The rapid iteration of information technology, such as big data, artificial intelligence and algorithm recommendation technology, has promoted the digital transformation of traditional society, and traditional journalism is also carrying out digital transformation and upgrading. In this context, as the overload of news information continues to intensify, algorithm recommendation news derived from big data has risen rapidly. Algorithm trust, data dominance, and the digitization of news media objectively lay the foundation for the application and development of algorithm recommendation news. Undoubtedly, algorithm recommendation news is of great significance for realizing the accurate distribution of news and enhancing the stickiness of news audiences. Intelligent, instantaneous algorithm recommendation news has the advantages of accuracy, efficiency, and individualization, but at the same time, as a complex and uncertain technology, algorithm brings multi-level, multi-link, multi-field risk challenges and institutional constraints. Algorithm recommendation news has also caused various ethical risks such as "algorithm black box" "algorithm deviation" "technical hegemony""responsibility gap" and "information leakage". At present, the academic circles are obviously insufficient in research and judgment on whether the algorithm recommendation technology itself is really mature, and on the ethical crisis that may be caused by algorithm recommendation news. In this regard, the three dimensions of the theory of technological uncertainty, including technological uncertainty, technological cognitive uncertainty, and technological institutional uncertainty, can provide an appropriate analysis framework for the ethical risks of algorithm recommendation news. From this framework, the root causes of the ethical risk of algorithm recommendation news can be clarified, which can be summarized as mathwashing and main body dispel in the dimension of technological uncertainty, the lack of ability and bottom line loss in the dimension of technological cognitive uncertainty, and the imperfection of legal norms and ethical system in the dimension of technological institutional uncertainty. Specifically, as an emerging technology, the existing ethical forms and legal norms are gradually unable to effectively regulate the ethical risk of algorithm recommendation news, and it is urgent to establish a professional and institutionalized regulatory system of ethical risk of algorithm recommendation news. What kind of principles should be followed in the legal regulation of ethical risk of algorithm recommendation news is the prerequisite and directional issue for the construction of the regulatory path. The analysis believes that the legal regulation of the ethical risk of algorithm recommendation news under technological uncertainty needs to adhere to the principle of news transparency, value neutrality, and rule of law with virtue. Of course, with the continuous evolution of algorithm recommendation technology, cloud computing and other emerging technologies, news transparency principle also need to keep pace with the times and effectively regulate the emerging ethical risks of algorithm recommendation news. News practitioners and algorithm recommended news distribution platforms must adhere to the principle of value neutrality to strengthen the subjectivity of "people" in algorithm recommendation news. And under the guidance of the principle of rule of law with virtue, the legal regulation paradigm of algorithm recommendation news ethical risk should be clarified. Proceeding from the above principles, the legal regulation of algorithm recommendation news ethical risks should target at different types of ethical risks, that is, to strengthen the protection of algorithm disclosure and algorithm interpretation rights, data rights, etc., in the dimension of technological uncertainty, to promote the cultivation of computational thinking and ethical constraints of news practitioners in the dimension of technological cognition uncertainty, and to adopt regulatory measures such as ethical structuring and legal accountability in the dimension of technological institutional uncertainty.