Neatly summarized in this blog:
Excellent resource for those who, like me, might benefit from knowing a bit about current research (and some classic papers) in economics but don’t have the time to read the literature. Nice feature from my point of view is that the author is also interested in innovations 
.
Hat tip to fellow PhD student Kevin Bryan for amazing work!
There has been some debate in the sciencey & science fictionish circles about whether searching for and contacting extra-terrestrial aliens is really such a great idea. No less a luminary than Stephen Hawking recently warned the humanity about the possible dangers of phoning the E.T. (as if the humans would listen…), and contact with hostile aliens has understandably been a staple of science fiction since the beginning.
In fiction, aliens are usually depicted lusting after our planet/water/bodies/female bodies (cross off as appropriate). There are some reasons to believe that these fears may have been exaggerated: as long as there are much easier pickings remaining in, say, the Asteroid Belt or the Oort cloud, a species capable of traveling across interstellar distances does not seem to be very likely to need much anything from the bottom of a deep gravity well also known as the Earth. Curiosity items and biological/historical information, perhaps, but wars do not seem to be the optimum method for obtaining them. Trading would be much easier for all concerned – and let’s face it, put a bit of glassbeadanium from a hyper-advanced civilization on offer, and you’ll get all the museums and collectors on Earth lining up for a chance to trade whatever treasures and/or employees they have for it.
However, some more recent works, such as The Killing Star by Pellegrino and Zebrowski (1995), depict a bit more dystopic universe. These authors have thoroughly understood what is also known as the Jon’s Law: Any interesting space drive (i.e. anything that is capable of interstellar flights in at least somewhat reasonable timescales) also happens to be an immensely powerful weapon of mass destruction.
Why? Because interstellar travel requires pretty humongous expenditures of energy. And that energy needs to be controlled very carefully; as one thinker puts it, how would you like to have the captain of the Exxon Valdez skippering a tramp freighter with an antimatter drive?
Consider just a rather simple, down-to-Earth example, a beamed propulsion space probe proposed by a noted hard sci-fi author and rocket scientist (no, really!) Robert L. Forward (1984, 1996). He believes that using only technologies currently being developed, and a rather modest outlay of funds compared to, say, the Olympics, the humanity could soon send a 785-ton interstellar probe hurtling through the cosmos at a rather brisk pace of 50 % of light speed, or 0.5 c. Now, what happens if this small probe just happens to have a slight brush-up with a planet?
It goes boom. Big time; with some 2600 gigatons to be precise. To get a sense of scale, one estimate puts the entire nuclear arsenal of the entire Earth at somewhat firecracker-y 6.4 gigatons, give or take some decimals.
I don’t know for sure what 2600 gigatons of flaming relativistic death will do to a planet, but I’m fairly certain it’d be bad news all round. There is a reason why techno-jargon for these things is Relativistic Kill Vehicle, or RKV. (Yay, acronyms!)
And did I mention that stopping a chunk of metal that’s coming for you at 0.5 c seems to be somewhat “challenging,” no matter what kind of technology you would be using? Even if the probe can be hit, much of it would simply break up – and instead of a single planet-shattering blast, you’d get what would amount to nearly 500 all-out nuclear wars being fought within a second. Not exactly good news, that. In fact, if one wants to relativisticly fry an inhabited planet, the optimal approach would most likely be to break the RKV into smaller fragments well before impact. Harder to detect, harder to intercept, more chances of hitting the planet and something important in it, and less energy wasted into gigantic fireballs that promptly exit the atmosphere. Also, longer baseline for distributed sensors, meaning better targeting capability.
That, my friends, was a single small probe from a pretty sub-standard civilization that has barely learned how to fly up to space and not burn all up when coming down. What if the attacker is using three such probes? Or twenty? Or rather larger 7850-ton ships Forward believes we could also have relatively quickly? (26 000 gigatons per ship, enough to punch sizable holes in the planet’s crust.)
In short, it seems that Attack will always be more effective than any Defense. The Attack Will Always Get Through, and when it does, the results will be spectacular. (From a safe vantage point that is, i.e. from the next star system.)
