Search results

[…] Conference 2020 commences next week in Brussels, bringing together academics, data protection authorities, policymakers, data scientists, and civil society to network, exchange ideas, and talk over the latest trends. Check out the panels and events FPF will be participating in below.  Algorithmic Regulation of Transportation Wednesday, January 22 at 11:45, Petite Halle We are […]

[…] and when it should not. It examines the relationship between precluded personal information, such as race, and the proxies for precluded information, such as names and zip codes. It proposes that the success of these measures depends on what types of proxies exist for the information blocked and it explores in which situations those […]

[…] of keeping kids off the internet. Jo Pedder, Head of Regulatory Strategy at the United Kingdom Information Commissioner’s Office discussed the UK’s implementation of the age-appropriate design code. The code’s goal is to empower kids on the internet while keeping them safe, rather than keeping them out of the digital world. Instead of a […]

[…] the search results webpage information relating to the outcome of the criminal case.  In the words of the Court, “the operator is in any event required, at the latest on the occasion of the request for de-referencing, to adjust the list of results in such a way that the overall picture it gives the internet […]

[…] and signed by the governor if the amendments are “consistent with and further the purpose and intent” of the Act. Next Steps According to the California Elections Code (ELECT CA ELEC § 9002), the California Attorney General will hold a 30-day review process and public comment period, followed by five additional days for proponents […]

[…] mechanisms transparent, access controls, monitoring, documentation, testing, and debugging. “Privacy or security harms in machine learning do not necessarily require direct access to underlying data or source code,” said Andrew Burt, Immuta Chief Privacy Officer and Legal Engineer. “We explore how creators of any machine learning system can limit the risk of unintended leakage […]

[…] explaining approaches to data protection. Unlike traditional software, in machine learning systems privacy or security harms do not necessarily require direct access to underlying data or source code. The whitepaper presents a layered approach to data protection in machine learning, including recommending techniques such as noise injection, inserting intermediaries between training data and the […]

[…] of their decisions, as use cases run the gamut of useful and creative applications as well as those which might be concerning. OpenAI, a group which actively promotes cooperativeness in AI research, designed a fake text generator they felt was so good, they decided the risks it posed made it too dangerous to release. […]

[…] and Innovation Foundation to undertake both projects. The Alliance will support data sharing efforts under way, help address and mitigate challenges that create barriers to sharing and promote practices that encourage more data sharing between industry and academic researchers. So far, more than 25 prominent companies are participating in the Alliance’s activities. In its […]

[…] not only to go beyond existing laws in addressing consumer privacy concerns, but also to help shape evolving legislative efforts. We are glad to see that the NAI is taking major steps in the right direction in order to continue to be on the front lines of protecting consumer privacy and promoting responsible business practices.