No Revival for the Industrial Research Lab

Bell Labs is dead. It remains dead. And we have killed it.

In fact, even the concept seems to be dead. The top result in Google for Industrial Research Lab is a retrospective history. Pluralize the query as Industrial Research Labs and the top result is a 1946 index of the many labs that used to exist. Try Corporate Research Lab and you’ll get the cheery article The Death Of Corporate Research Labs.

Summarized in this last piece, Rosenthal determines the cause of death:

Lack of anti-trust enforcement, pervasive short-termism, driven by Wall Street’s focus on quarterly results, and management’s focus on manipulating the stock price to maximize the value of their options

Looking backwards, this is a tragedy. How shall we comfort ourselves, the murderers of all murderers?

But looking forward, it’s an immense opportunity! So long as we remedy the underlying causes, the great industrial lab may rise again. We may already be on the right track. Antitrust pressure is rising, and privately held companies not subject to Wall Street’s demands are booming.

What about short-termism? Via Tyler Cowen, Warren (2014) finds “no clear evidence of flawed short-term oriented management practices”.

This is good news! The industrial research lab has fallen, but with the causes gone, it will rise again.

As Ben Southwood concludes his piece for Works in Progress “we will see the return of various large in-house labs.” [1]

I am not so optimistic. Regardless of the antitrust situation, industrial research labs will not return.

Southwood and Rosenthal’s findings are both derived from Ashish Arora, Sharon Belenzon, et al.'s The Changing Structure of American Innovation, worth reading in full. As he concludes:

It seems unlikely that corporate research will rediscover its glory days… For some time, quick wins from low-hanging fruit (such as optimizing auction or advertising formats) may cover up the problem, but the fundamental challenge of managing long-run research inside a for-profit corporation remains a formidable one… incumbent firms continue to rely on outside inventions to fuel their growth. In the longer run, therefore, university research will remain the principal source of new ideas for such inventions. [emphasis mine]

In other words: why bother innovating when you can let someone else do it for you? Firms will still engage in the development half of R&D, but this will take the form of translating existing findings into products, rather than breakthrough fundamental research. Arora & Belenzon again:

In summary, the new innovation ecosystem exhibits a deepening division of labor between universities that specialize in basic research, small start-ups converting promising new findings into inventions, and larger, more established firms specializing in product development and commercialization (Arora and Gambardella, 1994). Indeed, in a survey of over 6,000 manufacturing- and service-sector firms in the U.S., Arora et al. (2016) find that 49 percent of the innovating firms between 2007 and 2009 reported that their most important new product originated from an external source.

…As a result, federal research dollars for the university sector grew from an estimated level of $420 million (1982 dollars) in 1935-1936 to more than $2 billion (1982 dollars) in 1960 and $8.5 billion in 1985. Between 1960 and 1985, the share of university research of GNP grew almost twofold from 0.13 to 0.25… Corporate labs historically operated in an environment where university research and start-up inventions were scarce.

Arora & Belenzon cites a 4.25x increase from 1960 to 1985. What about the years since? Courtesy of the NSF:

Federal funding has continued to increase rapidly, up another 3.5x since 1985. For its part, institutional funding (meaning internal funding in the form of endowments, gifts and so on) has grown over 6x. Faced with this bounty, it’s no wonder firms lost their appetite for footing the bill themselves.

To some extent, this is great news! The industrial research lab may be dead, but that doesn’t mean innovation is over, it’s just coming from universities instead. More funding means more science can get done, and who cares if it happens in industry or academia?

Unfortunately, the research we see today is of a different nature. In a section titled “Inventions originating from large corporate labs are different”, Arora & Belenzon enumerate the kinds of innovations we’ve lost in the shift towards university labs:

  • Corporate labs work on general purpose technologies
  • Corporate labs solve practical problems
  • Corporate labs are multi-disciplinary and have more resources

Again, the paper is worth consulting for full details, but it suffices to say that different mechanisms for attracting, nurturing, and managing talent will result in different types of outputs. None of this is to say that the corporate labs were on balance superior to today’s university labs, merely that we are missing out on some innovations (and likely getting others in return).

Though more sensationally, it’s worth worrying that there’s been a profound exodus of top talent from research into industry. As Patrick Collison describes:

One thing that I think is underemphasized is that [corporate research labs] competed on the basis of compensation. They just paid more than other potential sources of unemployment. PARC’s strategy for aggregating the best computer scientists in the world was to pay them more than they would be earning in academia. And in the 70s, you couldn’t Google and earn millions of dollars a year, Silicon Valley hadn’t really left the launchpad.

To a significant extent, the same thing applies to Bell Labs. They were quite explicit that their strategy was to compensate really well and present more favorable employment than academia… It could be the case that because there are so many high return loci for super talent people to go and deploy their talents, you could never quite aggregate talent to the same extent.

…it’s hard to think of any major successes from these kinds of labs over the last 10 or 15 years. [lightly paraphrased for clarity]

As the lamentation goes, “The best minds of my generation are thinking about how to make people click ads.” It’s hard to prove that there has been a brain drain, but if so, it would indicate a strict loss in quality, as opposed to the more stylistic shifts Arora & Belenzon describes.

Bell Labs is dead, and it’s not coming back. Since corporate labs are uniquely suited to some kinds of valuable research, this loss is troubling.

Where does that leave us?

