Artificial Intelligence for Human Behavior Analysis is an emerging field at the intersection of computer science, psychology, and cognitive science. This course introduces the fundamental principles of behavior analysis, demonstrating how emotions, motivations, and social interactions influence human decision-making. Learners will explore how AI observes, decodes, and interprets behavior through various modalities, including speech, text, images, and video. By understanding how data is transformed into measurable patterns, participants gain a strong foundation in both theory and practice, preparing them for real-world applications.

The course highlights core AI techniques used in behavior analysis, including machine learning, neural networks, natural language processing, and computer vision. Learners discover how these models process multimodal data, including facial expressions, gestures, voice tone, and written communication, to uncover emotional states and social dynamics. Practical case studies demonstrate AI in action, with applications in healthcare, where it detects early signs of depression; in education, where it tailors lessons to student engagement; and in business, where it analyzes consumer preferences. Challenges such as overfitting and interpretability are also discussed.

Beyond technical skills, the course emphasizes ethical and social considerations in applying AI to human behavior. Topics include data privacy, fairness, informed consent, and the dangers of biased algorithms reinforcing stereotypes. Learners reflect on how misuse can lead to surveillance risks or harmful outcomes in sensitive domains like healthcare and justice. At the same time, frameworks for transparency and responsible design are presented. By the end, participants will be equipped to apply AI thoughtfully, striking a balance between innovation and respect for human dignity.