Government by Algorithms at the Light of Freedom of Information Regimes: A Case-by-Case Approach on ADM Systems within Public Education Sector

María Estrella Gutiérrez David
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Abstract

Abstract: What the Houston Court qualified as "mysterious 'black box' impervious to challenge" was in practice a sophisticated software of many layers of calculations, which rated teachers' effectiveness to make employment decisions. In the European Union, a system as such would fall under the Proposal for AI Regulation of 2021, which qualifies AI models in education and vocational training as "high-risk" systems. Automated decision-making systems (ADM systems), AI-driven or not, are being increasingly used by governments in public education for different purposes, such as handling applications for undergraduate admission or profiling students and teachers to assess their performance. Across cases and jurisdictions, there is growing evidence of how the use of ADM systems in the education sector is becoming quite problematic: arbitrary assignment of teaching posts in mobility procedures, undue barriers to access undergraduate studies, and frequent lack of transparency in their implementation and decisions. This Article discusses how Freedom of Information Act (FOIA) regimes may contribute to rendering governments' ADM systems (AI-driven or not) accountable. The analysis of the FOIA cases (Parcoursoup saga in France, MIUR in Italy, and Ofqual in the United Kingdom) shows to what extent decisions granting access to the source code, functional and technical specifications, or third-party audits allow public scrutiny of ADM systems, detection of their pathologies, and better understanding of their adverse impacts on rights and freedoms, individual or collective. This Article also addresses the constitutional value of the right of access to public records (Parcoursup), and the importance of proactive and mandatory public dissemination to ensure traceability, transparency, and accountability of the ADM systems for FOIA purposes. In this sense, some legal initiatives across jurisdictions (Canada, France, Spain, United States, European Union) enhancing transparency and accountability of algorithmic systems will be examined.
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信息自由制度下的算法政府:公共教育部门ADM系统的个案分析
摘要:被休斯顿法院称为“不可挑战的神秘‘黑盒子’”的东西,实际上是一个包含多层计算的复杂软件,用于评估教师做出雇佣决策的有效性。在欧盟,这样的系统将属于2021年人工智能监管提案,该提案将教育和职业培训中的人工智能模型定义为“高风险”系统。自动决策系统(ADM系统),无论是否由人工智能驱动,都越来越多地被政府用于公共教育的不同目的,例如处理本科入学申请或对学生和教师进行分析以评估他们的表现。在各个案例和司法管辖区,越来越多的证据表明,在教育部门使用ADM系统是如何变得相当有问题的:在流动程序中任意分配教学岗位,在获得本科学习方面存在不适当的障碍,以及在实施和决策中经常缺乏透明度。本文讨论了信息自由法案(FOIA)制度如何有助于使政府的ADM系统(人工智能驱动或非人工智能驱动)负责。对《信息自由法》案例(法国Parcoursoup案、意大利MIUR案和英国Ofqual案)的分析表明,授权获取源代码、功能和技术规范或第三方审计的决定,在多大程度上允许公众监督ADM系统,检测其病态,并更好地了解其对个人或集体权利和自由的不利影响。本文还讨论了获取公共记录权的宪法价值(Parcoursup),以及主动和强制性的公共传播的重要性,以确保ADM系统的可追溯性、透明度和问责性,以实现《信息自由法》的目的。在这个意义上,将审查各司法管辖区(加拿大、法国、西班牙、美国、欧洲联盟)加强算法系统透明度和问责制的一些法律倡议。
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