This seminar explores the conceptual foundations of artificial intelligence and offers practical guidance on using and evaluating AI tools responsibly in academic research.
This book provides a comprehensive foundation in Artificial Intelligence, exploring intelligent agents, state-space search algorithms, knowledge representation, machine learning paradigms, reasoning systems, and ethical AI implications for next-generation intelligent applications.
Inaugural Message [...]
New approaches to evaluating progress of AI should be built around diversity, partnership, and systemicity.
This seminar explores how to treat artificial intelligence as a configurable research method rather than a chatbot or generic software tool. It provides a rigorous framework for validating AI-enabled workflows, designing defensible studies, and making scientific claims that remain consistent with the available evidence...
This article implores clinicians to consider whether artificial intelligence models may induce delusionlike beliefs—and how to help overcome this phenomenon.
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