Technological Determinism

Social scientists and social historians are naturally keen to produce explanations for social phenomena. Event B happened because of A.

Sometimes the explanation involves some form of technology. Lewis Mumford traced the start of the Industrial Revolution to the invention of the mechanical clock, while Marshall McLuhan talks about the great medieval invention of typography that was the take-off moment into the new spaces of the modern world McLuhan 1962 p 79.

These explanations are sometimes read as implying some form of technological determinism. For example, many people read McLuhan as a technological determinist.

McLuhan furnished [the tech industry] with a narrative of historical inevitability, a technological determinism that they could call on to negate the consequences of their inventions - if it was fated to happen anyway, is it really their fault?

Daub 2020 pp 47-48

Although sometimes McLuhan claimed the opposite. After Peter Drucker had sought an explanation for the basic change in attitudes, beliefs, and values that had released the Technological Revolution, McLuhan's 1964 book set out to answer this question.

Far from being deterministic, however, the present study will, it is hoped, elucidate a principal factor in social change which may lead to a genuine increase of human autonomy.

McLuhan 1962 p 3

As McLuhan has said, there is no inevitability so long as there is a willingness to contemplate what is happening.

Postman Weingartner 1969 p 20

Raymond Williams saw McLuhan's stance as 

an apparently sophisticated technological determinism which has the significant effect of indicating a social and cultural determinism: a determinism, that is to say, which ratifies the society and culture we now have, and especially its most powerful internal directions.

Williams, second edition p 120

Neil Postman himself made some statements that were much more clearly deterministic. 

Once a technology is admitted, it plays out its hand; it does what it is designed to do.

Postman 1992

But causal explanation doesn't always mean inevitability. Explanations in history and the social sciences often have to be understood in terms of tendencies, probabilities and propensities, other-things-being-equal.

There is also a common belief that technological change is irreversible. A good counter-example to this is Japan's reversion to the sword between 1543 and 1879, as documented by Noel Perrin. What's interesting about this example is that it shows that technology reversal is possible under certain sociopolitical conditions, and also that these conditions are quite rare.

What is rather more common is for sociopolitical forces to inhibit the adoption of technology in the first place. In my article on Productivity, I borrowed the example of continuous-aim firing from E.E. Morison. This innovation was initially resisted by the Navy hierarchy (both UK and US), despite tests demonstrating a massive improvement in firing accuracy, at least in part because it would have disrupted the established power relations and social structure on board ship.

Evolution or Revolution?

How to characterize the two examples of technology change I mentioned at the beginning of this post - the mechanical clock and moveable type? It is important to remember that this isn't about the invention of clocks and printing, since these technologies were known across the ancient world from China to Egypt, but about significant improvements to these technologies, which made them more readily available to more people. It was these improvements that made other social changes possible.

Technologists are keen to take the credit for the positive effects of their innovations, while denying responsibility for any negative effects. The narrative of technological determinism plays into this, suggesting that the negative effects were somehow inevitable, and there was therefore little point in resisting them.

The tech industry ... likes to imbue the changes it yields with the character of natural law.

Daub 2020 p 5

If new tech is natural, then surely it is foolish for individual consumers to resist it. The rhetoric of early adopters and late adopters suggests that the former are somehow superior to the latter. Why bother with old fashioned electricity meters or doorbells, if you can afford smart technology? Are you some kind of technophobe or luddite or what?

What's wrong with the idea of technological determinism is not that it is true or false, but that it misrepresents the relationship between technology and society, as if they were two separate domains exerting gravitational force on each other. In my work on technology adoption, I used to talk about technology-in-use. Recent writing on the philosophy of technology (especially Stiegler and his followers) refer to this as pharmacological, using the term in its ancient Greek sense rather than referring specifically to the drug industry. If you want to think of technology as a drug that alters its users' perception of reality, then perhaps it's not such a leap from the drug industry to the tech industry.

But the word alters isn't right here, because it implies the existence of some unaltered reality prior to technology. As Stiegler and others make clear, there is no reality prior to technology: our reality and our selves have always been part of a sociotechnical world. 

Donna Harraway sees determinism as a discourse (in the Foucauldian sense) rather than as a theory of power and control.

