On November 2-3, 2017, the Future of Privacy Forum’s Research Coordination Network partnered with Facebook, Bentley University and University of Central Florida to host a workshop titled “Bridging Industry and Academia to Tackle Responsible Research and Privacy Practices”. As the title infers, the purpose of the workshop was to bring together key stakeholders from across industry, civil society, and academia to advance the privacy research agenda, focusing on topics including data analytics and privacy-preserving technologies, privacy and ethics in user research and people-centered privacy design.
As initiatives in each of these areas continue to gain considerable momentum, this was the opportune time to identify promising avenues for forming new academic and private sector collaborations. A primary goal of the workshop was to foster new collaborations and start working together to forge meaningful progress in these areas by creating possible research opportunities via “working groups”.
The 43 attendees comprised a mix from industry and academia. Organizations represented included Facebook, Microsoft, Knexus Research Corporation and Swiss Re. From the academic community, attendees included Professors of Computer Science, Law and Public Policy, Assistant Professors, and PhD/Doctoral/Graduate students from institutions such as MIT, Harvard, UC Berkley and NYU.
The workshop began with a thought provoking panel discussion with our distinguished Advisory Board members: Chris Clifton of Purdue University; Lorrie Cranor from Carnegie Mellon University; Lauri Kanerva of Facebook; Helen Nissenbaum from Cornell Tech and New York University; and Jules Polonetsky of Future of Privacy Forum. Participants then joined a working group based on the three main workshop themes mentioned above. These working groups developed concrete project ideas and developed new partnerships across disciplinary lines with the end-goal of working together to bring these project ideas to fruition.
Eight substantive themes were identified within the three main workshop topics. During working sessions, groups spent time developing a clearly defined problem statement for these identified themes. Themes and problem statements generated by the working groups included:
- Data Analytics and Privacy Preserving Technologies: Governance – Creating a risk matrix that supports a concrete governance framework for data analytics
- Data Analytics and Privacy Preserving Technologies: Outcomes Measurements – Bridging the gaps between computational privacy metrics and perceived privacy
- Differential Privacy – Towards practical deployments and interpretability of privacy guarantees
- Privacy and Ethics in User Research: Informed Consent – Models for informed consent for research at scale: Informing, consenting, and empowering users at scale
- Privacy and Ethics in User Research: Beyond IRB – Drafting clear guidelines for research that falls outside of IRBs (e.g., archived data, public data)
- Privacy and Ethics in User Research: Research Practices – Developing and distributing community norms around ethical research practices
- People-Centered Privacy Design: Understanding Users and Individual Differences – Developing better technology and policy norms to address peoples’ different perceptions and concerns?
- People-Centered Privacy Design: Rich, Complex, and Disconnected UIs –Enabling people to understand what the system knows and does, (b) enabling people to know if they should be worried, and (c) designing systems that allow people to make proactive and reactive choices about their data
The working groups plan to further develop the initial concepts created during the workshop and are expected to present concrete outcomes and deliverables at the next convening in about one year. The outcomes of this inaugural meeting will be sustained through future workshops that will be co-created by our growing community of academics and industry professionals. To learn more about this initiative, contact Margaret Honda at Future of Privacy Forum at [email protected].
This event is partially supported by National Science Foundation Grant No. 1654085. Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.