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Inflexibility of experts—Reality or myth?

How does the knowledge of experts affect their behaviour in situations that require unusual methods of dealing? One possibility, loosely originating in research on creativity and skill acquisition, is that an increase in expertise can lead to inflexibility of thought due to automation of procedures. Yet another possibility, based on expertise research, is that experts’ knowledge leads to flexibility of thought.
[the authors} tested these two possibilities in a series of experiments using the Einstellung (set) effect paradigm. Chess players tried to solve problems that had both a familiar but non-optimal solution and a better but less familiar one. The more familiar solution induced the Einstellung (set) effect even in experts, preventing them from finding the optimal solution. The presence of the non-optimal solution reduced experts’ problem solving ability was reduced to about that of players three standard deviations lower in skill level by the presence of the non-optimal solution. Inflexibility of thought induced by prior knowledge (i.e., the blocking effect of the familiar solution) was shown by experts but the more expert they were, the less prone they were to the effect. Inflexibility of experts is both reality and myth. But the greater the level of expertise, the more of a myth it becomes.
Merim Bilalić,Peter McLeoda and Fernand Gobet. 2007.

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When a novel approach is required, the experts’ knowledge can make them unable to adapt to the new task demands. Sternberg (1996) summarised this view of the inflexibility of experts: “…there are costs as well as benefits to expertise. One such cost is increased rigidity: The expert can become so entrenched in a point of view or a way of doing things that it becomes hard to see things differently.” (p. 347).

Our main goal, however, will be to try to uncover the mechanisms behind experts’ (in)ability to resist the Einstellung effect. This effect occurs in situations where people are unable to choose a less familiar, but optimal solution, rather than a familiar but non-optimal solution.

the creative product should go beyond previous knowledge and expertise, break links with the past and move away from stereotypical thinking. Implicit in this notion of creativity is that knowledge is necessary but not sufficient (for a different view see Hayes, 1989, Kulkarni and Simon, 1988 and Weisberg, 2006).

The ambivalent role of prior knowledge in creativity can be seen in many different research traditions.

The following quote from Kuhn’s famous work on ‘The Structure of Scientific Revolutions’ (1996/1962) summarises the view that very knowledgeable people can be inflexible: “Almost always the men who achieve these fundamental inventions… have been either very young or very new to the field whose paradigm they change” (p. 90). These creative minds were more open to new ideas and could accept the break with previous theories because they were not too deeply immersed in the established thought patterns of their more experienced colleagues.

knowledge is necessary but too much of it can be harmful for creativity—it is almost a necessary evil (see also Csikszentmihalyi, 1996 and Simonton, 1999). This view of creativity is not restricted to scientific research. As a popular ‘creativity trainer’ wrote: “Too much experience within a field may restrict creativity because you know so well how things should be done that you might be unable to escape to come up with new ideas” (deBono, 1968, p. 228).

The other area of research that is cited as providing theoretical reasons for expert inflexibility is skill acquisition with its central concept of automatization. Automatization has been seen as central to skill acquisition ever since Bryan and Harter (1899) claimed that higher level habits cannot be acquired unless lower level habits had been automated.

in all the frameworks, performance in the final phase of skill acquisition is fast, accurate, mostly effortless, seemingly beyond conscious control, in a word—automated. Automatization is generally considered advantageous because it saves time and cognitive resources that can be directed to other aspects of the task. But it is easy to see how this favourable aspect of skill can turn against the skilled individual. When the general features of a task trigger off an automated response but another, uncommon, response is required, experts may become victims of their automated task execution which, once initiated, is difficult to control.

We can define flexibility of thought as the ability to adapt to problems where it is necessary either to use new methods, techniques, knowledge or information, or to modify the existing method of dealing with the problem. In this sense, inflexibility of thought induced by prior experience has been demonstrated experimentally in two situations. In the first, participants can solve the problem with their existing knowledge and do so failing to notice that a superior, but less familiar, solution is available. In the second, a change in the task requires a novel procedure to be generated but experts have difficulty doing this because they cannot suppress the procedures they already possess.

A classic example of the first sort of harmful influence of prior experience on problem solution is the Einstellung (set) effect demonstrated by Luchins (1942) with the water–jug problem. Participants were given five introductory problems that could be solved using the same method. These were termed ‘Einstellung problems’ because the common solution method used for all of them was expected to induce a mental set for solving similar problems. The next two problems, termed ‘critical’, could be solved using the same method but a shorter and simpler solution was also possible. Over 80% of the participants failed to notice the shorter method and continued to use the longer method they had used successfully in the introductory problems. Luchins then presented an ‘extinction’ problem. This could not be solved using the original method but could be solved with the shorter method. Sixty four percent of the participants failed to solve the extinction (1-solution) problem. In comparison, only 5% of a control group who started with the critical (2-solution) problems and did not experience the introductory problems failed to solve the extinction problem (Luchins & Luchins, 1959). Thus, rather than improving their performance, the experimental group’s additional experience of the general problem situation blinded them to a simple solution which was found by almost everyone who had not had the extra experience. Luchins’ striking demonstration that experience can induce inflexibility of thought has been successfully repeated many times in a variety of formats (e.g., Atwood and Polson, 1976, Chen and Mo, 2004, Delaney et al., 2004, Lippman, 1996, Lovett and Anderson, 1996, McKelvie, 1990 and Woltz et al., 2000).