So – either interstellar travel is not really feasible, in which case we have little to fear from the E.Ts and the discussion whether SETI is a Good Idea is largely moot, or it is feasible, and we have the aforementioned problem. In answer to which, any aliens could be hell-bent on killing us off sooner rather than later simply because
In other words, we could be under threat simply because we may be a threat one day, some day. This is a sobering thought: if it is possible that we may be a threat, shouldn’t it be rational to exterminate us sooner rather than later?
Fortunately for us, there is one thing working in our favor. The alien attackers do not know whether we can already retaliate. Yes, they might fry us with their RKV’s or Alien Death Zappers (ADZ’s for MOAR acronyms!), but are they sure we are not hiding any of our own in the Asteroid Belt, for example? Really sure?
Of course, we know we don’t have those things. But think about an alien civilization picking up the first TV broadcasts from the Earth – incidentally, they’d probably see Hitler opening the 1936 Olympics, which may not be the best introduction to our species unless they’re really into uniforms, but let’s leave that for now. Could they really piece together enough information from our 1950s soap operas, observations of Earth from a distance, et cetera, to absolutely rule out that this species is incapable of building RKVs or something even nastier? What if – let’s say – the grainy broadcasts are all part of some futuristic version of a Renaissance Fair, or a religious ritual? What if it’s a trap ?
And if they then send their killer probes, what will happen during the 200-2000+ years or so the probes will need to reach us? (It seems likely there are no advanced civilizations within 100 light years from Earth, although one must always be ready to be surprised.) Are they really, really sure we then don’t have technologies, if not to defeat the attack, at least to respond in kind? After all, the aforementioned planet killers are likely to be within our reach during this century, and any space habitats in out-of-way places like the Asteroid Belt would have a good chance of surviving the initial attack.
Furthermore, are they absolutely certain we’re not talking to any other aliens? It would be somewhat suspicious if the last message from the Earth would scream about relativistic attack, and the recipients would very likely want to lock’n'load some RKV’s or ADZ’s of their own. Yes, nth aliens are unlikely, but if you find one species, that’s existence proof that it’s not impossible.
In short, it would seem that any civilization that has any reason to be afraid us would also be so afraid of us that it’s far from certain they would really want to hit us first. In other words, they would be deterred from attacking. Yes, they might be very concerned if humans get their dirty hands on relativistic space probes, and they might take a dim view of us practicing parallel parking with those vehicles in their neighborhood. But concerned enough to launch a preventive attack? Hardly.
After all, we’ve been there and we’re still around to tell the tale. From the late 1940s, a group of very eminent minds – including John von Neumann, widely considered one of the greatest mathematicians ever – became increasingly concerned with what they saw as the relentless logic of nuclear war. If there is a non-zero probability of a nuclear war, they said, it is logically only a matter of time before a war breaks out. And given the trend towards increasing numbers of nuclear weapons, a war in the far future would be far more devastating than a war today. So, they and their followers in the military argued, let’s bomb the nasty Commies before they do the same unto us. An example is given in the 1954 briefing to the President Eisenhower by a U.S. Joint Chiefs of Staff advance study group: the U.S., they said, should
“…deliberately precipitat[e] war with the USSR in the near future… before the USSR could achieve a large enough thermonuclear capability to be a real menace to [the] Continental U.S.”
(Kaku & Axelrod 1987:101)
Another air staff study from the period concluded that anyone calling for restraint and relying on retaliation in the event of nuclear attack, i.e. not advocating surprise attack, was a
“…pseudo-moralist who insists that [the U.S.] must accept this catastrophe.”
(Kaku & Axelrod, 1987:100; Rosenberg, 1983:196)
Substitute Aliens for the U.S., Humans for the USSR and RKV for thermonuclear, and there you go. Von Neumann et al‘s logic was sound, in theory, but in practice, these things are fortunately not so simple. It’s quite widely acknowledged now that the logic of deterrence – the inevitable retaliation – made deliberate nuclear wars pretty much impossible, although accidental wars remain threats enough on their own (as I’ve written before). I see no real reason why deterrence wouldn’t work in interstellar relationships: if hitting us is seen as a strategy to ensure continued survival of the alien species, and if any humans survive for long enough to hit back – even if retaliation takes hundreds of years to find and reach the perpetrators – the strategy will be deeply flawed. Simply put, the negative payoff from a not-100%-successful attack will be so large, and the likelihood of the attack being 100% successful so low, that ensuring survival of the species is not a good reason to try to kill off another. (Yes, there may be other reasons, but these, too, will be at least somewhat deterrable.)
