Great Power Brings Great Responsibility: Personalizing Conversational AI for Diverse Problem-Solvers

TL;DR

This paper explores personalizing conversational AI for diverse problem-solvers in open source software, aiming to improve accessibility and reduce bias in AI-driven support for newcomers.

Contribution

It proposes adapting AI responses to different problem-solving styles using persona-based prompt engineering to enhance inclusivity in OSS onboarding.

Findings

AI personalization can improve support for diverse problem-solving styles

Persona-based prompt engineering offers a promising strategy

Further research is needed to refine AI tools for OSS support

Abstract

Newcomers onboarding to Open Source Software (OSS) projects face many challenges. Large Language Models (LLMs), like ChatGPT, have emerged as potential resources for answering questions and providing guidance, with many developers now turning to ChatGPT over traditional Q&A sites like Stack Overflow. Nonetheless, LLMs may carry biases in presenting information, which can be especially impactful for newcomers whose problem-solving styles may not be broadly represented. This raises important questions about the accessibility of AI-driven support for newcomers to OSS projects. This vision paper outlines the potential of adapting AI responses to various problem-solving styles to avoid privileging a particular subgroup. We discuss the potential of AI persona-based prompt engineering as a strategy for interacting with AI. This study invites further research to refine AI-based tools to better support contributions to OSS projects.