法律 AI // 资讯总览
需要被持续追踪的
法律 AI 信号。
本期索引按监管、判例、实务与研究归档;可依主题或关键字定位已发布记录。
法律 AI // 资讯总览
本期索引按监管、判例、实务与研究归档;可依主题或关键字定位已发布记录。
原题: Co-constructing sociotechnical AI governance: participatory system mapping using algorithm registers
涉及法律行业大模型应用、律所与企业法务数智化实践指引。
arXiv论文《Co-constructing sociotechnical AI governance: participatory system mapping using algorithm registers》以荷兰一座城市的市政算法登记册为案例,研究一项利用业务规则引擎、辅助工作人员评估居民福利待遇资格的决策支持工具。研究团队通过访谈、调查和参与式系统制图工作坊,邀请市政工作人员、民间社会组织及监察专员等8名参与者,分析登记册能否帮助不同利益相关方绘制相关算法系统。研究进一步以系统理论过程分析将登记册置于更广泛的社会技术治理结构中。参与者识别出单凭算法登记册难以发现的风险,包括福利资格被拒、系统性能下降,以及当事人无法对错误决定提出异议。论文还讨论了直接和间接利益相关方参与对算法治理规范判断及系统安全分析的影响。
展示来源全文,完整内容以原文页面为准。
arXiv:2608.12166v1 Announce Type: new Abstract: Algorithm registers have been championed as a means of providing transparency on the use of algorithms in public services. Yet potential publics differ in their expectations of what should be made transparent and how, as well as in their interest in and ability to parse the information currently published in the registers. Moreover, it remains unclear how these instruments can represent the sociotechnical systems in which these algorithms are embedded, and how system-level transparency can facilitate accountability. In this paper, we ask, what do algorithm registers reveal (and occlude) about the sociotechnical systems governing algorithmic systems, and how can diverse stakeholder perspectives inform a more pluralistic system-theoretic safety analysis? To do this, we probe the municipal algorithm register of a Dutch city through a case study of a decision-support tool for caseworkers' assessment of citizens' welfare benefits eligibility based on legal automation through a business rule engine. Through interviews, surveys, and participatory system mapping workshops (with municipal staff, civil society organisations, and ombudsmen, N=8), we seek to understand to what extent the register allows stakeholders to map the algorithmic system in question. These maps inform a System-Theoretic Process Analysis (STPA) that situates the register within a wider sociotechnical governance structure. Participants' contributions allow us to identify potential safety hazards which would not have been possible to see using the algorithm register alone, including benefits eligibility denial, system performance deterioration, and inability to contest wrongful decisions. By engaging both direct and indirect stakeholders, we reflect on the normative dimensions of algorithm governance efforts and how politics shape the practice of system safety analysis.
文书与研报规范引注
《算法登记册如何揭示社会技术治理风险》(来源: arXiv cs.CY,发布日期: 2026/10/12,访问链接: https://arxiv.org/abs/2608.12166)