Human-Centered Design
Overview
This theme addresses an issue vital to developing AI for collective intelligence within every use domain: achieving successful interaction with human users. It applies methods from social and cognitive psychology and human factors to data collected from user studies of the prototypes produced by each domain-specific AI4CI Theme in order to derive human-centred design principles for effective, trustworthy AI agents that achieve behavioural change at scale within socio-technical human-AI collectives.
Case study
This theme’s case studies involve three parallel strands:
1 Bringing human-centered design considerations to the work within each of the domain-specific themes
This strand comprises participatory design methods involving academics and stakeholders prototype human-machine interfaces (HMIs) for the AI systems being developed across the Hub’s themes.
2 Developing Smart Agents that assist users in accessing, understanding, and acting on guidance derived from collective intelligence data
Data from human experiments informs a series of design iterations, focussing on factors such as accessibility, usability, and trust which are key to the adoption and continued use of new technologies.
Comparative analyses of these data reveal transfer effects between different theme settings, guiding development of demonstrators within each theme.
3 Pursuing fundamental questions related to understanding and managing “tipping points” in collective intelligence systems.
Testable predictions of how to identify and influence tipping point thresholds for behaviour change are derived from data based on the perceived capability of the system.
Combining the three strands ensures that research in each domain translates into usable, trustworthy demonstrator systems supported by insights into smart agent adoption, and that methods for anticipating and influencing collective change inform interaction design principles for practitioners across multiple socio-technical domains.