提出评估AI对话对齐人类沟通规范的新框架
Conversational Alignment with Artificial Intelligence in Context
- 基于语用学理论构建CONTEXT-ALIGN框架
- 指出当前大模型在对话上下文处理上存在根本局限
- 适合关注AI伦理与人机交互的研究者阅读
基于大语言模型的智能对话系统发展，引发了关于人类规范、价值观与实践如何影响AI设计与性能的重要问题。本文探讨了AI代理在对话中与人类交际规范和上下文处理实践保持一致的含义，并提出了评估开发者设计选择的新框架。首先，结合哲学与语言学中的会话语用学文献，提出一套期望标准，即CONTEXT-ALIGN框架，以实现对话对齐。随后指出，当前大语言模型（LLM）的架构、约束与功能可能对实现完全对话对齐构成根本性限制。
原文摘要 · Abstract (English)
The development of sophisticated artificial intelligence (AI) conversational agents based on large language models raises important questions about the relationship between human norms, values, and practices and AI design and performance. This article explores what it means for AI agents to be conversationally aligned to human communicative norms and practices for handling context and common ground and proposes a new framework for evaluating developers' design choices. We begin by drawing on the philosophical and linguistic literature on conversational pragmatics to motivate a set of desiderata, which we call the CONTEXT-ALIGN framework, for conversational alignment with human communicative practices. We then suggest that current large language model (LLM) architectures, constraints, and affordances may impose fundamental limitations on achieving full conversational alignment.
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