Explainable AI Applications for Human Behavior Analysis by P. Paramasivan Paperb
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In the paper titled “Explainable AI Applications for Human Behavior Analysis” by P. Paramasivan, the author explores the use of explainable artificial intelligence (AI) in analyzing human behavior.
The paper discusses how AI technologies can be used to analyze and understand human behavior in various contexts, such as healthcare, education, and social media. By using explainable AI, researchers and practitioners can gain insights into why individuals behave in certain ways, and how these behaviors can be influenced or changed.
The author highlights the importance of transparency and interpretability in AI models, especially when dealing with sensitive topics such as human behavior. By providing explanations for the AI’s decisions and recommendations, users can better understand and trust the technology.
Overall, the paper emphasizes the potential of explainable AI in improving our understanding of human behavior and guiding interventions to promote positive changes. It serves as a valuable resource for researchers, practitioners, and policymakers interested in leveraging AI for behavior analysis.
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