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A conceptual framework for the ethical deployment of Artificial Intelligence in addressing mental health challenges: Guidelines for Social Workers

Author

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  • Thomas Molala

    (University of Limpopo)

  • Jabulani Makhubele

    (University of Limpopo)

Abstract

The deployment of Artificial Intelligence (AI) technologies has great potential to address mental health challenges-However there are great ethical challenges associated with AI.  Purpose of the study: This study aims to develop conceptual ethical guidelines for Social Workers using AI in tackling mental health challenges.  Methodology: The methodology employed in this paper is literature review-specifically an Integrative literature review of all sources related to the topic under investigation Main findings: The paper has found that the use of AI possesses the following ethical concerns: risk to privacy, loss of autonomy and biasness. The paper has further found that ethical guidelines for Social Workers using AI in addressing mental health challenges- should include protection laws, the use of approved AI technologies for which there are accountability standards, and training on the use of technology. Applications of this study: To this end,  these guidelines will enable Social Workers to provide ethically sound AI-driven Social Work Services in dealing mental health challenges.  Novelty/Originality of this study: Ethical concerns pertaining to the use of AI affect all helping professionals, therefore the ethical guidelines provided in this paper are expected to assist allied professionals navigate ethical paradoxes. Â

Suggested Citation

  • Thomas Molala & Jabulani Makhubele, 2021. "A conceptual framework for the ethical deployment of Artificial Intelligence in addressing mental health challenges: Guidelines for Social Workers," Technium Social Sciences Journal, Technium Science, vol. 24(1), pages 696-706, October.
    • Handle: RePEc:tec:journl:v:24:y:2021:i:1:p:696-706
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    References listed on IDEAS

    as
    1. Snyder, Hannah, 2019. "Literature review as a research methodology: An overview and guidelines," Journal of Business Research, Elsevier, vol. 104(C), pages 333-339.
    2. Effy Vayena & Alessandro Blasimme & I Glenn Cohen, 2018. "Machine learning in medicine: Addressing ethical challenges," PLOS Medicine, Public Library of Science, vol. 15(11), pages 1-4, November.
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    More about this item

    Keywords

    ethics; artificial intelligence; mental health; Social work; technologies;
    All these keywords.

    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

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