Bias in AI algorithms can be reduced by implementing a new checklist
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Credit: Nazer LH et al., 2023, PLOS Digital Health, CC-BY 4.0 (https://creativecommons.org/licenses/by/4.0/)
In your coverage, please use this URL to provide access to articles freely available at PLOS Digital Health: https://journals.plos.org/digitalhealth/article?id=10.1371/journal.pdig.0000278
Article title: Bias in artificial intelligence algorithms and recommendations for mitigation
Author’s Country: Jordan, United States, Canada
Funding: The authors received no specific funding for this work.
Journal
PLOS Digital Health
DOI
10.1371/journal.pdig.0000278
Research methods
Commentary / editorial
Research Subjects
Not applicable
COI statement
Competing interests: I have read the journal policy and the author of this manuscript has the following competing interests: Janny Xue Chen Ke: receiving salary support as Clinical Data Lead, St. Paul, Canada, for the Supercluster and Canadian Digital Technology Consortium “Reducing Opioid Use for Pain Management” Project (Careteam Technologies Inc, Thrive Health Inc, Excelar Technologies, Providence Health Care Ventures Inc, and Xerus Inc.). Ashish K Khanna: Founding member of BrainX LLC & BrainX LLC Community. Piyush Mathur: Founder of BrainX LLC. & BrainX Community LLC.
