As global discourse on AI regulation gains momentum, this paper focuses on delineating the impact of ML on autonomy and fostering awareness. Respect for autonomy is a basic principle in bioethics that establishes persons as decision-makers. While the concept of autonomy in the context of ML appears in several European normative publications, it remains a theoretical concept that has yet to be widely accepted in ML practice. Our contribution is to bridge the theoretical and practical gap by encouraging the practical application of autonomy in decision-making within ML practice by identifying the conditioning factors that currently prevent it. Consequently, we focus on the different stages of the ML pipeline to identify the potential effects on ML end-users' autonomy. To improve its practical utility, we propose a related question for each detected impact, offering guidance for identifying possible focus points to respect ML end-users autonomy in decision-making.

翻译：随着全球关于人工智能监管的讨论日益升温，本文着重于厘清机器学习对自主性的影响并提升相关意识。尊重自主性是生命伦理学的一项基本原则，它将人确立为决策主体。尽管机器学习背景下的自主性概念已出现在若干欧洲规范性文献中，它仍是一个理论概念，尚未在机器学习实践中被广泛接纳。我们的贡献在于通过识别当前阻碍自主性实践的条件因素，促进自主性在机器学习实践决策中的实际应用，从而弥合理论与实践的鸿沟。为此，我们聚焦于机器学习流程的不同阶段，以识别其对机器学习终端用户自主性的潜在影响。为提升其实用性，我们针对每个已识别的影响提出了一个相关问题，为在决策中尊重机器学习终端用户自主性提供了识别可能关注点的指导。