I’ve collected a pile of quotes on risk-tolerance and how best to fund breakthroughs. There’s a dominant theme: big-government sponsorship is inimical to the truly-novel research that is necessary to generate breakthroughs. The argument goes like this:
Progress in research entails doing truly novel things, which means there are risks. Conversely, this implies that low-risk activities won’t yield major breakthroughs. Structural incentives for federal bureaucrats, for grant-approving committees, and hence for individual scientists ensure that low-risk, short-sighted activities are favored. Therefore, the progress of publicly-funded research is hobbled. In the private sector, the inefficient are winnowed out by natural selection. In contrast, the government is an assured stream of funding, so ineffective processes are not culled.
The counterpoints I’ve found are mostly to the effect that private funding isn’t necessarily immune to perverse incentives, nor does it necessarily have better ways of selecting winners (in fact, private-sector due-diligence is probably scientifically less rigorous). The upshot seems to be that private funding is the worst kind — except for all the others.
The following two sections are my thoughts; skip them if you want to go straight to the quotes.
Should we give up on public funding?
Writing off public-sector funding of science & research is a poor strategy for the long term. The government is the natural vehicle for socializing the inherent riskiness of scientific research, because:
- It can most effectively “average out” the fluctuations in success (ie, it can afford a larger portfolio & longer time-scale than private firms)
- The benefits of scientific research accrue to the whole of society, so it makes sense for society as a whole to sponsor it, rather than relying on the enlightened self-interest of corporations, which may result in a suboptimal expenditure (although perhaps over-eager investors are subsidizing the common good)
I question whether risk-aversion is inherent within the government. There are counterexamples (the Manhattan & Apollo projects, DARPA,…), but interestingly they primarily are within the context of wartime (WW2 and the Cold War). My hypothesis is that a lack of existential competition on the international scale is a precondition for the stagnation of federally-sponsored research. Not that natural selection happened at the national scale, but because the possibility of it was internalized as a willingness to take big risks and swing for the fences. However, there are interesting alternate hypotheses:
- The financial sector infected the government with a risk-management philosophy starting around the 1980’s. This is particularly interesting because it ties into society-wide/global trends. This would implicate the private sector as well.
- Every organization ossifies with old age. State-sponsored science was young and effective once upon a time, but it has inevitably aged.
What to do?
Aside from a war or power-cycling the entire enterprise, is there any way to improve the system? Perhaps, although I don’t claim to have a solution, I’m just trying to stimulate discussion. It’s a hard problem, no doubt. Without the feedback mechanism of the market, selection pressure for grantmakers is not natural selection. All that remains are subjective evaluations, or artificial quantitative measures (like publication count) that are subject to being gamed. Any feedback loop is also limited in effectiveness by the timescale it operates on. As the timescales approach the duration of a career, the chance for feedback goes to zero. Unfortunately, the issues are too complex to rely on anything less than human intelligence (ie, algorithms that could be back-tested).
The DARPA model and the COTS program are two interesting ideas for how to change the incentive structures of government-sponsored R&D. In both, a key insight is to reduce the amount of control exercised by the funding agency over how the funding recipient spends the money. However, there’s a tendency for reversion to the mean: unless the upstream incentives or selection pressures for the bureaucrats are modified, controls will creep back in after the inevitable screw-ups (ex: Solyndra). DARPA is supposed to have addressed this with term limits, such that there is no pressure to justify the decisions down the road b/c there’s no career path for the project managers to maintain. It’s not clear that this has been successful, long-term: there’s no pressure to avoid failures, but corresponding little reward for success. With COTS, the fixed-price contract absolutely changes the incentives compared to the price-plus contracts typical of defense. While the program has been successful so far (SpaceX delivering cargo & astronauts to the ISS), the real question is whether it will survive its first major failure.
On to the quotes:
Government-funded research is doomed to stagnation
It is time for corporations and entrepreneurs to recognize that they can no longer rely on governments to fund and on academia to conduct fundamental research. Instead of doing translational research and simply bringing academia’s fruits to market, they have to become bolder and take responsibility for what the future will look like, fund fundamental research, and bring to life a new vision for philanthropy.
