Machines have moved from supporting decision-making processes of humans to making decisions for humans. This shift has been accompanied by concerns regarding the impact of decisions made by algorithms on individuals and society. Unsurprisingly, the delegation of important decisions to machines has therefore triggered a debate on how to regulate the automated decision-making practices. In Europe, policymakers have attempted to address these concerns through a combination of individual rights and due processes established in data protection law, which relies on other statutes, e.g., anti-discrimination law and restricting trade secret laws, to achieve certain goals. This article adds to the literature by disentangling the challenges arising from automated decision-making systems and focusing on ones arising without malevolence but merely as unwanted side-effects of increased automation. Such side-effects include ones arising from the internal processes leading to a decision, the impacts of decisions, as well as the responsibility for decisions and have consequences on an individual and societal level. Upon this basis the article discusses the redress mechanisms provided in data protection law. It shows that the approaches within data protection law complement one another, but do not fully remedy the identified side-effects. This is particularly true for side-effects that lead to systemic societal shifts. To that end, new paradigms to guide future policymaking discourse are being explored.

机器已经从支持人类的决策过程转变为为人类做出决策。这种转变伴随着对算法决策对个人和社会影响的担忧。因此，毫不奇怪，将重要决策委派给机器引发了关于如何规范自动化决策实践的辩论。在欧洲，决策者试图通过结合个人权利和数据保护法中确立的正当程序来解决这些问题，数据保护法依赖于其他法规（例如反歧视法和限制性商业秘密法）来实现某些目标。本文通过梳理自动化决策系统带来的挑战，并集中精力研究那些没有恶意的问题，而这些挑战只是增加自动化的不良副作用，从而增加了文献资料。此类副作用包括由导致决策的内部过程，决策的影响以及决策的责任所引起的副作用，并对个人和社会产生影响。在此基础上，本文讨论了数据保护法中提供的补救机制。它表明，数据保护法中的方法是相辅相成的，但是并不能完全弥补已确定的副作用。对于导致系统性社会转变的副作用尤其如此。为此，正在探索指导未来政策制定话语的新范式。