Toward General Design Principles for Generative AI Applications

• URL: http://arxiv.org/abs/2301.05578v1
• Date: Fri, 13 Jan 2023 14:37:56 GMT
• Title: Toward General Design Principles for Generative AI Applications
• Authors: Justin D. Weisz, Michael Muller, Jessica He, Stephanie Houde
• Abstract summary: We present a set of seven principles for the design of generative AI applications. Six principles are focused on designing for characteristics of generative AI: multiple outcomes & imperfection; exploration & control; and mental models & explanations. We urge designers to design against potential harms that may be caused by a generative model's hazardous output, misuse, or potential for human displacement.
• Score: 16.11712547530946
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Generative AI technologies are growing in power, utility, and use. As generative technologies are being incorporated into mainstream applications, there is a need for guidance on how to design those applications to foster productive and safe use. Based on recent research on human-AI co-creation within the HCI and AI communities, we present a set of seven principles for the design of generative AI applications. These principles are grounded in an environment of generative variability. Six principles are focused on designing for characteristics of generative AI: multiple outcomes & imperfection; exploration & control; and mental models & explanations. In addition, we urge designers to design against potential harms that may be caused by a generative model's hazardous output, misuse, or potential for human displacement. We anticipate these principles to usefully inform design decisions made in the creation of novel human-AI applications, and we invite the community to apply, revise, and extend these principles to their own work.

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