Atkinson, David ORCID: https://orcid.org/0000-0002-2179-1652 (2026) AI, Judgement and Responsibility: Preserving Decision Authority in the Future Workforce. Other. House of Commons Business and Trade Committee Inquiry: Artificial Intelligence, Business and the Future of the Workforce, London.

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Abstract

This Written Evidence Submission to the House of Commons Business and Trade Committee Inquiry: Artificial Intelligence, Business and the Future of the Workforce, addresses Q1, Q4, Q5 and Q6 of the Call for Evidence on Artificial Intelligence, Business and the Future of the Workforce. It argues that AI is not only automating tasks but increasingly shaping how decisions are framed, which options are considered viable, and how outcomes are determined.

The primary risk is therefore not simply job displacement, but a compression of judgement: workers and managers remain accountable for decisions while operating within AI-structured environments that limit meaningful choice. This creates a growing misalignment between decision authority and decision exposure, with implications for job quality, professional judgement, and organisational risk.

AI may increase productivity, but these gains may be offset where decision-making becomes overly narrow, errors propagate quickly, and workers lose the capacity to challenge outputs. This risks forms of “brittle efficiency” that perform well under routine conditions but fail under uncertainty.

Policy should therefore shift from a primary focus on system performance to decision accountability in practice. In particular, Government should: ensure visibility of how AI-supported decisions are structured; align responsibility with genuine decision authority; strengthen education and training focused on judgement under uncertainty; support SMEs in responsible AI adoption; and redefine “human-in-the-loop” standards to require a real capacity to question and override AI outputs.

The effectiveness of AI adoption in the UK economy will depend not only on capability, but on preserving clear, accountable human judgement in AI-mediated workplaces.

Item Type:	Monograph (Other)
Status:	Published
Subjects:	H Social Sciences > H Social Sciences (General) H Social Sciences > HD Industries. Land use. Labor T Technology > T Technology (General)
School/Department:	York Business School
URI:	https://ray.yorksj.ac.uk/id/eprint/15567

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