Do Generative AI Tools Ensure Green Code? An Investigative Study

TL;DR

This study investigates the environmental sustainability of AI-generated code from ChatGPT, BARD, and Copilot, revealing that current tools often produce non-green code and highlighting the need for improved sustainable practices.

Contribution

It provides an initial assessment of the sustainability of AI-generated code, emphasizing the default non-green behavior of popular generative AI tools.

Findings

AI tools often generate non-green code by default

Current AI tools lack sustainable coding practices

Further research is needed for eco-friendly AI code generation

Abstract

Software sustainability is emerging as a primary concern, aiming to optimize resource utilization, minimize environmental impact, and promote a greener, more resilient digital ecosystem. The sustainability or "greenness" of software is typically determined by the adoption of sustainable coding practices. With a maturing ecosystem around generative AI, many software developers now rely on these tools to generate code using natural language prompts. Despite their potential advantages, there is a significant lack of studies on the sustainability aspects of AI-generated code. Specifically, how environmentally friendly is the AI-generated code based upon its adoption of sustainable coding practices? In this paper, we present the results of an early investigation into the sustainability aspects of AI-generated code across three popular generative AI tools - ChatGPT, BARD, and Copilot. The results highlight the default non-green behavior of tools for generating code, across multiple rules and scenarios. It underscores the need for further in-depth investigations and effective remediation strategies.