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Bias in AI algorithms could be mitigated by implementing new checklist

06.22.23 | PLOS

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In your coverage, please use this URL to provide access to the freely available article in 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 Countries : Jordan, United States, Canada

Funding: The authors received no specific funding for this work.

PLOS Digital Health

10.1371/journal.pdig.0000278

Commentary/editorial

Not applicable

Competing interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: Janny Xue Chen Ke: received salary support as Clinical Data Lead, St. Paul’s Hospital, Canada, for Project “Reducing Opioid Use for Pain Management” from Canadian Digital Technology Supercluster and Consortium (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 Community LLC. Piyush Mathur: Founder of BrainX LLC. & BrainX Community LLC.

Keywords

Article Information

Contact Information

Charlotte Bhaskar
PLOS
onepress@plos.org

How to Cite This Article

APA:
PLOS. (2023, June 22). Bias in AI algorithms could be mitigated by implementing new checklist. Brightsurf News. https://www.brightsurf.com/news/1EOGQ65L/bias-in-ai-algorithms-could-be-mitigated-by-implementing-new-checklist.html
MLA:
"Bias in AI algorithms could be mitigated by implementing new checklist." Brightsurf News, Jun. 22 2023, https://www.brightsurf.com/news/1EOGQ65L/bias-in-ai-algorithms-could-be-mitigated-by-implementing-new-checklist.html.