Ideally, conversational agents should be able to adapt to human users. However, state-of-the-art AI systems currently lack sophisticated adaptation capabilities. Our long-term goal is to develop artificial agents that can adapt to individuals/user groups at any level (age, expertise, language style, etc.) and that are perceived as trustable by users. The current project focuses on users of different age groups. This is important because conversational agents, such as the ones used in health care, should be appropriate for younger as well as older adults. The project answers the questions: (1) Can some degree of adaptation be achieved by training a state-of-the-art system with data targeted to specific age groups? (2) Does this lead to differences in the perceived degree of anthropomorphism, social presence, trust, appreciation and comprehensibility of the message? The project We will implement an open-source demo showcasing the results of the project, and findings will also be disseminated through blog posts and a hands-on workshop.
Research team:
- Margot van der Goot
- Raquel Fernández (Faculty of Science)
- Sandro Pezzelle (Faculty of Science)
Status: Ongoing since 1 January 2021
Funding: RPA Human(e) AI
Link: Click here