Side order of progress studies now I guess

July 27, 2014 — February 6, 2024

intellectual property
making things
the rather superior sort of city
Figure 1

I am especially interested in modeling how technology makes profound changes to the rules of the game, not just marginal changes in some parameters; So not, say, residual stochastic shocks (in the “Real Business Cycle” models), or as the slope of a marginal cost of production curve (in textbook microeconomics). That is, technological innovation that leads to a qualitative, rather than incremental, change in the state of play — respecting that a lot of marginal changes might indeed lead to major qualitative changes.

In recognition of that emphasis, I briefly called this entry “disruptive technology” instead of mere “innovation”, but then I felt like a TED speaker and woke up sweating in the night and changed it.

This is a vibrant area at the moment, readily disrupting itself. Brr. This notebook will probably explode soon and sporulate, leaving behind some smaller ones.

1 To consider

This concept, innovation, is at the very limit of modelability, surely?. The introduction of a new technology has many components, from social uptake, to supply chains, to the discovery process. The unexpected interactions with the other technologies out there. The internal combustion engine changed more than just transit times. The computer network altered more than just mail delivery times.

The cascade of effects from any one alteration is, it is likely, unknowable in advance, but might have some regularities, or at least some kind of underlying set of distributions as a stochastic process — some kind of branching process perhaps? Fixation processes, by analogy with evolutionary theory?

2 Where did the industrial revolution come from?

Figure 2

Gregory Clark and Julia Galef in podcast conversation: What caused the industrial revolution?:

the timing in 1770 in Britain makes it very, very difficult to explain the industrial revolution. The reason for that is that Britain at that time was institutionally a very stable society, and essentially had very little institutional change in the previous 80 years. When you’re trying to explain this event, it’s occurring against the kind of unchanged background of a society… with stable institutions. Very small government that mainly exists to fight more abroad. You have very stable wages within the society, they’re really not changing, the cost of capital was not changing. [..] It’s an economic environment which just looks very flat. Suddenly, in the middle of all of this, you’ve got this transforming event occurring.

3 Innovation networks

A well documented example of this is the “Product space” model, due originally to Hidalgo and Hausmann, and made purportedly more rigorous by Caldarelli et al.

Considers products and nations in a bipartite graph, and does various network statistics upon it.

Attempts to be predictive about the “natural level” of a country’s GDP.

(c.f. Felix Reed-Tsochas’ affinity for such graphs, har har) Note that there is an implicit third part in the graph, to whit “capabilities”, which represent infrastructure to manufacture products.

Frank Schweitzer et al have a similar notion of inter-firm R&D networks which may be related? See references.

random idea: Estimating number of SKUs as a surrogate for divisions of a modern economy a la Beinhocker (lots of research into this because of Long Tail theories, though the primary data is rarely included — might chase this.)

4 Hype cycle

This is a cute model of certain stylised types of overhypeing.

Figure 3: By NeedCokeNow, CC BY-SA 3.0, Link

The hype cycle itself is presumably on the plateau of productivity right now since Gartner has a steady business producing diagrams based on it.

5 Marginal returns on research

Figure 5

See Kevin Bryan’s paper reviews, especially Models of Innovation I: The Patent Race has a lot of papers discussed which I should file one day > I’ve been going through some old literature on innovation again as part of a current project, so I figured I ought put up a little review of this literature. I’ll cover five strands: the patent race, the partial equilibrium/auction, the quality ladder, sequential innovation a la Scotchmer and Green, and bandit experimentation.

Moore’s law versus Eroom’s law governing trends in marginal research productivity. What does the paucity of new drugs mean? Is this the same as the problem in science? The difficulties form the basis of François Chollet’s arguments against the likelihood of a hard AI singularity and The Singularity is not coming relate this to the question of a technological singularity.

Is science slowing down? Experiencing diminishing returns? Are good ideas getting harder to find? (Bloom et al. 2020)

Figure 6: Eroom’s law: Declining marginal productivity in drug research, via John D Cook

Is it just me, or does this resemble a maximal statistic, or perhaps a rarefaction curve? See Scannell et al. (2012).

  • Who gains from innovation?

    Do technological improvements primarily result in lower prices for consumers or in higher profits for producers? If producers are able to capture (or appropriate) most of the social returns to innovation, then profits will rise and prices will fall relatively little.

