Generative AI models perturb the foundations of effective human communication. They present new challenges to contextual confidence, disrupting participants' ability to identify the authentic context of communication and their ability to protect communication from reuse and recombination outside its intended context. In this paper, we describe strategies--tools, technologies and policies--that aim to stabilize communication in the face of these challenges. The strategies we discuss fall into two broad categories. Containment strategies aim to reassert context in environments where it is currently threatened--a reaction to the context-free expectations and norms established by the internet. Mobilization strategies, by contrast, view the rise of generative AI as an opportunity to proactively set new and higher expectations around privacy and authenticity in mediated communication.

翻译：生成式人工智能模型扰乱了人类有效沟通的基础。它们对语境信心提出了新的挑战，破坏了参与者识别沟通真实语境的能力，以及保护沟通不被在预期语境之外重复使用和重新组合的能力。在本文中，我们描述了旨在应对这些挑战、稳定沟通的策略——包括工具、技术和政策。我们讨论的策略分为两大类。遏制策略旨在重新确立当前受到威胁的环境中的语境——这是对互联网建立的无语境期望和规范的反应。而动员策略则将生成式人工智能的兴起视为一个机会，主动在媒介沟通中设定关于隐私和真实性的新的、更高的期望。