Accessible Contestability in Algorithm-Assisted Adult Social Care: Legal Limits and Governance Duties in Scotland after the Data (Use and Access) Act 2025

Artificial intelligence is already present in Scottish social care. Documented uses include AI-assisted transcription and assessment drafting in local-authority social work, facial-analysis tools for pain assessment in care homes, machine-learning monitoring in supported housing, and developing AI-supported referral triage. Public evidence does not yet establish the prevalence or institutional distribution of these systems. It does establish that the legal problem is current rather than hypothetical. This article argues that the principal risk is not confined to a machine taking the final decision. AI systems increasingly shape the evidential record, the classification of need, the priority assigned, and the information presented to the human decision-maker. Meaningful human involvement must therefore include verification of AI-generated records and not merely human approval of a final outcome. The Data (Use and Access) Act 2025 provides an important statutory framework through new Articles 22A to 22D of the UK GDPR. Its safeguards remain incomplete for systems that materially influence a decision while a human officer remains formally involved. Scottish adult social care provides a demanding setting in which to address that gap. It combines devolved assessment and self-directed support duties, integrated delivery, equality law, digital exclusion, complaints architecture, and decisions with immediate consequences for autonomy and daily life. The article develops an Accessible Contestability Framework that ranks each element by legal strength. Its nine elements are accessible notice, explanation sufficient for challenge, meaningful human reconsideration, record provenance and verification, correction and contextualisation of data, multi-channel access, support and advocacy signposting, complaint and redress signposting, and audit and procurement evidence. The framework is not presented as a new freestanding legal rule. It is a disciplined account of how existing legal duties and governance standards should constrain both automated decisions and AI-mediated evidential production in Scottish adult social care.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-06-28
DOI
https://doi.org/10.5281/zenodo.21012250
Primary Topic
Ethics and Social Impacts of AI
Type
preprint
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preprint

Accessible Contestability in Algorithm-Assisted Adult Social Care: Legal Limits and Governance Duties in Scotland after the Data (Use and Access) Act 2025

Nils Koesters
Zenodo (CERN European Organization for Nuclear Research)
Ethics and Social Impacts of AI
preprint

Accessible Contestability in Algorithm-Assisted Adult Social Care: Legal Limits and Governance Duties in Scotland after the Data (Use and Access) Act 2025

Nils Koesters
preprint en

Abstract

Artificial intelligence is already present in Scottish social care. Documented uses include AI-assisted transcription and assessment drafting in local-authority social work, facial-analysis tools for pain assessment in care homes, machine-learning monitoring in supported housing, and developing AI-supported referral triage. Public evidence does not yet establish the prevalence or institutional distribution of these systems. It does establish that the legal problem is current rather than hypothetical. This article argues that the principal risk is not confined to a machine taking the final decision. AI systems increasingly shape the evidential record, the classification of need, the priority assigned, and the information presented to the human decision-maker. Meaningful human involvement must therefore include verification of AI-generated records and not merely human approval of a final outcome. The Data (Use and Access) Act 2025 provides an important statutory framework through new Articles 22A to 22D of the UK GDPR. Its safeguards remain incomplete for systems that materially influence a decision while a human officer remains formally involved. Scottish adult social care provides a demanding setting in which to address that gap. It combines devolved assessment and self-directed support duties, integrated delivery, equality law, digital exclusion, complaints architecture, and decisions with immediate consequences for autonomy and daily life. The article develops an Accessible Contestability Framework that ranks each element by legal strength. Its nine elements are accessible notice, explanation sufficient for challenge, meaningful human reconsideration, record provenance and verification, correction and contextualisation of data, multi-channel access, support and advocacy signposting, complaint and redress signposting, and audit and procurement evidence. The framework is not presented as a new freestanding legal rule. It is a disciplined account of how existing legal duties and governance standards should constrain both automated decisions and AI-mediated evidential production in Scottish adult social care.

Zenodo (CERN European Organization for Nuclear Research)
Wanfang Data (China) (CN)
Reduced inequalities
Ethics and Social Impacts of AI
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