Abstract The rush to understand new socio-economic contexts created by the wide adoption of AI is justified by its far-ranging consequences, spanning almost every walk of life. Yet, the public sector's predicament is a tragic double bind: its obligations to protect citizens from potential algorithmic harms are at odds with the temptation to increase its own efficiency - or in other words - to govern algorithms, while governing by algorithms. Whether such dual role is even possible, has been a matter of debate, the challenge stemming from algorithms' intrinsic properties, that make them distinct from other digital solutions, long embraced by the governments, create externalities that rule-based programming lacks. As the pressures to deploy automated decision making systems in the public sector become prevalent, this paper aims to examine how the use of AI in the public sector in relation to existing data governance regimes and national regulatory practices can be intensifying existing power asymmetries. To this end, investigating the legal and policy instruments associated with the use of AI for strenghtening the immigration process control system in Canada; “optimising” the employment services” in Poland, and personalising the digital service experience in Finland, the paper advocates for the need of a common framework to evaluate the potential impact of the use of AI in the public sector. In this regard, it discusses the specific effects of automated decision support systems on public services and the growing expectations for governments to play a more prevalent role in the digital society and to ensure that the potential of technology is harnessed, while negative effects are controlled and possibly avoided. This is of particular importance in light of the current COVID-19 emergency crisis where AI and the underpinning regulatory framework of data ecosystems, have become crucial policy issues as more and more innovations are based on large scale data collections from digital devices, and the real-time accessibility of information and services, contact and relationships between institutions and citizens could strengthen – or undermine - trust in governance systems and democracy.

中文翻译：

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公共部门的人工智能治理：民主环境中自动化决策前沿的三个故事

摘要 人们急于了解人工智能的广泛采用所创造的新社会经济背景，其影响范围广泛，几乎遍及各行各业。然而，公共部门的困境是一个悲剧性的双重束缚：它保护公民免受潜在算法危害的义务与提高自身效率的诱惑——或者换句话说——管理算法的诱惑不一致，同时由算法进行管理。这种双重角色是否可能，一直是一个有争议的问题，算法的内在属性带来的挑战使它们与政府长期接受的其他数字解决方案不同，创造了基于规则的编程所缺乏的外部性。随着在公共部门部署自动化决策系统的压力变得普遍，本文旨在研究与现有数据治理制度和国家监管实践相关的公共部门使用人工智能如何加剧现有的权力不对称。为此，调查与使用人工智能加强加拿大移民程序控制系统相关的法律和政策工具；在波兰“优化”就业服务，并在芬兰个性化数字服务体验，该论文主张需要一个通用框架来评估在公共部门使用人工智能的潜在影响。在这方面，它讨论了自动化决策支持系统对公共服务的具体影响以及对政府在数字社会中发挥更普遍作用并确保利用技术潜力的日益增长的期望，而负面影响得到控制并可能避免。鉴于当前的 COVID-19 紧急危机，随着越来越多的创新基于从数字设备收集的大规模数据，人工智能和数据生态系统的基础监管框架已成为关键的政策问题，这一点尤为重要。 - 信息和服务的及时获取、机构与公民之间的联系和关系可以加强或削弱对治理系统和民主的信任。