User-centred design actions for lightweight evaluation of an interactive machine learning toolkit

• Autor(a) principal: Bernardo, Francisco
• Data de Publicação: 2018
• Outros Autores: Grierson, Mick, Fiebrink, Rebecca
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: https://doi.org/10.7559/citarj.v10i2.509

Machine learning offers great potential to developers and end users in the creative industries. For example, it can support new sensor-based interactions, procedural content generation and end-user product customisation. However, designing machine learning toolkits for adoption by creative developers is still a nascent effort. This work focuses on the application of user-centred design with creative end-user developers for informing the design of an interactive machine learning toolkit. We introduce a framework for user-centred design actions that we developed within the context of an European Union innovation project, RAPID-MIX. We illustrate the application of the framework with two actions for lightweight formative evaluation of our toolkit—the JUCE Machine Learning Hackathon and the RAPID-MIX API workshop at eNTERFACE’17. We describe how we used these actions to uncover conceptual and technical limitations. We also discuss how these actions provided us with a better understanding of users, helped us to refine the scope of the design space, and informed improvements to the toolkit. We conclude with a reflection about the knowledge we obtained from applying user-centred design to creative technology, in the context of an innovation project in the creative industries.