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In an Era of Tech Innovation, Whispers of Declining Research Productivity
Productivity rates have not grown over the past several decades despite the large expansion of the overall research effort
Wall Street Journal
By Irving Wladawsky-Berger
Jul 13, 2018 12:41 pm ET

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In a 2009 paper, The Burden of Knowledge and the �Death of the Renaissance Man�: Is Innovation Getting Harder?, Northwestern economist Benjamin Jones argued that �If innovation increases the stock of knowledge, then the educational burden on successive cohorts of innovators may increase.� His theory is based on two simple observations.

First, �innovators are not born at the frontier of knowledge.� They must undertake considerable education to reach the frontiers of knowledge where the majority of innovation takes place. Individuals can only absorb knowledge at a limited rate, so their education occupies considerable time and a significant portion of their lives.

Second, the stock of knowledge has been rapidly expanding across most disciplines, over the past 150 years, and particularly over the past several decades. If reaching the frontiers of knowledge requires standing on the shoulders of giants, �one must first climb up their backs, and the greater the body of knowledge, the harder this climb becomes.�

Innovators can compensate for this increasing knowledge burden in two key ways. They can choose to learn more, thus continuing to lengthen their education. Or they can become more specialized, narrowing their area of expertise and forcing them to work in teams of innovators with complementary specialized expertise.

Mr. Jones presented evidence that both, longer educational periods and greater specialization, are actually happening. PhD�s have been taking longer in most fields, and additional postdoctoral training is often required for leading-edge academic and research positions. Analysis of a rich patent data set shows that the age of first patent has been increasing over time at a substantial rate. A similar analysis also shows that more and more research is being conducted by teams, and the size of the teams has been going up over the years. He further shows that teamwork and specialization are greater in fields with deeper knowledge.

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If gifted children today will need more training than they would 50 years ago to get the frontiers of knowledge, this argues for accelerating their early education. They do not need 13 years to learn what is being taught in K-12.

Originally Posted by WSJ piece

Digital innovation is recombinant in nature, based on building blocks and platforms. In this view, �the true work of innovation is not coming up with something big and new, but instead recombining things that already exist.�

I had started a lengthy-ish response to the OP as I read through that article, but stopped when I read the bit above, which is an updated form of this statement from the late 19th century:

Originally Posted by Albert Michelson, circa 1894

� it seems probable that most of the grand underlying principles have been firmly established � the future truths of physical science are to be looked for in the sixth place of decimals.

Research has two branches: normal and revolutionary. Normal research works within existing models to develop them as far as possible (in a sense, to the metaphorical sixth place of decimals). Examples: GPS systems, technology enabling confirmation that gravity waves exist, stuff that comes out of Silicon Valley. Revolutionary research, on the other hand, upends an existing model. Examples of revolutionary research: relativity, natural selection, calculus.

Both branches are essential for scientific progress. Unfortunately, today, many people labor under the false assumption that teamwork --- which is inherently normal science --- is the only way forward. There's too much knowledge! Gone are the days of lone researchers making big discoveries! Wrong: this outlook shows a complete misunderstanding of how revolutionary research works. Teamwork is A way forward in normal science, but not the sole way forward in the research endeavor, and it is highly unlikely to yield a revolutionary discovery.

I'll add only that if teamwork is increasing, yet (meaningful) output is decreasing, perhaps teamwork is not living up to its reputation.

Diminishing marginal returns for the average stock of education is what we�re seeing. In large part, this is because the proportion of what Val calls normal research has grown as a share of the total pool of research conducted. IOW, a lot of tinkering, without much genuine discovery.

I�d argue our problem is also partly cultural. The pursuit of PhDs strongly favours risk aversion in research mandates (i.e. chasing grant money for topics known by government funders.) If the vast majority of our researchers expect cushy lifestyles on the other side of their PhD or postdoctoral work, and universities are bowing to political pressure to pump out imminently marketable research, then the shortening of the pure research cycle is also core to the problem. Real, revolutionary work requires an open mandate to chase down lots of tangents. Sadly, the academic model rarely supports that degree of exploration.

Prospect theory says we�re cognitively biased against accurate measurements of extremely improbable, strong upside events. Yup.