About this Issue

Today’s cities and communities, and their residents, are increasingly connected. Sensor networks and always-on data flows produce new service models and analytics to make modern cities and local communities more livable, sustainable, and equitable. At the same time, connected smart city devices raise concerns about individuals’ privacy, autonomy, and freedom of choice, as well as potential discrimination by institutions.

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Working collaboratively with public, private, and civil society leaders, FPF is developing best practices to guide how cities and local communities collect, manage, and use personal data to improve services for individuals. FPF and its Civic Data Privacy Leaders Network & Smart Communities Working Group seek to promote fair and transparent data uses, provide practical guidance to help local governments navigate complicated privacy-related issues, and help individuals better understand and engage with data-driven programs in their communities.

FPF’s ultimate goal is to help individuals, local communities, and technology providers maximize the benefits of responsible data use while minimizing privacy risks to individuals and communities.

Highlights Include:

  • FPF established the Civic Data Privacy Leaders Network, which convenes government privacy leaders for smart cities and communities to help local governments strengthen their ability to collect, use, and share data in a responsible manner. It is supported by the National  Science Foundation and Big Data Spokes program. Its members are producing a privacy risk assessment framework for smart city projects and holding workshops in partnership with MetroLab Network, a national network of 40+ city-university partnerships.
  • FPF was awarded a nationally-competitive grant from the National Science Foundation: Smart Privacy for Smart Cities: A Research Collaborative to Protect Privacy and Use Data Responsibly.
  • FPF developed Nothing to Hide: Tools for Talking (and Listening) About Data Privacy for Integrated Data Systems, a toolkit to help local government agencies lead privacy-sensitive, inclusive engagement about uses of data they collect in the course of delivering public services.
  • FPF published a report supporting stakeholder engagement and communications for researchers and practitioners working to advance administrative data research.
  • FPF created an Open Data Risk Assessment for the City of Seattle. This report provides tools and guidance to municipalities navigating the complex policy, operational, technical, organizational, and ethical standards that support privacy-protective open data programs.
    • FPF published an interactive visual guide to smart city technologies and data flows, Shedding Light on Smart City Privacy.
    • FPF published a central repository of Smart City Privacy Best Practices for privacy-related guidance documents, best practices, reports, codes of conduct, and other resources relevant to smart communities.
    • FPF convened a roundtable, Privacy in the Smart City: Finding the Middle Ground, to discuss how communities can secure the social benefits of new technologies while protecting individual privacy.
    • FPF contributed a chapter to the Cambridge Handbook of Consumer Privacy on Smart Cities: Privacy, Transparency, Community.
    • FPF filed comments on the NITRD Smart Cities and Communities Federal Strategic Plan.
    • FPF filed comments before the New York City Taxi & Limousine Commission and the California Public Utilities Commission regarding municipal collection of corporate data.
    • FPF is developing a Smart and Equitable Communities Privacy Impact Assessment for municipal technology and privacy leaders.
    • FPF has co-hosted events with strategic partners MetroLab Networks and NYU, and has presented or led panels at numerous smart cities, open data, and human rights-oriented events.

We invite you to join the Future of Privacy Forum and participate in the Smart Communities Working Group (FPF supporters or Advisory Board members) or the Civic Data Privacy Leaders Network (local government officials). 

To learn more or to join, contact Kelsey Finch at [email protected]

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Municipal Leaders Joining Network to Advance Civic Data Privacy
Spotlight

March 28, 2019 | editor

Municipal Leaders Joining Network to Advance Civic Data Privacy

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 […]

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What's Happening: Smart Communities

Smart Communities: A Conversation with Kelsey Finch
Top Story

February 12, 2019 | editor

Smart Communities: A Conversation with Kelsey Finch

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, […]

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Nothing to Hide: Tools for Talking (and Listening) About Data Privacy for Integrated Data Systems
Top Story

October 31, 2018 | Kelsey Finch

Nothing to Hide: Tools for Talking (and Listening) About Data Privacy for Integrated Data Systems

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.

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FPF Publishes Model Open Data Benefit-Risk Analysis
Top Story

January 30, 2018 | Kelsey Finch

FPF Publishes Model Open Data Benefit-Risk Analysis

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.

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