True Believers

The researchers who study the science of science funding look to venture capitalists and angel investors with curiosity and awe. They wonder if or how the lessons from startup investors can inform science funding. How can they stomach the risk and failure? Why can't science funding do the same?

A good example is the dialog between Carl Bergstrom and Paula Stephan after her “Practices and Attitudes Regarding Risky Research” presentation at the Metascience 2019 conference:

Bergstrom: "I completely agree with your analysis of the mental frame of review panels and insuring against failure, that's totally consistent with my experience. I never thought I would stand up in spitting distance of Sand Hill Road and tell 300 people we should start emulating VC culture. But, that said, [VCs] are almost comically doing the opposite — going for the 100X and everything else can fail fast, if it's only making 3X we're not interested. What can we do, if anything — what should we do, if anything — to import aspects of that decision making model into scientific funding?"

Stephan: "I think first of all it's really important to remind reviewers why we're funding research, as a government particularly... I think a lot of reviewers totally lose sight of the rationale of what brought the funding to the table, and don't think about the portfolio at all, and don't think about the fact that they need to invest — at least part of it — on the long shot..."

Bergstrom: “Is it because we can more easily measure the value and weigh them against the costs, in VC land?”

From an outside point of view, it can seem like a math problem. VCs are able to better measure returns against cost to justify the lost bets. Or maybe it’s a systemic problem. The peer-review panels are designed to avoid and avert risk.

Those aspects are part of the story but they overlook a critical element of the Silicon Valley ecosystem. It has less to do with money and process and more to do with creating a culture of belief. The great new companies and technological breakthroughs always start small and at the edge, just like scientific discoveries. They usually involve a group of outsiders who believe in each other and an idea, even though it's covered in reasons not to work. They're able to find just enough traction to stay alive and grow, while simultaneously peeling off doubt and sharpening the concept through experimentation. Navigating the path from wild idea to rigorously-tested breakthrough involves persistence and sustained belief.

Importantly, this belief is not certainty or blind faith. It’s curiosity mixed with confidence and commitment to a process. It’s inherently risky because it carries the possibility of failure. It works similarly in science. Here is the biologist E.O. Wilson describing the process:

The ideal scientist thinks like a poet and only later works like a bookkeeper. Keep in mind that innovators in both literature and science are basically dreamers and storytellers. In the early stages of the creation of both literature and science, everything in the mind is a story. There is an imagined ending, and usually an imagined beginning, and a selection of bits and pieces that might fit in between. In works of literature and science alike, any part can be changed, causing a ripple among the other parts, some of which are discarded and new ones added. The surviving fragments are variously joined and separated, and moved about as the story forms. One scenario emerges, then another. The scenarios, whether literary or scientific in nature, compete with one another. Some overlap. Words and sentences (or equations or experiments) are tried to make sense of the whole thing. Early on, an end to all the imagining is conceived. It arrives at a wondrous denouement (or scientific breakthrough). But is it the best, is it true?

Starting and operating an early-stage company is different than operating a larger, later-stage company. The former requires a high degree of belief and creativity, while the latter requires more skepticism and proof. The ratio inverts along the path. Rigorous testing is the challenge of the scientific process and the entrepreneurial journey. The early stage requires a different type of investor; it needs true believers.

The best angel investors understand the fragility of early stage ideas. They help embolden belief and sustain it through time, when it’s tested and shaped through the buzzsaw of the marketplace. They often have more entrepreneurial DNA than traditional investors. And because no one knows which companies will succeed, it pays to take lots of new ideas seriously. Great angel investors know how to judge an entrepreneur or team by what they could become. They bring a balance of skepticism and optimism. They're belief dealers.

It’s possible that the attributes of a good science investor are different than a good scientist. This is true in the entrepreneurial world — the best investors aren’t always great company operators, and vice versa. The Venn diagram doesn’t overlap perfectly. Who knows, we may find next great science funder in an unexpected place — a J.C.R Licklider for longevity or quantum computing who’s been working in industry, stuck outside of academia.

In a previous essay, I proposed a "science angel" pilot program to create more of this persona in the scientific world. I made the case based on existing data and literature, but there is a worthwhile argument from the belief angle, too. Creating and encouraging a class of science angels will strengthen the knowledge ecosystem by injecting belief and risk taking at the edges, exactly where it's needed most (and seemingly discouraged).

Increasing the surface area of discovery requires boldness and belief in the early stages of curiosity. Of course this belief exists in science already, in countless labs across the country through mentoring relationships between professors and ambitious students. We should add financial momentum. Science funding needs more novel experimentation like this to improve the process. It’s time to think beyond the debates of lotteries versus peer review or people versus projects.

Popular science stories often focus on breakthroughs while discounting the long, lonely pursuit of a problem. Everyone has become aware of the gene-editing tool CRISPR-Cas9, which won the Nobel Prize for its scientific and commercial potential. But unpacking the winding backstory of ideas and contributions that laid the path to that discovery shows the importance of sustained belief. Walter Isaacson's biography of Jennifer Doudna, The Code Breaker, also recounts the story of Francisco Mojica, a Spanish researcher who discovered and named the CRISPR phenomenon:

The first researcher to figure out the function of the repeated sequences was Francisco Mojica, a graduate student at the University of Alicante on the Mediterranean coast of Spain. In 1990, he began working on a PhD dissertation on archaea, which, like bacteria, are single-cell organisms without a nucleus. The archaea he was studying thrive in salt ponds that are ten times saltier than the ocean. He was sequencing regions that he thought might explain its love of salt when he spotted fourteen identical DNA sequences that were repeated at regular intervals. They seemed to be palindromes, meaning they read the same backward and forward.

At first he assumed that he had screwed up the sequencing. “I thought it was a mistake, because sequencing was hard back then,” he says with a hearty laugh. But by 1992, when his data kept showing these regularly spaced repeats, Mojica wondered if anyone else had found something similar. Google did not yet exist, nor did online indexes, so he manually sorted through citations for the word “repeat” in a set of Current Contents, a printed index of scholarly papers. Because this was in a previous century, when very few publications were online, whenever he found a listing that looked promising, he had to go to the library to find the relevant journal. Eventually he found Ishino’s paper.

The E. coli bacterium that Ishino studied is a very different organism from Mojica’s archaea. So it was surprising that they both had these repeated sequences and spacer segments. This convinced Mojica that the phenomenon must have some important biological purpose. In a paper he published in 1995, he and his thesis advisor dubbed them “tandem repeats,” and they guessed, incorrectly, that they might have something to do with cell replication.

After doing two quick postdoctoral stints, one in Salt Lake City and the other at Oxford, Mojica returned in 1997 to the University of Alicante, which was just a few miles from where he was born, and launched a research group to study these mysterious repeated sequences. It was difficult to get funding. “I was told to stop obsessing about repeats, because there were a lot of those type of phenomena in organisms, and mine were probably nothing special,” he says.

We’re all lucky he stuck with it. Science can be a decade-long slog through unknown and uncertain terrain. Scientists, especially early-career folks like Mojica, should be better equipped on that journey. Money and belief is the fuel they need. Let’s provide more of both.