While it is undoubtedly true that there are areas that require individuals with Tiger’s precocity and clarity of purpose, as complexity increases — as technology spins the world into vaster webs of interconnected systems in which each individual only sees a small part — we also need more Rogers: people who start broad and embrace diverse experiences and perspectives while they progress. People with range.

The most momentous personality changes occur between age eighteen and one’s late twenties, so specializing early is a task of predicting match quality for a person who does not yet exist. It could work, but it makes for worse odds. Plus, while personality change slows, it does not stop at any age. Sometimes it can actually happen instantly.

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Short-term rehearsal gave purely short-term benefits. Struggling to hold on to information and then recall it had helped the group distracted by math problems transfer the information from short-term to long-term memory. The group with more and immediate rehearsal opportunity recalled nearly nothing on the pop quiz. Repetition, it turned out, was less important than struggle. It isn’t bad to get an answer right while studying. Progress just should not happen too quickly,

In 1998, he helped organize the first “advanced chess” tournament, in which each human player, including Kasparov himself, paired with a computer. Years of pattern study were obviated. The machine partner could handle tactics so the human could focus on strategy. It was like Tiger Woods facing off in a golf video game against the best gamers. His years of repetition would be neutralized, and the contest would shift to one of strategy rather than tactical execution. In chess, it changed the pecking order instantly. “Human creativity was even more paramount under these conditions, not less,” according to Kasparov. Kasparov settled for a 3–3 draw with a player he had trounced four games to zero just a month earlier in a traditional match. “My advantage in calculating tactics had been nullified by the machine.” The primary benefit of years of experience with specialized training was outsourced, and in a contest where humans focused on strategy, he suddenly had peers. A few years later, the first “freestyle chess” tournament was held. Teams could be made up of multiple humans and computers. The lifetime-of-specialized-practice advantage that had been diluted in advanced chess was obliterated in freestyle. A duo of amateur players with three normal computers not only destroyed Hydra, the best chess supercomputer, they also crushed teams of grandmasters using computers. Kasparov concluded that the humans on the winning team were the best at “coaching” multiple computers on what to examine, and then synthesizing that information for an overall strategy. Human/Computer combo teams — known as “centaurs” — were playing the highest level of chess ever seen. If Deep Blue’s victory over Kasparov signaled the transfer of chess power from humans to computers, the victory of centaurs over Hydra symbolized something more interesting still: humans empowered to do what they do best without the prerequisite of years of specialized pattern recognition.

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In England and Wales, students were expected to pick a path with knowledge only of the limited menu they had been exposed to early in high school. That is sort of like being forced to choose at sixteen whether you want to marry your high school sweetheart. At the time it might seem like a great idea, but the more you experience, the less great that idea looks in hindsight. In England and Wales, adults were more likely to get divorced from the careers they had invested in because they settled down too early.

Deep analogical thinking is the practice of recognizing conceptual similarities in multiple domains or scenarios that may seem to have little in common on the surface. It is a powerful tool for solving wicked problems, and Kepler was an analogy addict, so Gentner is naturally very fond of him.

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In 2009, Kahneman and Klein took the unusual step of coauthoring a paper in which they laid out their views and sought common ground. And they found it. Whether or not experience inevitably led to expertise, they agreed, depended entirely on the domain in question. Narrow experience made for better chess and poker players and firefighters, but not for better predictors of financial or political trends, or of how employees or patients would perform.

The benefits to increased match quality . . . outweigh the greater loss in skills.” Learning stuff was less important than learning about oneself. Exploration is not just a whimsical luxury of education; it is a central benefit.

Career goals that once felt safe and certain can appear ludicrous, to use Darwin’s adjective, when examined in the light of more self-knowledge. Our work preferences and our life preferences do not stay the same, because we do not stay the same.

In professional networks that acted as fertile soil for successful groups, individuals moved easily among teams, crossing organizational and disciplinary boundaries and finding new collaborators. Networks that spawned unsuccessful teams, conversely, were broken into small, isolated clusters in which the same people collaborated over and over. Efficient and comfortable, perhaps, but apparently not a creative engine.

The challenge we all face is how to maintain the benefits of breadth, diverse experience, interdisciplinary thinking, and delayed concentration in a world that increasingly incentivizes, even demands, hyperspecialization.