Designing seamless, frictionless user experiences has long been a dominant trend in both applied behavioral science and artificial intelligence (AI), in which the goal of making desirable actions easy and efficient informs efforts to minimize friction in user experiences. However, in some settings, friction can be genuinely beneficial, such as the insertion of deliberate delays to increase reflection, preventing individuals from resorting to automatic or biased behaviors, and enhancing opportunities for unexpected discoveries. More recently, the popularization and availability of AI on a widespread scale has only increased the need to examine how friction can help or hinder users of AI; it also suggests a need to consider how positive friction can benefit AI practitioners, both during development processes (e.g., working with diverse teams) and to inform how AI is designed into offerings. This paper first proposes a "positive friction" model that can help characterize how friction is currently beneficial in user and developer experiences with AI, diagnose the potential need for friction where it may not yet exist in these contexts, and inform how positive friction can be used to generate solutions, especially as advances in AI continue to be progress and new opportunities emerge. It then explores this model in the context of AI users and developers by proposing the value of taking a hybrid "AI+human" lens, and concludes by suggesting questions for further exploration.

设计出无缝、无摩擦的用户体验一直是应用行为科学和人工智能领域的主要趋势，在此中，使令人愉快的行为变得容易和高效的目标在减少用户体验中的摩擦方面起着重要的作用。然而，在某些情况下，摩擦确实有益处，例如故意延迟以增加思考时间，防止个体采取自动或偏见行为，并提供意外发现的机会。本文首次提出了一个“正向摩擦”模型，可以帮助描述目前在用户和开发者与人工智能的经验中摩擦是如何有益的，诊断出这些情境中可能需要摩擦的潜在需求，并提供如何利用正向摩擦生成解决方案的信息，特别是随着人工智能的进展和新机会的出现。然后，它在人工智能用户和开发者的背景下探讨了这个模型，提议采用混合“人工智能+人类”的视角，并提出了进一步探索的问题。

人工智能与人类互动中“积极摩擦”的行为模式探索