Technological determination is only one ideological space opened up by the reconceptions of machine and organism as coded texts through which we engage in the play of ·writing and reading the world.

As Rob Safer notes,

Human history for Haraway isn’t a rigid procession of cause determining effect, but a process of becoming that depends upon human history’s conception of itself, via the medium of myth.

Finally, one of the best arguments against technological determinism is presented by Andrew Feenberg, who provides examples to show the tremendous flexibility of the technical system. It is not rigidly constraining but, on the contrary, can adapt to a variety of social demands.

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Adrian Daub, What Tech Calls Thinking (Farrar Straus and Giroux, 2020) 

Andrew Feenberg, Subversive Rationalization: Technology, Power, Democracy (Inquiry 35, 1992, pp 301-22)

Donna Haraway, Cyborg Manifesto (Socialist Review, 1985)

Marshall McLuhan, The Gutenberg Galaxy (University of Toronto Press, 1962) 

E.E. Morison, Men Machine and Modern Times (MIT Press, 1966)

Lewis Mumford, Technics and Civilization (London: Routledge, 1934)

John Durham Peters, “You Mean My Whole Fallacy Is Wrong”: On Technological Determinism  (Representations 140 (1): 10–26.  November 2017)

Noel Perrin, Giving up the gun (New Yorker, 13 November 1965), Giving up the gun (David R Godine, 1988)

Neil Postman, Technolopoly: the surrender of culture to technology (Knopf, 1992)

Neil Postman and Charles Weingartner, Teaching as a Subversive Activity (Delacorte 1969) page references to Penguin 1971 edition

Jacob Riley, Technological Determinism, Control, and Education: Neil Postman and Bernard Stiegler (1 October 2013)

Federica Russo, Digital Technologies, Ethical Questions, and the Need of an Informational Framework  (Philosophy and Technology volume 31, pages 655–667, November 2018)

Rob Safer, Haraway’s Theory of History in the Cyborg Manifesto (16 March 2015)

Richard Veryard, Demanding Higher Productivity (data processing 28/7, September 1986)

Raymond Williams, Television, Technology and Cultural Form (Routledge, 1974, 1990)

Related posts: Smart Guns (May 2014), The Social Dilemma (December 2020)

Evolution or Revolution 3

Let me start this post with some quotes from @adriandaub's book What Tech Calls Thinking.

Disruption has become a way to tell a story about the meaning of both discontinuity and continuity.

Daub p 119

One ought to be skeptical of unsubstantiated claims of something's being totally new and not following the hitherto established rules (of business, of politics, of common sense), just as one is skeptical of claims that something which really does feel and look unprecedented is simply a continuation of the status quo.

Daub pp 115-6

For example, Uber.

Uber claims to have revolutionized the experience of hailing a cab, but really that experience has stayed largely the same. What it has managed to get rid of were steady jobs, unions, and anyone other than Uber's making money on the whole enterprise.

Daub p 105

Clayton Christensen would agree. In an article restating his original definition of the term Disruptive Innovation, he put Uber into the category of what he calls Sustaining Innovation.

Uber’s financial and strategic achievements do not qualify the company as genuinely disruptive—although the company is almost always described that way.

HBR 2015

However, as I pointed out on Twitter earlier today, Christensen's use of the word disruptive has been widely diverted by big tech vendors and big consultancies in an attempt to glamorize their marketing to big corporates. If you put the name of any of the big consultancies into an Internet search engine together with the word disruption, you can find many examples of this. Here's one picked at random: Discover how you can seize the upside of disruption across your industry.

The same experiment can be tried with other jargon terms, such as paradigm shift. By the way, Daub notes that Alex Karp, one of the founders of Palantir, wrote his doctoral dissertation on jargon - speech that is used more for the feelings it engenders and transports in certain quarters than for its informational content (Daub p 85).

@jchyip thinks we should try to stick to Christensen's original definitions. But although I don't approve of vendors fudging perfectly good technical terms for their own marketing purposes, there is sometimes a limit to the extent to which we can insist that such terms still carry their original meaning.

