Some Chinese Apps Allow Users to Easily Close “Personalize Recommendations”
Economic Daily reported on Wednesday that, as of Tuesday, some apps have allowed users to close “personalized recommendations” based on algorithms with one click.
Companies that made the move include ByteDance’s Douyin and Toutiao, Tencent‘s WeChat, shopping platform Taobao, internet search platform Baidu, restaurant review platform Dianping, Twitter-like Weibo and lifestyle sharing platform Xiaohongshu.
Personalized recommendations often helps to improve the user’s experience. Whether users like cute animals, food or beauty products, the platform’s algorithm will continuously recommend similar content to them. However, at present, most apps bury the ability to turn off the feature deep into their settings menus.
WeChat, Dianping and other apps launched personal information collection list to show consumers what information they have collected and how they are using it.
According to the report released by the Internet Development Research Center of Peking University, 60% of the respondents are worried that their information will be leaked in the digital environment, 70% are worried that their personal preferences and interests will be illegally collected by algorithms, and 50% say they want to escape from the network and smartphone under the constraints of algorithms.
In January of this year, Chinese authorities released regulations that were carried out in March to clarify that algorithm recommendation service providers should inform users of their services in a noticeable manner. Further, platforms should give end users a chance to opt out of the information gathering and the ability to enable or disable the feature as they desire.
In addition, for those who provide algorithm recommendation services to minors, the elderly, workers and consumers, the regulations give specific requirements. The service providers are not allowed to induce minors to indulge in the Internet or implement differential treatment on transactions according to consumers’ preferences and buying habits. In terms of algorithms for workers, order allocation, remuneration composition and payment, working hours, rewards and punishments should be established.