Einstellung phenomena, in contrast, are notoriously difficult to notice. In the critical, 2-solution problem of an Einstellung task an inefficient method of dealing with the problem is transferred but the method produces a solution. So the person experiencing the effect does not realise that there is any need to look for a better one.

Saariluoma (1990), however, reported that the only exceptions to the fixated group of players were “the one master who was not fixated the first time, and the Grand Master, who saw both alternatives” (p. 45). It seems that more skilful participants may be able to resist becoming fixated by the familiar but non-optimal solution. Given the current empirical evidence, it is not entirely clear how they were able to resist choosing the familiar solution.

By conventional standards all the players in Group 1 were experts but there were differences in flexibility between them. The ‘super’ experts (more than 5 SDs above average skill level) were flexible. They first saw the good solution, just like the ordinary experts, but this did not prevent them finding a better one. In contrast, the ‘ordinary’ experts (3 SDs above average skill level) were inflexible. When they could see a good solution they were unable to find a better one although they saw it when the good solution was no longer available. We have demonstrated for the first time an expertise effect in flexibility in problem solving—the more knowledgeable the experts were, the less likely they were to be trapped by the immediate appeal of the familiar solution. More expertise provides more resources to resist the temptation to choose a familiar but non-optimal solution.

The Einstellung effect was remarkably powerful. It reduced the performance of ordinary experts to that of average players. The gap between ordinary experts and average players (about three SDs) is a dramatic gulf in skill. Normally, average players have no chance of beating ordinary experts. Yet, the Einstellung effect reduced the performance of ordinary experts to that of average players. The hidden power of the Einstellung effect was demonstrated by the inaccurate metacognition of another group of experts who seriously underestimated the effect of the presence of the familiar solution. Why does the Einstellung effect have such a dramatic effect on the performance of experts?

== psychological inertia
== dilemma: have to have the skill and automation to solve "above average" problems; don't want to have the skill to solve "creative" problems.

This illustrates the main danger of the Einstellung effect—there is no feedback available on the inappropriateness of the well-known solution. Consequently, players do not spend too much time pondering other solutions. In those few moments of reflection, only the most skilful experts managed to find the optimal solution.

== how do you know that your solution is the best?

ideality principle, system models, dilemma resolution

Both experiments show that although experts can be trapped by the immediate appeal of a well-known solution to a problem, the more expertise players possess the more likely they are to find the optimal solution once they start to look further.

The contrasting performance of our ‘ordinary’ experts (around 3 SDs above average performance) and our ‘super’ experts (more than 5 SDs above average performance) suggests that both options are possible depending on the expertise level and the problem difficulty. In the first experiment the ordinary experts all spotted a well-known solution. They looked for a better one but failed to find it. Similarly, the super experts all found the well-known solution first and then looked for a better one. In contrast to the ordinary experts, they all found it.

The failure of the ordinary experts to find a better solution when they had already found a good one supports the view that experts can be vulnerable to inflexible thought patterns. But the performance of the super experts shows that ‘experts are inflexible’ would be the wrong conclusion to draw from this failure. The Einstellung effect is very powerful—the problem solving capability of our ordinary experts was reduced by about three SDs when a well-known solution was apparent to them. But the super experts, at least with the range of difficulty of problems used here, were less susceptible to the effect. Greater expertise led to greater flexibility, not less.

"fast" thinking in the arousal state.

vs "slow" thinking in the "afterthought" phase.

We have proposed a two-stage model, where a solution is first proposed by memory retrieval; this is then followed by a quick search for a potentially better solution. Our data suggest that super experts are more flexible because they are more efficient in both stages: they are more likely to find the optimal solution right away by memory retrieval; failing so, they are still more likely to find the optimal solution by search.

As Palmeri (1997) put it in his account of automaticity and categorization: “whereas novices seem to rely on slow, conscious, deductive reasoning, experts seem to rely on fast, relatively unconscious processing—the chess master ‘sees’ the right moves” (p. 346).

The serious consequences of the Einstellung effect have been demonstrated by Reason (1990) who showed that many accidents in real life are caused by experienced system users such nuclear power-station controllers being stuck in their well-practiced routines and unable to adopt a new pattern of thought when a system malfunction meant that the familiar pattern was no longer appropriate.

== The Apollo 13 situation

We showed that ordinary experts can be inflexible, that is unable to resist the temptation of choosing a well-known solution, and that for them ‘inflexibility of experts’ is reality. However, we also showed that super experts maintain control over their performance, noticing and taking into account even the smallest, and, on first sight, maybe irrelevant, details. Inflexibility of experts is both myth and reality. But the greater the degree of expertise, the more of a myth it becomes.

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Inflexibility of experts—Reality or myth?

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chess experts experiements

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