Boosting user trust to increase the uptake of recommendations

Dr Shlomo Berkovsky

Macquarie University, Australia

Resumen/Abstract

The level of trust a user places in a recommender is crucial to the success of recommendations. Although prior work established various factors that build and sustain user trust, their comparative power and impact on the uptake of recommendations received less attention. We conducted a user study examining the impact of various recommendation interfaces and content selection strategies on user trust. Following this, we conducted another study that evaluated the impact of including proponents (people or avatars) in the interface. Our results can inform the design of future recommender system interfaces. Profesor proponente EPS: Iván Cantador.

Curriculum ponente

Shlomo Berkovsky is the leader of the Interactive Medical AI research stream at Macquarie University. The stream focuses on the use of Artificial Intelligence and Machine Learning methods to develop usable patient models and personalised predictions of diagnosis and care. The stream also studies how clinicians and patients interact with health technologies and how Large Language Models can improve patient care. His other areas of expertise include user modelling, online personalisation, and behaviour change technologies.