A Japanese Macaque on the cover of Life. (Photo credit: Wikipedia)
Sometime in 1952, Imo started having problems: strange humans were offering her food and spying on her. As a two-year-old female Japanese macaque on Koshima Island, she typically ate a wide variety of plants, fungi, and fruits. But now here were these Japanese biologists coming along with notebooks, luring her into a new habitat with sweet potatoes.
One annoying thing was that these biologists would scatter sweet potatoes on a sandy beach, away from her home in the forest. Imo’s troop would have to pick each potato up, and then rub the sand off with their hands, a somewhat laborious task. It was an unexpected and novel difficulty because the troop was used to eating on surfaces without sand. But Imo made a curious discovery. She noticed that if she dipped a sand-covered sweet potato in the water, she could clean it much faster.
Five years later, the practice of sweet potato washing had spread throughout most, but not all, of Imo’s troop. Four out of five young and middle aged monkeys had adopted Imo’s innovation, but one peculiar observation was that older monkeys remained conservative. Only eighteen percent of the senior monkeys, all of them female, learned the new habit. The majority of the old stuck to toilsome hand-scrubbing.
Two years later, the Japanese biologists decided to try a new one on Imo’s troop. This time they scattered wheat on the beach. To eat the wheat, the monkeys would have to pick out the grains one by one from thousands of particles of sand. If cleaning sand off a potato was difficult, picking grains out of sand had to be much worse. Now four-years-old, Imo—surprise, surprise—innovated again. She discovered that she could scoop handfuls of mixed sand and grain and then toss the mix out onto the water. The heavier sand would sink and the lighter wheat grains were left floating. She could harvest them with ease off the water’s surface.
The spread of skimming wheat off the water followed the same pattern as the spread of potato washing. First younger monkeys would adopt it, slightly older and very young monkeys would follow on, but then much older monkeys would lag or resist completely.
Sociologists have described a technology adoption life cycle, which represents the way an invention spreads throughout a community. It’s depicted as a bell curve where the x-axis represents time and the y-axis represents the number of adopters.
Imo, oddly preternatural, was on the left side of the curve…twice. (There’s a saying in Silicon Valley: once you’re lucky; twice you’re good.) She was young and she was inventive. The oldest monkeys resisted her ideas. For humans, this story is as old as Babylon and as recent as social media. Cures for cancer notwithstanding, early adopters of new products and practices tend to be younger. Laggards tend to be older.
The wild, speculative question is whether the inclinations underlying this pattern are woven into the fabric of our DNA.
Now, to be sure, we could ask questions about how accurate the Japanese biologists’s observations were. This is one study of one snow monkey troop in the 1950s, admittedly not a big sample size. I’ve taken this account of Imo from chapter seven of E.O. Wilson’s monumental book, Sociobiology: The New Synthesis. Maybe innovations by other monkeys went undocumented. It could simply be random chance.
Still, it makes you wonder. Why do mathematicians, rock stars, poets, scientists, and chess players have peak years of creativity during their 20s and 30s? Why do the young tend to be more innovative than the old?
The theory of fluid and crystallized intelligence provides some clues. Fluid intelligence refers to the ability to solve novel problems. It doesn’t involve specific knowledge or long-term memory of facts. Tests using spatial relationships, speed of processing, and working memory aim to measure it. Crystallized intelligence, on the other hand, involves all the facts, skills, and knowledge accumulated throughout life.
It is true that older people are wiser than younger people because they’ve acquired more knowledge. But the research on fluid and crystallized intelligence indicates that fluid intelligence peaks around twenty and then declines without reversal.
This hardening of the mind raises an interesting question when combined with a broad global trend: the demographics of aging populations in Europe, Japan, the United States, and other high income countries. For instance, in 2010, the median age in Japan was 45; in 2030, the UN projects it will be 52. Germany is only slightly behind. In 2010, its median age was 44; in 2030 it will be 49. Similar trends hold for most European countries, too.
The standard concern is that the expanding retiree bulge threatens the stability of pension and health care programs. At some tipping point in the near future there will be too few workers to support a far greater number of retirees. And that’s true.
But a much larger concern looms. If the young tend to be more creative and to adopt new ideas more readily than the old, then the coming demographic changes—rising median ages across the West—portend a strong headwind for innovation in the next decades. Not only will we have fewer workers, but we’ll also have fewer inventors and what new ideas we have will face stronger resistance.
It’s already happening.
Benjamin Jones, an economist at Northwestern University, has gathered data on the careers of innovators and scientists over the last century. What he found is that careers are starting and peaking much later than they used to—the mean age at which innovators launch their first inventions has increased by eight years since 1900, from 23 to about 31 today; and the average age for greatest achievement, the age at which Nobel Prize winners write their best papers and inventors create their breakthrough technologies, rose by about six years in the same time period.
And the delay has a downside. Even though people are living longer, Jones's research shows we do not see a shift in the productivity of innovators beyond middle age. They start later than they used to, but they still slow down in their 50s, which means the late start truncates careers and limits the number of discoveries. The overall effect is even stronger if we allow that scientists and innovators tend to take more risks and do their best work when they are young.
Maybe we’re not so different from Japanese macaques after all.
