Work

Generalization—a key challenge for responsible AI in patient-facing clinical applications

Year: 2024

Type: article

Abstract: Generalization – the ability of AI systems to apply and/or extrapolate their knowledge to new data which might differ from the original training data – is a major challenge for the effective and responsible implementation of human-centric AI applications. Current debate in bioethics proposes selective prediction as a solution. Here we explore data-based reasons for generalization challenges and look at how selective predictions might be implemented technically, focusing on clinical AI applications in real-world healthcare settings.

Source: npj Digital Medicine

DOI: 10.1038/s41746-024-01127-3

Authors: Lea Goetz, Nabeel Seedat, Robert Vandersluis, Mihaela van der Schaar

Institutions: GlaxoSmithKline (United Kingdom), University of Cambridge, Cambridge Centre for AI in Medicine

Language: English

Topic: Artificial Intelligence in Healthcare and Education

Subfield: Health Informatics

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $3,790