But that’s enough qualitative rationalization for now. The next installment of this post will detail the history of One Million Interstellar Wars, fought by yours truly (it’s amazing what you can do with telepresence these days). With that, I’ll show quantitatively why preventive attacks are generally not a good idea – except, perhaps, in a few well-defined cases. Also: what we can do to avoid painting a bullseye on the Earth.
Is this fair use?
Yours truly, a humble and stupid PhD student, recently committed an embarassing faux pas in a conference. While listening intently to a very interesting and relevant presentation in a packed plenary session, I was photographing the slides (thick with text and graphics, as usual) instead of trying to divide my attention between listening and making notes. However, one of the conference organizers noticed my efforts and politely asked whether I had asked the presenter the permission to record the presentation.
Apparently, the concept of “fair use” didn’t cover photographing every slide of the presentation, even though just about every slide was chock-full of very important information.
As far as I know, the organizer was in the right: because I hadn’t asked the permission beforehand, I committed a breach of etiquette. I shouldn’t have photographed the slides, even though I had planned to only use them to back up my own notes. But is this interpretation of “fair use” really in line with the spirit of science and the purpose of scientific conferences?
As a presenter, I’ve so far been more than happy if someone is sufficiently interested in my ideas to record whatever parts of the presentation he or she chooses. This is simply because as a researcher, I want to spread my ideas as far and wide as possible, and it’s certain that recordings AND notes go farther than notes alone. I find it difficult to even think of situations where I wouldn’t want someone to record what I’m saying or showing; if there is something I don’t want to spread around the globe in 80 hours, the rule #1 is do not present it to a global audience. Hence, I honestly hadn’t even thought that someone might object.
But reflecting on the matter, I do understand that some presenters might feel differently, although I still think that presenting something one doesn’t want to spread is somewhat counterproductive. It should also be obvious that recording with the intention of passing the material on as one’s own (aka plagiarism) is definitely wrong. I also know – now – that “fair use” doesn’t really cover recording entire presentations, even if for the sole purpose of note-taking. So the question is, should we avoid recording presentations or collectively reach a solution what “fair use” means in this context?
It is probably clear already that my position is one of maximum openness. In a world where even eyeglasses might come with cameras and every cellphone is capable of making perfectly adequate if not Hi-Fi quality audio records, I feel that restricting the note-taking to writing and typing is simply Ludditic.
It is also needlessly unappreciative of different learning strategies. I can’t speak for others, but I know that I have lots of trouble trying to understand and remember spoken lectures. This is especially difficult when the language used is bad English, as is quite commonly the case. I need notes and I need the slides, or I need the paper; otherwise I have very little hope for remembering the important points just some days later.
Finally, restricting recording by default is also counterproductive from the viewpoint of the presenter herself. Bad notes and bad memory conspire to make the audience forget the presentations faster than it takes them to leave the plenary room.
There are probably very good arguments against recording conference presentations, but being a stupid PhD student, so far I haven’t been able to think of any. Perhaps the most compelling counterarguments, that recordings help plagiarism or stealing of ideas, are problematic on at least two counts. First, in the era of increasingly efficient and automated search engines, copying unattributed ideas that have been presented to a broader audience is a career-limiting move, particularly if there’s a possibility the presentation been recorded by others; second, what prevents individuals with eidetic memory or hidden cameras from doing so already? Memory wipes and cavity searches?
Of course, the correct way to record presentations exists: one should simply ask in advance whether the presenter allows it. But as anyone familiar with conferences knows, it’s sometimes difficult to know in advance what the really interesting presentations are, and it’s also sometimes a bit difficult to ask the permission beforehand – particularly so in plenary sessions. I, for one, have never seen anyone actually do so, although I’ve seen even tape recorders employed!
