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""AI Data"" explores the increasing role of artificial intelligence in education and its profound ethical implications. It investigates how student data is collected, processed, and used, often before careful consideration of privacy rights. The book highlights the growing use of algorithmic decision-making, where AI algorithms make critical decisions about students, and emphasizes the need for fairness, transparency, and accountability in AI deployment within educational settings. Did you know that seemingly innocuous data points, when aggregated, can create detailed student profiles? This raises concerns about potential misuse by educational institutions and third-party vendors discussed in the book. The book uniquely deconstructs the ""black box"" of AI in education, providing a framework for understanding the technical aspects of AI systems and evaluating potential biases.
""AI Data"" progresses systematically, starting with fundamental AI and data analytics concepts like machine learning, and then delving into data collection practices, algorithms, and ethical implications. It culminates in exploring solutions and best practices for responsible AI implementation, focusing on policy recommendations and technical safeguards.
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