And to my mind this is not just a dispute about the meaning of the word disruptive but a question of which discourse shall prevail. I have long argued that claims of continuity and novelty are not always mututally exclusive, since they may simply be alternative descriptions of the same thing for different audiences. The choice of description is then a question of framing rather than some objective truth. As Daub notes

The way the term is used today really implies that whatever continuity is being disrupted deserved to be disrupted.

Daub p 119

For more on this, see the earlier posts in this series: Evolution or Revolution (May 2006), Evolution or Revolution 2 (March 2010)

In a comment below the March 2010 post, @cecildjx asked my opinion on the (relative) significance of the Internet versus the iPhone. Here's what I answered.

My argument is that our feelings about technology are fundamentally and systematically distorted by glamour and proximity. Of course we are often fascinated by the most-recent, and we tend to take the less-recent for granted, but that is an unreliable basis for believing that the recent is (or will turn out to be) more significant from a larger historical perspective.

What I really find interesting (from a socio-historical perspective) is how quickly technologies can shift from fascinating to taken-for-granted. Since I started work, my working life have been transformed by a range of tools, including word processing, spreadsheets, mobile phones, fax machines, email and internet. Apart from a few developers working for Microsoft or Google, is anyone nowadays fascinated by word processors or spreadsheets? If we pay attention to the social changes brought about by the Internet, and ignore the social changes brought about by the word processor, then of course we will get a distorted view of the internet's importance. If we glamorize the iPhone while regarding older mobile telephones as uninteresting, we end up making a fetish of some specific design features of a particular product.

If we have a distorted sense of which innovations are truly disruptive or significant, we also have a distorted sense of technological change as a whole. There is a widespread belief that the pace of technological change is increasing, but this could be an illusion caused (again) by proximity. See my post on Rates of Evolution (September 2007), where I also note that some stakeholders have a vested interest in talking up the pace of technology change.

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Clayton M. Christensen, Michael E. Raynor, and Rory McDonald, What Is Disruptive Innovation? (HBR Magazine, December 2015)

Adrian Daub, What Tech Calls Thinking (Farrar Straus and Giroux, 2020)

Thanks to @jchyip for kicking off the most recent discussion.

Evolution or Revolution 2

@ceciiil asserts a difference between @oscarberg and @bduperrin in his post E2.0 Evangelists : the Revolutionaries and the Evolutionaries (March 24, 2010).

I'm not convinced by this distinction. Cecil says that revolutionaries believe in disruption and evolutionaries believe in incremental change. But these beliefs are not mutually exclusive. In a simple linear world perhaps, incremental change is unlikely to be disruptive. But in a complex dynamic world, incremental change can often trigger disruptive change. (There is a branch of mathematics called Catastrophe Theory, dedicated to the study of such non-linear phenomena. And Hegelians define dialectics as the transformation of quantity into quality - see for example Anti-Dühring by Frederick Engels.)

So I have long argued that the difference between evolution and revolution is largely a difference of perspective. Not either/or but both/and.

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The following is an extract from Chapter 5 of my book on the Component-Based Business (Springer 2001).

A sudden change is often described as a revolution. A progressive change over time is often described as an evolution.

Even in biology, the distinction between sudden change and slow change is problematic. If you had been sitting on the seashore many millions of years ago, you might have seen the first sea creatures crawl onto land, and this might seem a sudden and dramatic event, from a human perspective. However, a squid might see this event as relatively unimportant, merely as one of many tentative explorations by a few creatures at the margins of the oceans, or as a fairly routine extension to previous innovations within a large and diverse community of sea creatures.

Many present-day commentators characterize the emergence of computing, or the Internet, or E-Business, as revolutionary. From one perspective, these appear to be previously unseen phenomena, emerging suddenly into public awareness from the obscurity of some other domain. From another perspective, the same phenomena appear to be a natural consequence of a large number of independently planned and executed moves by a large number of engineers, businessmen and others, whose origins can be traced back to innovations made years ago, decades ago, perhaps even centuries ago.

Thus the same phenomenon can be described as revolutionary AND evolutionary at the same time, depending on where you’re standing, and the amount of history you’re prepared to absorb.

If I describe a change as revolutionary, I’m inviting you to concentrate your attention on certain aspects of the change. I want you to see it as a dramatic break with the past, with sweeping implications across a fairly wide domain.