    How much of the profits from a new technology are captured by innovators will vary greatly across industries. For sectors where knowledge is in the public domain, such as weather forecasting, the new knowledge cannot be appropriated and productivity improvements are passed on in lower prices. In other industries with well-defined products and strong patents, such as pharmaceuticals, producers may be successful in capturing a large fraction of social gains in “Schumpeterian profits.”

Danny Crichton, The dual PhD problem of today’s startups:

Software is so democratized today, we forget just how blisteringly difficult almost all other facets of human endeavor are to even start. A middle schooler can build and deploy a web service scalable to millions of people with some lines of code (learned from easily and widely accessible resources on the internet) and some basic cloud infrastructure tools that are designed to onboard new users expeditiously.

Try that with rocketry. Or with pharma. Or with autonomous vehicles. Or any of the interesting new frontiers with green fields that are just sitting there waiting for the taking.

Andreessen Horowitz critiques AI startup hype that claims we have a unicorn factory.

Tamay Besiroglu:

I found that the marginal returns of researchers are rapidly declining. There is what’s called a ‘standing on toes’ effect: researcher productivity declines as the field grows. Because ML has recently grown very quickly, this makes better ML models much harder to find.

His thesis Besiroglu (2020) goes into depth.

Rebranded: Danny Dorling, Slowdown: The End of the Great Acceleration—and Why It’s Good for the Planet, the Economy, and Our Lives..

Via Rob Dunne, Arora et al. (2023):

We study the relationships between corporate R&D and three components of public science: knowledge, human capital, and invention. We identify the relationships through firm-specific exposure to changes in federal agency R&D budgets that are driven by the political composition of congressional appropriations subcommittees. Our results indicate that R&D by established firms, which account for more than three-quarters of business R&D, is affected by scientific knowledge produced by universities only when the latter is embodied in inventions or PhD scientists. Human capital trained by universities fosters innovation in firms. However, inventions from universities and public research institutes substitute for corporate inventions and reduce the demand for internal research by corporations, perhaps reflecting downstream competition from startups that commercialize university inventions. Moreover, abstract knowledge advances per se elicit little or no response. Our findings question the belief that public science represents a non-rival public good that feeds into corporate R&D through knowledge spillovers.

6 Stagnation

  • Jason Crawford, Technological stagnation: Why I came around

  • Thiel, P. A. (2014). Zero to one: notes on startups, or how to build the future:

    “Thiel begins with the contrarian premise that we live in an age of technological stagnation, even if we’re too distracted by shiny mobile devices to notice. Information technology has improved rapidly, but there is no reason why progress should be limited to computers or Silicon Valley. Progress can be achieved in any industry or area of business. It comes from the most important skill that every leader must master: learning to think for yourself.

    Doing what someone else already knows how to do takes the world from 1 to n, adding more of something familiar. But when you do something new, you go from 0 to 1. The next Bill Gates will not build an operating system. The next Larry Page or Sergey Brin won’t make a search engine. Tomorrow’s champions will not win by competing ruthlessly in today’s marketplace. They will escape competition altogether, because their businesses will be unique.”

    I gather this is re-introducing Austrian economics to the silicon valley age. The sting will be in the policy prescriptions.

  • Sam Kriss is glum and hyperbolical as always. The Long, Slow, Rotten March of Progress:

    None of these start-ups are doing anything new or interesting. Which shouldn’t be surprising: how often does anyone have a really good idea? What you actually get is just code, sloshing around, congealing into apps and firms that exist simply to exist. Uber for dogs, GrubHub for clothes, Patreon for sex, Slack for death, PayPal for God, WhatsApp for the spaceless non-void into which a blind universe expands.

I wonder how well supported is Hartmann, Krabbe, and Spicer (2019):

What is driving the declining quality of innovation-driven entrepreneurship? In this paper, we argue the growing entrepreneurship industry is an important yet overlooked explanation. This rapidly growing industry has transformed the nature of entrepreneurship and encouraged a particular form of low-quality entrepreneurship. It has done so by leveraging the Ideology of Entrepreneurialism to mass-produce and mass-market products that make possible what we term Veblenian Entrepreneurship. This is entrepreneurship pursued primarily as a form of conspicuous consumption. Aside from lowering average entrepreneurial quality, Veblenian Entrepreneurship has a range of (short-run) positive and (medium and long-run) negative effects for both individuals and society at large. We argue that the rise of the Veblenian Entrepreneur has contributed to creating an increasingly Untrepreneurial Economy. That is an economy which superficially appears innovation-driven and dynamic, but is actually rife with inefficiencies and unable to generate economically meaningful growth through innovation.

