The Computers Are Social Actors paradigm suggests people exhibit social/anthropomorphic biases in their treatment of technology. Such insights have encouraged the design of interfaces that interact with users in more social (chatty or even friend-like) ways. However, in typical `dark pattern' fashion, social-emotional responses to systems as (seemingly sentient) agents can be harnessed to manipulate user behaviour. An increasingly common example is app notifications that assume person-like tones to persuade or pressure users into compliance. Regardless of being manipulative, difficulties meeting contextual social expectations can make automated social acting seem rude, invasive, tactless, and even disrespectful - constituting 'social' anti-patterns. This paper explores ways to improve how automated systems treat people in interactions. We mixed four qualitative methods to elicit user experiences and preferences regarding how automated systems "talk" to/at them. We identify an emerging 'social' class of dark and anti-patterns, and propose guidelines for helping (social) interfaces treat users in more respectful, tactful, and autonomy-supportive ways.

翻译：“计算机即社会行为者”范式表明，人们在对待技术时会表现出社会性/拟人化倾向。这类见解激励了以更社交化（闲聊式甚至类似朋友）方式与用户交互的界面设计。然而，在典型的“暗模式”套路中，将系统视为（看似有感知能力的）主体所引发的社会情感反应，可能被用于操纵用户行为。一个日益常见的例子是采用拟人口吻的应用程序通知，以此劝说或施压用户顺从。即便不考虑其操纵性，若无法满足情境化的社交期望，自动化社交行为也可能显得粗鲁、侵犯性、不得体甚至不尊重——构成“社交”反模式。本文探索了改善自动化系统与用户互动方式的可能性。我们结合四种定性方法，收集用户对自动化系统如何与/向他们“交谈”的体验与偏好。研究识别出一类新兴的“社交”暗模式与反模式，并提出指南，帮助（社交）界面以更尊重、得体且支持用户自主性的方式对待用户。