Tech and Telecom

X’s Algorithm Will Soon Become Fully Open For Everyone to Peek Inside

X may soon offer greater transparency into how content is ranked and recommended on the platform. On Saturday, owner Elon Musk said the company plans to make its updated recommendation algorithm open source within seven days.

In a post on X, Musk said the release will include all code used to determine how both organic and advertising posts are recommended to users. He added that the company plans to repeat this process every four weeks and publish comprehensive developer notes explaining what has changed between releases.

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Ongoing Regulatory Scrutiny

X’s recommendation system has faced increasing scrutiny from regulators. Authorities in France and the European Commission have opened investigations into the platform’s algorithm. The European Commission recently extended a data retention order through 2026, which it originally issued to X at the start of last year.

Regulatory pressure has intensified amid broader concerns about accountability on the platform. Attention has increased following incidents involving X’s chatbot, Grok, which was found generating underage nsfw material in response to user prompts and has also been used to digitally undress women without consent.

Past Transparency Promises

Musk has previously pledged to open-source X’s algorithm following his takeover of Twitter. In 2023, the company published code related to the platform’s “For You” feed on GitHub. However, analysts at the time noted that the release omitted key components and did not fully explain how recommendations worked. The code has also not been kept up to date since its release.

In his latest post, Musk said the upcoming releases will be more detailed and regularly maintained. “This will be repeated every four weeks, with comprehensive developer notes, to help you understand what changed,” he wrote.

It remains unclear how much insight the new releases will provide or whether they will address ongoing regulatory and public concerns around content moderation and recommendation practices on the platform.

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Published by
Afaq Wajdan Malik