Quotes About Problem-solving

One way to look at design—any kind of design—is that it's essentially about constraints

The most challenging part of programming is conceptualizing the problem, and many errors in programming are conceptual errors. Because

Hurrying to solve a problem is one of the most time-ineffective things you can do.

Dijkstra pointed out that no one's skull is really big enough to contain a modern computer program (Dijkstra 1972), which means that we as software developers shouldn't try to cram whole programs into our skulls at once; we should try to organize our programs in such a way that we can safely focus on one part of it at a time.

An algorithm gives you the instructions directly. A heuristic tells you how to discover the instructions for yourself, or at least where to look for them.

The problem is that we are not trained to discriminate when the mind is useful and when it is not, and we have not developed the skills to shift out of a fused problem-solving mode of mind into a descriptively engaged mode of mind.

As human beings increasingly look inward, life begins to seem more like a problem to be solved than a process to be fully experienced.

Consider the kind of questions that kids ask. Sure, they may be silly or simplistic or out of bounds. But kids are also relentlessly curious and relatively unbiased. Because they know so little, they don't carry around the preconceptions that often stop people from seeing things as they are. When it comes to solving problems, this is a big advantage.

Whatever problem you're trying to solve, make sure you're not just attacking the noisy part of the problem that happens to capture your attention.

Incentives are the cornerstone of modern life. And understanding them—or, often, deciphering them—is the key to understanding a problem, and how it might be solved.

The fact is that solving problem is hard. If a given problem still exists, you can bet that a lot of people have already come along and failed to solve it. Easy problems evaporate; it is the hard ones that linger. Furthermore, it takes a lot of time to track down, organize, and analyze the data to answer one small question well.

But when it comes to solving problems, one of the best ways to start is by putting away your moral compass.

first is about problem solving generally. Kobayashi redefined the problem he was trying to solve. What question were his competitors asking? It was essentially: How do I eat more hot dogs? Kobayashi asked a different question: How do I make hot dogs easier

So when it comes to solving problems, channeling your inner child can really pay off. It all starts with thinking small.

But when it comes to solving problems, one of the best ways to start is by putting away your moral compass. Why? When you are consumed with the rightness or wrongness of a given issue—whether it's fracking or gun control or genetically engineered food—it's easy to lose track of what the issue actually is.

After all, just because you're at the office is no reason to stop thinking.

Innovations usually begin life with an attempt to solve a specific problem, but once they get into circulation, they end up triggering other changes that would have been extremely difficult to predict.

Wagner found that after an initial exposure to the numerical test, "sleeping on the problem" more than doubled the test subjects' ability to discover the hidden rule. The mental recombinations of sleep helped them explore the full range of solutions to the puzzle, detecting patterns that they had failed to perceive in their initial training period. The work of dreams turns out to be a particularly chaotic, yet productive, way of exploring the adjacent possible.

Innovations usually begin life with an attempt to solve a specific problem, but once they get into circulation, they end up triggering other changes that would have been extremely difficult to predict. This is a pattern of change that appears constantly in evolutionary history.

But the finest minds of the era were also devoted to an equally pressing question: What are we going to do with all of this shit?

The individuals in the high-IQ group might have scored better individually on intelligence tests, but when it came to solving problems as a group, diversity matters more than individual brainpower.

Good ideas are like the NeoNurture device. They are, inevitably, constrained by the parts and skills that surround them.

imagine a business problem as a maze. One person might be motivated to make it through the maze as quickly and safely as possible in order to get a tangible reward, such as money—the same way a mouse would rush through for a piece of cheese. This person would look for the simplest, most straightforward path and then take it. In fact, if he is in a real rush to get that reward, he might just take the most beaten path and solve the problem exactly as it has been solved before.

be one of the key functions of the lab conference. In Dunbar's research, outsiders working on different problems were much less likely to dismiss the apparent error as useless noise. Coming at the problem from a different perspective, with few preconceived ideas about what the "correct" result was supposed to be, allowed them to conceptualize scenarios where the mistake might actually be meaningful.