论文标题
在基于人工智能的个性化系统中应用透明度
Applying Transparency in Artificial Intelligence based Personalization Systems
论文作者
论文摘要
基于人工智能的系统越来越多地使用个性化为用户提供相关的内容，产品和解决方案。个性化旨在支持用户并满足其各自的需求和偏好。但是，由于算法的进步和缺乏透明度，用户越来越容易受到在线操作的影响。这种操作降低了用户对与之交互的系统的信任，自主权和满意度的水平。提高透明度是基于个性化系统的重要目标。不幸的是，系统设计人员在评估和实施其开发系统中的透明度方面缺乏指导。 在这项工作中，我们结合了技术伦理学和计算机科学的见解，以生成用于机器生成个性化的透明度最佳实践列表。基于这些最佳实践，我们开发了一个清单，希望由希望评估和提高其算法系统透明度的设计师使用。采用设计师的观点，我们将清单应用于著名的在线服务，并讨论其优势和缺点。我们鼓励研究人员在各种环境中采用清单，并致力于基于共识的工具来衡量个性化社区的透明度。
Artificial Intelligence based systems increasingly use personalization to provide users with relevant content, products, and solutions. Personalization is intended to support users and address their respective needs and preferences. However, users are becoming increasingly vulnerable to online manipulation due to algorithmic advancements and lack of transparency. Such manipulation decreases users' levels of trust, autonomy, and satisfaction concerning the systems with which they interact. Increasing transparency is an important goal for personalization based systems. Unfortunately, system designers lack guidance in assessing and implementing transparency in their developed systems. In this work we combine insights from technology ethics and computer science to generate a list of transparency best practices for machine generated personalization. Based on these best practices, we develop a checklist to be used by designers wishing to evaluate and increase the transparency of their algorithmic systems. Adopting a designer perspective, we apply the checklist to prominent online services and discuss its advantages and shortcomings. We encourage researchers to adopt the checklist in various environments and to work towards a consensus-based tool for measuring transparency in the personalization community.
