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TikTok is working on a clone of its recommendation algorithm

by
May 31, 2024
in Economy
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TikTok is working on a clone of its recommendation algorithm

TikTok is working on a clone of its recommendation algorithm

Quick Look:

TikTok is reportedly developing a separate recommendation algorithm for its 170 million U.S. users. This move could facilitate a future divestiture of TikTok’s U.S. assets, although no immediate plans are set. U.S. legislation mandating the sale of TikTok’s U.S. operations is driven by data privacy and security concerns.

A recent report has sparked significant interest in TikTok‘s potential strategy to develop a separate recommendation algorithm specifically for its 170 million U.S. users. This move could lead to an operational model that functions independently from its Chinese parent company, ByteDance.

The Alleged Algorithm Split

TikTok is actively working on creating a clone of its powerful recommendation algorithm tailored for its U.S. user base. The sources suggest that this initiative could pave the way for a future divestiture of TikTok’s U.S. assets, though no immediate plans for such a sale are in place.

The concept of splitting the algorithm code is not entirely new. Reports indicate that discussions around this plan began last year, well before the enactment of a bill mandating the sale of TikTok’s U.S. operations due to national security concerns. These concerns stem from the app’s Chinese ownership and its potential ties to the Beijing government. The bill, which has heightened the stakes for TikTok’s operations in the U.S., was signed into law in April of this year.

National Security and Legislative Pressures

The legislative backdrop plays a critical role in this scenario. The U.S. government is pushing for TikTok to sever ties with ByteDance due to apprehensions about data privacy and national security. Lawmakers fear that the Chinese government could access user data, posing significant risks.

The bill enforcing the sale of TikTok’s U.S. operations underscores these concerns. It highlights the need for a solution that ensures data sovereignty and security. In light of this, developing an independent algorithm for the U.S. market can be seen as a strategic step. This aligns with regulatory requirements and mitigates risks.

However, TikTok’s response to these developments has been both defensive and critical. Initially declining to comment on the Reuters article, the company later took to social media platform X (formerly Twitter) to refute the claims. In their statement, TikTok asserted that the Reuters report was misleading and factually incorrect.

TikTok’s Firm Stance

TikTok highlighted the impracticality of the ‘qualified divestiture’ demanded by the newly enacted Act. The company pointed out that meeting such a divestiture’s legal, commercial, and technological requirements within the 270-day timeline stipulated by the Act is unfeasible.

TikTok’s firm stance against the divestiture requirement reflects broader concerns about the viability and implications of splitting its algorithm code. The company’s response indicates that while the creation of a U.S.-specific algorithm might be technically possible, it is fraught with significant legal and operational hurdles.

As the situation evolves, TikTok’s operations in the U.S. remain uncertain. The app’s popularity among American users adds another layer of complexity to the debate, as any significant changes to its algorithm or ownership structure could impact user experience and engagement.

The report about TikTok’s potential move to develop a separate recommendation algorithm for its U.S. users has stirred considerable speculation. It could represent a step towards greater autonomy and compliance with U.S. regulatory demands. However, the practical and legal challenges outlined by TikTok suggest that the road ahead is far from straightforward. The outcome of this development will be closely watched by industry observers, policymakers, and TikTok’s extensive user base alike.

The post TikTok is working on a clone of its recommendation algorithm appeared first on FinanceBrokerage.

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