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. 2020 Dec;22(2):71-74.

Participatory Machine Learning Using Community-Based System Dynamics

Vinodkumar Prabhakaran  1 , Donald Martin Jr  2
Affiliations

Participatory Machine Learning Using Community-Based System Dynamics

Vinodkumar Prabhakaran et al. Health Hum Rights. 2020 Dec.
No abstract available

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Conflict of interest statement

Competing interests: None declared.

References

    1. Wang F., Preininger A. “AI in health: State of the art, challenges, and future directions,”. Yearbook of Medical Informatics. 2019;28(1):16. - PMC - PubMed
    1. Raso F. A., Hilligoss H., Krishnamurthy V. Berkman Klein Center Research Publication; 2018. “Artificial intelligence and human rights: Opportunities and risks,”. 2018-6.
    1. Obermeyer Z., Powers B., Vogeli C., Mullainathan S. “Dissecting racial bias in an algorithm used to manage the health of populations,”. Science. 2019;366(6464):447–453. - PubMed
    1. Martin Jr. D., Prabhakaran V., Kuhlberg J. “Extending the machine learning abstraction boundary: A Complex systems approach to incorporate societal context,”. 2020. arXiv:2006.09663.
    1. Martin Jr. D., Prabhakaran V., Kuhlberg J. “Participatory problem formulation for fairer machine learning through community based system dynamics,”. 2020. ICLR Workshop on Machine Learning in Real Life, April 26.

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