UCLIC Research Seminar Series
For those attending online, please use the following link: ucl.zoom.us/j/95024123695
Engaging end user groups with machine learning (ML) models can help align the design of predictive systems with people's needs and expectations. In this talk, I will present a co-design study  investigating the benefits and challenges of using computational notebooks to inform ML models with end user groups. We used computational notebooks to engage young adults, carers, and clinicians with an example ML model that predicted health risk in diabetes care. Through co-design workshops and retrospective interviews, we found that participants particularly valued using the interactive data visualisations of the computational notebooks to scaffold multidisciplinary learning, anticipate benefits and harms of the example ML model, and create fictional feature importance plots to highlight care needs. Participants also reported challenges, from running code cells to managing information asymmetries and power imbalances. Based on this understanding, I will discuss the potential of leveraging interactive technologies, such as computational notebooks, as co-design tools to meet end user needs early in ML model lifecycles.
 Amid Ayobi, Jacob Hughes, Christopher J Duckworth, Jakub J Dylag, Sam James, Paul Marshall, Matthew Guy, Anitha Kumaran, Adriane Chapman, Michael Boniface, and Aisling Ann O'Kane. 2023. Computational Notebooks as Co-Design Tools: Engaging Young Adults Living with Diabetes, Family Carers, and Clinicians with Machine Learning Models. CHI'23, Preprint: discovery.ucl.ac.uk/id/eprint/10166134
Dr Amid Ayobi is a Lecturer in Digital Health in the Department of Computer Science at University College London and is part of the UCL Interaction Centre. His research aims to inform the design of agency supportive digital health technologies.
He completed his PhD studies at UCLIC focusing on self-tracking practices by people living with multiple sclerosis. He investigated the digital mental health experiences of people from diverse ethnic backgrounds and health risk prediction needs of young adults living with diabetes as a postdoctoral researcher at the University of Bristol. Prior to rejoining UCLIC, he gained HCI expertise working as a lecturer at Cardiff University and R&D labs at IBM, SAP, and Microsoft.