数据正义、算法歧视与规制

Data Justice, Algorithmic Discrimination and Regulation

大数据的蓬勃发展,推动着人工智能算法在工商业活动中的深度应用,此过程中,数据分析和算法内部演算带来了针对特定群体的歧视性对待。作为传统歧视在算法领域的一种技术表现,算法歧视主要根源于归纳式逻辑等技术陷阱,相较于传统歧视而言,算法歧视造成了更深层的非正义现象。对此,应通过数据开放、算法透明与优化、伦理审查等手段推动算法监管转型,逐步建立完善的算法监管制度,实现对算法歧视的法律规制,确保数字时代社会的安全和发展。

The booming development of big data has promoted the deep application of artificial intelligence algorithms in industrial and commercial activities,and in this process,data analysis and internal algorithms have brought about discriminatory treatment against specific groups.As a technical manifestation of traditional social discrimination in the field of algorithms,algorithmic discrimination is mainly rooted in technical traps such as inductive logic,which causes deeper injustice phenomena compared to traditional discrimination.In this regard,we should promote the transformation of algorithm regulation by means of data opening,algorithm transparency and optimization,and ethical review,and gradually establish a perfect algorithm regulation system to realize the legal regulation of algorithm discrimination and ensure the safety and development of society in the digital era.