Toward General Design Principles for Generative AI Applications

Abstract

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.

Typology of Risks of Generative Text-to-Image Models

“…The mechanisms for enabling participatory projects have been previously explored [16,17,25,127]. Participatory projects can involve redefining the principles of generative AI design to be more human-centric and inclusive [78,169], such as the creation of creative assistive technologies [78,121,177]. Data acquisition, a fundamental aspect of these projects, can target underrepresented or misrepresented communities to address disparities [164].…”

ChatGPT vs. Bard: A Comparative Study

“…Additionally, they may infringe upon copyrights, licenses, and intellectual property rights. The potential for misuse, including the spread of disinformation, fraud, code generation for cyberattacks, or illegitimate surveillance and censorship, must be acknowledged [153]. At the time of composing this text, a lawsuit has been filed against GitHub, Microsoft, and OpenAI concerning alleged copyright violations in the training of Codex [154].…”

“…Designers can implement preventative measures to mitigate misuse, such as watermarking generated images, using blocklists to avoid undesirable content, or requiring multiple reviews before using model outputs. However, it may be challenging to prevent intentional misuse by users [153].…”

A.I., Fashion and Rights

“…This leads to a significant paradigmatic shift in the field of design: the evolution in the generation of images and forms, especially through the use of generative algorithms, facilitates the creation of high-quality and realistic content. This evolution expands creative possibilities (Wingström et al, 2023;Miller, 2020), while simultaneously introducing new ethical and methodological challenges (Siau, K., & Wang, W.; Luce, 2019). The arrival of these new tools is redefining the relationship between design and mathematics, between project and computational geometry, paving the way for an unprecedented interaction between different disciplines.…”

“…Defining the ownership and authorship of a design created by an algorithm poses new legal challenges, necessitating updated and specific regulatory frameworks for the sector. AI-driven automation in the fashion sector also raises important questions about social impact, particularly regarding the future of work (Wingström et al, 2023) and the role AI plays in the evolution of professional skills. It is crucial to consider how AI can both replace and enhance human labor, requiring careful consideration of the social and economic implications.…”