Therefore, to clarify what is OK and to encourage people to use the modern note-taking tools to the fullest (i.e. to help folks spend their time doing sciencey stuff instead of deciphering scribbled notes), I offer two humble suggestions. First, to presenters: please state in advance whether you allow the presentations to be recorded, and with what limitations. Second, to conference organizers, who are in a position to determine in advance whether recordings should be allowed or disallowed by default. How about moving to the 21st Century by informing presenters and the audience that by default, recordings are allowed, and if a presenter wants to prevent (overt) recording, she needs to inform the audience before the presentation?
Meanwhile, smartened by the experience, I already added a statement in bold red type to my Keynote master slides:
RECORDING AND REDISTRIBUTION PERMITTED, EVEN ENCOURAGED!
In this paper, me and Julia Kasmire from Delft University of Technology introduce an improved, simplified computer simulation model for studying technological evolution. The paper was presented by yours truly at the 26th European Conference on Modeling and Simulation in Koblenz, Germany in May 2012. I recommend the place and especially the wines there – jolly good all round.
The background for the model is in the realization that simulation models for technological evolution are somewhat limited. For example, the NK model made famous by Kauffman (1993) of Santa Fe Institute fame and used, often with modifications, by many researchers (e.g. Auerswald et al 2000; Frenken 2001, 2006; Murmann and Frenken 2006; Almirall and Casadesus-Masanell 2010, etc etc.) has provided very nice insights into complex technological problems. Nevertheless, it suffers from several problems.
The first problem is exogeneity. Exogeneity means that the search landscape is fixed at the beginning of the simulation; it does not change or evolve as a result of discoveries that the agents in the simulation may make. In philosophical terms, this is roughly equivalent to the Platonic idealism: that there exist somewhere an abstract form of perfect, ideal Thing-ness for each thing, waiting for us to find it. While interesting, this reduces the technological evolution to a search problem: how to search most efficiently through a complex landscape for the most ideal Thing that can possibly be found?
In addition, the NK model does not really model the way technologies are related to each other, or how some technologies depend from each other. If a lucky guess in the search process lands an agent on the perfect blueprint for perfect fusion reactor, it doesn’t matter whether the unobtainium for that reactor has been discovered or not.
An alternative, the percolation model, has been used by e.g. Silverberg and Verspagen (2005). In percolation model, technological development is modeled as (surprise surprise) percolation through 2-dimensional lattice. The idea is to find an uninterrupted route from the bottom to the top, when there are various obstacles strewn around. (It’s bit more complicated than that, but read the paper.) One can rather easily alter the parameters of search, and most importantly, this model does model the “keystone” technologies that are required for finding other technologies.
But the lack of internal structure presents a problem for both models. Technologies are hierarchies of components, just as e.g. Murmann and Frenken (2006) so nicely illustrate. But NK models do not model internal complexity at all – they do not really have components, only alternatives – and the percolation models stoop to this level only as far as the uninterrupted route can be found. Therein lies a problem: what if we want to model not just how technologies are found, but how they improve over time?
Thankfully, the brainiacs with the Santa Fe Institute – namely, the famed economist W. Brian Arthur and computer scientist Wolfgang Polak – have thought about this, too. Arthur and Polak gave the world a very intriguing model of technological evolution in 2004. In the model, they show how technology “bootstraps” and builds itself from simpler components, and how the components themselves improve over time. Their model was based on Boolean logic gates (NAND to be exact); random combinations of these gates eventually satisfied a host of needs speficically defined in the simulation (e.g. adder circuits, other logic gates, etc.).
Very nice, but try to code the model with the experience of a social scientist! Furthermore, extending the model seemed to be a bit difficult. So one night, lying on the carpet, I came up with an idea: for the computer, it’s all ones and zeros anyway when you get down to it, so why not just use ones?
The end result was the ADDER. The very simple idea in the model is that technologies are composed of fundamental building blocks or “primitives.” Different combinations of these primitives produce new products, which can then be used as components in further technologies. And so forth!
This model is easy to code, it’s fast, and it’s understandable. Furthermore, it’s extendable in a way Arthur and Polak’s model really isn’t. We have high hopes for it, and wish to use it in many, many experiments later on. For the details, go forth, to the paper already, shoo!