Firstly, since academia lacks the mechanism for competitive displacement, bloat accumulating over time and inevitably rising risk-aversion can grow without bound . If a firm becomes inefficient, it collapses and is replaced by another one. If science becomes inefficient… it continues to take in money and people and, well, scientific progress slows down. Secondly, as I pointed out above, science is severely afflicted by the problem of misaligned timescales. Grantmakers’ planning horizons (note that I’m talking about specific individuals who make specific decisions, not abstract institutions that theoretically care about the long-term) are severely limited by their own career planning horizons and by their understanding of what it takes to work on fundamental problems with little short-term payoff.Alexey Guzey, Reviving Patronage and Revolutionary Industrial Research
[S]oftware […] has a convex performance-to-value curve, as with creative fields. Most fields have concave curves, in that not screwing up is more important than hitting the top bars. This convexity means two things. First, it means that managing to the middle decreases total performance. Second, it means that risk (measured by the increasing first derivative of a convex function) is positively rather than negatively correlated with expected return.michaelochurch on reddit
Now, the Valley tech scene does just fine with a 90% failure rate, because the win associated with backing successful execution of a really disruptive idea is much more than a 10x return on investment. The good ones return 50x, and the home runs deliver 100x or more.The Innovation Dead End
Colin Percival, On the Use of a Life
“So why am I not an academic? There are many factors, […] but most of them can be summarized as “academia is a lousy place to do novel research”. [….] My supervisor cautioned me of the risks of doing work which was overly novel as a young academic: Committees don’t know what to make of you, and they don’t have any reputational prior to fall back upon. […] In many ways, starting my own company has given me the sort of freedom which academics aspire to. […A]cademic institutions systemically promote exactly the sort of short-term optimization of which, ironically, the private sector is often accused. Is entrepreneurship a trap? No; right now, it’s one of the only ways to avoid being trapped.
Why not just have the government, or some large almost-government organization like Fannie Mae, do the venture investing instead of private funds?Paul Graham, Inequality and Risk
I’ll tell you why that wouldn’t work. Because then you’re asking government or almost-government employees to do the one thing they are least able to do: take risks.
As anyone who has worked for the government knows, the important thing is not to make the right choices, but to make choices that can be justified later if they fail.
In today’s university funding system, you need grants (well, maybe you don’t truly need them once you have tenure, but they’re very nice to have). So who decides which people get the grants? It’s their peers, who are all working on exactly the same things that everybody is working on. And if you submit a proposal that says “I’m going to go off and work on this crazy idea, and maybe there’s a one in a thousand chance that I’ll discover some of the secrets of the universe, and a 99.9% chance that I’ll come up with bubkes,” you get turned down. But if a thousand really smart people did this, maybe we’d actually have a chance of making some progress. […] This is roughly how I discovered the quantum factoring algorithm.Peter Shor comment on Peter Woit’s blog
Shor concludes with an appeal for individual scientists to sneak off and do ‘bootleg research’ or use their spare time. I think this is misguided — we should fix the systematics, not rely on individuals to buck the incentive structure. Individual researchers working in their spare time are limited in the scope of what they can address. While quantum information theory requires little more than pencil and paper, fusion energy research, for example, is not amenable to this approach.
Well-meaning but disastrous government initiatives to support the startup ecosystem relentlessly pump money into the startup scene. This money is advertised as “free” or “non-dilutive”, but in reality it’s the most expensive kind of money you can imagine: it’s distracting, it begs justification, it kills creativity, and it turns your startup into a government work program.Alex Danco, Why the Canadian Tech Scene Doesn’t Work
You cannot simply add money and create a tech scene. If you do, then either that money will be too freely available and attract the wrong kind of opportunists, or it’ll be like grant money that takes up so much of the founder’s time and energy that it distracts them from actually starting and running the business in the first place.Alex Danco, The social subsidy of angel investing
There’s a tremendous bias against taking risks. Everyone is trying to optimize their ass-covering.Elon Musk interview, in the context of major aerospace government contractors
There are some very interesting tangents here as well: Alex Danco’s remark about “money will be too freely available and attract the wrong kind of opportunists” raises an interesting question about the moral hazard of easy VC money and the Pareto front for funding effectiveness vs selectiveness.
Private-sector funding isn’t perfect
The private sector can also suffer from the same perverse incentives. Style is just as important as substance in raising capital. Investors don’t have the technical expertise for due diligence on highly technical topics. Individual researchers have inherent incentives to be risk-averse, regardless of the funding source.
Because, you know, when it comes down to it, the pointy-haired boss doesn’t mind if his company gets their ass kicked, so long as no one can prove it’s his fault.Paul Graham, Revenge of the Nerds
As a friend of mine said, “Most VCs can’t do anything that would sound bad to the kind of doofuses who run pension funds.” Angels can take greater risks because they don’t have to answer to anyone.Paul Graham, The Hacker’s Guide to Investors
Private money is in some sense philanthropic, in that most VCs are not able to effectively pick winners, and angel investors are motivated less by expected financial reward than by social credit. This harkens back to Renaissance patronage of the sciences (see also Alexey Guzey’s article).
