Introduction

“Cloaked consent,” the practice of gaining consent through deception and manipulative design patterns, is a common practice embedded in the technical landscape.¹ In 2013, TouchID came to iPhone users as a breakthrough in an effortless, password-absent future.² Six years later, the use of biometrics has fully integrated into consumer products, services, and even family vacations.³ With the turn of the 2010s, AI-powered facial recognition arrived at doorbell cameras and airport terminals, ushering in an array of opaque data practices with AI-based tooling.⁴ At the center of these innovations, standards for transparency are absent, leading to distrust, lack of understanding, and loss of autonomy.⁵

Transparency is a powerful lever for consumer education at scale, which is evidenced through the ubiquity of Food and Drug Administration (FDA) nutrition labels. Of respondents interviewed for this report, 95 percent read FDA nutrition labels ‘every’ or ‘most of the time’ and look to them for information on components (e.g., ingredients or materials), potential harms of use (e.g., allergens or toxicity), and provenance. With 91 percent of consumers (97 percent for those ages 18–34) skipping over data and privacy policies due to lack of accessibility, consumers then lack understanding of the tools they use. This is further exacerbated by emergent technologies like generative AI.⁶ By not creating a transparent design system for communicating policies and appropriate uses for generative AI tools, global consumers will experience a wider digital divide, an eroded national security landscape, and continued propagation of misinformation. This research proposes a label for generative AI tools based in universal design to provide consumers accessible information on generative AI tool functionality, potential harms of use, and available data protection policies.