Motive Generators in Major Innovators and Tweakers

Malcom Gladwell published an article titled “The tweaker: The real genius of Steve Jobs” in the  New Yorker (Nov. 2011).  He marshalled several examples from Isaacson’s book on Jobs to make the point that Jobs was more of a tweaker than grand inventor. Gladwell is close to the mark in saying that “Jobs’s sensibility was editorial, not inventive. His gift lay in taking what was in front of him—the tablet with stylus—and ruthlessly refining it.”  But Gladwell’s own paper needs a tweak in the form of a concept which gets to the heart of Steve Jobs as innovator: As I argued in a post in August, Steve Jobs, like most innovative knowledge workers, had particularly developed motive generators.

In his book, The Emotion Machine, Marvin Minsky (2006) uses the term “critics” for something akin to the concept of motive generators. While of course critics sometimes confer praise to their objects, the term “critic”brings to mind negative assessments. Negativity seems to be what motivator generators produce most of the time. (The English lexicon has far more negative-affect words than positive ones. Progress comes more from identifying and resolving problems than basking in the glow of pleasant satisfaction.) However, the term motivator generator has a more general connotation: motive generators are also involved in detecting opportunities and telling us to pursue or continue a course of action that appears promising, feels good, etc.

Regardless of the terminology, the point Sloman, Minsky and I make is that our assessments don’t appear out of nowhere. There must be fine-grained mechanisms in the mind that generate motivational states, including cognitive motivational states (meaning, about knowledge); and there are other mechanisms that manage these states (motivator management processes). In Steve Jobs’s case the motivators were often very intense and very insistent. Partly due to historical influences dating back to Aristotle, and partly to a narrow interpretation of the name of their field, cognitive scientists (including AI types and cognitive psychologists) tend not to inquire deeply into the mechanisms that generate motivators. They assume goals, assessments, constraints, and other motivators as given; then they explore processes that solve the given problems. However, to fully understand learning,  innovation, and the development of expertise, we need to study asynchronous motive generators and how they direct and interact with problem-solving processes. By asynchronous, I mean processes that operate in parallel with more global, attention-bearing processes.

Gladwell’s distinction between major inventors, tweakers and implementers comes from Meisenzahl & Mokyr. This distinction is useful for historians and economics researchers, because they study phenomena from the outside and over long time scales. In contrast, cognitive scientists model the internal workings of the mind and can measure mental processes by the millisecond. (Incidentally, that is what really got me hooked in 1988: suddenly psychology became (reverse) engineering! E.g., Sternberg found that it takes 250 ms to retrieve an item from working memory. How cool is that level of precision!?)

Very creative knowledge work involves both producing and pruning new ideas, big and small. Of course, some minds venture further afield than others. But whether a knowledge worker ends up pursuing a significant major invention or a significant refinement depends not merely on the cognitive processes and inclinations underlying his or her innovations but on historical, economical and circumstantial factors. In either case, there is a lot of tweaking going on, though historians do not normally have access to sufficiently fine-grained records. Future historians might; and I suspect the major innovators will be shown to be tweakers.

Behind the big ideas there is always a personal history of detailed refinement. The interplay between the creation and selection of ideas is discussed in Daniel Dennett’s (1974) charming paper, “Why the law of effect will not go away”.

“The poet Paul Valérie said: ‘It takes two to invent anything.’ He was not referring to collaborative partnerships between people but to a bifurcation in the individual inventor. ‘The one’, he says, ‘makes up combinations; the other one chooses, recognizes what he wishes and what is important to him in the mass of the things which the former has imparted to him. What we call genius is much less the work of the first one than the readiness of the second one to grasp the value of what has been laid before him and to choose it.’” (Also reprinted in Brainstorms.)

I wouldn’t say that one is more important than the other. But I do believe that the role of motive generators (including evaluators and comparators) has been vastly underestimated in cognitive science.  Motive generators are the engine of progress, of innovation. They are what make you detect that a solution is suboptimal. They don’t just tell you “By the way, this is not right” in a dry and factual manner. Instead they make you feel it in an insistent  and intense way. Insistence is what makes a motivator distract your attention. Intensity is what makes it drive your behaviour. (I’ll write more about the distinction between intensity and insistence in the future. But you can refer to Chapter 3 of my Ph.D. thesis in the interim if you’re curious.)

For example, In 1997 Jobs took over as CEO and decided Apple needed a new marketing campaign to tell the world (and Apple) that Apple was alive and stood for something special. Lee Clow, a marketing guru, presented Jobs with a pitch for what was to become the highly successful Think Different campaign. Here is what Jobs said about it in retrospect.