As someone who has worked in what I cannot call a dotcom exit scam (because it did certain necessary tasks to be legally distinct from a scam and yet not ever enough to plausibly succeed) I am sympathetic to rants about this.

7 Building innovative societies and places

See astroturf and artificial reefs for now.

8 Progress studies

This needs tidying.

Originally (?) proposed by Patrick Collison and Tyler Cowen, We Need a New Science of Progress. The idea invites critique; that is kind of its purpose.

9 Geniuses and eccentrics

See stroppy people.

10 Incoming

Figure 7

New Things Under the Sun

New Things Under the Sun is a living literature review on social science research about innovation. Articles come in two flavors:

  • claims: a narrow claim about innovation based on a synthesis of academic papers

  • arguments: a broad claim about innovation based on a synthesis of claims

There are also index pages, which group claim articles into topics, and provide a short description of what each is about.

The website is growing all the time as articles get added and updated: subscribe to the substack newsletter to learn what’s new.

New Things Under the Sun is created by Matt Clancy, research fellow at Open Philanthropy. You can learn more about this project on the about page.

11 References

Aghion, Bloom, Blundell, et al. 2002. Competition and Innovation: An Inverted U Relationship.” Working Paper 9269.
Aghion, Harris, Howitt, et al. 2001. Competition, Imitation and Growth with Step-by-Step Innovation.” The Review of Economic Studies.
Arbesman, and Christakis. 2011. Eurekometrics: Analyzing the Nature of Discovery.” PLoS Comput Biol.
Arbilly, and Laland. 2017. The Magnitude of Innovation and Its Evolution in Social Animals.” Proceedings of the Royal Society B: Biological Sciences.
Arora, Belenzon, Cioaca, et al. 2023. The Effect of Public Science on Corporate R&D.” SSRN Scholarly Paper 4645071.
Arthur, W. Brian. 1989. Competing Technologies, Increasing Returns, and Lock-In by Historical Events.” The Economic Journal.
Arthur, W Brian. 2007. The Structure of Invention.” Research Policy.
Atkin, Chen, and Popov. 2022. “The Returns to Face-to-Face Interactions: Knowledge Spillovers in Silicon Valley.”
Baber. 2010. Society: The Rise of the ‘Technium’.” Nature.
Behrens, Giljum, Kovanda, et al. 2007. The Material Basis of the Global Economy: Worldwide Patterns of Natural Resource Extraction and Their Implications for Sustainable Resource Use Policies.” Ecological Economics, Special Section - Ecosystem Services and Agriculture Ecosystem Services and Agriculture,.
Beinhocker, Eric D. 2007. Origin of Wealth: Evolution, Complexity, and the Radical Remaking of Economics.
Beinhocker, Eric D. 2011. Evolution as Computation: Integrating Self-Organization with Generalized Darwinism.” Journal of Institutional Economics.
Benkler. 2017. Law, Innovation, and Collaboration in Networked Economy and Society.” Annual Review of Law and Social Science.
Besiroglu. 2020. Are Models Getting Harder to Find?
Bhattacharya, and Packalen. 2020. Stagnation and Scientific Incentives.” Working Paper 26752.
Bloom, Jones, Van Reenen, et al. 2020. Are Ideas Getting Harder to Find? American Economic Review.
Bloom, Van Reenen, and Williams. 2019. A Toolkit of Policies to Promote Innovation.” Journal of Economic Perspectives.
Castellani, and Rajaram. 2019. How Large Must a Population Be to Accomplish Great Things? Sociology and Complexity Science Blog,.
Cauwels, and Sornette. 2020. Are ‘Flow of Ideas’ and ‘Research Productivity’ in Secular Decline? SSRN Scholarly Paper.
Chu, and Evans. 2021. Slowed Canonical Progress in Large Fields of Science.” Proceedings of the National Academy of Sciences.
Collison, and Nielsen. 2018. Science Is Getting Less Bang for Its Buck.” The Atlantic.
