Artificial intelligence is often discussed in terms of extremes. Some people predict that AI will soon surpass human intelligence and take over society. Others fear catastrophic outcomes from powerful machines.
In a recent GeekPlanet podcast interview, Dr. Donald C. Wunsch II offered a calmer and more realistic perspective. Drawing on decades of experience in engineering and artificial intelligence, Wunsch argues that the real issues with AI are not science fiction threats but human choices, policy failures, and hype.
A Career Built on Engineering Reality
Dr. Donald Wunsch is an endowed professor of electrical and computer engineering at Missouri University of Science and Technology. He also directs the Kummer Institute for Artificial Intelligence and Autonomous Systems. Over his career, Wunsch has worked on neural networks, adaptive systems, machine learning, and AI engineering. He is a Fellow of the IEEE, a rare and prestigious honor that recognizes major contributions to the field.
But what really makes Wunsch stand out is his focus on what AI can actually do today. Instead of speculating about artificial general intelligence, which would match or exceed human intelligence, he concentrates on real world systems that engineers build and deploy right now. His recent paper, notably titled “Artificial General Intelligence Is Nowhere Near, Artificial Specific Stupidity Is Already Here,” challenges both over optimism and fear-based narratives about AI.
Lessons from the early days: at one time, the industry opposed neural networks
During the interview, Robert J. Marks and Donald Wunsch reflected on their early work in artificial intelligence, especially in neural networks, which is loosely inspired by some ideas from neuroscience.
In the late twentieth century, neural networks faced strong opposition from supporters of symbolic AI and expert systems. Funding dried up, and many researchers abandoned the field.
Wunsch and others persisted. Over time, neural networks proved their value and became central to modern machine learning and deep learning. Wunsch emphasized that progress in AI often requires patience and resilience.
Being told you are wrong does not always mean you are wrong. Sometimes it means the field has not caught up yet.
These experiences shaped Wunsch’s cautious attitude toward current AI claims. Having lived through past cycles of hype and disappointment, he is skeptical of bold predictions that ignore technical limits and practical constraints.
The Kummer Institute and cross-campus AI
Missouri Science and Technology University’s Kummer Institute was created through a major gift from alumnus Fred Kummer. The institute supports AI research across many disciplines, not just engineering.
Rather than focusing on flashy demonstrations, the Institute emphasizes thoughtful development and responsible use of AI. Wunsch supports faculty proposals, helps define a long term vision for AI at the university, and mentors researchers and students. This cross-discipline approach reflects his belief that AI should be shaped by many fields, including economics, ethics, and social science.
Cutting through the hype
Wunsch personally curates articles from sources such as the New York Times and the Wall Street Journal. His goal is to provide high signal and low noise content.
On the podcast, he offers the opinion that much of what is written about AI today is exaggerated or misleading. Headlines are designed for clicks, not for understanding. By filtering out hype, he hopes readers can better understand both the promise and the limits of AI. This effort reflects his broader concern that public misunderstanding can lead to poor policy and misuse of technology.
Real risks come from human decisions
A central theme of Wunsch’s work is that how humans design, deploy, and control AI systems pose the real risks. Concentrated power, lack of oversight, and careless policy decisions can cause harm long before machines become truly autonomous.
Today’s systems, he argues, often fail in narrow and predictable ways. These failures can still be serious when AI is used in areas like finance, healthcare, or defense. Calling these systems intelligent can mask their weaknesses and encourage blind trust. Wunsch uses the phrase “artificial specific stupidity” to describe systems that perform well in limited tasks but fail badly outside them.
A balanced way forward
He offers a grounded and thoughtful voice in a noisy AI debate. He does not deny the value of artificial intelligence, nor does he dismiss future possibilities. Instead, he urges engineers, policymakers, and the public to focus on reality rather than speculation.
AI, as Wunsch sees it, is a powerful tool shaped by human hands. Its future depends less on machines becoming conscious and more on whether society can use technology wisely. By emphasizing engineering realism, historical perspective, and careful judgment, Wunsch reminds us that progress does not require panic or blind optimism. It requires understanding, responsibility, and humility.
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