Explainable AI for Sustainability: Bridging Trust, Ethics, and Accountability
Praveen Kumar Myakala, Anil Kumar Jonnalagadda · Advances in intelligent systems research/Advances in Intelligent Systems Research · 2025
Artificial intelligence (AI) has shown immense potential for addressing sustainability challenges, from optimizing energy systems to advancing precision agriculture.However, the opacity of many AI systems undermines trust, accountability, and ethical alignment, limiting their adoption in high-stake domains.This study highlights the importance of integrating Explainable AI (XAI) into sustainability applications to improve transparency and stakeholder trust.We propose a three-pillar framework centered on technical innovation, stakeholder participation, and policy alignment, supported by case studies in renewable energy optimization and precision agriculture.These examples demonstrate how XAI fosters ethical decision making, improves resource efficiency, and promotes environmental justice.Finally, we discuss future research directions for scaling XAI solutions in various sustainability contexts while ensuring fairness and accountability.