Fig. 1. Seven principles for the design of generative AI systems. Six of these principles are presented in overlapping circles, indicating their relationships to each other. One principle stands alone, the directive to design against potential harms that may be caused by a generative model's output, misuse, or other harmful effects. These principles are bounded in an environment of generative variability, in which the outputs of a generative AI application may vary in quantity, quality, character, or other characteristics.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.CCS Concepts: • Human-centered computing → HCI design and evaluation methods; Interaction paradigms; HCI theory, concepts and models.