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[…] when they talk about de-identification? How does anonymous data differ from pseudonymous or de-identified information? Data identifiability is not binary. Data lies on a spectrum with multiple shades of identifiability. This is a primer on how to distinguish different categories of data. FPF.ORG Produced byIn collaboration withIn collaboration with LIMITED or NONE IN PLACE […]

[…] number of key starts, for instance. Should data be processed, stored, or retained off the vehicle, it should be for the limited purpose of diagnosing, servicing, or repairing the technology. Drivers should have clear and easily accessible means of accessing and deleting personal information. 89 Allowing a person to whom data relates to request […]

IS SUE BRIEF: YOUTH PRIVACY IN IMMERSIVE TECHNOLOGIES 1 ISSUE BRIEF YOUTH & ED U.S. POLICY Youth Privacy in Immersive Technologies: Regulatory Enforcement, Self-Regulatory Guidance, and Remaining Uncertainties Author: Bailey Sanchez, Jameson Spivack, FPF, March 2024 A u t h o r e d B y : B ailey Sanchez SeniorC ounselforYouth & Education,Future ofPrivacy […]

[…] number of key starts, for instance. Should data be processed, stored, or retained off the vehicle, it should be for the limited purpose of diagnosing, servicing, or repairing the technology. Drivers should have clear and easily accessible means of accessing and deleting personal information. 89 Allowing a person to whom data relates to request […]

[…] number of key starts, for instance. Should data be processed, stored, or retained off the vehicle, it should be for the limited purpose of diagnosing, servicing, or repairing the technology. Drivers should have clear and easily accessible means of accessing and deleting personal information. 89 Allowing a person to whom data relates to request […]

[…] will be biased by age, race, and gender, working more accurately on people demographically similar to those it was trained on. Joy Buolamwini and Timnit Gebru, Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification, Proceedings of Machine Learning Research, Conference on Fairness, Accountability, and Transparency (Feb. 2018), https://proceedings.mlr.press/v81/buolamwini18a/buolamwini18a.pdf . 41 RISK FRAMEWORK FOR […]

[…] ADPPA and its record of bipartisan support make it a potential third model for state privacy legislation. There is already legislation in Michigan (SB 1182) that contains shades of ADPPA in its formulation of a private right of action. What, if any, additional language or concepts from ADPPA will gain traction at the state […]

[…] user’s head-mounted display (HMD). This allows the user’s “hands” to interact with virtual content. For example, MR or VR maintenance training could allow a mechanic to practice repairing a virtual car engine before performing these actions in the real world. Gesture-based controls utilize ML models, specifically deep learning, to construct 3D copies of the […]

[…] retrieved by physically inserting a compatible device into the port. This port enables access to information that can help service technicians measure emissions, diagnose performance issues, or repair your vehicle. Owners may also choose to plug in a third-party device (or “dongle”) into the OBD-II port in some vehicles to collect or share information […]

[…] on AD AS technologies, 24 with savings generated through lower insurance premiums, 25 reductions in legal claims, improved driver retention, 26 lower operating costs, and improved vehicle repair and maintenance. 27 C. Technological Advancements in Cloud Computing and Artificial Intelligen ce Have Improved ADAS Functionality and Effectiveness ADAS technologies are not new. Indeed, features […]