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Ethically-sound Artificial Intelligence for Potential Deployment in Social Work Education and Practice: A Global South Perspective.

Domain:

education

Record type:

paper
Creator:
Molala, ThommyZimba, Zibonele
Editor:
Pillay, Anban W.Jembere, EdgarGerber, Aurona
Publisher:
Steering Committee of the Southern African Conference for Artificial Intelligence Research, South Africa
Host:avatar

The adoption of AI technologies has been uneven between the Global South and North, with the former lagging far behind. Similarly, there has been a disproportional adoption of AI technologies among professions, with helping professions, specifically social work in the Global South also lagging far behind. However, AI technologies are susceptible to ethical risks like bias, and the violation of privacy and autonomy, among others. Thus, the Global North countries are making advances in AI ethics, while their Global South counterparts are falling behind. Without ethical guidelines for AI in the Global South countries, specifically in the profession of social work, the implementation of AI technologies may induce ethical and legal challenges. To this end, this study aims to propose the design of ethically-sound AI for deployment in social work education and practice. To do this, the study has adopted an integrative literature review methodology, which included only articles cognate and germane to AI ethics and AI in social work published in international and peer reviewed journals. The Directory of Open Access Journals, Google scholar and PubMed databases were searched using key search terms such as AI ethics, machine learning ethics, AI in social work/welfare and counselling chatbots. A total of 460 articles were found. However, only 40 (inclusive of articles identified through reference check) met the inclusion criteria and were reviewed. Consequently, the study proposed ethically-sound guidelines for AI in social work education and practice. Finally, the study recommends supporting the AI ecosystem in the Global South in order produce contextually-relevant technologies.

Visit

doi.org

Tags

Artificial Intelligence ethicssocial workmachine learning algorithms

Licenses

info:eu-repo/semantics/openAccessCreative Commons Attribution Share Alike 4.0 Internationalhttps://creativecommons.org/licenses/by-sa/4.0/legalcode

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