One option is to attempt a massive overhaul of the entire system. If corporate labs have dwindled in the face of the government funded university system, we ought to redirect some portion of those tax dollars to industry instead and seek a better balance. To some extent, this already happens. DARPA awards funding to small businesses through it’s Small Business Innovation Research grants, as does the NIH.

Even here, corporate labs won’t have the same incentives they had in the glory days from 1940-1970. So long as the university system thrives, firms will pursue growth through innovations discovered externally.

In that light, I have a different proposal: Instead of reviving the corporate research lab out of nostalgia, we should consider the more specific goals these labs accomplished, and then target them directly. If we are eager for more multi-disciplinary or research more closely tied to practical problems, we ought to build institutions to pursue those particular aims.

Even more broadly, we can think of institutions as just one of many possible mechanisms to allocate human capital. Nadia’s Helium Grants are also a mechanism for talent allocation, as is venture capital, and as is Substack.

The scientific world is not merely a collection of modules that produce research in hermetic isolation. Rather, it is better understood as an interconnected ecosystem. Increased profitability in software may cause cost disease elsewhere. An exciting new topic in one field could cause a genius exodus in another. Without this understanding of how it all interacts, attempts to recreate a single piece of the 1960s without the supporting context are doomed from the start.

We should seek to understand conditions as they exist today, think deeply about the particular aims we wish to satisfy, then design improved mechanisms within a contemporary environment.

Thanks to Ashish Arora and Nintil for their comments.

See also
Nintil – Fund People not Projects
Alexey – Reviving Patronage and Revolutionary Industrial Research
Nadia Eghbal – Seed stage philanthropy

[1] Ben Southwood read the same paper as Rosenthal and came to the opposite conclusion: the decline was the result of too much antitrust enforcement. The two only appear correlated because success driven by corporate research leads to antitrust. His full quote is “Perhaps antitrust bodies will be restrained, and we will see the return of various large in-house labs.”, but my summary of the conclusion as optimistic still stands.

Frequently Asked Questions

What about Google Quantum?
I’m horrifically unqualified to make this judgement, but this does stand out as an important achivement.

Jack Hidary of Google’s quantum computing initiatives once said: “We literally created a spreadsheet of the experts in this space. We only came up with 800 names globally.” So maybe this is the exception that proves the rule, and Google was able to succeed precisely because there is not a thriving university system for quantum computing.

It’s also worth understanding the achievement as a result of Google’s partnership with NASA, though I don’t know the details of each party’s contributions.

What about AI?
Again, I’m not really confident here, but as I understand it, breakthroughs in AI consist largely of scaling up existing techniques, or inventing new techniques to enable greater scale.

If that’s a fair summary, the apparent dominance of firms in AI research would seem to be a product of their outsized resources, namely compute and data.

Still, why invest in research instead of applying the findings from academia? My guess is that the field is just moving too quickly, and being even a year or two ahead makes a huge difference.

Does this present a promising blueprint for other fields? Maybe. There are other fields that could see dramatic progress powered largely by advances in compute. Or maybe other fields that are amenable to AI-driven progress sooner than we expect. Though even in these cases, I would not expect Google to take over unless the results translate easily into profits. Instead, we’ll likely continue to see Google partner with universities, while staying focused on their own core competence.

What about Open AI?
OpenAI is a non-profit wrapped in a capped-profit LP, managed like a startup.

But okay, incorporation aside, why does it exist? It could be that AI Safety really is the primary concern, and Open AI was founded by a small group of eccentric billionaires motivated by a contrarian research hypothesis. Or maybe that was once the ostensible excuse, and now it’s just a regular startup that bootstrapped talent agglomeration through hype.

I’m not sure, and I very much hope to read the history of OpenAI once someone (or something) writes it.

What about the development in R&D?
Although the dedicated in-house lab is dead, corporate R&D spending is not.

From Nicholas Bloom in his Conversation with Tyler:

The share of R&D in the US and Europe… funded by the government has been declining over time. In fact, in the US, when you go back to the '60s, roughly two-thirds of it is funded by the government and one-third by private firms. Now it’s the reverse.

According to the NSF, it might be more like 75% private firms:

(I assume “private firms” just means non-governmental, as opposed to “firms not listed on public markets”.)

So yes, corporate R&D spending is very high, but remember that it’s a broad category.

When I think about Bell Labs, I think about Claude Shannon’s Information Theory, a leap in basic research that powered the information age, althought it wasn’t invented for any narrow purpose.

In contrast, the D in R&D stands for “development”, and won’t yield this kind of fundamental breakthrough. Take a look at Google’s 10-K. The costs are broken down as:

  • Cost of revenues
  • Research and development
  • Sales and marketing
  • General and administrative
  • European Commission fines [for antitrust violations]

As described Quartz, “Much of those costs [of revenues] were from the fees Google pays companies like Apple to be the default search engine on iPhones and other devices, which are called traffic acquisition costs.”

So the R&D line refers to Google’s actual published research and the cost of cutting-edge projects like their Quantum Computing initiative, but it’s also just the cost of hiring engineers to work on ads. So yes, corporate R&D spending is high by some measure, but a lot of it is development, and a lot of that development has nothing to do with what we think of as research.

Exactly how much is research and how much is development? I’m not sure, and in some cases, it’s not even clear where you would draw the line.