This is a course on Privacy and Artificial Intelligence. You will find all the reading texts available. The author has tried the best to get the accurate information but if there is a mistake, please comment.
Course Objectives for "Privacy and Artificial Intelligence" (June 2025)
Understand the fundamental privacy-related problems introduced by artificial intelligence, including excessive data collection, unauthorized access, lack of transparency, and regulatory complexity.
Develop an understanding of how AI systems can impact user rights, consent management, and the integrity of personal data.
Gain insight into the nature and consequences of algorithmic bias, discrimination, and AI hallucinations in real-world applications.
Comprehend the challenges associated with cross-border data transfers, vendor and third-party risks, and the global compliance landscape.
Recognize the importance of privacy and security by design in AI development and the principles of data minimization and robust access controls.
Understand the significance of transparency, explainability, and dynamic consent management in building user trust and meeting regulatory requirements.
Appreciate the role of privacy-enhancing technologies (PETs), continuous monitoring, and incident response in maintaining AI system integrity and compliance.
Understand the responsibilities and best practices for different stakeholders, including governments, organizations, vendors, employees, industry groups, international bodies, consumers, and the public, in protecting privacy within the AI ecosystem.
Develop an awareness of practical checklists and frameworks that guide privacy protection efforts for each stakeholder group.
Gain a comprehensive perspective on how collaboration, training, and adaptive governance contribute to effective privacy management in the context of artificial intelligence.
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