The roots of innovation ecosystems
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Innovation ecosystems recapitulate the behavior of natural ecosystems in many ways. One of these is that they undergo ecosystem succession. Just as scrapy pioneer species literally prepare soil for more complex communities to develop in nature, so do scrapy thinkers and entrepreneurs create the conditions for intermediate institutions, and eventually complex innovation communities, to thrive.
If innovation ecosystems undergo ecological succession in the same way that natural ones do, then it is fruitful to ask: In what order does this succession occur? What factors cause one type of ecosystem to transition into another? Where does this process begin? A natural place to begin this line of questioning is with the university, and particularly the research university.
The modern research university, just like our modern usage of the term “innovation”, began evolving toward its current state after the second world war.
The existential threat of the war years meant that academic scientists around the world were effectively conscripted to support their country’s military in developing technologies for war. Those expelled by their country of origin, including, decisively, most of continental Europe’s Jewish scientists, took up positions in the US or UK. In all but a few cases, they were quickly integrated into the military-scientific machine. Never-before-seen sums of money were lavished on scientists and engineers. In return the government was to decide, at least at a high level, how it was spent.
Vannevar Bush, then the Director of the US Office of Scientific Research and Development (superseded by the NSF) proposed that the then unprecedented government support of academic science be continued into the post-war era.
Institutions that are now seen as bedrocks of innovation in the US and the world - MIT, Harvard, Stanford, UC Berkeley - solidified these positions by hosting massive military research programs on their campuses, in effect calling “dibs” on the best and brightest scientists and engineers available. MIT’s Rad Lab, Harvard’s Computation Lab, Berkeley’s Radiation Lab, and later, MIT’s Semi-Automatic Ground Environment air defense system (SAGE), employed hundreds of scientists each and became central to the inventions of RADAR, SONAR, nuclear energy, and computers, as well as a host of new materials and devices.
The end of war in 1945 meant the prospect of the government winding down support for research to pre-war levels. Universities across the country would be left with empty buildings and scientists of all stripes left without jobs. No doubt already hearing rumblings of this from his perch in Washington, DC, Vannevar Bush penned a now-famous letter to President Roosevelt arguing that government support for science should not be diminished after the war, but simply re-oriented toward fighting a new “war of science against disease.” Bush’s proposal, though not implemented in its details, laid the conceptual groundwork for the centrality of the NSF and NIH in postwar research. Both his letter, since published as “Science, the Endless Frontier”, and Roosevelt’s response merit a read by anyone interested in the history of scientific research.
To this day, the majority of basic research research in the US is conducted by professors and graduate students on university campuses, funded in large part by government agencies. Roosevelt's initial vision of a “war of science against disease” also persists; more than half of all government funding for research remains dedicated to advancing human health.
Chart: Federally financed academic R&D expenditures, by agency and field: FY 2018
One other major government intervention is important to note as we consider how University-based innovation came to be what it is today: the Bayh-Dole act of 1980. When government agencies took center stage in funding university research post World War II, they also became some of the largest recipients of US patents; Anything invented using government funds was, by default, government property. This posed a problem, however, as the government was unwilling to grant exclusive patent rights to any company. How could you give private entities exclusive access to technologies owned and paid for by taxpayers? But without exclusive rights, private entities were unwilling to invest the large sums of money required to further develop and commercialize them. Why would they? Any competitor could come to Uncle Sam, get access to the same patent, and free-ride off of their investment? As a result, private industry saw academic research as “contaminated” by government funding. With no one willing to invest in commercializing them, the majority of academic innovations ended up gathering dust on a shelf. By 1978 the government had received over 28,000 patents from it’s funding of University research. Fewer than 4% had ever been licensed.
Bayh-Dole brought these inventions back into play with a simple remedy: transferring the rights of patent ownership from the government agency that funded the research to the institution where it was conducted. Universities were now able to negotiate licenses - including exclusive licenses - with whomever they saw fit. And they did. The results were felt across the economy, but most acutely by the biotech industry, where commercialization of academically-discovered drugs skyrocketed.
Chart: The number of drugs discovered annually in the course of public sector research that eventually received FDA approval.
Over the course of the 20th century, the innovation ecosystem of the US evolved from the bare rock and lichen of the pre-war system, where small numbers of scrappy researchers competed for limited private resources, to a stable, intermediate ecosystem centered around the university and underwritten by the public via government agencies.
The first shift in the 1940s- from private to public funding of research - stabilized the soil for permanent innovation ecosystems to form around universities, especially in major cities
The second shift in the 1980s- from public to private ownership of research-derived patents - provided the nutrients needed for the resulting innovations to grow and bear fruit and for new “species” of companies (startups) and capital (venture capital) to evolve.
Forty years apart, each of these shifts represented a major perturbation to the US research ecosystem that drastically altered it’s structure and the arrangement of its parts, from where innovation takes place, to who funds it, to who owns it’s outputs.
While much has changed since the 1980s, more has stayed the same. The major players - tech transfer offices, venture capitalists, startups, corporate acquirers - act and interact in much same way that they did forty years ago. They have evolved, certainly. They have experimented with new strategies around the margins. Niche players have emerged to fill valuable gaps. A few climax ecosystems, especially Boston and SF, have grown dense and fruitful. But the playbooks for TTOs, VCs, and startups remain - with some tweaks here and there - relatively unchanged.
What’s Next?
We are now forty years on from Bayh Dole and it seems reasonable to ask: are we due for another major shift?
We’ll leave it to the experts to speculate on what the next major perturbation will be; it may be a fool’s errand, as these things are notoriously resistant to prediction. But based on the past, one might venture a few (obvious?) thoughts on what things may look like after it occurs.
The most highly specialized players of today’s order are the most vulnerable. Their degree of adaptation to the existing ecosystem structure - today a great strength - is exactly what makes them most vulnerable to exogenous shocks to it.
The apex species of the next alignment are already here. Like mammals before the K-Pg extinction event, they are just waiting for conditions to shift in their favor.
The “food chain” (i.e. the flow of capital) will look drastically different. Entire categories of innovation funders (VCs?) and innovation buyers (big Pharma?) will go extinct.
Universities will still play a major role. Like crocodilians, universities seem to benefit from punctuated equilibrium, making them extremely resilient to exogenous forces.
Each of these themes deserves its own post, which we hope to return to in the next year. In the meantime, we would love to hear your thoughts.
Which players in today’s ecosystem do you think are most vulnerable to a major perturbation?
How will the future food chain look different from today’s? Who will be on top?
What roll will research universities play?
Email or leave a comment to let us know what you think!
What we’re reading:
How to Build a GPT-3 for Science. This year was a breakthrough year for AI. How do we harness these breakthroughs for science? A16Z argues: "we need tools that can “treat scientific publications as substrates to be combined and analyzed at scale” and then fed into emerging AI models. Incidentally, this is what we are building with Portal Stargaze. More on that, here.
How Do We Make an Entrepreneurial State? (🔒) - We need institutions that can combine the agility of a startup with the stability of the state. But how?
Are Technologies Inevitable? (Long Read) - To what degree does innovation follow the laws of Darwinian evolution? What does this mean for those who conduct and fund research?