Food for thought!
"Can old scientists learn new tricks?
Famed polymath Sir Isaac Newton did much of his work developing calculus in the mid-1660s, when he had not yet celebrated his 25th birthday.
Albert Einstein’s “annus mirabilis,” during which he published the revolutionary papers that would become the foundation of modern physics, occurred when he was only 26 years old.
And Maria Skłodowska-Curie was just 31 when she discovered radium and polonium.
These anecdotes give the impression that scientists hit their creative peak relatively early in their careers, an idea that has been supported by some studies. Other research, however, has found no such relationship between age and declining creativity, while one theory holds that more experienced researchers are better poised to generate new ideas. According to a Policy Article published yesterday in Science, the relationship between age and innovation may be more complicated than that.
The authors of the new study analyzed a dataset of more than 12.5 million scientists who published between 1960 and 2020.
They found that, as the years since initial publication increased, scientists became more adept at forging links between previously unconnected ideas.
At the same time, however, their capacity for truly disruptive innovation—work that overturns established paradigms with transformative breakthroughs—sharply declined.
This cycle held true across disciplines, from computer science to biology.
The study authors also note the existence of a “nostalgia effect,” in which scientists increasingly cite older papers as their career progresses. “These findings highlight a universal tension between science’s forward momentum and aging scientists’ growing attachment to the intellectual past,” the team writes.
The researchers also found that nations with younger scientific workforces, such as China and India, tend to produce a larger share of disruptive papers.
The United States, which has a comparatively older workforce (in part thanks to a 1994 Supreme Court decision that removed mandatory university retirement), has lower rates of disruption. “Together with the nostalgia effect, these results suggest that familiarity with established ideas narrows the scope of creative search,” the study authors write. “Aging scientists grow more adept at recombining what they know but become less inclined (or able) to abandon old concepts and replace them with new ones.”
Of course, referencing foundational papers and building on existing knowledge remains an integral part of the scientific enterprise. “Aging people are not less creative, they are just creative differently ,” ...
find ways to balance novelty with disruption, he argues, potentially by encouraging more collaborations across generations and welcoming young scientists from other nations. ...
Even the greatest minds, the study authors note in their paper, risk becoming set in their ways as they age.
In his later years, for example, Einstein struggled to develop a unified field theory and refused to accept the rise of quantum mechanics.
Speaking of quantum theory, physicist Werner Heisenberg published his pioneering work on the subject in 1925, when he was just 23 years old."
From the abstract:
"Scientific careers today are marked by growing polarization:
A small number of scientists now remain active and influential for longer than ever , whereas many others pass through research as temporary workers.
Lengthened training periods, the elimination of mandatory retirement, and funding systems that reward experience have concentrated resources among senior scientists.
As science becomes increasingly dependent on its aging core, a central question arises: How does academic age influence creativity?
The answer has long divided scholars. Analyzing more than 12.5 million scientists who published between 1960 and 2020,
we find that novelty—the linking of previously unconnected ideas—increases with academic age,
whereas disruption—the replacement of established ideas with new ones—declines.
These and other findings invite reflection on potential implications for policy, such as funding, tenure, and promotion systems; immigration and mobility; workforce development; and incentives for (and barriers to) collaboration and innovation."
ScienceAdviser
