From Technological Alienation to Value Regression: Ethical Regulation of Algorithmic Bias in the Post-Truth Era

In the current post-truth era characterized by an information explosion and complex and ever-changing circumstances, a large amount of false information and misleading content is widely disseminated, and the public's perception is easily disturbed. As a key mechanism for information screening and pushing, algorithms have seen their bias issues becoming increasingly prominent. In particular, the technological breakthrough of generative artificial intelligence has further transformed the infrastructure of the internet society. Its potential algorithmic bias and discrimination will not only solidify the systemic discrimination and inequality in human society, but may even intensify and create new biases, posing a systemic threat to social fairness and social progress. The algorithmic bias in the post-truth era has a non-negligible impact throughout the entire process of information production, information dissemination, and information construction. The ethical dilemma urgently needs to be addressed. This study reveals the generation logic and manifestations of algorithmic bias in the post-truth era, constructs a systematic path that integrates "technology, value, and institution" as a trinity, provides practical solutions to cope with the ethical challenges of algorithmic bias in the post-truth era, and helps build a more rational, inclusive, and just information society.