collaboration

AI-Human Collaboration: From Quant to Qual, Turning Data into Meaning

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Written by Paulina Bondaronek and Siobhán Healy-Cullen

Image depicting AI-Human collab created using rather primitive prompting in Ideogram.

Machine-assisted topic analysis (MATA) aims to use the efficiency of Artificial Intelligence and combines it with the nuanced and rich insights derived from qualitative analysis. I call this a “meaningful AI-Human collaboration”. MATA was developed in response to a significant challenge during the COVID-19 pandemic; I was tasked with analysing and providing actionable insights based on 16,000 free-text responses to the question “How could we improve the service” (rapidly). The service in question was the NHS Test & Trace, which managed the pandemic response in England. With only my eyeballs to rely on (…and my expertise as a Behavioural Scientist), I recognised the potential of technology to speed up this task.

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Psychology’s participatory problem and five things you can do right now to fix it!

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By Brett Scholz

couple holding hands
Photo by Marcus Aurelius on Pexels.com

Critical health psychologists generally want to practice acts of allyship through and beyond their work. In this post, Brett Scholz presents a call to go beyond thinking of consumers as participants in your research practice, and to instead ensure you collaborate and engage with consumers in epistemic practices. 

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