Can Requirements Engineering Support Explainable Artificial Intelligence? Towards a User-Centric Approach for Explainability Requirements
This work addresses the problem of AI opacity for stakeholders by suggesting a user-centric approach, but it is incremental as it builds on existing RE practices.
The paper tackles the challenge of making AI systems more explainable by exploring synergies between requirements engineering and Explainable AI, proposing a framework and research directions to address XAI issues.
With the recent proliferation of artificial intelligence systems, there has been a surge in the demand for explainability of these systems. Explanations help to reduce system opacity, support transparency, and increase stakeholder trust. In this position paper, we discuss synergies between requirements engineering (RE) and Explainable AI (XAI). We highlight challenges in the field of XAI, and propose a framework and research directions on how RE practices can help to mitigate these challenges.