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

TL;DR

This paper explores how software practitioners perceive the socio-emotional gap in human-AI collaboration, emphasizing the importance of functional capabilities over replicating human socio-emotional intelligence for effective teamwork.

Contribution

It introduces the concept of functional equivalents—technical capabilities that enable effective collaboration without mimicking human socio-emotional traits.

Findings

Practitioners view AI as intellectual teammates, not social partners.

Socio-emotional gap is seen as a functional gap, not a failure to exhibit SEI.

Functional design of AI can achieve collaborative outcomes similar to human SEI.

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.