Janin Koch

PhD Candidate at Aalto University

Tools for Inspiration Seeking: Raising Open Questions

An increasing trend toward the digitalization of design practice and research on tools for augmenting creativity will encourage novel ways of designing in the future. Especially, tools for collecting and interacting with digital inspirational material present great opportunities for current design practice. However, the complex nature of such highly creative practice raises new challenges and questions in relation to such developments. We present three tools for inspiration seeking as a base for discussing open questions identified in our previous work. These tools vary in their agency within current practice for seeking and interacting with digital inspirational material to allow a wider scope of analysis. We intend to use these questions to discuss future guidelines for designing such tools and systems.

Published at DIS’18 Workshop: Designing interactive systems to support and augment creativity

Paper Download: Tools for Inspiration Seeking

Design implications for Designing with a Collaborative AI

This paper proposes a framework for a collaborative designing system from an interaction design perspective. Using the agent-based model from the mixed-initiative interaction framework as a starting point, an ideal interaction scenario in a web design context is described and implications for designing collaborative systems are presented. Previous work on machine learning and artificial intelligence for interaction design has already looked at recognition of designers’ intent and combinatorial problem-solving in design. This paper, in contrast, focuses on the interaction design perspective of designing such a system, and introduces a framework that highlights requirements in this context. The framework uses the notion of task model and world model from agent-based models as a frame, and the resulting implications call for a stronger involvement of designers in the process. ”
Position paper at the AAAI Spring Symposium on Designing the User Experience of Machine Learning Systems, 2017.

Paper Download: Design implications for Designing with a Collaborative AI

Learning Layout Design: Challenges and Opportunities

This position paper discusses the use of machine learning methods in layout design. Interactive layouts are pervasive and a central part of e.g. GUIs, Web interfaces, menus and forms. They have been hard to design algorithmically because search spaces are large and multiple factors contributing to design choices. We argue that in order to touch base with real design practices, machine learning approaches should take into account the requirements posed by user-centered design. We have identified four touch points to user-centered design. For each touch point we discuss both opportunities and challenges and show results from our on-going work.

Citation: Koch, Janin, Weir, Daryl and Antti Oulasvirta. "Learning Layout Design: Challenges and Opportunities." Workshop paper CHI Conference Extended Abstracts on Human Factors in Computing Systems. ACM, 2016.

Paper Download: Learning Layout Design: Challenges and Opportunities

Imagining the future of stress therapy through a design exploration

In this paper, we present a design exploration of the domain of stress therapy, involving stress researchers and professional therapists. We address the problem of using bio-data, collected during the course of everyday live, in stress therapy. The challenge is centered on how to visualize data in a way that can be useful for therapists and patients. We present our results and reflect on our design exploration, arguing that research through design can provide useful insights in domains that are hard to access using other methods of inquiry, as well as support imagination of future scenarios.

Paper Download: Imagining the future of stress therapy through a design exploration