Our paper:
References:
Arthur WB and Polak W (2004) The evolution of technology within a simple computer model. Complexity, 23-31. Available at:http://doi.wiley.com/10.1002/cplx.20130.
Almirall E and Casadesus-Masanell R (2010) Open versus closed innovation: A model of discovery and divergence. Academy of Management Review 35(1): 27-47.
Auerswald P, Kauffman SA, Lobo J and Shell K (2000) The production recipes approach to modeling technological innovation: An application to learning by doing. Journal of Economic Dynamics and Control 24(3): 389-450. Available at: http://linkinghub.elsevier.com/retrieve/pii/S0165188998000918.
Frenken K (2001) Understanding Product Innovation using Complex Systems Theory. University of Amsterdam.
Frenken K (2006) Innovation, Evolution and Complexity Theory. Cheltenham and Northampton: Edward Elgar.
Kauffman SA (1993) The Origins of Order. Self-Organization and Selection in Evolution. New York and Oxford: Oxford University Press.
Murmann J and Frenken K (2006) Toward a systematic framework for research on dominant designs, technological innovations, and industrial change. Research Policy 35(7): 925-952. Available at: http://linkinghub.elsevier.com/retrieve/pii/S0048733306000862.
Silverberg G and Verspagen B (2005) A percolation model of innovation in complex technology spaces. Journal of Economic Dynamics and Control 29(1-2): 225-244. Available at: http://linkinghub.elsevier.com/retrieve/pii/S0165188904000132.
The following is a short essay I wrote last year for the course “Developing professional skills in academic work.” In it, I outline some ideas how to do management research that
The essay was originally published in 2011 in Räsänen, Keijo (ed.) Tutkijat kertovat. Kymmenen esseetä akateemisesta työstä.
An English version may follow, or not.
Recently, I came across a working paper by two very big names in design/innovation research – Donald A. Norman and Roberto Verganti. The paper was very interesting, not the least since the hill-climbing paradigm of innovation presented therein is almost exactly what I and Lotta Hassi wrote about nearly three years ago. In addition to this certified streak of pure genius, Norman’s and Verganti’s piece argues that
All of which is great, but during the last year or so, I’ve come to question the whole idea of neatly separating novelty into incremental and radical innovations. My problem, which I ran into while researching the evolution of technology, is this: I cannot, in all honesty, find anything particularly “radical” from the innovations I’ve studied.
Innovations are generally defined as “radical” if they are novel and have a major impact, one way or another. A general yet seldom expressed assumption seems to be that a radical innovation (that is, one which has a significant impact) must somehow be a radical departure from existing practice, i.e. it must also be novel and/or unique. (Yes, there is something of a tautology going on here.)
As an example, Dahlin and Behrens (2005; excellent paper, by the way – all innovation scholars should take note) suggest a measure of radicalness for patents: how many patent citations the patent in question has. The logic is that radical inventions (note, not yet innovations) are so different from “prior art” that they do not have antecedents in the field.
But when we think about innovation process, how do these radically-different-from-prior-art inventions actually come about? Many people seem to believe that in order to find radical inventions, one must “think outside the box” and throw out all the “outdated assumptions” about how the world works. Some, myself included, have even made a tidy profit from advising companies in these matters.
There is some truth to these claims. It is indeed often helpful not to take the assumptions for granted and to think outside the box. But when one looks at the history of actual radical innovations, one doesn’t see much of creativity exercises, wild experimentation, or black turtlenecks (well, except at that one company). Radical innovations simply don’t seem to happen by thinking outside the box, by stimulating creativity, or – for that matter – by hiring members of the “creative class” either.
Instead, most radical innovations seem to result from steady, methodical, even boring work of staid, solid and pragmatic tinkerers. There is experimentation aplenty, to be sure, but it is very much planned and very much non-random. A significant characteristic is that experiments tend to be very small increments to state-of-the-art; simple adjustments may be tested and tweaked and tested all over again, for years in some cases.
