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Beyond the artifact: AI and the future of research

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Presentation

PRS Annual Conference 2026 · Physiotherapy Research Society · 24 April 2026

Keynote presentation

Overview

A keynote for the 44th Annual Conference of the Physiotherapy Research Society, themed “Beyond the Dataset: Engaging People, Powering Change.”

The argument starts from first principles: research exists to help us better understand the world, and everything else — journals, theses, peer review, assessment systems — is infrastructure. AI is now in contact with every part of that ecosystem: doing research, learning about research, engaging with research, and shaping the platforms around it. The central question is therefore not whether AI is being used, but what it is being used for.

The keynote moves through four stages:

  • How AI has broken the inferential chain between research artefacts and the processes they were meant to evidence; “fluency used to be signal; now it is noise”
  • The PhD as a worked example: the thesis is the artefact, the researcher is the product, and AI can now execute much of the work through which researchers have traditionally formed their expertise
  • What disciplined use of AI in research actually requires: planning before handoff, documentation as infrastructure, and protecting evaluative judgement
  • What becomes more valuable as execution becomes cheap: research taste, evaluative judgement, and the capacity to set direction and take responsibility for consequences

The session closes with a diagnostic rather than a rule: when AI accelerates understanding, it serves the purpose; when it accelerates output, it serves the infrastructure.

Slides

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  • Research taste

    Research taste is the cultivated capacity to recognise which problems are worth pursuing, which collaborators will amplify your work, and which under-explored areas have genuine leverage — before you can fully prove any of those judgements.

  • The PhD is a process of becoming: Reimagining AI and PhD assessment

    AI has disrupted doctoral education in two ways: the immediate question of AI-assisted writing, and the deeper question of what the PhD means when AI can conduct research from scratch. This post argues that the thesis was always a proxy for the person; evidence of an identity shift, not the thing being assessed in its own right.

  • Research industrial complex

    The research industrial complex describes the self-reinforcing system of incentives across universities, funding bodies, journals, and publishers that rewards publication volume and impact metrics over meaningful scientific progress. The term draws on Eisenhower's military-industrial complex to highlight how interconnected institutional interests can sustain a system that actively works against its own stated mission.

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