If I describe a change as evolutionary, I’m inviting you to take a different perspective. I want you to be aware of the links between the past and the future, and the extent to which previous patterns and innovations are being adapted and reused.

Some people feel safer with evolutionary descriptions of change, while others feel happier with revolutionary descriptions. As a manager or consultant, I might feel the need to motivate some people, while reassuring others. Sometimes I want to emphasize continuity; at other times, I want to emphasize novelty. At least from a logical point of view, I’m not necessarily contradicting myself if I describe things differently for different stakeholders – although there may be ethical or practical difficulties if the descriptions diverge too greatly.

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Related Posts

Evolution or Revolution (May 2006)

Red Queen Effect 2

Dave Bayless has responded to Critiques of the Red Queen Model, including my comments on this blog (Red Queen Effect, see also Rates of Evolution). 

Dave chooses to define innovation as "launching new products". Both John Hagel and I believe that there are other kinds of innovation that are important. But I have a more fundamental concern with Dave's definition - if I don't know exactly what counts as a "new product", then I don't know how to count them. If this year's model has a slightly faster chip than last year's model, or a brushed aluminium case, does that count as a "new product"? Let's say the iPod is a new product, but is the iPhone really a new product, or just a fancy redesign of an old product?

Lots of people in product development have a vested interest in labelling everything as "new improved". Pharma companies spend a small fortune looking for variations on existing drugs, so they can get patent protection for the "new" formula. But if you take these descriptions at face value, you get a fundamentally distorted view of the underlying technology change.

This is why I think we need a rigorous model of technology change, which handles some of the complications I raise in my previous blog entries.

 

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Update March 2022

Following a brief exchange with Dave on Linked-In, I have looked at another of his earlier posts, which refers to the work of Professor Charles Fine on industry clockspeed. 

In a paper written in 1996, Fine compared product technology clockspeed between aerospace (commercial aircraft) and media (infotainment). He noted that Boeing was launching roughly two new products per decade, while Disney was launching one new product per year, and concluding that media therefore has a faster clockspeed than aerospace. 

There are several problems with this comparison. Firstly, it doesn't seem to represent a fair comparison between the true rate of innovation in the two industries. If Disney films are made to a formula, and the basic formula doesn't change, how much innovation does each new film represent? This comes back to the point I raised in my original posts above.

Fine presumed that "Disney's product development teams ... work on a cycle time geared to the time between new product introductions". I don't have any inside information on Disney, and it appears he didn't either but from my experience in comparable media organizations I should expect multiple development teams working in parallel, with the ones doing the most innovative work taking several years to complete something.

Furthermore, Fine also observes that other parties in the Disney ecosystem (notably the distribution channels) have a much faster clockspeed. So he notes that "clockspeed may not be well-defined at the industry level since many industries are composites of others".

For John Hagel and myself, the more interesting innovation in the media industry was not Disney or Pixar churning out blockbuster films, but these firms converting themselves to platforms. But does the platform itself count as a product?

 

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Dave Bayless, Is the Pace of Business Really Increasing (7 September 2007), Critiques of the Red Queen Model (1 October 2007)

Charles H Fine, Industry Clockspeed and Competency Chain Design: An Introductory Essay (MIT Sloan WP 147-96, March 1996) 

John Hagel, Disney, Pixar and Jobs (3 February 2006)

Richard Veryard, Technology Hype Curve (16 September 2005), Disney, Pixar, Apple and Jobs (6 February 2006), Red Queen Effect (19 September 2005), Rates of Evolution (3 September 2007)

Rates of Evolution

A fascinating paper by Philip D. Gingerich shows how the observed rate of evolutionary change (measured in darwins), varies hugely according to the measurement context. (See table at foot of this post). In other words, the observed rate of biological evolution appears to be proportional to the proximity of scientists. Does a similar phenomenon apply to technological evolution?

(Note: I am not assuming that technological evolution is the same as biological evolution - merely that looking at one domain may prompt some interesting and important questions for the other domain.)

I have always been wary of the common belief that technological change is accelerating. I think this belief derives from a combination of proximity, selectivity and distorted perception. I think we can sometimes be disproportionately impressed by the glamour of recent technology, and misled by the commercially-driven measures of intellectual property (such as volumes of patent activity and product releases). We should also note that some commentators (such as industry analysts) have a vested interest in talking up the pace of technology change (Red Queen Hypothesis, Technology Hype Curve).