As an example, let’s take what is arguably the most radical innovation of the 20th Century (if not all the time): the aeroplane. By the late 1890s, many people around the world had the means and the interest to build the first heavier-than-air flying machine. In general, these people fell into two broad types: those who were really thinking outside the box, and the Wright brothers. (Yes, this is a bit unfair generalization.)
Most of their competitors did just what several innovation gurus seem to implicitly recommend: they thought out more or less wild ideas, built the prototypes, and tested them. Unfortunately, by testing entire flying machines, they were playing a double or nothing game: if the basic idea behind their contraption was unsound, they had just lost a considerable amount of time and money.
The Wright brothers took a different tack. They started to methodically extend the prior art in a series of carefully controlled experiments. Instead of building whole aeroplanes, they tested particular components and their configurations. Bit by bit, they had a better understanding of just what combination of components would make a viable airplane. Only when they had high confidence of actually making the airplane work, they built one.
It worked from the start.
Every time something similar happens, an outside observer might be startled and believe the inventor made a huge conceptual leap, attributable perhaps to the singular, non-replicable genius of the inventor in question. This is understandable, but wrong. In real life, there are few if any great conceptual leaps, when seen from the inside. But there are many examples of small, methodical – incremental – steps leading to a “radical” outcome. We just tend to assume a conceptual leap, because those steps are rarely visible to outsiders. Indeed, sometimes even the inventor may be unaware of the steps that contributed to the invention.
I have trouble believing great inventions can even happen in any other way. Human brains have a lot of trouble trying to keep track of more than a few complex ideas and their combinations. Since radical innovations almost by definition require a significant juggling of complex ideas, making conceptual leaps without any stepping stones on the way seems a bit unrealistic.
So, what I believe is this: all innovations, whether incremental or radical, are fundamentally the same. What we call “incremental” is just a label we affix to those innovations that do not seem to be that consequential to us, the general (or scholarly) public. But many of these incremental improvements pave way, one way or another, to radical innovations.
Those what we call “radical” innovations may simply be a way of labelling an example of so-called self-organizing criticality. When we have a lot of incremental improvement going on, it’s almost inevitable that some improvements will turn out to be far more significant than the others. An avalanche – a cascade – of effects ensues. But when carefully considered, the triggering improvement need not be any different in any real sense from those improvements that failed to make the waves, so to speak.
There is some evidence that a 1/f or lognormal distribution, a fingerprint of self-organizing criticality (SOC), is visible in patent data. For example, Silverberg and Verspagen (2005), discussing the available evidence, conclude that patent citation statistics are extremely skewed, in a 1/f manner: very few patents are cited extremely often, while most are cited hardly at all. They also adapt a computer model that is known to exhibit SOC behavior and generate data that matches the patent data fairly well.
So, the claims that Norman and Verganti make in the paper I started this essay with are not necessarily wrong. But the implication – that incremental improvement and radical innovation require completely different approaches – is, in my opinion, potentially misleading. In particular, the hill-climbing metaphor, originally borrowed from evolutionary biology, oversimplifies things a little bit. Instead of hills, the landscape might resemble more a series of interconnected ridgelines. This “genetic drift” across more or less selection-neutral areas of the landscape is now thought to explain how new features and species actually evolve. In technological terms, the selection-neutral features might be small changes that do not really have an effect on the cost or user experience, but cumulatively may take the product far from its origins. (There is also another matter with the hill-climbing paradigm and its use as a metaphor: it assumes the landscape to be climbed will be stationary. This is not usually the case.)
What I and a colleague from the Netherlands are currently working on relates to these problems. We’re building a computer model of innovation that hopefully sheds a bit of light into how radical can emerge from the incremental. A preliminary paper detailing the problem and the proposed model will be presented at Technoport 2012 conference in Norway, and submissions of more detailed version are in for a couple of other conferences as well. I’ve also been doing some work on more selection-neutral models, but that’s farther off.
But what practical implications can I offer in the meantime? As far as money-making schemes i.e. companies are concerned, I have this to offer: if there is a choice between an “ideas guy” and an “execution guy,” pick the latter. There is a saying about how everyone has an idea, but without relentless, tenacious, stubborn execution, most ideas remain just that. And in my experience, it’s the execution that’s the hard part.
