EXPLAINABLE ARTIFICIAL INTELLIGENCE FOR SMART CITY

Authors : Dr. E. LOGASHANMUGAM

part of The Research Monograph Series in Computing, Electrical & Communication Networks book series

Notes

Explainable Artificial Intelligence (XAI) is a growing field that aims to create machine learning models and algorithms that are transparent and interpretable by humans. In the context of smart cities, XAI can be used to help citizens and decision-makers understand how AI systems are making decisions that affect their daily lives. Smart cities rely on data and machine learning algorithms to make decisions about everything from traffic flow to public safety. However, these systems are often opaque and difficult for non-experts to understand. XAI can help to address this issue by providing explanations for the decisions made by AI systems in a way that is accessible and understandable to citizens. For example, imagine a smart city system that uses machine learning to predict traffic patterns and adjust traffic lights in real-time. With XAI, citizens could be provided with an explanation for why a particular light was changed or why a certain route was recommended. This would help citizens to trust and understand the system, and could even lead to improvements in the system’s performance as citizens provide feedback on the explanations.

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Dr. E. LOGASHANMUGAM

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