SEATTLE, June 21, 2022 /PRNewswire/ — Will intelligent machines ever replace lawyers, doctors, computer programmers and world leaders? What about composers, painters and novelists? Are we just wetware, natural computers doomed to obsolescence by the overpowered artificial intelligence of tomorrow? A pioneer in computer intelligence says “no way”.
Non-Computable You explains how humans are unique and why artificial intelligence will never replicate you.
Robert J. Marks, II most recent book, Uncomputable You: What You Do That Artificial Intelligence Will Never Do (Discovery Institute Press 2022) explains how humans are unique and why artificial intelligence will never replicate humans.
In You not calculable Marks answers these and other fascinating questions with his mix of whimsy and expertise. Take a look at the geniuses behind today’s AI – their weaknesses, their follies and their friendships – as told by someone inside. Under the author’s constant and engaging guidance, discover the exciting possibilities of artificial intelligence, but also discover how many of the captivating claims about AI are grossly overstated. Marks shows why there are powers the AI will never possess, no matter what. These powers belong to another, to you not calculable.
“The emotions that make us human will never be replicated by a machine,” Marks says. “These include compassion, love, empathy, elation, sadness, fear, anger, disgust, pleasure, pride, excitement, embarrassment, regret, jealousy, grief, hope, and faith. Properly defined, creativity, sensitivity, and understanding are also on the list. These and other non-algorithmic traits are proof that you cannot be calculated.
Robert J. Marks Ph.D., is Emeritus Professor of Electrical and Computer Engineering at Baylor University. He is director of the Walter Bradley Center for Natural and Artificial Intelligence at the Discovery Institute and hosts the Mind Matters Podcast. Marks is a member of the Institute of Electrical and Electronic Engineers (IEEE) and the Optical Society of America. He was founding chair of the IEEE Neural Networks Council and served as editor of the IEEE Transactions on Neural Networks. He is co-author of the books Neural Smithing: Supervised Learning in Artificial Neural Networks Feedforward (MIT Press) and Introduction to Scalable Computing (scientific world).
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SOURCE Discovery Institute