[T]he median VC loses money. That’s one of the most surprising things I’ve learned about VC while working on Y Combinator. Only a fraction of VCs even have positive returns. The rest exist to satisfy demand among fund managers for venture capital as an asset class.Paul Graham, Angel Investing
… angel investing fulfils [sic] a completely different purpose in Silicon Valley than it does elsewhere. It’s not just a financial activity; it’s a social status exercise. [….] From the outside, angel investing may look like it’s motivated simply by money. But there’s more to it than that. To insiders, it’s more about your role and reputation within the community than it is about the money. The real motivator isn’t greed, it’s social standing.Alex Danco, The Social Subsidy of Angel Investing
Much of what counts for successful funding in the private sector is personality, not substance:
A lot of what startup founders do is just posturing. It works. VCs themselves have no idea of the extent to which the startups they like are the ones that are best at selling themselves to VCs.  It’s exactly the same phenomenon we saw a step earlier. VCs get money by seeming confident to LPs, and founders get money by seeming confident to VCs.Paul Graham, What Startups Are Really Like
The Silicon Valley tech ecosystem is a world of pattern matching amidst uncertainty.We pattern match ideas, we pattern match companies, but most of all we pattern match people. […] If you’re too different, you won’t fit the pattern at all, so people will ignore you.Alex Danco, Social Capital in Silicon Valley
This could be related to the fact that venture capital doesn’t have a great substitute for peer review:
First-rate technical people do not generally hire themselves out to do due diligence for VCs. So the most difficult part for startup founders is often responding politely to the inane questions of the “expert” they send to look you over.Paul Graham, How to Fund a Start-up
As an aside, I suspect that the issue of hiring experts for due diligence is probably more on the demand-side. First, part of the prestige of being an investor lies in the appearance of discernment. Outsourcing that would reduce the social/emotional returns. Second, it creates a principle-agent problem. Third, there’s probably some value to NOT having technical experts involved, because they would decrease the diversity of what gets funded.
There’s no silver bullet
Innovative people gravitate to startups, so it’s hard to tell cause from effect:
There’s no magic incentive structure that fixes this problem. If you think startups encourage innovation because early employees are rewarded disproportionately for success, think again. Startups benefit from selection bias — people looking to play it safe don’t take a job with a startup in the first place.Jocelyn Goldfein, The Innovation Dead End
To the extent that you only live once, you can’t socialize the risk of taking a big gamble on your project:
As individuals, we have no portfolio strategy […] When we fail, most rational people respond by trying to avoid dumb ideas and pick smart bets with clear impact the next time. […T]he self-same employees who are innovating and taking risks with you today are going to become risk averse and careful once they start failing — and sooner or later, they (and you) will fail.Jocelyn Goldfein, The Innovation Dead End
Stagnation is a function of the age of an organization. (Cf. Collapse: How Societies Chose to Fail or Succeed – complex societies respond to challenges by increasing in complexity, until diminishing returns set in.)
I have a hypothesis that a lot of the useless bureaucracy isn’t a function of government/private, or size of organization, it’s time. As an organization gets older, it’s gotten burned more times, and created more rules to deal with it. For example, all the “normal” space launch companies and NASA […] killed astronauts, and had a huge number of rockets explode […] This resulted in the creation of rules to attempt to reduce risk. […] SpaceX last year had a failure where they destroyed a customer’s satellite during an on-pad test where the satellite didn’t really need to be mounted. […] I’ll bet SpaceX is going to be a lot more cagey in the future about test firing rockets with payload aboard.
Eventually, a private company will go out of business, but the Government won’t declare bankruptcy. So there’s less limit on governments getting bloated with stuff like this.CatCube on SlateStarCodex
In practice, there’s no surefire algorithm to tell the difference between truly novel good ideas and truly novel bad ideas.
[I]nnovative ideas are roughly indistinguishable from dumb ideas. If something seems like a clearly good idea, it is also an obvious idea. So everyone is doing it! The big ideas that fundamentally change the status quo usually have fatal-seeming flaws that keep (almost) everyone from pursuing them….
OK, OK, so picking good ideas is hard, but that’s what defines great innovators, right? The ability to tell the “crazy” idea from the “crazy awesome” idea? It would be nice to believe that — but empirically speaking, there’s no evidence to support it. The best track record of repeated technical innovation in high tech is the collective Silicon Valley startup scene. And guess what — 9 out of 10 VC-backed startups fail. The absolute best-of-the-best, most profitable VCs? Maybe a 25% success rate.Jocelyn Goldfein, The Innovation Dead End
Maybe this mistaken attitude toward risk actually came from the business world and infected the government (which would explain why the government used to be able to do innovative things).
[T]he mantra of this technocratic system of management is the word “risk”, which if you do a word analysis, didn’t really exist in political coverage until the mid 80s. It comes from finance, but as economics colonised the whole of politics, that word spread everywhere, and everything becomes about risk-analysis and how to stop bad things happening in the future.
Politics gave up saying that it could change the world for the better and became a wing of management, saying instead that it could stop bad things from happening.Adam Curtis, quoted in an interview The antidote to civilisational collapse