Technology in use

In many blogposts I have mentioned the distinction between technology as designed/built and technology in use.

I am not sure when I first used these exact terms. I presented a paper to an IFIP conference in 1995 where I used the terms technology-as-device and technology-in-its-usage. By 2002, I was using the terms "technology as built" and "technology in use" in my lecture notes for an Org Behaviour module I taught (together with Aidan Ward) at City University. With an explicit link to espoused theory and theory-in-use (Argyris).

Among other things, this distinction is important for questions of technology adoption and maturity. See the following posts 

• Blame PowerPoint (October 2009) 
• What is Technology Maturity (December 2009)
  

I have also talked about system-as-designed versus system-in-use - for example in my post on Ecosystem SOA 2 (June 2010). See also Trusting the Schema (March 2023).

Related concepts include Inscription (Akrich) and Enacted Technology (Fountain). Discussion of these and further links can be found in the following posts:

• Enacted Technology (July 2004)
• Strawberry Picking (October 2004)
  
• Inscription and Loose Coupling (September 2005)

And returning to the distinction between espoused theory and theory-in-use. In my post on the National Decision Model (May 2014) I also introduced the concept of theory-in-view, which (as I discovered more recently) is similar to Lolle Nauta's concept of exemplary situation.

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Richard Veryard, IT Implementation or Delivery? Thoughts on Assimilation, Accommodation and Maturity. Paper presented to the first IFIP WG 8.6 Working Conference, on the Diffusion and Adoption of Information Technology, Oslo, October 1995. 

Richard Veryard and Aidan Ward, Technology and Change (City University 2002) 

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)

Venturesome Consumption

Chris Potts pointed me to the work of Amar Bhidé, which raises some interesting and important questions for innovation and organization change in general, and for EA in particular.

Venturesome Consumption, Innovation and Globalization (pdf)
Paper for a Joint Conference of CESifo and the Center on Capitalism and Society
“Perspectives on the Performance of the Continent’s Economies”
Venice, 21 - 22 July 2006
by Amar Bhidé

1. Absorptive capacity. I think this concept is important both for inter-enterprise innovation (adoption of new business models, practices and technologies by the enterprise as a whole) and intra-enterprise innovation (diffusion of new systems and processes across the organization). Within Lenscraft, this is covered by the Adoption Engineering lens.

2. Productivity and competitive advantage. There is an important question about how innovation generates value, and for whom. If all players in a competitive industry adopt (are forced to adopt) the same innovation, then none of them may gain any net value, but all of them may avoid losing value. Arguably the customers are the beneficiaries, but this is not a straightforward calculation. For example, customers benefit more than banks from the ubiquity of ATMs, although this is hard to quantify, and with other technologies it may be difficult to demonstrate any customer benefit at all. On a Marxian argument, although technology can produce a short-term improvement in profit in an industry, the longer-term effect on profit is downwards, in which case it would be puzzling why monopolies would ever bother. (Indeed, in some utilities, the pressure for technological innovation seems to come largely from the regulators.) The Marxian argument about the falling rate of profit isn't universally applicable, but it behoves champions of innovation within organizations to understand where it does and doesn't apply.

3. ROI. The first two points are not addressed in the bog-standard business case, and the ROI is often grossly over-estimated, based on extremely naive assumptions. A proper joined-up systems analysis would expose the weaknesses here. This relates to what Bhidé calls Knightian uncertainty.

4. Resourceful problem solving. The users have an active role in producing what I have called the "technology-in-use". This also links to the work of Erik von Hippel.
http://www.users.globalnet.co.uk/~rxv/orgmgt/ob8.pdf

5. Barriers to innovation and diffusion. Bhidé is interested in national borders; some of us may be more interested in organizational boundaries (both external and internal). But the word "barriers" is an inadequate metaphor - in reality there is a landscape with uphill and downhill contours, making some paths easier and quicker than others, but few paths are completely impassable.

6. One of the consequences of this analysis is that we should be modelling the internal and external flows of knowledge and ideas, as a critical element of a business model. To some extent this is already done in industries like pharma, but these flows largely focus on product development knowledge and don't provide a more general picture.

7. Overall, an important plea for the demand side of innovation to be taken as seriously as the supply side. I completely agree with this.

Strawberry Picking

Have found an interesting paper on Adjusting to Technological Change in Strawberry Harvest Work (pdf) by Howard R. Rosenberg. A version published in Choices Magazine, May 2004. 

Strawberry picking is a highly skilled and labour-intensive activity, which amounts to some 40% of the total production costs of strawberries. The machine discussed by Rosenberg doesn't remove the skilled elements of the work, but it does remove some of the back-breaking elements.

This innovation cannot be evaluated in purely technical terms. Instead, we must look at the machine as it is embedded in a given set of working practices. We call this Technology-In-Use, or Enacted Technology.

As Rosenberg puts it: "Costs, benefits and ultimate success of the transition to machine-aided strawberry harvest depend on synchronizing the use of the machine with the attributes of the people whose labor remains the most essential factor of production."  

Here are some of the further issues Rosenberg identifies: 

Crew Configuration and Membership Does work in a machine crew require a different orientation or set of abilities than in conventional crews? Will employee recruitment, selection and assignment be designed to create crews who tend to work at a similar pace? Will crew members rotate through the stacker and machine operator jobs? 

Speed of the Machine How fast will the machine creep down the field? More importantly, who decides? 

New Pay Rates What share of efficiency gains will be allocated to compensate for the increased volume of berry handling and to raise individual worker earnings? How much will pay be based on time and how much on output? What is a fair relationship between old and new piece rates? 

Scheduling, Rest Breaks and Safety Training Are any adjustments needed to explain or alleviate possible ergonomic risks of increased picking time? 

Introduction of the New System Itself When and how will workers be informed about the machine system and the changes around it? Will they have a choice of working in a traditional or a machine-aided crew?  

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. 

Change Agent Cascade

This is a popular pattern of change management.



A change agent adopts and enacts some technology, and also produces a series of messages concerning this technology. This set of actions and messages represents the change agency of this agent, which has some effect (with some delay) on the behaviour of other agents.



The scale of the effect depends on the number of agents influenced, and the degree of influence on each one. This in turn may depend (among other things) on trust.



Many people will be influenced by multiple change agents. There is a positive effect when the actions and messages of different change agents appear to reinforce one another, but without excessive uniformity.



We can make three important observations about this process. Firstly, the technology is disseminated across a network of trust. This gives us ways to think about (and possibly manage) the ability of a new technology to access different parts of a complex organization



Secondly, transmission from one change agent to another often involves some alteration – adopt, adapt, improve. Knowledge and understanding may be attenuated or distorted; working practices may be refined or simplified. Thus the technology is typically not enacted uniformly across the space, but may be transmuted in sometimes surprising ways.



Thirdly, there are many technology cascades operating across the same space at the same time, interacting with one another in complex and unpredictable ways.



In general, therefore, the outcome for a given technology in a given space depends on the geometry of the space, as well as the logic of interaction between technologies. Technology change management must pay careful attention to these matters.