Major technological breakthroughs don’t drive productivity on their own—people do. Drawing on historical examples from early industrialization and firsthand experience developing FBI fingerprint recognition systems, this article argues that progress comes from learning by doing, not simply adopting more powerful tools. In every case, the biggest gains emerged when individuals closest to the work experimented, refined processes, and improved systems through hands-on use.
The same principle applies to artificial intelligence today. While much of the AI conversation centers on model size and technical benchmarks, most real economic value will come from how workers and organizations integrate AI into everyday workflows. Across industries—from software and manufacturing to healthcare and finance—AI performs best when treated as a learning system, continually improved by the people who use it, rather than as a static piece of capital equipment.
The article concludes that the future of AI depends on broad-based participation, not a small technical elite. A “Digital Land-Grant” approach to education and workforce development would prioritize practical experience, enabling professionals across fields to adapt, improve, and collaborate with AI tools. As history shows, transformative revolutions are won not by better machines alone, but by better tinkerers—and the AI era will be no different.
Former Federal Reserve Bank President, Wharton Dean, and university leader, Dr. Patrick Harker offers rare insight at the intersection of economics, policy, and innovation. With deep experience in both the public and private sectors, he breaks down complex issues into clear, actionable takeaways for today’s business and civic leaders. Contact us today to bring Harker to your next speaking event.
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