Work

Benchmarking bias: Expanding clinical AI model card to incorporate bias reporting of social and non-social factors

Year: 2023

Type: preprint

Abstract: Clinical AI model reporting cards should be expanded to incorporate a broad bias reporting of both social and non-social factors. Non-social factors consider the role of other factors, such as disease dependent, anatomic, or instrument factors on AI model bias, which are essential to ensure safe deployment.

Source: arXiv (Cornell University)

DOI: 10.48550/arxiv.2311.12560

Authors: Heming, Carolina A. M., Abdalla, Mohamed, Mohanna, Shahram, Ahluwalia, Monish, Zhang, Linglin, Trivedi, Hari, Woo, MinJae, Fine, Benjamin, Gichoya, Judy Wawira, Celi, Leo Anthony, Seyyed-Kalantari, Laleh

Institutions: University of Iowa, University of Alberta, Trillium Health Centre, York University, Queen's University, Kingston Health Sciences Centre, Kennesaw State University, Emory University, Harvard University, Massachusetts Institute of Technology, Vector Institute

Language: English

Topic: Ethics and Social Impacts of AI

Subfield: Safety Research

Field: Social Sciences

Domain: Social Sciences

SDG: Good health and well-being

Open Access status: green

Funders: Canada First Research Excellence Fund, Natural Sciences and Engineering Research Council of Canada, National Institute of Biomedical Imaging and Bioengineering

Awards: G7075035638, G7597440964

OpenAlex ID: W4388927925

Cites:

Cited by: 4

Related to: 10