Feedforward in Generative AI: Opportunities for a Design Space

Bibliographic Details
Title: Feedforward in Generative AI: Opportunities for a Design Space
Authors: Min, Bryan, Xia, Haijun
Publication Year: 2025
Collection: Computer Science
Subject Terms: Computer Science - Human-Computer Interaction
More Details: Generative AI (GenAI) models have become more capable than ever at augmenting productivity and cognition across diverse contexts. However, a fundamental challenge remains as users struggle to anticipate what AI will generate. As a result, they must engage in excessive turn-taking with the AI's feedback to clarify their intent, leading to significant cognitive load and time investment. Our goal is to advance the perspective that in order for users to seamlessly leverage the full potential of GenAI systems across various contexts, we must design GenAI systems that not only provide informative feedback but also informative feedforward -- designs that tell users what AI will generate before the user submits their prompt. To spark discussion on feedforward in GenAI, we designed diverse instantiations of feedforward across four GenAI applications: conversational UIs, document editors, malleable interfaces, and automation agents, and discussed how these designs can contribute to a more rigorous investigation of a design space and a set of guidelines for feedforward in all GenAI systems.
Comment: 5 pages, 3 figures
Document Type: Working Paper
Access URL: http://arxiv.org/abs/2502.14229
Accession Number: edsarx.2502.14229
Database: arXiv
More Details
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