The video platform's recommendation algorithm is intended to promote addiction risks as well as eating and anxiety disorders.
AI-generated summary
The Digital Services Act obliges large online platforms in the EU to minimize the risks of their offerings and ensure transparency.
Tiktok's recommendation algorithm can be dangerous - the EU Commission comes to this conclusion in a preliminary investigation report. According to the report published in Brussels on Friday, the Chinese video platform violates European law because it does not adequately protect users.
For several years now, particularly large online platforms in the EU have been subject to strict regulations. The Digital Services Act, one of the central EU laws for platform regulation, stipulates that digital companies must minimize the risks of their offerings and make this transparent.
According to the commission, Tiktok is said to have violated these requirements. Tiktok’s “For You” feed shows users videos one after the other that are tailored to their previous user behavior. This is how the app makes its money: In order to be able to display as much advertising as possible, it wants to get users to spend as much time as possible on the platform. The platform does this with the help of its algorithm, which always displays the content that the user has viewed for a particularly long time in the past.
The EU Commission has accused Tiktok of using its algorithm to fuel addiction, eating and anxiety disorders. She ordered the company to make changes to the “harmful” functioning of its app to protect users’ mental health. The so-called rabbit hole effect - meaning falling deeper and deeper into a rabbit hole - can have negative effects on the mental health of users, especially vulnerable adults and minors.
Tiktok is accused of not having examined these risks enough and of not taking effective action against the dangers. Tiktok has made certain changes to its recommendations to reduce the risk of the rabbit hole effect. However, the Commission says it does not consider it to be effective enough. For example, the EU Commission assumes that the content displayed does not necessarily change even if users mark content as “not interesting” to them.
For example, the commission is now demanding that Tiktok take greater account of users' explicit preferences in its recommendations and no longer use viewing time as an indicator for recommendations.
Tiktok can now respond to the allegations. If these are seen as confirmed, a fine of up to six percent of the company's global annual turnover can theoretically be imposed. In comparable cases, however, the penalties have always been well below this maximum amount.
In addition, the EU Commission is investigating further allegations against Tiktok. This is about the suspicion of the addictive design of the platform, the lack of access to data for scientists and the lack of protection of minors.
AI outlook — possibilities, not facts
Tiktok needs to make adjustments to the recommendation algorithm.
Likely · Within months

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The EU Commission accuses Tiktok of endangering the mental health of young users through addictive algorithms and illegal platform design. The parent company Bytedance faces high fines if the proceedings have a negative outcome.

The EU Commission is calling on Tiktok to fundamentally change its algorithm to reduce mental health risks such as addiction and eating disorders. The 'Rabbit Hole' effect should be stopped through more user control and a move away from pure dwell time logic.

The EU Commission warns about the risks of the TikTok algorithm. The video recommendations could increase psychological problems and promote addictive behavior. Brussels calls for fundamental changes to the 'For You' site to better protect users.

The EU Commission has asked TikTok to make changes to its algorithm to protect users from so-called rabbit hole effects. If the rules are ignored, the parent company ByteDances could face high fines.

The EU Commission warns against Tiktok video recommendations that could exacerbate psychological problems. The algorithm creates so-called rabbit hole effects through personalized feeds, which are inadequately contained.