About

This project started as my thesis project, after exploring Machine Learning pre-trained models througout my Masters program at Carnegie Mellon University.

I wanted to focus on the Generative phase synthesis as a space to apply ML models to optimize work and assist Designers.

During this analysis, I asked myself how do designers generate ideas?

• What kind of methods/processes do they go through?

• Might there be an opportunity to use machine intelligence to make the process undemanding and focused on the creative instead of the time-consuming small tasks?

During the generative research phase, many participatory activities allow for collaboration between the designer and the user. During this collaboration, some of the methods may include the following: creative toolkits, design workshops, card sorting, collages, cognitive mapping, affinity diagrams, and flexible modeling, to name a few (Hanington & Martin, 2019).

Based on my experience as an interaction designer and the interviews with other professional designers, I noticed that affinity diagrams were a standard method used by all of us. Although the collaborative methods mentioned before are valuable, I wanted to concentrate on a frequent generative approach for designers to engage with (Lucero, 2015).

Thinking, of course, the AI integration with this method could enhance their sense-making and reduce time-consuming tasks, like the clustering component, and potentially generate more ideas.

“In design practice, affinity diagrams are used to analyze a design problem or create first design solutions. With a given design problem in mind, designers write down words, short sentences or make small sketches on sticky notes to stimulate diversity in ideation phases. Ideas are then clustered to identify common issues and potential solutions” (Lucero, 2015).