Yue Zhang

Improve Perceived Trustworthiness and Fairness in Automated Decision-Making: The Role of Mental Models

Project Summary

My research aims to improve efficiency and trustworthiness in AI-augmented decision-making by investigating the role of mental models. In cognitive psychology, mental models refer to representations of how a person interacts with the system. An ideal mental model helps people to understand the purpose of the system and the way the system functions, also allows users to predict possible behaviours of a system, hence facilitates interactions. As collective decision-making with AI will become more ubiquitous in various fields, building a suitable mental model of the AI is important to improve people’s trust in decisions made by algorithms and build conversational AI agents. The research will also investigate how human decision-makers interact with AI. For instance, when to trust and distrust decisions produced by algorithms? How to help users draw a clear error boundary of the AI decision system? The hope is that the results will improve trust and adoption in AI decision support systems. 

Research Interests

AI and decision-making. 

Human centered AI. 

Human computer interactions. 

Behavioural economics. 

Background

BSc in Psychology, University of Bristol.

MSc in Applied Psychology and Economic Behaviour, University of Bath.

Two years working in consultancy and media planning. 

Supervisors

Dr Janina Hoffmann 

Yue Zhang