other Safe by Default – Panoptykon Foundation and People vs BigTech’s Briefing Moving away from engagement-based rankings towards safe, rights-respecting, and human centric recommender systems. 05.03.2024
other Joint Submission on the Commission’s Guidelines for Providers of VLOPs and VLOSEs on the Mitigation of Systemic Risks for Electoral Processes Part 1 introduces how recommender systems contribute to systemic risks. Part 2 responds to the Commission’s proposals to moderate virality of content that threatens the integrity of the electoral process. 07.03.2024
Article Monologue of the Algorithm: how Facebook turns users data into its profit. Video explained Does Facebook identify and manipulate your feelings? Is it able to recognize your personality type, habits, interests, political views, level of income? Does it use all the information in order to reach you with personalized ads or sponsored content? You bet! 13.01.2018 Text
Article Can the EU Digital Services Act contest the power of Big Tech’s algorithms? A progressive report on the Digital Services Act (DSA) adopted by the Committee on Civil Liberties, Justice and Home Affairs (LIBE) in the European Parliament in July is the first major improvement of the draft law presented by the European Commission in December. MEPs expressed support for default protections from tracking and profiling for the purposes of advertising and recommending or ranking content. Now the ball is in the court of the leading committee on internal market and consumer protection (IMCO), which received 1313 pages of amendments to be voted in November. Panoptykon Foundation explores if the Parliament would succeed in adopting a position that will contest the power of dominant online platforms which shape the digital public sphere in line with their commercial interests, at the expense of individuals and societies. 03.08.2021 Text
Article Webinar: Alternative recommender systems in the DSA [recording] Facebook Files provided yet another confirmation that the company's extremely profitable recommender systems come at a high price paid by vulnerable individuals and our societies. Algorithms optimised for engagement amplify toxic content, such as hate speech or disinformation, and target humans based on their vulnerabilities. 23.11.2021 Text