But consider these questions:

Did the lightbulb or bicycle change more

• between the years 1880-1900?
• or between the years 1980-2000?

Did the computer change more

• from 1950 to 1970?
• from 1980 to 2000?

It is certainly true that there have been huge numbers of small modifications to devices such as lightbulbs, bicycles and computers since 1980. There has also been a proliferation of variations and mutations. But will any of this innovation be remembered in fifty years time? From a historical perspective, this kind of detailed technological refinement (or even hyperactivity) may seem rather less significant than the initial burst of technical creativity when the device was taking shape in the first place.

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Notes

Context	Timescale of Observations	Observed Rate of Change
Laboratory	1.5 - 10 years	60,000 darwins
Colonization studies	70 - 300 years	400 darwins
Post-pleistocene mammals	1,000 - 10,000 years	4 darwins
Fossil record	Millions of years	0.1 darwins

Philip D. Gingerich, Rates of Evolution: Effects of Time and Temporal Scaling. Science 14 October 1983: Vol. 222. no. 4620, pp. 159 - 161

Update: Professor Gingerich's book Rates of Evolution was published by Cambridge University Press in 2019.

See also: Delayed Success - Evolution (April 2023)

Evolution or Revolution

Mache Creeger asks Evolution or Revolution = Where is the High in High-Tech?

"We work in an industry that prides itself on 'changing the world', one that chants a constant mantra of innovation and where new products could aptly be described as 'this year’s breakthrough of the century'. While there are some genuine revolutions in the technology industry, including cellphones, GPS (global positioning system), quantum computing, encryption, and global access to content, the vast majority of new product introductions are evolutionary, not revolutionary. Real technical breakthroughs are few and far between. Most new products are just a recycling of an earlier idea."

This represents a challenge to the popular belief in the accelerating rate of technical change. I have blogged about this before: Death of Software, Innovation or Refinement.

Bob Wyman complains about Creeger's distinction between evolution and revolution, and insists that Evolution = Revolution. There are undoubtedly some complications in evolutionary theory that Creeger doesn't mention. (Wyman references over a dozen articles in Wikipedia.) But I don't think this alters Creeger's basic argument about the pace of technological change. Wyman suggests that the current situation may be interpreted as part of an evolutionary cycle, and hopes (even predicts) that there is more innovation just around the corner.

"Today's thinkers are no less smart and no less innovative than were the folk working 'back in the day'. The difference is that today we're all still focused on working through the implications of the last revolution. In time we'll exhaust the realm of easily achieved secondary innovations and we'll then be ready to move on to more revolutionary 'Cambrian' times again. It is always like this. It always has been and it always will be."

He appeals vaguely to various intellectual authorities (including Stephen Jay Gould and the entire Santa Fe Institute) in support of this wishful thinking, before falling back on some popular but lightweight business literature (Clayton Christensen: The Innovator's Dilemma, The Innovator's Solution).

Ultimately, the comparison between biological evolution and technological evolution may be useful as an explanatory device, or as a source of interesting hypotheses, but not as a reliable source of predictions about the future.

How can we measure the true pace of technological change? Some people use patent activity as a metric, but this metric is made almost meaningless by the vast number of trivial patents, as both Creeger and Wyman agree. How can we decide which are the major innovations? Creeger mentions a few, but Wyman has his doubts even about these.

The success of evolutionary theory is based in part on painstaking observation and classification by generations of biologists. We simply don't have an equivalent body of knowledge about technological innovation. What we have is large amounts of hype and hot air, and a relatively small number of detailed scientific studies of particular innovations.

Even in the absence of detailed empirical data, however, it is always useful to step back from the current obsession with technical wizardry, and try to get a bigger picture of technological change. In this spirit, I welcome both Creeger's polemic and Wyman's reinterpretation, while remaining cautious about the inevitable subjectivity of both.


Related Posts
Evolution or Revolution 2 (March 2010)

Differential Adoption

Where there are two competing technologies in a given space, we may be able to learn something interesting from the differential patterns of adoption. (In studying a technology in relation to its adoption space, we get a better understanding of both.)