[Clow] and his team had come up with this brilliant idea, “Think Different.” And it was ten times better than anything the other agencies showed. It choked me up, and it still makes me cry to think about it, both the fact that Lee cared so much and also how brilliant his “Think Different” idea was. Every once in a while, I find myself in the presence of purity—purity of spirit and love— and I always cry. It always just reaches in and grabs me. That was one of those moments. There was a purity about that I will never forget. I cried in my office as he was showing me the idea, and I still cry when I think about it.

The affect  jumps off the page at us. If Jobs’s recollection is veridical, his motive generators at the time must have been firing wildly to indicate a very promising marketing path. However, regarding a specific draft copy of the central advertisement, Jobs exclaimed to one of Clow’s employees : “This is shit! […] It’s advertising agency shit and I hate it.”  (Isaacson, 2001).)   There were several rounds of rejection and fine tuning before the campaign was actually launched.

Steve Jobs’s mind was a great example of an engine for generating and responding to insistent motivators about products (cognitive itches). But look into any expert and you will find someone who gets annoyed at imperfection and then gets on with perfecting. Jobs lacked self-regulation. Losing one’s cool behaviourally is not a requirement for progressing; but neither Jobs nor the apparently cool, Jean PiagetTom Landry or John Wooden could have fully kept their cool inside and still been so successful: their motives were often (and had to be) insistent and intense, even while they seemed to be in control from the outside. Antonio Damasio makes a related point about the importance of affect in rationality with examples of people who are incapable of emotion being unable to make decisions. Unfortunately, Damasio’s theory lacks a detailed account of motivator generators and motivators; see Sloman, 1999. In future posts I will explain how insistence is a key concept to understanding “emotion”, or what Sloman and I technically call “perturbance”.

In his paper, Dennett, following Herbert Simon, also provides a missing link to evolution, where (1) random variation can only lead to progress if natural selection operates; and (2) apparently large scale progress is the result of something much more gradual. Insights may not be due to processes that rely on random variation, but they do rely on variation. In The Emotion Machine, Minsky wrote “Evolution is often described as a process of selecting beneficial changes — but most of evolution’s work involves rejecting changes that have bad effects.”  So it is with the mind.

Gladwell was right to emphasize the editing of Steve Jobs. Obviously, designing knowledge or other products involves an interaction of producing ideas, rejecting them and refining them. In this post, I have suggested that underlying these interactions, there are motivator generators at work in our minds. These mechanisms detect problems in current solutions. They motivate us to enforce or change the problem specification. They get us to design better solutions. Developing expertise involves growing and configuring myriads of motivator generators.

Stay tuned to for explanations of the role of motivator generators in progressive problem-solving, the development of your expertise, tips and more.


Beaudoin, Luc. P. (2011). Experts’ productive learning from formal knowledge: Motive generators and productive practice. A symposium in Honour of Aaron Sloman: from animals to robots and back: Reflections on hard problems in the study of cognition.

Beaudoin, Luc P, & Sloman, A. (1993). A study of motive processing and attention. In A. Sloman, D. Hogg, G. Humphreys, D. Partridge, & A. Ramsay (Eds.), Prospects for Artificial Intelligence (pp. 229-238). Amsterdam: IOS Press.

Beaudoin, Luc P. (1994). Goal processing in autonomous agents (Ph.D. thesis). Birmingham, England.

Damásio, A. (1994). Descartes’ Error: Emotion, reason and the human brain (336 pp). New York: Avon Books.

Dennett, D. C. (1975). Why the Law of Effect will not Go Away. Journal for the Theory of Social Behaviour, 5(2), 169-188. doi:10.1111/j.1468-5914.1975.tb00350.x

Gladwell, M. (2011, November). The tweaker: The real genius of Steve Jobs. The New Yorker, 32-35.

Hawes, N. (2011). A survey of motivation frameworks for intelligent systems. Artificial Intelligence, 175(5-6), 1020 – 1036.

Meisenzahl, R. R., & Mokyr, J. (2010). The rate and direction of invention in the British industrial revolution: incentives and institutions. In S. Stern & J. Lerner (Eds.), The Rate and Direction of Inventive Activity.

Minsky, M. (2006). The emotion machine: Commonsense thinking, artificial intelligence, and the future of the human mind (387 p.). Simon & Schuster.

Simon, H. A. (1970). Sciences of the Artificial (p. 123). The MIT Press.

Sloman, A. (1998). Damasio, Descartes, Alarms and meta-management. Proceedings International Conference on Systems, Man, and Cybernetics (pp. 2652–7.). San Diego: IEEE.



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Luc P. Beaudoin

Head of CogZest. Author of Cognitive Productivity . Cognitive productivity consultant and public speaker. Adjunct Professor of Education, Simon Fraser University Co-founder of CogSci Apps Corp. See About Me for more information.

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