Innovation is often treated as if it begins and ends with a powerful idea. Eugene Fitzgerald, the Merton C. Flemings SMA Professor in MIT’s Department of Materials Science and Engineering, argues for a different view in his latest book, The Invisible Engine: Why Innovation Evades Control.
Drawing on a decade of work with large research programs, Fitzgerald describes innovation as a process that depends on many actors, shifting conditions, and the hard work of turning knowledge into value. His argument is especially pointed at a time when artificial intelligence is changing how people think about knowledge, research, and invention.
Innovation as a system, not a spark
Fitzgerald’s core point is that innovation is commonly misunderstood because it is too often reduced to the first discovery. In his view, discovery matters, but it is only one part of a larger system.
That system brings together science, economics, industry, and society. Fitzgerald says his book grew out of work in research-to-market activity, including the MIT and Masdar Institute Cooperative Program and the MIT-Singapore Alliance for Research and Technology. These programs were not only about producing knowledge inside one field. They required people to connect research with markets, institutions, and implementation.
Traditional academic journals can record discoveries inside individual disciplines. Fitzgerald’s concern is that large collaborative projects often lack a comparable intellectual framework. When science, economics, and society meet at scale, the work becomes harder to describe, measure, and guide.
That gap led him to focus on the innovation process itself. What began as a practical attempt to help complex research programs work became a broader effort to explain how innovation can move from possibility toward impact.
What Fitzgerald means by the invisible engine
The phrase “invisible engine” refers to a decentralized form of collective intelligence. It includes people and companies whose separate actions can eventually produce surprise in the marketplace.
Fitzgerald connects that idea to Frank Knight, an economist from the early 1900s who studied the Industrial Revolution. Knight’s focus was the entrepreneur. In Fitzgerald’s account, the entrepreneur takes on uncertainty by bringing something into the world before the outcome is known.
The reward comes when the market is surprised: people want the thing, and it can actually be made or delivered. Because the entrepreneur reaches that opportunity first, profit becomes possible.
This framing matters because it shifts attention away from control. Innovation, in this account, is not a machine that an institution simply programs. It is an evolving process in which uncertainty, discovery, application, and adoption interact.
The strained silicon lesson
Fitzgerald’s own experience with semiconductor technologies shaped the book’s ideas. At AT&T Bell Laboratories in the 1990s, he co-invented strained silicon, a technology that helped extend Moore’s Law. The source describes Moore’s Law as the semiconductor industry’s long-standing trend of increasing the number of transistors on chips roughly every two years.
At Bell Labs, Fitzgerald and a colleague found a way to strain silicon in thin-film form with very few defects. As physics, it was a major result. But Fitzgerald wanted the discovery to matter outside scientific recognition, so he asked his manager what should happen next.
The answer was to talk to the marketing people at AT&T. Looking back, Fitzgerald says that made sense because even strong industrial labs could create many things they could not always commercialize.
His path then moved through MIT, a startup, and wider industry adoption. A settlement with Intel followed a patent dispute, after the industry found that strained silicon was needed to extend Moore’s Law. Fitzgerald emphasizes that this path was not a detour from innovation. It was the innovation process itself.
Three kinds of research investment
One of Fitzgerald’s main criticisms is that people often treat research investment as if it has one purpose and one path to economic impact. He separates it into three categories, each with a different role.
- Altruistic science: This is investment in academic institutions with the purpose of producing educated people. Fitzgerald says it is not carried out in the context where ideas must later succeed, and he describes the direct economic yield over the years as basically zero.
- Strategic research: This work is organized around a goal rather than a single field of science or technology. Fitzgerald uses a new F-35 as an example, where the customer, in this case the government, needs advances from multiple domains to come together.
- Fundamental innovation: This category covers the full route from research to economic growth, including 10-, 15-, or 20-year time horizons. It keeps technology, implementation, and market in view at the same time.
For Fitzgerald, fundamental innovation is different because it must hold three variables together. Technology asks what is physically possible. Implementation asks how something can be built and delivered. Market asks who will adopt it, and why.
That combination makes innovation a moving target. Researchers may be advancing the science while the world around them is also changing. Market applications, new technology options, and implementation realities all have to be considered before value can emerge.
Who needs this way of thinking
Fitzgerald says he wrote the book for several audiences: individual innovators and students; researchers and faculty; corporate leaders; research funders; and policy-makers. These groups all face versions of the same question: how to invest in the far future when outcomes cannot be fully known in advance.
The answer offered in The Invisible Engine is not a formula. It is a more realistic picture of how innovation works. Ideas matter, but they do not become valuable by themselves.
Innovation requires contact with the world. It needs science, economics, implementation, markets, institutions, and people willing to work through uncertainty. Fitzgerald’s argument is that the future is shaped less by isolated breakthroughs than by the long, uneven process that turns research into something society can actually use.