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X to open-source its feed algorithm after regulatory scrutiny

X will make its recommendation algorithm open source in seven days, according to owner Elon Musk.

The platform will release the code that determines which posts and ads users see, with updates and developer notes set to be shared every four weeks.

Musk did not give a reason for the move.

X has faced regulatory scrutiny in Europe and the UK over content moderation, transparency, and the spread of AI-generated sexualized images on the platform.

French authorities requested X’s algorithm last July as part of a probe into bias, but the company refused, citing political motives.

🔗 Source: Bloomberg

🧠 Food for thought

Implications, context, and why it matters.

X’s past open-source releases missed production details; transparency still in question

  • In 2023, X posted parts of its recommendation code 1. It omitted ads logic plus configs and parameters. Candidate retrieval plus trust and safety systems were absent. Data and build tools were missing too. The repo had no top-level build or workspace file, and it listed few contributors 2.
  • Under the Digital Services Act, Very Large Online Platforms (VLOPs) must complete yearly independent audits that cover algorithmic systems, including recommendation and ad tech 3. The work lacks standard methods, so results vary by firm and by how they read the rules 4.
  • Transparency still hinges on what ships this time 2. Does it contain production ranking logic, licensing terms, and full model architectures 2? Earlier posts centered on the For You system layout, without a full build for production use 2.

EU transparency rules and tight audit timelines boost third-party compliance tools

  • Compliance vendors see an opening as VLOPs must meet a reasonable assurance audit standard each year 5. Few auditors have the needed technical skills, which tightens supply 6.
  • The first DSA audits landed in August 2024 6. VLOPs must also publish transparency reports every six months 7. That timetable drives demand for explainability, moderation accuracy tracking, and automated reporting tools 7.
  • Platforms must give vetted researchers (approved academics and nonprofits) access to data for studies of systemic risks 7. That need creates room for research infrastructure and secure data portals that support compliance 7.

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