and registration

More information about the program, speakers and registration can be found on the event website.