Technical Understanding from Interactive Machine Learning Experience: a Study Through a Public Event for Science Museum Visitors

Abstract

While AI technology is becoming increasingly prevalent in our daily lives, the comprehension of machine learning (ML) among non-experts remains limited. Interactive machine learning (IML) has the potential to serve as a tool for end users, but many existing IML systems are designed for users with a certain level of expertise. Consequently, it remains unclear whether IML experiences can enhance the comprehension of ordinary users. In this study, we conducted a public event using an IML system to assess whether participants could gain technical comprehension through hands-on IML experiences. We implemented an interactive sound classification system featuring visualization of internal feature representation and invited visitors at a science museum to freely interact with it. By analyzing user behavior and questionnaire responses, we discuss the potential and limitations of IML systems as a tool for promoting technical comprehension among non-experts.

Art galleries usage of artificial intelligence

“…AI-based discovery of habitats are being embedded into museum collections (Jones et al, 2024). This enabling the use of more interactive machine learning experiences for museum visitors wanting a more technologically advanced experience (Kawabe et al, 2024). Increasingly cultural institutions including art galleries and museums are utilising specific forms of AI such as natural language processing and rule-based modelling as a way to increase visitor satisfaction (Grossmann et al, 2024).…”