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The controversy surrounding AI pioneer Geoffrey Hinton’s Nobel Prize misses the point

The recent Nobel Prize awarded to Geoffrey Hinton for his contributions to artificial intelligence (AI) has sparked controversy, exposing a deeper problem of how society rewards innovation. While Hinton is celebrated for his pioneering work in artificial intelligence and for popularizing backpropagation, critics, including artificial intelligence expert Jürgen Schmidhuber, argue that the award overlooks the seminal contributions of Paul Werbos and Shun-Ichi Amari—two figures whose ground-breaking work decades ago laid the foundation for modern neural networks. Werbos’ 1974 PhD thesis and Amari’s 1972 adaptive learning model were essential stepping stones, but their efforts were largely overshadowed by the visibility of later figures such as Hinton.

The Nobel Prize – the highest honor in science – should recognize the full spectrum of contributions. The oversight in Hinton’s case reflects a broader misunderstanding of innovation itself. The myth of the lone genius, often embodied by figures like Steve Jobs and Elon Musk, dominates public narratives, leading us to believe that major breakthroughs happen in isolation. In reality, most progress results from cumulative, collaborative efforts. While Hinton’s recognition is well-deserved, it highlights a common flaw in how credit is distributed: The contributions of early pioneers often fade from view as those who build on their work take center stage.

This is not a problem unique to AI. The history of technology is full of similar stories. Steve Jobs didn’t invent the iPhone from scratch. The iPhone was the product of incremental innovations in smartphones, just as the Macintosh borrowed heavily from innovations developed at Xerox PARC. Jobs’ brilliance lay in perfecting these technologies, making them intuitive and accessible to the masses. As Jobs himself acknowledged, “Good artists copy, great artists steal,” a nod to the reality that innovation often involves improving existing ideas rather than creating something entirely new.

Elon Musk’s association with Tesla provides another telling example. Musk joined Tesla in 2004, years after it was founded by Martin Eberhard and Marc Tarpenning. While Musk is often credited with revolutionizing the electric vehicle industry, electric cars have been around for over a century. Musk’s genius was not in inventing electric vehicles, but in turning the concept into a desirable, scalable and profitable product. Tesla’s success came not from invention, but from relentless execution and refinement, pushing the boundaries in battery technology and autonomous driving.

This dynamic is central to Silicon Valley, where companies routinely build on existing ideas and take them to new heights. Facebook (now Meta) didn’t invent social networking—MySpace and Friendster had already created the category. Google wasn’t the first search engine – AltaVista and others existed long before that. What made Facebook and Google successful was their ability to refine and scale these concepts worldwide. Silicon Valley’s real strength lies not in creating entirely new technologies, but in improving and expanding existing ones.

Artificial intelligence follows a similar path. Hinton’s work was essential, but it rested on the shoulders of earlier research. The contributions of Werbos and Amari were instrumental in the development of neural network techniques that would later lead to breakthroughs such as AlphaGo and OpenAI’s GPT. These technologies did not materialize out of thin air – they were the result of decades of incremental progress. Focusing too much on individual numbers distorts the reality of technological progress, which is almost always a collaborative, multi-layered process.

This brings us to a fundamental truth about innovation: being the first to develop an idea is not as important as being the one to refine it, scale it, and execute it effectively. Innovation is not about singular genius, but about collective progress. When we credit only the most visible figures, we miss the contributions of those who laid the groundwork for the discoveries.

The controversy surrounding Hinton’s Nobel Prize should trigger a reassessment of how we recognize innovation. The seminal work of Werbos and Amari deserves greater recognition, as their early efforts were instrumental in enabling Hinton’s advances. Innovation is rarely the product of one person’s genius – it’s a collaborative journey built on incremental improvements over time.

Looking ahead, the most significant advances in AI and other technologies will likely come not from those who invent entirely new concepts, but from those who can refine and adapt existing ideas to meet new challenges. Tesla’s success was not in creating the electric vehicle, but in making it something desirable, scalable and practical. Apple’s triumph was not about inventing the smartphone or the personal computer, but about making them accessible and indispensable.

True innovation is measured not by where an idea begins, but by how it evolves, how it is improved, and how it transforms industries. The innovators we celebrate should include not only those who popularize ideas, but also those who lay the groundwork for those breakthroughs. Only by recognizing this wider network of collaborators can we fully appreciate how progress really happens.

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