Design Principles for Generative AI Applications

Generative AI applications present unique design challenges. As generative AI technologies are increasingly being incorporated into mainstream applications, there is an urgent need for guidance on how to design user experiences that foster efective and safe use. We present six principles for the design of generative AI applica­ tions that address unique characteristics of generative AI UX and ofer new interpretations and extensions of known issues in the design of AI applications. Each principle is coupled with a set of design strategies for implementing that principle via UX capabil­ ities or through the design process. The principles and strategies were developed through an iterative process involving literature review, feedback from design practitioners, validation against realworld generative AI applications, and incorporation into the design process of two generative AI applications. We anticipate the princi­ ples to usefully inform the design of generative AI applications by driving actionable design recommendations.

Introduction. Generative AI technologies have reached an infection point in consumer adoption and enterprise value, sparked by technological advancements in machine learning architectures such as GANs [56, 79], VAEs [86], and transformers [38, 170]. Models such as Style- GAN [79], GPT [20, 130, 137, 138], and Codex [28] have demon­ strated that powerful generative models can produce works at a human-like level of fdelity. Today, consumer applications such as ChatGPT1, DreamStudio2, and DALL-E3 are making these technolo­ gies widely available and setting the bar for people’s expectations of what generative AI can do. Startups such as Cohere4 and An­ thropic5 are reducing the friction of embedding large language models in consumer applications. Enterprises such as IBM, Mi­ crosoft, Amazon, and Google are creating platforms for businesses to infuse generative technologies into their products and services.

Discussion / Conclusion. We identifed a set of six principles important to the design of gen­ erative AI applications, along with a companion set of 24 strategies for implementing those principles within a user experience. These principles were developed iteratively using a combination of criti­ cal conceptual analyses (to ensure scientifc validity) and empirical work (to ensure real-world utility). We conclude that the principles and strategies form a toolbox that design practitioners can use holistically or selectively as they craft user experiences for generative AI applications. Design prac­ titioners know their users and their needs best – exemplifed by Use a human-centered approach – and it is our hope that we have provided useful vocabulary for them to understand and design for the new and diferent kinds of uses that generative AI systems ofer. We developed a set of six principles for the design of applications that incorporate generative AI technologies. Three principles – De­ sign Responsibly, Design for Mental Models, and Design for Appropriate Trust & Reliance – ofer new interpretations of known issues with the design of AI systems when viewed through the lens of generative AI.