Drag or Traction: Understanding How Designers Appropriate Friction in AI Ideation Outputs

TL;DR

This paper introduces Generative Friction, a method of intentionally disrupting AI outputs to foster human creativity and reduce design fixation, supported by a qualitative study on designer interactions.

Contribution

It conceptualizes Generative Friction as a novel approach to enhance human-AI collaboration by transforming AI outputs into semi-finished materials for creative input.

Findings

Designers mined keywords from broken text to generate ideas.

Delays served as a workspace for independent thought.

Friction disposition influences whether users find friction liberating or obstructive.

Abstract

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.