弥合社会情感鸿沟：面向软件工程的人机协作的功能维度
Bridging the Socio-Emotional Gap: The Functional Dimension of Human-AI Collaboration for Software Engineering
AI总结：
本文研究了人机协作中社会情感鸿沟问题，提出通过功能等效设计实现有效协作，而非复制人类情感智能特征。
摘要：
随着生成式人工智能模型被用于支持软件工程师及其开发团队，理解有效的人机协作（HAIC）变得越来越重要。社会情感智能（SEI）增强了人类队友之间的协作，但其在HAIC中的作用仍不清楚。当前的AI系统缺乏人类在团队合作中带来的SEI能力，这在协作动态中可能产生潜在的鸿沟。在本研究中，我们调查软件从业者如何看待HAIC中的社会情感鸿沟，以及AI系统需要哪些能力才能实现有效的协作。通过与10名从业者进行半结构化访谈，我们考察他们如何思考与人类队友或AI队友协作，重点是他们的SEI期望以及他们所设想的AI能力。结果表明，从业者目前将AI模型视为智力队友而非社交伙伴，并期望AI模型比人类队友表现出更少的SEI属性。然而，他们认为社会情感鸿沟不是AI无法展现SEI特征的失败，而是在协作能力上的功能鸿沟（AI无法协商责任、适应性地调整或维持持续的合作关系）。我们引入了“功能等效”概念：技术能力（内部认知、情境智能、适应性学习和协作智能）能够实现与人类SEI属性相当的协作结果。我们的发现表明，与AI进行有效协作以完成SE任务可能从功能设计而非复制人类SEI特征中获益，从而重新定义协作为功能对齐。
英文摘要：
As GenAI models are adopted to support software engineers and their development teams, understanding effective human-AI collaboration (HAIC) is increasingly important. Socio-emotional intelligence (SEI) enhances collaboration among human teammates, but its role in HAIC remains unclear. Current AI systems lack SEI capabilities that humans bring to teamwork, creating a potential gap in collaborative dynamics. In this study, we investigate how software practitioners perceive the socio-emotional gap in HAIC and what capabilities AI systems require for effective collaboration. Through semi-structured interviews with 10 practitioners, we examine how they think about collaborating with human versus AI teammates, focusing on their SEI expectations and the AI capabilities they envision. Results indicate that practitioners currently view AI models as intellectual teammates rather than social partners and expect fewer SEI attributes from them than from human teammates. However, they see the socio-emotional gap not as AIs failure to exhibit SEI traits, but as a functional gap in collaborative capabilities (AIs inability to negotiate responsibilities, adapt contextually, or maintain sustained partnerships). We introduce the concept of functional equivalents: technical capabilities (internal cognition, contextual intelligence, adaptive learning, and collaborative intelligence) that achieve collaborative outcomes comparable to human SEI attributes. Our findings suggest that effective collaboration with AI for SE tasks may benefit from functional design rather than replicating human SEI traits for SE tasks, thereby redefining collaboration as functional alignment.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
