Barry Smith, Jobst Landgrebe

Why Machines Will Never Rule the World: Artificial Intelligence without Fear

24:05 min
Philosophy & Ideology, Health & Science
342 pages, 2022

While artificial intelligence achievements dominate headlines with promises of machines surpassing human capabilities, Landgrebe and Smith challenge, exposing the mathematical barriers preventing artificial general intelligence. The problem lies in widespread misconceptions about AI's potential, fueling both unrealistic expectations and fears about machine dominance over humanity. Their work systematically dismantles AGI claims by examining human intelligence as a complex biological system that cannot be computationally modeled, analyzing why machines cannot master language, social behavior, or consciousness itself. Through evidence from mathematics, physics, linguistics, and biology, the authors demonstrate that current AI successes represent sophisticated statistical processing rather than genuine intelligence. This short provides clarity amid AI hype, showing that while narrow AI will transform many industries, the dream of human-level machine intelligence remains mathematically impossible.

Barry Smith

Barry Smith is Distinguished Julian Park Professor of Philosophy at the University at Buffalo and one of the most widely cited contemporary philosophers with over 700 publications. He serves as Director of the National Center for Ontological Research and is the lead developer of Basic Formal Ontology, which became the first piece of philosophy to achieve international standardization status. His pioneering work in applied ontology has been funded by major institutions including the National Institutes of Health and the Department of Defense. Smith's interdisciplinary contributions bridge theoretical philosophy with practical applications in biomedical informatics and data science.

Chapters

AGI promises ignore fundamental mathematical barriers that prevent comprehensive modeling of complex systems, making artificial general intelligence impossible despite decades of optimistic predictions and current AI successes in narrow domains.
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