RSS and Atom represent two competing standards for internet syndication. James Snell recently posted a quick note of some of the technical differences: So what's the deal with Atom? He has now discovered some evidence of differential adoption between RSS and Atom. It turns out RSS and Atom really are different.

However, we need to interpret this evidence carefully. Technology often goes in clusters - one technology drags other technologies on its coattails - and it is not always obvious which technology is the determining factor in the user selection.

(In biological evolution, there is a phenomon known as genetic coupling, which links together apparently distinct features and prevents them from developing independently of one another. Thus natural selection doesn't prove the advantages of a single feature in isolation, merely the aggregate advantages of some group of features. Similar coupling often happens with interdependent technologies, and this complicates the study of technology adoption.)

In this particular example, the user preference for either Atom or RSS is correlated to a user preference for different news readers (e.g. Bloglines versus RSS readers).

• Bloglines readers are more likely to subscribe to Atom.
• Atom readers are more likely to use Bloglines.

There are many possible ways of explaining this correlation. Maybe this has something to do with the characteristics of the Bloglines user (of which I'm one). Or perhaps it has something to do with the design of the Bloglines subscription mechanism. Where a blog offers both an RSS feed and an Atom feed, Bloglines readers are given the choice. (For my part, I always choose the Atom feed.)

In his recent book Democratizing Innovation (free download here), Eric von Hippel discusses lead users and identifies three characteristics as follows:

• ahead of the majority of users in their populations with respect to an important market trend,
• expecting to gain relatively high benefits from a solution to the needs they have encountered there,
• and a significant source of innovation - many of the novel products they develop for their own use will appeal to other users too and so might provide the basis for products manufacturers would wish to commercialize
  

James Snell refers to this book, and suggests that Atom users may be lead users in this sense. But the differences between Atom and RSS (as described by James) don't seem to warrant this suggestion. Is there any evidence that these Atom users are actually exploiting the technical differences between Atom and RSS, and/or generating significant quantities of user-centred innovation?

Technorati Tags: Atom-enabled innovation RSS technology adoption

A model of trust

originally posted by John

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With its amazing, true-to-life 8bn light year wide cubic chunk of the universe available for research, the Virgo Consortium's Millennium Simulation could finally answer Religious America’s burning question: did dinosaurs really walk in the Garden of Eden with Adam and Eve? Creationists won’t like the answer any more than they like the simulation so they’ll just have to stick with their Microsoft version of the universe I suppose.

Enacted Technology

In her work on the Virtual State, Jane Fountain has made an important distinction between what she calls Objective Technology and Enacted Technology. She points out that technological outcomes are largely driven by the Enacted Technology, and this is only indirectly dependent on the Objective Technology. 

 

 

For many years we have been making a similar distinction: between Technology-as-Designed and Technology-in-Use. (Our concept of Technology-in-Use is broadly the same as Fountain’s concept of Enacted Technology, but we are uneasy with her characterization of Objective Technology.) 

As technology change management practitioners, we can make the following observations. 

Firstly, there is a many-to-many relationship between Designed Technology and Enacted Technology. Not only can the same Designed Technology be enacted in many different ways (even within the same organization), but the enacting process can sometimes nullify design differences. (In other words, technological features which designers think highly significant can often prove irrelevant in the context of use.) 

The procurement process often focuses on the Designed Technology, or the so-called Objective Technology, although there may be some attention on how the technology has been enacted elsewhere. This means that the procurement process often fails to make good connections to the desired/expected outcomes, while often spending lots of time on technical features with minor impact on outcomes. 

Secondly, there may be loose co-evolution between the Designed Technology and the Enacted Technology, but without tight synchronization. Sometimes new features are added to the Design that only slowly filter into practice; sometimes new practices emerge in the Enacted Technology and only get reflected in the Design after some delay. 

Thirdly, the gap between Designed Technology and Enacted Technology is itself a subject of interest, and can reveal something about the maturity of both the technology and the organization. 

 

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Jane E Fountain, Building the Virtual State: Information Technology and Institutional Changes (Washington DC: Brookings, 2001). A draft of Chapter 6 is available via academia.edu.