Connected technologies and always-on data flows are helping make today’s cities and communities more livable, productive, and sustainable. At the same time, these technologies raise concerns about individual privacy, freedom of choice, and institutional discrimination. How do we leverage the benefits of a data-rich society while giving members of our community the confidence of knowing their privacy is protected? How can we address pressing local problems — from housing to highways, potholes to policing — and deliver public services in equitable, privacy-conscious ways? Working collaboratively with public, private, academic, and civil society leaders, FPF builds tools and best practices to guide how cities and local communities collect, manage, and use personal data to improve services for individuals. A cornerstone of this work is FPF’s Civic Privacy Leaders Network, a peer network supported by the National Science Foundation that brings together privacy leaders from 30+ local governments across the U.S. and Canada to navigate emerging privacy issues, share practical guidance, and promote fair and transparent data practices. FPF’s smart communities work is led by Kelsey Finch. Visit the Smart Communities Resources web page for a comprehensive list of FPF’s ongoing work in this area.
Privacy Impact Assessment Policies Help Cities Use and Share Data Responsibly with their Communities
As the world urbanizes, local governments are turning to “Smart City” initiatives and the data they generate to more effectively manage transportation systems, support real-time infrastructure maintenance, automatically administer public services, enable transparent governance and open data, and support emergency services in public areas. Data held by public and private organizations have the potential to […]
By Gabriela Zanfir-Fortuna and Chelsey Colbert The European Data Protection Board recently published its draft Guidelines 1/2020 on processing personal data in the context of connected vehicles and mobility related applications, which are open for feedback until March 20. The EDPB writes that the main challenge for complying with European data protection and privacy laws […]
By Kelsey Finch, FPF Senior Counsel The MetroLab Network’s Annual Summit brought together an inspired group of civic, academic, industry, and nonprofit leaders to discuss the most important issues in smart cities and civic innovation. For the third year in a row, FPF partnered with MetroLab Network to promote data privacy perspectives and to advance responsible […]
Sidewalk Labs Releases Detailed Plans for Collaboration with City of Toronto on Quayside Smart City Project, Including Proposed Privacy and Data Protection Framework
By: Suzie Allen Experts Highlight Data Protection Safeguards, Opportunities, and Risks “Master Innovation and Development Plan” will be Vetted by City Residents, Officials Last week, Sidewalk Labs unveiled its proposed “Master Innovation and Development Plan” (MIDP) for Sidewalk Toronto, a project that would design a smart city district in Toronto’s Eastern Waterfront. The proposal will […]
Connected technologies and always-on data flows are helping make today’s cities and communities more livable, productive, and equitable. At the same time, these technologies raise concerns about individual privacy, autonomy, freedom of choice, and institutional discrimination. How do we leverage the benefits of a data-rich society while giving members of our community the confidence of […]
One of FPF Policy Counsel Kelsey Finch’s areas of focus is Smart Communities, a field which draws from many of FPF’s issue areas. From her Seattle office, she has the opportunity to do hands-on work with cities in the Pacific Northwest. Last year, she worked with city officials on Seattle’s first Open Data Risk Assessment, […]
Data-driven and evidence-based social policy innovation can help governments serve communities better, smarter, and faster. Integrated Data Systems (IDS) use data that government agencies routinely collect in the normal course of delivering public services to shape local policy and practice. They can use data to evaluate the effectiveness of new initiatives or bridge gaps between public services and community providers.
Future of Privacy Forum and Actionable Intelligence for Social Policy Release ‘Nothing to Hide: Tools for Talking (and Listening) About Data Privacy for Integrated Data Systems’
Washington, DC – Today, Future of Privacy Forum and Actionable Intelligence for Social Policy released Nothing to Hide: Tools for Talking (and Listening) About Data Privacy for Integrated Data Systems. Nothing to Hide provides governments and their partners working to integrate data for policy and program improvement with the necessary tools to lead privacy-sensitive, inclusive engagement efforts. In addition to a narrative step-by-step guide to communication and engagement on data privacy, the toolkit is supplemented with action-oriented appendices, including worksheets, checklists, exercises, and additional resources.
FPF Publishes Report Supporting Stakeholder Engagement and Communications for Researchers and Practitioners Working to Advance Administrative Data Research
The ADRF Network is an evolving grassroots effort among researchers and organizations who are seeking to collaborate around improving access to and promoting the ethical use of administrative data in social science research. As supporters of evidence-based policymaking and research, FPF has been an integral part of the Network since its launch and has chaired the network’s Data Privacy and Security Working Group since November 2017.
This Report first describes inherent privacy risks in an open data landscape, with an emphasis on potential harms related to re-identification, data quality, and fairness. To address these risks, the Report includes a Model Open Data Benefit-Risk Analysis (“Model Analysis”). The Model Analysis evaluates the types of data contained in a proposed open dataset, the potential benefits – and concomitant risks – of releasing the dataset publicly, and strategies for effective de-identification and risk mitigation.