Cristelli, Tacchella, and Pietronero. 2015. The Heterogeneous Dynamics of Economic Complexity.” PLoS ONE.
David. 1985. “Clio and the Economics of QWERTY.” The American Economic Review.
Filimonov, Vladimir, Bicchetti, Maystre, et al. 2014. Quantification of the High Level of Endogeneity and of Structural Regime Shifts in Commodity Markets.” Journal of International Money and Finance, Understanding International Commodity Price Fluctuations,.
Filimonov, Vladimir, and Sornette. 2012. Quantifying Reflexivity in Financial Markets: Toward a Prediction of Flash Crashes.” Physical Review E.
Filimonov, V., and Sornette. 2013. A Stable and Robust Calibration Scheme of the Log-Periodic Power Law Model.” Physica A: Statistical Mechanics and Its Applications.
Flyvbjerg, and Gardner. 2023. How Big Things Get Done: The Surprising Factors That Determine the Fate of Every Project, from Home Renovations to Space Exploration and Everything In Between.
Frenken. 2006. Innovation, Evolution and Complexity Theory.
Funtowicz, and Ravetz. 1994. The Worth of a Songbird: Ecological Economics as a Post-Normal Science.” Ecological Economics.
Goldenberg, Libai, Louzoun, et al. 2004. Inevitably Reborn: The Reawakening of Extinct Innovations.” Technological Forecasting and Social Change.
Hammond, Adriaanse, Bringzeu, et al. 1997. Resource Flows: The Material Basis of Industrial Economies.
Hartmann, Krabbe, and Spicer. 2019. Towards an Untrepreneurial Economy? The Entrepreneurship Industry and the Rise of the Veblenian Entrepreneur.” SSRN Scholarly Paper ID 3479042.
Hawken, Lovins, and Lovins. 2000. Natural Capitalism: Creating the Next Industrial Revolution.
Iribarren, and Moro. 2011. Branching Dynamics of Viral Information Spreading.” Physical Review E.
Jackson. 2008. Social and Economic Networks.
Kali, Reyes, McGee, et al. 2013. Growth Networks.” Journal of Development Economics.
Kelly, and Gráda. 2022. Connecting the Scientific and Industrial Revolutions: The Role of Practical Mathematics.” The Journal of Economic History.
König, Battiston, Napoletano, et al. 2011. Recombinant Knowledge and the Evolution of Innovation Networks.” Journal of Economic Behavior & Organization.
König, Battiston, Napoletano, et al. 2012. The Efficiency and Stability of R&D Networks.” Games and Economic Behavior.
Lane, and Maxfield. 2005. Ontological Uncertainty and Innovation.” Journal of Evolutionary Economics.
Lehman, and Stanley. 2011. Abandoning Objectives: Evolution Through the Search for Novelty Alone.” Evolutionary Computation.
Loreto, Servedio, Strogatz, et al. 2016. Dynamics on Expanding Spaces: Modeling the Emergence of Novelties.” In Creativity and Universality in Language. Lecture Notes in Morphogenesis.
Mokyr. 1990. The Lever of Riches: Technological Creativity and Economic Progress.
Moussaïd, Kämmer, Analytis, et al. 2013. Social Influence and the Collective Dynamics of Opinion Formation.” PLoS ONE.
Napolitano, Evangelou, Pugliese, et al. n.d. Technology Networks: The Autocatalytic Origins of Innovation.” Royal Society Open Science.
Nelson, and Winter. 2002. Evolutionary Theorizing in Economics.” The Journal of Economic Perspectives.
Nordhaus. 2005. Schumpeterian Profits and the Alchemist Fallacy.” SSRN Scholarly Paper ID 820309.
Nowak, and Krakauer. 1999. “The Evolution of Language.” Proceedings of the National Academy of Sciences of the United States of America.
Ollhoff, and Walcheski. 2002. Stepping in Wholes: Introduction to Complex Systems.
Onnela, and Reed-Tsochas. 2010. Spontaneous Emergence of Social Influence in Online Systems.” Proceedings of the National Academy of Sciences.
Ormerod, and Bentley. 2010. “Modelling Creative Innovation.” Cultural Science.
Ormerod, and Colbaugh. 2006. “Cascades of Failure and Extinction in Evolving Complex Systems.” Journal of Artificial Societies and Social Simulation.
