Drag or Traction: Understanding How Designers Appropriate Friction in AI Ideation Outputs
For designers using AI tools, this work identifies a new design strategy to prevent fixation and preserve user agency, but findings are preliminary due to small sample size.
This paper introduces Generative Friction, intentional disruptions in AI output (fragmentation, delay, ambiguity) to counter design fixation. In a study with six designers, high-disposition users found friction liberating, while low-disposition users experienced drag.
Seamless AI presents output as a finished, polished product that users consume rather than shape. This risks design fixation: users anchor on AI suggestions rather than generating their own ideas. We propose Generative Friction, which introduces intentional disruptions to AI output (fragmentation, delay, ambiguity) designed to transform it from finished product into semi-finished material, inviting human contribution rather than passive acceptance. In a qualitative study with six designers, we identified the different ways in which designers appropriated the different types of friction: users mined keywords from broken text, used delays as workspace for independent thought, and solved metaphors as creative puzzles. However, this transformation was not universal, motivating the concept of Friction Disposition, a user's propensity to interpret resistance as invitation rather than obstruction. Grounded in tolerance for ambiguity and pre-existing workflow orientation, Friction Disposition emerged as a potential moderator: high-disposition users treated friction as "liberating," while low-disposition users experienced drag. We contribute the concept of Generative Friction as distinct from Protective Friction, with design implications for AI tools that counter fixation while preserving agency.