The current wave of digital transformation has spurred digitisation reforms and has led to prodigious development of AI & NLP systems, with several of them entering the public domain. There is a perception that these systems have a non trivial impact on society but there is a dearth of literature in critical AI on what are the kinds of these systems and how do they operate. This paper constructs a broad taxonomy of NLP systems which impact or are impacted by the ``public'' and provides a concrete analyses via various instrumental and normative lenses on the socio-technical nature of these systems. This paper categorises thirty examples of these systems into seven families, namely; finance, customer service, policy making, education, healthcare, law, and security, based on their public use cases. It then critically analyses these applications, first the priors and assumptions they are based on, then their mechanisms, possible methods of data collection, the models and error functions used, etc. This paper further delves into exploring the socio-economic and political contexts in which these families of systems are generally used and their potential impact on the same, and the function creep of these systems. It provides commentary on the potential long-term downstream impact of these systems on communities which use them. Aside from providing a birds eye view of what exists our in depth analysis provides insights on what is lacking in the current discourse on NLP in particular and critical AI in general, proposes additions to the current framework of analysis, provides recommendations future research direction, and highlights the need to importance of exploring the social in this socio-technical system.

翻译：当前数字化转型浪潮推动了数字化改革，促使人工智能与自然语言处理系统蓬勃发展，其中部分系统已进入公共领域。人们普遍认为这些系统对社会产生了不可忽视的影响，但关于这些系统的类型及其运作机制，批判性人工智能领域的文献仍显匮乏。本文构建了一个影响或被"公众"影响的自然语言处理系统的广义分类体系，并通过多种工具性与规范性视角，对这些系统的社会技术本质进行了具体分析。基于公共用例，本文将三十个典型系统实例划分为七大家族：金融、客户服务、政策制定、教育、医疗、法律与安全。随后，本文对这些应用进行了批判性分析，首先探讨其前提假设与预设，进而剖析其机制、可能的数据收集方法、模型及误差函数等。本文进一步深入探究这些系统家族通常应用的社会经济与政治背景及其潜在影响，并分析这些系统的功能蔓延现象。本文还评述了这些系统对其使用社区可能产生的长期下游影响。除提供宏观全景概览外，本文的深度分析揭示了当前自然语言处理领域（特别是批判性人工智能整体）的话语缺失，提出了对现有分析框架的补充建议，指明了未来研究方向，并强调了在这一社会技术系统中探索社会维度的必要性与重要性。