  Human culture has evolved for thousands of years and thrived in the era of
Internet. Due to the availability of big data, we could do research on human
culture by analyzing its representation such as user item rating values on
websites like MovieLens and Douban. Industrial workers have applied recommender
systems in big data to predict user behavior and promote web traffic. In this
paper, we analyze the social impact of an algorithm named ZeroMat to show that
human culture is locked into a state where individual's cultural taste is
predictable at high precision without historic data. We also provide solutions
to this problem and interpretation of current Chinese government's regulations
and policies.
