随着人工智能技术的广泛应用,“大数据杀熟”、“人工智能侵权”以及“算法歧视”等负面事件频发,原先人们以为的人工智能价值中立性也因此而遭到质疑。目前国内对此的相关研究仍较多集中于概念层面,本文拟在已有研究基础上,进一步从机器学习的算法层面,从数据的社会性、算法的价值偏好以及决策的偏见强化三个角度,分析人工智能的价值非中立性实质,并对其可能引发的伦理问题与决策风险提出建议。

With the wide application of artificial intelligence technology, negative events occur frequently, such as "big data price discrimination", "artificial intelligence infringement", "algorithm discrimination" and so on. The value neutrality of artificial intelligence, which was deemed by people before, has been questioned a lot. The existing relevant researches in China are mainly discussions at the conceptual level. This article, based on the existing researches, illustrated the value non-neutrality essence of artificial intelligence at the algorithm level of machine learning, from the aspects of the sociality of data, the value preference of algorithm and the reinforcement of decision bias. And then, presented some suggestions on the ethical problems and decision risks caused by the value non-neutrality essence of artificial intelligence.

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国家社会科学基金青年项目“笛卡尔的表征主义问题研究”（19CZX043）；中国科学技术大学青年创新基金项目“人工智能认识论中的表征问题”（WK2111050003）