The ideas in Ignorance by Stuart Firestein, surprisingly, reiterate and clarify many principles of designing and building great web products. The ideas aligned well enough that I kept thinking I was reading a startup book. Now that I think of it, it’s one of the best startup books I’ve read in a long time.
Putting out the science vibes
At the start he shows that facts are the building blocks for a new question — not a hypothesis. A question is more valuable than a hypothesis. You can get attached to a hypothesis and fight for its survival long past its expiration date.
The facts serve mainly to access the ignorance. As a scientist, you don’t do something with what you know to defend someone, treat someone, or make someone a pile of money. You use those facts to frame a new question — to speculate about a new black cat. In other words, scientists don’t concentrate on what they know, which is considerable and minuscule, but rather on what they don’t know.
With every answer to every question, a scientist can build a collection of facts. This becomes more and more opportunity to connect better and better questions.
But how does a scientist use facts beyond simply accumulating them? As raw material, not as finished product. In those facts is the next round of questions, improved questions with new unknowns. Mistaking the raw material for the product is a subtle error but one that can have surprisingly far-reaching consequences. Understanding this error and its ramifications, and setting it straight, is crucial to understanding science.
This is starting to become a fascinating and counterintuitive analogy. A product you sell to someone is not the “finished product” at all, it’s a means to another end. How it’s used will give access to more questions about how people might use it in the future. Design is never done.
Being a scientist requires having faith in uncertainty, finding pleasure in mystery, and learning to cultivate doubt. There is no surer way to screw up an experiment than to be certain of its outcome.
This is getting back to framing something up as a question instead of a hypothesis. Once you start looking for a specific outcome, you start blinding yourself to potential uses of your facts. Big breakthroughs come through an unexpected combination of facts that reveal a new question with huge potential.
The problem with the dichotomy between basic and applied research is that it is fundamentally false — that’s why it never seems to get solved and we endlessly oscillate back and forth in favor of one, then the other — as if they were two things and not just one research effort. Following ignorance often leads to marvelous inventions. But trying to take short cuts, to short circuit the process by going directly to the application, rarely produces anything of value.
Whoa! This nails the problem of building solutions without first knowing what questions you’re trying to ask. If you’re attempting to create value immediately, you’re missing all the opportunities to find the questions that make a larger, more meaningful impact. Value creation is a side-effect of pursuing bigger and better questions.
Great scientists, the pioneers that we admire, are not concerned with results but with the next questions. The eminent physicist Enrico Fermi told his students that an experiment that successfully proves a hypothesis is a measurement; one that doesn’t is a discovery. A discovery — an uncovering — of a new ignorance.
If you try something that doesn’t work it’s not a failure, it’s access to more questions that can reveal deeper needs of your customers. There’s a good chance a “failure” is the only way to discover a flawed perception. If you’re continually “succeeding” with your research, you may not be asking interesting enough questions and they’ll lead you to a dead end.
Something can be unknown, and you test it out for a bit, but then you can see, often pretty quickly, that it is not connected to other things that are unknown and therefore it is not likely to be interesting or worthy of pursuit. If it seems as though you are working away on a project and nothing that anyone else is doing or has done becomes helpful to your work, then you begin to think that you are perhaps in some cul-de-sac of irrelevance. This happens to graduate students quite often. They start a project with a question that is mostly untouched or has received little attention. But some ways into it, the data doesn’t seem to lead anywhere, they keep proving the same small thing over and over again, and eventually there is nothing to do but abandon the project. So connectedness seems to be an important quality.
This is a brilliant example of getting excited about doing something new without realizing that isn’t attached to larger questions. Young companies can hit their local maximum quickly by attacking a non-connected problem and later have to change their strategy. A fetish for the new can be keeping you stuck in a cul-de-sac of irrelevance (I love that phrase).
Each week doctoral and postdoctoral students in labs around the world scour the pages of these journals for the latest finding in their field and then try to think of the next experiment so they can get to work on their Nature paper. But of course it’s already too late; the folks who wrote that paper have already figured out the next experiments—in fact, they’ve probably just about finished them. I have a colleague who always suggests that his students look not to yesterday’s issue of Nature or Science for experimental ideas but rather to work that is at least 10 years or more old. This is work that is ready to be revisited, ready for revision. Questions still lurk in the data, questions that have now ripened and matured, that could not be answered then with the available techniques. More than likely they could not even have been asked because they didn’t fit any current thinking. But now they come alive, suddenly possible, potential, promising.
Problems with the most potential may have been “solved” and have become stale. They no longer satisfying their audience. These types of problems are difficult to spot and rarely show up on our radar. Fortunately, these problems have established markets and include profitable companies that prove people are willing to invest in the problem.
About the Book
The first half is high level concepts. The second half is case studies fleshing out concepts in detail. If you’re in a hurry you should at least read the first half — it alone is worth the price of the book.
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