Hey there, time traveller!
This article was published 20/8/2019 (604 days ago), so information in it may no longer be current.
Ottawa has just invested $30 million in food processing innovation as part of the $1 billion directed to five innovation clusters. Proponents of this collaboration of Prairie industry, universities, and government believe that "this supercluster will make Canada a leading source for plant proteins and, ultimately, feed the world."
Will such collaboration work, without great scientists/innovators/entrepreneurs leading the work?
Traditionally we have deified the inventor/entrepreneur. James Watt, Thomas Edison, Henry Ford, Bill Gates, Jeff Bezos, Albert Einstein, Steve Jobs, Mark Zuckerberg, and Elon Musk are household names standing astride modern technology and economy. Our inventors stand at the core of the modern economy.
As an aside, the names I used are all men. Will we see great women inventors who become household names? Maybe, perhaps not in the short term ... and not because women cannot be inventors. Understanding this reveals the "innovation in innovation" that is marking technical advance in the 21st century.
Women certainly have the "smarts" to invent. I saw a terrific movie recently about Hedy Lamarr, the legendary Hollywood beauty of the 1940s and '50s. However, she also harboured a secret as the co-inventor of a technique for cloaking communications. That invention has evolved as an important element of modern cellphone and communications technology.
Three reasons have relegated the era of the "great" inventor to the past, if the notion was even ever valid.
First, historians of technology now see a multitude of forces creating the conditions for innovation. In their groundbreaking work, The Sources of Invention, Jewkes, Sawers and Stillerman argue that the great inventors of the past actually just happened to be in the right place at the right time. Inventors such as James Watt relied on decades of smaller innovations and a multitude of discoveries by lesser known tinkerers.
In Bourgeois Equality: How Ideas, Not Capital or Institutions, Enriched the World, Diedre McCloskey writes of the myriad of small innovations that serve as the foundations for progress that contribute "brick by brick" to economic progress. Discovery Channel’s How It’s Made, shows this perfectly — every process and machine on that TV show reveals how the myriad of small tweaks of anonymous inventors support constant improvement.
Second, the process of science and invention have changed. For example, an international quartet of scientists, Jennifer Doudna. Emmanuelle Charpentier, Martin Jinek and Feng Zhang — two women and two men — are at the forefront of CRISPR, the current hot technology for genetic modification. While Nobel prizes are probable for any or all of these scientists, none will likely become household names, unlike the innovators I cited at the start.
I wanted to measure the changing context of scientific collaboration. So, I used the prestigious science journal Nature as my source, examining the authorship of the articles for the last week of June for 2019 and the last week of June for 1969 — two test weeks 50 years apart. In particular I wanted to gain a sense for numbers of authors for the "articles" and "letter", the core research studies published by this journal. I had the idea that papers with multiple authors would be associated with more collaboration in science and that this has increased over time. I was amazed at the results.
In 1969 the typical study had 2.3 authors. None had more than seven authors and most had one or two. In 2019, the average number of authors jumped to 18.3 per article. None had a single author and only one had two authors. Most had multiple authors, with one at 40 authors and another at an astounding 87… for a five-page article! Moreover, these teams of authors represented multiple research centres and universities globally. Truly, science has become collaborative and international.
Third, and finally, artificial intelligence is rapidly becoming an indispensable partner in all intellectual activity. In pharmacy, for example, discovering new medications requires sifting through many possible combinations of compounds just to identify potential candidates for clinical trials. One of the challenges to discovery is the volume of data that scientists must process. Computer-aided or "machine learning" where researchers team with machines is indispensable for scientific progress.
The lone scientist and inventor will recede into the myths of history and it is likely that no one man or woman will ever become as well known as the inventors I cited. As a middle-rank, resource-based economy, $1 billion invested in super-clusters seems large, but my sense is that it is nowhere near enough and rather than regional, the real action will be international.
Gregory Mason is an associate professor of economics at the University of Manitoba.