Learning Subjective Knowledge with Designer-Like Thinking and Interactive Machine Teaching

Abstract

Aesthetics is a crucial aspect of design that plays a critical role in the creation process and customers' perception of outcomes. However, aesthetic expressions are highly subjective and nuanced. It often relies on designers' experiences and many trials and errors to get it right. Our research first investigated how designers and artists curated aesthetic materials and utilized them in their daily practice. Based on the result, we applied Langley's human-like learning framework to develop an interactive Style Agent system. It aims to learn designers' aesthetic expertise and utilize AI's capability to empower practitioner's creativity. In this paper, we used typographic posters as examples and conducted a preliminary evaluation of our prototype. The results showed that our system provided a modular structure for effortlessly annotating users' subjective perceptions and making the visualizations easy to interpret through performance. Overall, it acts as a facilitator to help enhance their own aesthetic awareness and empowers them to expand their design space.