Teaching Empathy in Software Engineering Education in the Age of Artificial Intelligence

TL;DR

This paper explores how empathy can be integrated into software engineering education, especially in the context of AI, by analyzing teaching practices that embed empathy into technical coursework.

Contribution

It provides a structured framework of five categories for operationalizing empathy in AI-related software engineering education, emphasizing core development activities.

Findings

Empathy can be embedded within core development activities.

Five categories operationalize empathy: societal framing, fairness, diversity, stakeholder awareness, reflection.

Practices support reasoning about bias, accessibility, and societal impact.

Abstract

Empathy has been discussed as a relevant human capability in software engineering, particularly in activities that require understanding users, stakeholders, and the societal implications of technological systems. This relevance becomes more pronounced in the context of artificial intelligence, where software increasingly participates in decisions that affect diverse individuals and communities. However, limited guidance exists on how empathy can be integrated into technical software engineering education in ways that connect with the development of AI-enabled systems. This study investigates teaching practices that educators use to incorporate empathy into software engineering courses. Using qualitative analysis of educator-reported practices, we identified five categories through which empathy is operationalized within technical coursework: societal framing of AI systems, fairness and accessibility considerations in design and evaluation, representation of diverse users, stakeholder role awareness and responsibility, and structured reflection and feedback during development processes. The findings indicate that empathy can be embedded within core development activities rather than taught as a separate topic, enabling students to reason about bias, accessibility, accountability, and the societal consequences of AI technologies. These results contribute a structured view of how empathy-oriented practices can be incorporated into software engineering education to support the preparation of students who will develop AI-enabled systems.