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Designing for Situated AI-Human Decision Making: Lessons Learned from a Primary Care Deployment

Ben Wilson Orcid Logo, Darren Scott Orcid Logo, Matt Roach Orcid Logo, Emily Nielsen Orcid Logo, Bertie Muller

Proceedings of the 1st International Workshop on Designing and Building Hybrid Human–AI Systems (SYNERGY 2024), Arenzano (Genoa), Italy, June 03, 2024., Volume: 3701

Swansea University Authors: Ben Wilson Orcid Logo, Matt Roach Orcid Logo, Bertie Muller

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Abstract

We present a case study of AI deployment in a UK primary care (family doctor) setting. This demonstrates some of the challenges of real-world deployment of AI-human systems for decision-making. We use the seven domains of the NASSS (nonadoption, abandonment, scale-up, spread, and sustainability) fra...

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Published in: Proceedings of the 1st International Workshop on Designing and Building Hybrid Human–AI Systems (SYNERGY 2024), Arenzano (Genoa), Italy, June 03, 2024.
ISSN: 1613-0073
Published: 2024
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URI: https://cronfa.swan.ac.uk/Record/cronfa67653
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Abstract: We present a case study of AI deployment in a UK primary care (family doctor) setting. This demonstrates some of the challenges of real-world deployment of AI-human systems for decision-making. We use the seven domains of the NASSS (nonadoption, abandonment, scale-up, spread, and sustainability) framework to structure the presentation of our evaluation. We highlight three key lessons that should inform not only future deployments and evaluations, but future design work itself. The lessons are to attend to wider impacts, incorporate quality improvement and quality assurance techniques and employ participatory design, iterative development and formative evaluation.
Item Description: https://ceur-ws.org/Vol-3701/
College: Faculty of Science and Engineering

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