WebXAII: an open-source web framework to study human-XAI interaction

Reproducibility gap in XAI research: Currently, researchers studying how humans interact with AI explanations typically build custom interfaces that aren't shared publicly, making it difficult for other scientists to reproduce or build upon their work—WebXAII addresses this by providing a reusable platform.

Democratizing XAI research: The framework is designed so that researchers can implement experimental protocols with "minimal programming skills" by using structured configuration files, potentially opening up human-XAI interaction research to a broader range of scientists who may lack extensive software development expertise.

Standardizing human-AI interaction studies: By providing a common platform that can "embody full experimental protocols" and record participant responses, WebXAII enables more consistent and comparable studies across different research groups investigating how people understand and trust AI explanations.

Addressing real-world AI adoption challenges: The paper emphasizes that XAI research is expanding due to "growing societal implications" of AI adoption across diverse applications, suggesting that better tools for understanding human-XAI interaction are critical for responsible deployment of AI systems in society.

Open-source approach to responsible AI: By making WebXAII open-source and shareable, the framework supports transparency and collaborative research practices that are foundational to developing more trustworthy and understandable AI systems.