Showing results for viiia20 pronged promised syria
FPF-PPPM-2021Digest-R4
[…] the companies are permitted to share any de- identified data. If the tracking data is shared according to rules for de-identified data, then regardless of what is promised in principle, in practice taking a name off a dataset accomplishes very little. The second class of threats is broadly concerned with an improved ability to […]
Girot_Transferring
Transferring Personal Data in Asia : A path to legal certainty and regional convergence This Comparative Review sets out proposals for how Asian public stakeholders may promote legal certainty and greater consistency between the ir respective laws and regulation s on cross -border transfers of personal data in the region. Despite differences between the philosophies […]
Transferring Personal Data in Asia – A Path To Legal Certainty And Regional Convergence-1
Transferring Personal Data in Asia : A path to legal certainty and regional convergence This Comparative Review sets out proposals for how Asian public stakeholders may promote legal certainty and greater consistency between the ir respective laws and regulation s on cross -border transfers of personal data in the region. Despite differences between the philosophies […]
Workshop Report: Privacy & Pandemics – Responsible Use of Data During Times of Crisis
In October 2020, the Future of Privacy Forum (FPF) convened a virtual workshop entitled “Privacy and Pandemics: Responsible Uses of Technology and Health Data During Times of Crisis” with invited computer science, privacy law, public policy, social science, and health information experts from around the world to examine benefits, risks, and strategies for the collection […]
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1 NSF Convergence Accelerator Privacy and Pandemics: Responsible Use of Data During Times of Crisis Jules Polonetsky, CEO, Future of Privacy Forum Dr. Sara Jordan, Policy Counsel, Artificial Intelligence, Future of Privacy Forum Christy Harris, Director of Technology and Privacy Research , Future of Privacy Forum John Verdi, Vice President of Policy, Future of Privacy […]
Machine Learning and Speech: A Review of FPF’s Digital Data Flows Masterclass
On Wednesday, December 9, 2020, FPF hosted a Digital Data Flows Masterclass on Machine Learning and Speech. The masterclass on Machine Learning and Speech is the first masterclass of a new series after completing the VUB-FPF Digital Data Flows Masterclass series with eight topics. Professor Marine Carpuat (Associate Professor in Computer Science at the University of Maryland) starts […]
COVID-19: FEDERATED LEARNING FOR PRIVACY PRESERVING MULTI-INSTITUTIONAL COLLABORATION
COVID-19: FEDERATED LEARNING FOR PRIVACY PRESERVING MULTI-INSTITUTIONAL COLLABORATION
Tech is not the Limit | Trust is: Why apps could not solve this crisis and will not solve the next
[…] apps: centralized apps where the data are stored by a central authority and decentralized apps that send and store data in a distributed manner. If implemented as promised, a decentralized app (most use the Google/Apple-supported privacy-respecting approach and API 3 ) can prevent, or at least limit, the abuse of data. But this approach […]
Tech is not the Limit | Trust is: Why apps could not solve this crisis and will not solve the next
[…] apps: centralized apps where the data are stored by a central authority and decentralized apps that send and store data in a distributed manner. If implemented as promised, a decentralized app (most use the Google/Apple-supported privacy-respecting approach and API 3 ) can prevent, or at least limit, the abuse of data. But this approach […]
Empowering Researchers in Times of Crisis
[…] expertise are conducted in silos and reconciliation of approaches is difficult. Appropriately setting the privacy versus utility trade-off [2] is not a given. We propose a two- pronged strategy for trusted intermediaries to reduce tensions between privacy and the need for data access: 1) grow a multiskilled and proactive data governance team through direct […]