UK-Canada grant funds AI that aligns feedback with how audiences actually interpret it
_akpiper · x · 2026-11-04
An international research team won a UK–Canada "Doing AI Differently" grant for the project "What Experts Say, What People Hear: Designing AI for Audience-Centred, Value-Aligned Feedback."
- Core problem: even accurate, well-intentioned advice can fail because people interpret it through their own experiences, concerns and values; simplifying expert language is not the same as making it easier to understand or act on.
- First use case is stroke recovery, working with Cambridge University Hospitals and bringing together clinicians, patients and carers.
- The work draws on Stuart Hall's encoding/decoding theory, aiming for AI that spots where interpretations diverge and bridges the gap without sacrificing accuracy or individual agency.
- Collaborators span Cambridge, Sheffield, McGill and Alberta, illustrating how the humanities can help shape AI design rather than only study its consequences.
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