Online platforms have a wealth of data, run countless experiments and use industrial-scale algorithms to optimize user experience. Despite this, many users seem to regret the time they spend on these platforms. One possible explanation is that incentives are misaligned: platforms are not optimizing for user happiness. We suggest the problem runs deeper, transcending the specific incentives of any particular platform, and instead stems from a mistaken foundational assumption. To understand what users want, platforms look at what users do. This is a kind of revealed-preference assumption that is ubiquitous in user models. Yet research has demonstrated, and personal experience affirms, that we often make choices in the moment that are inconsistent with what we actually want: we can choose mindlessly or myopically, behaviors that feel entirely familiar on online platforms. In this work, we develop a model of media consumption where users have inconsistent preferences. We consider what happens when a platform that simply wants to maximize user utility is only able to observe behavioral data in the form of user engagement. Our model produces phenomena related to overconsumption that are familiar from everyday experience, but difficult to capture in traditional user interaction models. A key ingredient is a formulation for how platforms determine what to show users: they optimize over a large set of potential content (the content manifold) parametrized by underlying features of the content. We show how the relationship between engagement and utility depends on the structure of the content manifold, characterizing when engagement optimization leads to good utility outcomes. By linking these effects to abstractions of platform design choices, our model thus creates a theoretical framework and vocabulary in which to explore interactions between design, behavioral science, and social media.
翻译:在线平台拥有丰富的数据, 进行无数的实验, 并使用工业规模的算法来优化用户经验。 尽管如此, 许多用户似乎对在平台上花费的时间表示遗憾。 一个可能的解释是激励机制不正确: 平台并不最有利于用户的幸福。 我们建议问题会更深, 超越任何特定平台的具体激励机制, 取自错误的基础假设。 要理解用户想要什么, 平台看用户做什么。 这是一个在用户模式中普遍存在的披露偏好假设。 然而, 研究显示, 个人经验证实, 我们经常在与我们实际想要的不相符的时刻做出选择: 我们可以盲目地或短视地选择激励用户的快乐。 在这项工作中, 我们开发了一个媒体消费模式的模式, 用户有不一致的偏好选择。 我们考虑的是, 一个仅仅想要最大限度地提高用户效用的平台, 只能以用户参与的形式观察行为数据, 我们的模式产生一种与过度理解的逻辑框架相关的现象, 在日常经验中, 但却很难在传统用户互动模式内容中找到它们是如何理解的。 一个关键的因素是, 如何优化设计平台, 如何在用户的构建一个潜在的设计平台时, 如何以最优化的。