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“I don’t think people are ready to trust these algorithms at face value”: trust and the use of machine learning algorithms in the diagnosis of rare disease by Nina Hallowell; Shirlene Badger; Aurelia Sauerbrei; Christoffer Nellåker; Angeliki Kerasidou is a Medicine article available to read on EtoBox.

What is “I don’t think people are ready to trust these algorithms at face value”: trust and the use of machine learning algorithms in the diagnosis of rare disease about?

## Abstract ## Background As the use of AI becomes more pervasive, and computerised systems are used in clinical decision-making, the role of trust in, and the trustworthiness of, AI tools will need to be addressed. Using the case of computational phenotyping to support the diagnosis of rare disease in dysmorphology, this paper explores under what conditions we could place trust in medical AI tools, which employ machine learning. ## Methods Semi-structured qualitative interviews (n = 20) with stakeholders (clinical geneticists, data scientists, bioinformaticians, industry and patient support group spokespersons) who design and/or work with computational phenotyping (CP) systems. The method of constant comparison was used to analyse the interview data. ## Results Interviewees emphasized the importance of establishing trust in the use of CP technology in identifying rare diseases. Trust was formulated in two interrelated ways in these data. First, interviewees talked about the importance of using CP tools within the context of a trust relationship; arguing that patients will need to trust clinicians who use AI tools and that clinicians will need to trust AI developers, if they are to

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Author

Nina Hallowell; Shirlene Badger; Aurelia Sauerbrei; Christoffer Nellåker; Angeliki Kerasidou

Publisher

Springer Science and Business Media LLC

Published

2022

Language

EN

Field

Medicine (Health Sciences)