In general, I might suggest amending that popular wisdom, “the best way to have a good idea is to have many ideas.” In my opinion, the best way to have a good idea is to have many experiments. Of which this essay is one, so feel free to comment .
References
Dahlin, K. B., D. M. Behrens. 2005. When is an invention really radical? Defining and measuring technological radicalness. Research Policy 34(5) p.717-737.
Silverberg, G., B. Verspagen. 2005. A percolation model of innovation in complex technology spaces. Journal of Economic Dynamics and Control 29(1-2) p.225-244. Available at: http://linkinghub.elsevier.com/retrieve/pii/S0165188904000132 .
Some notes about what previous thinkers have said about innovations and the evolution of technology. We’ll begin by notes I made from Ruttan’s classic 1959 article, “Usher and Schumpeter on invention, innovation, and technological change.” As the title says, it’s a comparison of Schumpeter’s (known to most students of economics) and Usher’s (known mostly to students of technological change) views on the subject.
Notably, Usher’s theory of “cumulative synthesis” is a remarkably successful theory explaining how inventions and innovations occur. It’s the basis of much of the work I’m currently doing, as it has greatly informed Arthur’s thesis of combinatorial evolution of technology (Arthur 2009).
Schumpeter and Usher on innovations (From Ruttan 1959)
Schumpeter
Schumpeter’s discussion of the role of innovation in economic growth is stated in its most developed form in Chapters III and IV of Business Cycles (Schumpeter 1939). Schumpeter identified innovation as the essential function of the entrepreneur. He made the innovator and the process of innovation one of the three elements (along with credit and profit maximization) of a theory of economic development.
To Schumpeter, innovation and the innovator were quite distinct from invention and the inventor. In his opinion, innovation is possible without anything we should identify as invention, and the social process which produces innovations is distinctly different “economically and sociologically” from the social process which produces inventions.
Schumpeter’s “rigorous” definition of innovation is a change in the form of the production function:
“This function describes the way in which quantity of products varies if quantity of factors vary. If, instead of quantities of factors we vary the form of the function, we have an innovation.” (Schumpeter 1939:87-88)
The inputs were only labor and land – this differs from the neoclassical formulation in that capital is excluded. However, in Schumpeter’s view, innovations cannot be measured through changes in production function, as price changes and non-neutrality of innovation would effectively limit the possibilities of measurement.
NOTE: Schumpeter’s definition is quite close to the definition of technological change as used by economists. See e.g. Solow’s work.
According to Ruttan (1959:599), who was a colleague of Schumpeter, he was “primarily interested in changes in the production functions of the technological leaders – the innovating firms – because of the growth forces which adoption of new methods of production set in motion.” This contrasts to many other economists who have concentrated their attention to the production function, which describes the average performance of the economy or industry.
NOTE: Many computer models of technological evolution, such as NK models, calculate average performance. In a sense, it might be thought of as the production function.
Schumpeter did not give explicit attention to the process by which innovation is generated. There is nothing in Schumpeter’s works that can be identified as a theory of innovation. Although the business cycle is a direct consequence of the appearance of clusters of innovations, no real explanation for the clusters is given and a theoretical basis is explicitly eschewed. However, three cycles – Kitchen (40 months), Juglar (10 years) and Kondratieff (60 years) – are observed.
Usher (on the emergence of strategic inventions)
Usher’s thesis is most fully presented in Chapter IV of the revised edition of History of Mechanical Inventions (Usher 1954). According to Ruttan (1959), Usher forms the basis of a theory of innovation that is lacking from Schumpeter’s works.
One problem faced by economists is that “invention” is difficult to define. Usher defines inventions as the emergence of “new things” which require an “act of insight” going beyond the normal exercise of technical or professional skills.
“Acts of skill include all learned activities whether the process of learning is an achievement of an isolated adult individual or a response to instructions by other individuals. Inventive acts of insight are unlearned activities that result in new organizations of prior knowledge and experience…” (Usher 1954:526)
“Such acts of insight frequently emerge in the course of performing acts of skill, though characteristically the act of insight is induced by the conscious perception of an unsatisfactory gap in knowledge or mode of action.” (Usher 1954:523)
Usher identifies three general approaches to the problem of explaining the emergence of inventions in contrast with the performance of acts of skill. These are the transcendentalist, the mechanistic process, and the cumulative synthesis.
