Concordance as evidence in the Watson for Oncology decision-support system

Show simple item record Tupasela, Aaro Di Nucci, Ezio 2020-12-23T15:59:01Z 2020-12-23T15:59:01Z 2020-12
dc.identifier.citation Tupasela , A & Di Nucci , E 2020 , ' Concordance as evidence in the Watson for Oncology decision-support system ' , AI & Society , vol. 35 , no. 4 , pp. 811-818 .
dc.identifier.other PURE: 131328739
dc.identifier.other PURE UUID: dcf411a0-80fe-449a-8c81-f477eb316fa9
dc.identifier.other WOS: 000510371200001
dc.description.abstract Machine learning platforms have emerged as a new promissory technology that some argue will revolutionize work practices across a broad range of professions, including medical care. During the past few years, IBM has been testing its Watson for Oncology platform at several oncology departments around the world. Published reports, news stories, as well as our own empirical research show that in some cases, the levels of concordance over recommended treatment protocols between the platform and human oncologists have been quite low. Other studies supported by IBM claim concordance rates as high as 96%. We use the Watson for Oncology case to examine the practice of using concordance levels between tumor boards and a machine learning decision-support system as a form of evidence. We address a challenge related to the epistemic authority between oncologists on tumor boards and the Watson Oncology platform by arguing that the use of concordance levels as a form of evidence of quality or trustworthiness is problematic. Although the platform provides links to the literature from which it draws its conclusion, it obfuscates the scoring criteria that it uses to value some studies over others. In other words, the platform "black boxes" the values that are coded into its scoring system. en
dc.format.extent 8
dc.language.iso eng
dc.relation.ispartof AI & Society
dc.rights cc_by
dc.rights.uri info:eu-repo/semantics/openAccess
dc.subject 113 Computer and information sciences
dc.subject Artificial intelligence
dc.subject CANCER
dc.subject Clinical trials
dc.subject Decision support
dc.subject IBM
dc.subject Machine learning
dc.subject Oncology
dc.subject Watson for Oncology
dc.title Concordance as evidence in the Watson for Oncology decision-support system en
dc.type Article
dc.contributor.organization Academic Disciplines of the Faculty of Social Sciences
dc.description.reviewstatus Peer reviewed
dc.relation.issn 0951-5666
dc.rights.accesslevel openAccess
dc.type.version publishedVersion

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