Related Insights

Comments on Updates to the ONC Voluntary Personal Health Record Model Privacy Notice

Privacy questions arise due to the volume and sensitivity of health data generated by consumer-focused apps, devices, and platforms, including the potential analytics uses that can be made of such data. Transparency about data practices is essential not just as a fundamental element of privacy, but is also key to engendering consumer trust, which in turn is critical to the adoption of these services. Without trust, consumers will resist using apps or devices and the industry as a whole will suffer. Overall, transparency practices should be guided by the principle that the consumer should not be surprised. The more unexpected or potentially objectionable a data collection or usage is, the greater the obligation to explain it to consumers.

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Letter to House of Representatives leadership opposing H.R. 2666

Dear Speaker Ryan and Leader Pelosi –– The undersigned organizations strongly urge you to oppose H.R. 2666, the “No Rate Regulation of Broadband Internet Access Act.” A broad coalition wrote to you this week detailing the many ways this legislation would undermine the public interest and the Open Internet; we are particularly concerned about the bill’s impact on consumer privacy.

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CDT Letter on Employee Privacy Legislation

CDT is pleased that policymakers are addressing the issue of employee privacy. Technological advancements have increased efficiency in the modern workplace but also blurred the lines between personal and work life. The availability of fine-grained information about individuals, such as their location, their activity levels, or their online habits, have made it tempting for employers to monitor their employees in a way that erodes an individual’s ability to control the collection, use, and sharing of her personal information. Economic fair play, as well as the dignity of the individual, is at stake when her privacy is infringed upon in the workplace. We agree that codifying protections for employees is necessary and write to share our perspective and recommendations for how model legislation can be responsive to current, and near-future, workplace technology trends.

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Letter to Wheeler on Broadband Privacy Rulemaking

March 16, 2016 Tom Wheeler Chairman Federal Communications Commission 445 12th Street SW, Washington, D.C. 20554 Re: Broadband Privacy Rulemaking Dear Chairman Wheeler: In the last two years, the civil rights community has begun analyzing the potential disproportionate impact of data collection and use practices on the constituencies we represent. In 2014, many of our organizations adopted the Civil Rights Principles for the Era of Big Data….

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CDT & PI Third-Party Intervention

Following the 2014 decision of the Court of Justice of the EU to strike down an EU-wide mandatory data retention scheme because it breached privacy rights, the national data retention laws of a number of EU Member States have also come under scrutiny. CDT and Privacy International have now intervened in a case against France to argue that the country’s sweeping data retention requirements violate EU law, as well as the European Convention on Human Rights.

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Broadband Privacy Letter to Tom Wheeler

Dear Chairman Wheeler: The undersigned organizations urge you to commence a rulemaking as soon as possible to protect the privacy of broadband consumers. As Commissioner Julie Brill of the Federal Trade Commission (FTC) stated in a recent speech on broadband and privacy, the Federal Communications Commission’s (FCC) reclassification of broadband as a Title II common carrier service adds it as “a brawnier cop on the beat” on privacy issues.

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Digital Decisions: Policy Tools in Automated Decision-Making

Digital technology has empowered new voices, made the world more accessible, and increased the speed of almost every decision we make as businesses, communities, and individuals. Much of this convenience is powered by lines of code that rapidly execute instructions based on rules set by programmers (or, in the case of machine learning, generated from statistical correlations in massive datasets)—otherwise known as algorithms.

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