Research Summary: Generative AI May Reinforce Social Biases in Software Engineering Education

Generative Artificial Intelligence (GenAI) systems, despite their widespread deployment, pose a risk of reinforcing social biases if not carefully evaluated. This risk is particularly pronounced in educational settings, where early exposure to biased systems can influence students' interests and career paths. Research indicates that GenAI use by software engineering instructors, specifically in tasks like team formation and educational content generation, may inadvertently perpetuate software-specific social biases.

Why it matters

The pervasive integration of Generative AI across various domains necessitates a critical examination of its societal impacts, particularly concerning bias reinforcement. Unmitigated biases in educational tools can negatively impact talent development, diversity, and innovation within critical sectors like software engineering, potentially shaping an unrepresentative future workforce.

Key insights

• GenAI deployment without thorough evaluation can lead to unintended consequences, including the amplification of stereotypes and social biases.
• The educational sector is particularly vulnerable to these risks, as early-stage interactions with biased systems can shape student trajectories.
• Specific investigations into GenAI use by software engineering instructors highlight the potential for reinforcing software-specific social biases.
• Representative tasks examined include GenAI-assisted team formation based on student profiles and the generation of visual content for educational materials.

Source

arXiv — Computers and Society — https://arxiv.org/abs/2609.28483