Pezzey, and Anderies. 2003. The Effect of Subsistence on Collapse and Institutional Adaptation in Population-Resource Societies.” Journal of Development Economics.
Philippon. 2022. Additive Growth.” Working Paper. Working Paper Series.
Renn. 2020. The Evolution of Knowledge: Rethinking Science for the Anthropocene.
Repenning. 2002. “A Simulation-Based Approach to Understanding the Dynamics of Innovation Implementation.” Organization Science.
Rivkin. 2001. “Reproducing Knowledge: Replication Without Imitation at Moderate Complexity.” Organization Science.
Rizzo Jr. 1996. The Economics of Time and Ignorance: With a New Introduction.
Rosewell, and Ormerod. 2004. How Much Can Firms Know? Computing in Economics and Finance 2004.
Rosicky. 2001. “Information and Social Systems Evolution.” In.
Rossman. 2012. Climbing the Charts: What Radio Airplay Tells Us about the Diffusion of Innovation.
Scannell, Blanckley, Boldon, et al. 2012. Diagnosing the Decline in Pharmaceutical R&D Efficiency.” Nature Reviews Drug Discovery.
Schweitzer, Fagiolo, Sornette, et al. 2009. Economic Networks: The New Challenges.” Science.
Serafinelli, and Tabellini. 2017. Creativity Over Time and Space.” SSRN Electronic Journal.
———. 2018. Creativity and Freedom.” (blog).
Solé, Ricard V, Corominas-Murtra, Valverde, et al. 2010. Language Networks: Their Structure, Function, and Evolution.” Complexity.
Solé, Ricard V., Valverde, Casals, et al. 2013. The Evolutionary Ecology of Technological Innovations.” Complexity.
Sood, Mathieu, Shreim, et al. 2010. Interacting Branching Process as a Simple Model of Innovation.” Physical Review Letters.
Spranzi. 2004. Galileo and the Mountains of the Moon: Analogical Reasoning, Models and Metaphors in Scientific Discovery.” Journal of Cognition and Culture.
Stadler, Stadler, Wagner, et al. 2001. The Topology of the Possible: Formal Spaces Underlying Patterns of Evolutionary Change.” Journal of Theoretical Biology.
Stebbing. 2006. Genetic Parsimony: A Factor in the Evolution of Complexity, Order and Emergence.” Biological Journal of the Linnean Society,.
Sterman. 2000. Business Dynamics.
Straatman, White, and Banzhaf. 2008. “An Artificial Chemistry-Based Model of Economies.” Artificial Life.
Sutton. 2001. Technology and Market Structure: Theory and History.
Tacchella, Cristelli, Caldarelli, et al. 2012. A New Metrics for Countries’ Fitness and Products’ Complexity.” Scientific Reports.
Tainter. 1995. Sustainability of Complex Societies.” Futures.
Thiel. 2014. Zero to One: Notes on Startups, or How to Build the Future.
Thorngate, Liu, and Chowdhury. 2011. “The Competition for Attention and the Evolution of Science.” Journal of Artificial Societies and Social Simulation.
Tomasello, Napoletano, Garas, et al. 2013. The Rise and Fall of R&D Networks.” arXiv:1304.3623 [Physics].
Topolinski, and Reber. 2010. Gaining Insight Into the ?Aha? Experience.” Current Directions in Psychological Science.
Tria, Loreto, Servedio, et al. 2013. The Dynamics of Correlated Novelties.” arXiv:1310.1953 [Physics].
Valverde, Solé, Bedau, et al. 2007. Topology and Evolution of Technology Innovation Networks.” Phys. Rev. E.
Vitali, Glattfelder, and Battiston. 2011. The Network of Global Corporate Control.” PLoS ONE.
Wong, and Bartlett. 2022. Asymptotic Burnout and Homeostatic Awakening: A Possible Solution to the Fermi Paradox? Journal of The Royal Society Interface.
Wu, Wang, and Evans. 2019. Large Teams Develop and Small Teams Disrupt Science and Technology.” Nature.
Young. 1998. Individual Strategy and Social Structure : An Evolutionary Theory of Institutions.
———. 2002. “The Diffusion of Innovations in Social Networks.”
———. 2005. The Spread of Innovations Through Social Learning.”
Zabell. 1992. Predicting the Unpredictable.” Synthese.