The transcendentalist approach attributes the emergence of invention to the inspiration of the occasional genius who from time to time achieves a direct knowledge of essential truth through the exercise of intuition. This Usher rejects as unhistorical: acts of insight have not been the rare, unusual phenomenon, and they are not accidents but require a highly specific conditioning of the mind – think Pasteur’s “fortune favours the prepared mind.”
Usher also rejects the mechanistic process, which was espoused by Chicago sociologists such as Ogburn (1922) and Gilfillan (1935). However, he stresses that their empirical results are important. These sociologists demonstrated that the process of invention typically represents a new combination of a relatively large number of indiidual elements accumulated over long periods of time. However, Usher thinks that this process is not merely an instrument of historical necessity: discontinuities cannot, in his opinion, be explained by the mechanistic approach, but require aforementioned acts of insight. Only a limited number of individuals are operating under conditions which bring both an awareness of the problem and the elements of a solution within their frame of reference. Even then, it is not certain that the specific act of insight required for a solution will occur.
Usher’s alternative is the cumulative synthesis approach. Drawing on the insights into metnal and social processes provided by Gestalt psychology, major inventions are visualized as emerging from the cumulative synthesis of relatively simple inventions, each of which requires an individual “act of insight.”
Individual invention comprises of four steps:
1. Perception of the problem, in which an incomplete or unsatisfactory pattern or method of satisfying a want is perceived.
2. Setting the stage, in which the elements or data necessary for a solution are brought together through some particular configuration of events or thought. Among the elements of the solution is an individual who possesses sufficient skill in manipulating the other elements.
3. The act of insight, in which the essential solution of the problem is found. Usher stresses that large uncertainties surround the act of insight. This uncertainty makes it impossible to predict the timing or the precise configuration of a solution in advance.
4. Critical revision, in which the newly perceived relations become fully understood and effectively worked into the entire context to which they belong, possibly calling for new acts of insight.
A major or strategic invention represents the cumulative synthesis of many individual inventions, and will usually involve all the separate steps that may be found in individual inventions.
According to Ruttan (1959:602), Usher’s cumulative synthesis theory provides a unified theory of the social processes by which “new things” Come into existence, and is broad enough to encompass the whole range of activities characterized by the terms science, invention, and innovation. The artificial distinction between the processes of invention and innovation is no longer required.
Usher’s theory also clarifies the points at which conscious efforts to speed the rate or alter the direction of innovation can be effective. The conscious effort is useful around the second and fourth steps in the aforementioned process – in setting the stage and in critical revision. An appropriate research environment which consciously brings together the elements of a solution can set the stage so that fewer elements are left to chance. In the critical revision stage, many of the elements required – testing, for example – are “acts of skill” rather than “acts of insight.” (“Applied research” or R&D is concerned with this critical revision stage, mostly.)
Transcendentalist approach obscures these possibilities with its dependence of the “great man;” mechanistic process denies the possibility altogether.
A limitation of Usher’s theory, according to Ruttan (1959:605), is that it is not a predictive theory – as Usher himself asserts (Usher 1954:66). However, Ruttan notes that since Usher predicts that focus on the two stages of “setting the stage” and “critical revision” should make inventions more likely, the effective institutionalization of applied research and the growing interest in the problem of creating an institutional environment favorable to “basic research” do provide an operational test that is consistent with Usher’s theory (Ruttan 1959:605).
References
Arthur, B.W., 2009. The Nature of Technology: What it is and how it evolves. Free Press, New York.
Gilfillan, S.C. 1935. The Sociology of Invention. Chicago: Follett Publishing.
Ogburn, William F. 1922. Social Change. New York: Viking Press.
Ruttan, V.W., 1959. Usher and Schumpeter on invention, innovation, and technological change. The Quarterly Journal of Economics 596–606.
Schumpeter, J. A. 1939. Business Cycles, vol. I. New York: McGraw-Hill.
Usher, A. P., 1954. A History of Mechanical Inventions. Cambridge, Harvard University Press.
