On November 30, the FTC released a staff summary of its September 15, 2016 public workshop, Putting Disclosures to the Test.  Numerous goods and services, from home appliances to financial services, make use of disclosures to inform users of their privacy practices.  These disclosures—whether delivered offline or online, via text, video, or audio—are a key tool for consumers in learning the information they need to make informed decisions in the marketplace.  The FTC has previously issued guidance about making effective digital disclosures and mobile privacy notices.  The workshop went beyond these areas and discussed disclosures for a range of products through the lens of multiple disciplines.

The FTC workshop had nearly 1,000 attendants (including, of course, online participants).  These participants explored the following topics:

Disclosure effectiveness.  A large portion of the workshop was devoted to discussion of how to make disclosures most effective.  In the first panel of the day, researchers presented multiple frameworks for assessing disclosure effectiveness drawn from cognitive science and other disciplines.  A number of traits have an impact on the effectiveness of disclosures, including attention, motivation, attitude, and risk tolerance.  Subsequent panels focused on some of these issues in particular, with a panel each devoted to attention, comprehension, and impact on decision-making and behavior.

Case studies.  In another panel, four researchers presented case studies relating to advertising disclosures, drug package labels, and study consent forms.  These studies were performed using different methodologies, and panelists discussed the tradeoffs in their methods and the wide variety of circumstances in which disclosures are used.

Looking toward the future.  The final panel of the workshop presented new approaches and applications to disclosure design.  Proposals ranged from shortening informed consent disclosures for medical studies based on feedback regarding what participants find most important, to a mobile phone app that would use machine learning to predict what types of permissions the user would allow, ultimately enabling the device to ask for permission to access sensitive data less frequently.  While noting that these proposals may raise legal and ethical issues, presenters also noted that these approaches could reduce the burden on users to read and manage disclosures and choices, and therefore increase the likelihood that users will pay attention to the information that is most important to their situation.