Documentation Practices of Artificial Intelligence

人工智能（AI）在透明度和问责方面面临着持续的挑战，这需要严格的文档记录。通过文献综述文档实践，我们提供了流行趋势、持久问题以及影响文档记录的多方面因素的概述。我们对关键特征（如范围、目标受众、支持多模式和自动化水平）的研究，强调了文档记录实践的动态演变，突显了向更全面、更引人入胜和更自动化的文档记录的转变。

AI documentation faces challenges in terms of transparency and accountability, which requires rigorous documentation. The paper aims to provide an overview of prevailing trends, persistent issues, and factors influencing the documentation practices.

The paper highlights a dynamic evolution in AI documentation practices, underscored by a shift towards a more holistic, engaging, and automated documentation. The key characteristics such as scope, target audiences, support for multimodality, and level of automation are examined.

The paper provides an overview of prevailing trends and persistent issues in AI documentation practices. The examination of key characteristics highlights a dynamic evolution in documentation practices, underscored by a shift towards a more holistic, engaging, and automated documentation. The paper also discusses the importance of transparency and accountability in AI documentation. No experiments or datasets were used in this literature review.

Related work includes recent research on AI documentation practices such as 'Documenting AI Research for Transparency and Compliance' by Gebru et al., 'Towards Transparent and Trusted AI Development: Mechanisms and Processes' by Liu et al., and 'Documentation in AI: A Systematic Literature Review' by Gao et al.