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This study examines the content and layout of the proposed broadband consumer disclosure labels mandated by the U.S. Federal Communications Commission (FCC). Our large-scale user study identifies key consumer preferences and comprehension factors through a two-phase survey of 2,500 broadband internet consumers. Findings reveal strong support for broadband labels, but dissatisfaction with the FCC's proposed labels from 2016. Participants generally struggled to use the label for cost computations and plan comparisons. Technical terms confused participants, but providing participants with brief education made the terms usable. Participants desired additional information, including reliability, speed measures for both periods when performance is “normal” and periods when performance is much worse than normal, quality-of-experience ratings, and detailed network management practices. This feedback informed our improved label designs that outperformed the 2016 labels in comprehension and preference. Overall, consumers valued clear pricing and performance details, comprehensive information, and an easy-to-understand format for plan comparison. Requiring broadband service providers to deposit machine-readable plan information in a publicly accessible database would enable third parties to further customize how information is presented to meet these consumer needs. Our work additionally highlights the need for user studies of labels to ensure they meet consumer demands. 

In this paper we describe the iterative evaluation and refinement of a consent flow for a chatbot being developed by a large U.S. health insurance company. This chatbot’s use of a cloud service provider triggers a requirement for users to agree to a HIPAA authorization. We highlight remote usability study and online survey findings indicating that simplifying the interface and language of the consent flow can improve the user experience and help users who read the content understand how their data may be used. However, we observe that most users in our studies, even those using our improved consent flows, missed important information in the authorization until we asked them to review it again. We also show that many people are overconfident about the privacy and security of healthcare data and that many people believe HIPAA protects in far more contexts than it actually does. Given that our redesigns following best practices did not produce many meaningful improvements in informed consent, we argue for the need for research on alternate approaches to health data disclosures such as standardized disclosures; methods borrowed from clinical research contexts such as multimedia formats, quizzes, and conversational approaches; and automated privacy assistants. 

Many websites have added cookie consent interfaces to meet regulatory consent requirements. While prior work has demonstrated that they often use dark patterns — design techniques that lead users to less privacy-protective options — other usability aspects of these interfaces have been less explored. This study contributes a comprehensive, two-stage usability assessment of cookie consent interfaces. We first inspected 191 consent interfaces against five dark pattern heuristics and identified design choices that may impact usability. We then conducted a 1,109-participant online between-subjects experiment exploring the usability impact of seven design parameters. Participants were exposed to one of 12 consent interface variants during a shopping task on a prototype e-commerce website and answered a survey about their experience. Our findings suggest that a fully-blocking consent interface with in-line cookie options accompanied by a persistent button enabling users to later change their consent decision best meets several design objectives.