How TikTok Reads Your Mind

Julian McAuley, a professor of computer science at the University of California San Diego, who also reviewed the document, said in an email that the paper was short on detail about how exactly TikTok does its predictions, but that the description of its recommendation engine is “totally reasonable, but traditional stuff.” The company’s edge, he said, comes from combining machine learning with “fantastic volumes of data, highly engaged users, and a setting where users are amenable to consuming algorithmically recommended content (think how few other settings have all of these characteristics!). Not some algorithmic magic.”

Mr. McAuley added that he was a bit perplexed about why people were always asking him about TikTok.

“There seems to be some perception (by the media? or the public?) that they’ve cracked some magic code for recommendation, but most of what I’ve seen seems pretty normal,” he wrote.

And indeed, the document does much to demystify the sort of recommendation system that tech companies often present as impossibly hard for critics and regulators to grasp, but that typically focus on features that any ordinary user can understand. The Journal’s coverage of leaked Facebook documents, for instance, illustrated how Facebook’s decision to give more weight to comments helped divisive content spread. While the models may be complex, there’s nothing inherently sinister or incomprehensible about the TikTok recommendation algorithm outlined in the document.

But the document also makes clear that TikTok has done nothing to sever its ties with its Chinese parent, ByteDance, whose ownership became a spasmodic focus at the end of President Donald J. Trump’s administration in 2020, when he attempted to force the sale of TikTok to an American company allied with his administration, Oracle.

The TikTok document refers questions to an engineering manager whose LinkedIn biography says he works on both TikTok and ByteDance’s similar Chinese app, Douyin, offering a glimpse at the remaining global element of an increasingly divided tech industry, the engineering talent. According to LinkedIn, the engineering manager attended Peking University, received a master’s degree in computer science at Columbia University and worked for Facebook for two years before coming to ByteDance in Beijing in 2017. The document is written in clear, but nonnative, English, and comes from the perspective of the Chinese tech industry. It makes no references, for instance, to rival American companies like Facebook and Google, but includes a discussion of “if Toutiao/Kuaishou/Weibo have done something similar, can we launch the same strategy as they have done?”

TikTok’s development process, the document says, is closely intertwined with the process of Douyin’s. The document at one point refers TikTok employees to the “Launch Process for Douyin Recommendation Strategy,” and links to an internal company document that it says is the “same document for TikTok and Douyin.”

Article source: https://www.nytimes.com/2021/12/05/business/media/tiktok-algorithm.html