AI Chatbots in the Voluntary Sector: A Sociotechnical Perspective on Access, Risk, and Governance
Morovat, Mahtab (Matti) and Liang, Yin (2026) AI Chatbots in the Voluntary Sector: A Sociotechnical Perspective on Access, Risk, and Governance. In: Handbook of Human-Centric AI in Organizations. Edward Elgar Publishing. (In Press)
| Item Type: | Book Section |
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Abstract
AI adoption in the voluntary and community sector is accelerating as organisations respond to rising demand, resource constraints, and pressure to widen access to services. Chatbots can support scalable, always-available service delivery for vulnerable groups. However, their use in frontline settings raises ethical and organisational challenges where care, trust, and accountability are central. We argue that chatbot deployment should be understood as a sociotechnical problem shaped by tensions between access and risk, automation and human judgement, personalisation and privacy, and user dignity. Drawing on an integrative review of AI governance, healthcare chatbot, and nonprofit literature, alongside illustrative examples from high-stakes service contexts, the chapter identifies the structural tensions shaping design, implementation, and oversight. It then proposes a dual-loop framework linking real-time service interactions with organisational monitoring, learning, and adaptation to help operationalise ethical principles in complex service environments.
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More Information
| Additional Information: This is a draft chapter/article. The final version is available in Handbook of Human-Centric AI in Organizations edited by [insert editor(s) or author(s)], published in 20xx, Edward Elgar Publishing Ltd http://dx.doi.org/10.4337/978XXXXXXXXXX.000XX It is deposited under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way. Without limiting the author's and publisher's exclusive rights, any unauthorised use of this work to train generative artificial intelligence (Al) technologies is expressly prohibited. |
| Depositing User: Matti Morovat |
Identifiers
| Item ID: 20489 |
| URI: https://sure.sunderland.ac.uk/id/eprint/20489 |
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Catalogue record
| Date Deposited: 28 Jul 2026 09:42 |
| Last Modified: 28 Jul 2026 09:42 |
| Author: |
Mahtab (Matti) Morovat
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| Author: | Yin Liang |
University Divisions
Faculty of Business and Technology > School of Business, Management and TourismSubjects
Computing > Artificial IntelligenceSocial Sciences
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