Abstract: [Purpose/Significance] The study aims to deeply explore the ethical issues of artificial intelligence, clarify the current research status on gender equity in artificial intelligence decision-making, as well as to chart a directions for future research in this area, with the ultimate goal of promoting gender equity in artificial intelligence decision-making. [Design/Methodology] Using a systematic literature review method, the study searched eight domestic and international databases for relevant subject literature from 2000 to the present, yielding a total of 3,869 articles. After preliminary and re-screening, we finally included 50 highly relevant documents in our analysis to identify the topics, components and patterns of current research on gender equity in artificial intelligence decision-making, and to introduce the information ecology theory to build a research ecosystem. [Findings/Conclusion] In terms of sociotechnical perspectives, current research on gender equity in AI-based decision-making focuses on four key areas: analyzing gender bias phenomena at the macro level, examining this bias in subdivided fields, understanding the role of artificial intelligence in promoting gender equity, and human perception of equity in decision-making. The research encompasses four dimensions: information, information subject, information environment and information technology. Furthermore, the research patterns include the traditional type of values radiation, the technology-driven exploration type, and the multidimensional collaborative type. [Originality/Value] The study systematically analyzes current domestic and foreign research on gender equity in artificial intelligence decision-making, and builds an all-round, collaborative gender-equity information ecosystem in artificial intelligence decision-making from an information ecological perspective. It provides references for future research from the information circulation interaction mechanism, multi-subject cooperation mechanism and human-intelligence integration collaboration mechanism.

Keywords: Artificial intelligence, Artificial intelligence decision-making, Gender equity, Gender bias, Information ecosystem