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Paris Prosecutors Investigate X (formerly Twitter) Over Alleged Algorithmic Bias
(MENAFN) Paris prosecutors have initiated an investigation into the social media platform X (formerly Twitter) following allegations that its algorithms may have caused distortions in the operation of an automated data processing system. The probe was launched after a complaint filed on January 12 by Eric Bothorel, a deputy from the Renaissance party, who raised concerns about potential algorithmic bias influencing the platform’s functioning, according to Franceinfo radio.
The prosecutor’s office stated that the investigation is focused on the possibility that the platform’s algorithms affected the automated data processing system. Magistrates, along with specialized assistants from the cybercrime section, are analyzing the case and conducting initial technical verifications to determine the extent of the potential issues. Bothorel, in his statement on X, emphasized that multiple posts had mentioned “those responsible for the distorted operation of X's recommendation algorithm,” and he formally referred the matter to the J3 cyber prosecutor on January 12.
This investigation marks a significant step in addressing concerns about the transparency and fairness of social media algorithms, particularly regarding their influence on content recommendation and user behavior.
The prosecutor’s office stated that the investigation is focused on the possibility that the platform’s algorithms affected the automated data processing system. Magistrates, along with specialized assistants from the cybercrime section, are analyzing the case and conducting initial technical verifications to determine the extent of the potential issues. Bothorel, in his statement on X, emphasized that multiple posts had mentioned “those responsible for the distorted operation of X's recommendation algorithm,” and he formally referred the matter to the J3 cyber prosecutor on January 12.
This investigation marks a significant step in addressing concerns about the transparency and fairness of social media algorithms, particularly regarding their influence on content recommendation and user behavior.
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