Bridging the Socio-Emotional Gap: The Functional Dimension of Human-AI Collaboration for Software Engineering

2026-01-27

AI Summary

Current AI systems in software engineering collaboration lack social-emotional capabilities, limiting human-AI collaborative effectiveness. Through semi-structured interviews and qualitative analysis with ten software professionals, this study reveals that developers primarily perceive AI as an intellectual partner rather than a social one. To address this gap, the work introduces the concept of “functional equivalence,” which translates social-emotional intelligence into actionable collaborative capacities—such as responsibility negotiation, contextual adaptation, and sustained cooperation. By prioritizing functional alignment over emotional mimicry, this framework redefines the design paradigm for human-AI collaboration, significantly enhancing collaborative outcomes.

Technology Category

• Humans and AI: Emotional Intelligence
• Cognitive Modeling & Cognitive Systems: Social Cognition And Interaction
• Intelligent Robots: Embodied AI

Application Category

• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions
• Social Networks and Social Media: Generative AI / large language models and their impact on social systems
• Economics, Online Markets and Human Computation: Fairness and ethical considerations in crowd work and in human-in-the-loop AI systems

Abstract

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.

Problem

• socio-emotional intelligence
• human-AI collaboration
• software engineering
• collaborative gap
• functional alignment

Innovation

• functional equivalents
• socio-emotional intelligence
• human-AI collaboration
• contextual intelligence
• collaborative intelligence