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FPF-Europe-report-DPA-Strategies_-from-2021-and-beyond-3-2
[…] document analyzed, allowing the reader to dive deeper into the relevant details. It also includes a summary of the EDPSтАЩ 4 -year strategy, covering the 2020 – 2024 period, which promises to deeply influence how DPAs across Europe understand and approach data protection challenges brought by emerging technologies. With this repo rt, FPF hopes […]
India’s new Intermediary & Digital Media Rules: Expanding the Boundaries of Executive Power in Digital Regulation
[…] liability and regulation of publishers of digital content have generated significant debate since their release in February 2021. The Information Technology (Intermediary Guidelines and Digital Media Ethics Code) Rules, 2021 (the Rules) have: recast the conditions to obtain ‘safe harbour’ from liability for online intermediaries, and unveiled an extensive regulatory regime for a newly […]
Model-Privacy-Regime
[…] trekking to or calling a series of 81. C AL. CIV. CODE § 1798.29. 82. Id. §§ 1785.11.1, 1785.11.6, 1786.60, 1798.85–.86; C AL. FAM . CODE § 2024.5 (West 2004). SOLOVE .DOC 2/2/2006 4:27:56 PM No. 2] A MODEL REGIME OF PRIVACY PROTECTION 375 different local offices. Today, massive database companies sweep up the […]
South Korea: The First Case Where the Personal Information Protection Act was Applied to an AI System
[…] and operate “Iruda.” Therefore, PIPC determined that ScatterLab processed the user’s personal information beyond the purpose of collection. In addition, ScatterLab posted its AI models on the code sharing and collaboration platform Github from October 2019 to January 2021, which included 1,431 KakaoTalk messages revealing 22 names (excluding last names), 34 locations (excluding districts […]
Automated Decision-Making Systems: Considerations for State Policymakers
[…] religion, health conditions, or other highly personal information). In some cases, non-sensitive data can act as a “proxy” for sensitive information (such as the use of zip code as a proxy for race). Data may also be obtained from sources of varying quality, accuracy, or ethical collection, for example: public records, government collection, regulated […]
4858d4e3-fece-4e56-8a57-66a5d440c361-AI Regulation draft
[…] intelligence in the Union. 1 OJ [..] 2 […] 3 Position of the European Parliament of [..] 2 (4) In her political guidelines for the 2019 – 2024 Commission “A Union that strives for more” 4 President -elect von der Leyen announce d the Commission would put forward legislation for a coordinated European approach […]
The Spectrum of Artificial Intelligence – An Infographic Tool
[…] allow you to fill out your tax forms and ensure your information included and provided in a way that is within current legal requirements of the tax code. Healthcare – Ambient Charting, where conversations between doctors and patients are recorded and added to the patient record as they happen, with key words and followups […]
Artificial Intelligence and the COVID-19 Pandemic
[…] care professionals that leverage audio-visual data, text analysis, chatbots, and sensors. Based on our analysis, we recommend that AI app developers: Improve the fairness of the data; Code check the apps; Validate the models of existing systems; and Improve confidence in recommendations Contents: I. Overview Political and structural responses II. Analysis of COVID-19 […]
New White Paper Explores Privacy and Security Risk to Machine Learning Systems
[…] 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 […]
Warning Signs: Identifying Privacy and Security Risks to Machine Learning Systems
[…] 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 […]