The Nature of Intuitive Thought by L. Järvilehto (2015)

© The Author(s) 2015
L. Järvilehto, The Nature and Function of Intuitive Thought and Decision Making,
SpringerBriefs in Well-Being and Quality of Life Research,
DOI 10.1007/978-3-319-18176-9_2 http://www.springer.com/gp/book/9783319181752

This is a book chapter I had a look at to think about what people mean when they talk about things being intuitive. I’ve been thinking a lot about how placement on a page or blackboard, writing style, colour etc. can make certain conclusions about the things being written feel intuitive, and what exactly that might mean. This chapter is a nice summary of the cognitive science on the topic.

There’s a lot of talk about System 1 and System 2, those being ‘in charge of autonomous and non-conscious cognition, and volitional and conscious cognition, respectively’ p. 23. These systems seem to be helpful way to think, albeit metaphorical:

The dual-system formulations of dual processing present a compelling picture of
how the mind works. As Evans and Frankish, among others, argue, these formulations
are, however, currently oversimplified. (Evans and Frankish 2009, p. vi).
According to Kahneman, the two systems are rather “characters in a story”—
abstractions used to make sense of how our cognition takes place. (Kahneman
2011, p. 19 ff.) He notes, “‘System 1 does X’ is a shortcut for ‘X occurs automatically.’
And ‘System 2 is mobilized to do Y’ is a shortcut for ‘arousal increases,
pupils dilate, attention is focused, and activity Y is performed.’” (Kahneman 2011,
p. 415). p. 28

Their relationship to working memory seems important:

One of the critical distinctions of the two types of processes is whether they
employ working memory. “In place of type 2 processes, we can talk of analytic
processes [that] are those which manipulate explicit representations through
working memory and exert conscious, volitional control on behavior” (Evans 2009,
p. 42). While the working memory is often likened to System 2, the two are not in
fact entirely the same:
Working memory does nothing on its own. It requires, at the very least, content. And this
content is supplied by a whole host of implicit cognitive systems. For example, the contents
of our consciousness include visual and other perceptual representations of the world,
extracted meanings of linguistic discourse, episodic memories, and retrieved beliefs of
relevance to the current context, and so on. So if there is a new mind, distinct from the old,
it does not operate entirely or even mostly by type 2 processes. On the contrary, it functions
mostly by type 1 processes. (Evans 2009, p. 37).
Type 2 processes need the constant application of working memory, such as in
calculating by using an algorithm, in evaluating various choices in decisionmaking,
or in practicing a new skill. p. 29

This is interesting because Cognitive Load Theory is based on working out how to reduce load on the working memory through design choices.

As
Engle points out, working memory is not just about memory, but rather using
attention to maintain or suppress information. He holds that working memory concerns
memory only indirectly, and that a greater capacity in working memory means a greater ability to control attention rather than a larger memory. (Engle 2002, p. 20.)

There’s a nice association between intuition and heuristics here, nice because relevance theory is so based in ideas about heuristics:

Gerd Gigerenzer presents a four-fold taxonomy for explaining intuitions.
According to Gigerenzer, gut feelings are produced by non-conscious rules of
thumb. These are, in turn, based on evolved capacities of the brain and environmental
structures.
Gut feelings are intuitions as experienced. They “appear quickly in consciousness,
we do not fully understand why we have them, but we are prepared to act on
them.” (Gigerenzer 2007, pp. 47–48.) The problem with the trustworthiness of gut
feelings is that many other things appear suddenly in our minds that bear a similar
clarity and that we feel like acting on, for example the urge to grab an extra dessert.
But not all such reactive System 1 behaviors are good for us.
Rules of thumb are, according to Gigerenzer, what produces gut feelings. These
are very simple heuristics that are triggered either by another thought or by an
environmental cue, for example the recognition heuristic, where a familiar brand
evokes positive feelings. (Gigerenzer 2007, pp. 47–48.) Evolved capacities are what
rules of thumb are constructed of. They include capacities such as the ability to
track objects or to recognize familiar brands. (Gigerenzer 2007, pp. 47–48.)
And finally, environmental structures determine whether a rule of thumb works
or not. The recognition heuristic may work well when picking up a can of soda or
even stocks, if it is directed towards trusted and well-known brands. (Gigerenzer
2007, pp. 47–48.) p. 41

Gary Klein has developed a similar position to Gigerenzer’s in his famous
decision-making research. In Klein’s recognition-primed decision making model,
decisions are made neither by a rational, conscious weighing scheme, nor by a fast
non-conscious calculation, but are based rather on quickly recognizing viable
strategies for action based on expertise. (Klein 1998.)
Like Gigerenzer’s, Klein’s idea is based on Herbert Simon’s conception of
intuition as recognition. According to Klein’s research, people do not in fact typically
make decisions by rationally evaluating choices. (Klein 1998, loc 202.)
Rather, a great majority pick up a choice that first comes to mind, mentally simulate
it, and if it seems to work, go with the first viable one, without ever considering
options. This decision-making scheme follows the strategy of satisficing, (accepting
the first viable option), made famous by Simon, in contrast to the more rational
strategy of optimizing, i.e. weighing all possible options and picking the one that
comes out on top as best. (Simon 1956.)
The difference between Gigerenzer’s and Klein’s positions is in that where
Gigerenzer assumes that gut feelings are produced by heuristics or rules of thumb
that are typical to all humans and produced by our environment, Klein’s idea of
recognition-priming is based on picking up much more individually complex
strategies of action based on prior experience and expertise.p. 42

The author works hard to distinguish ontogenetic from phylogenetic.

The gist here is that we generate a considerable amount of ontogenetic Type 1
processes, or habits, by exercise, deliberate practice and daily experience. p. 43

The author is also quite interested in situated mind ideas, and brings in questions of environment.

Martela and Saarinen delineate three principles of systems intelligence. First, we
must see our environment as a system we are embedded in. Second, we need to
understand that intelligent behavior cannot be traced back only to the capacities of
an individual, but arise as features of the entire system in which the individuals
operate. And lastly, intelligent behavior is always relative to a context. (Martela and
Saarinen 2008, p. 196 ff.) p. 48

 

Relevance and rationality by NICHOLAS ALLOTT

Abstract
Subjects’ poor performance relative to normative standards on reasoning tasks has
been supposed to have ‘bleak implications for rationality’ (Nisbett & Borgida, 1975).
More recent experimental work suggests that considerations of relevance underlie
performance in at least some reasoning paradigms (Sperber et al., 1995; Girotto et al.,
2001; Van der Henst et al., 2002). It is argued here that this finding has positive
implications for human rationality since the relevance theoretic comprehension
procedure is computationally efficient and well-adapted to the ostensive
communicative environment: it is a good example of bounded and adaptive rationality
in Gigerenzer’s terms (Gigerenzer and Todd, 1999), and, uniquely, it is a fast and
frugal satisficing heuristic which seeks optimal solutions.

Relevance and rationality by NICHOLAS ALLOTT

5.2 Optimization under constraints
We have established that no realistic model of reasoning, including therefore the
relevance theoretic comprehension procedure, can be an example of unbounded
rationality. Next I will consider optimization under constraints. This vision of
rationality ‘holds that the mind should calculate the benefits and costs of searching
for each further piece of information and stop search as soon as the costs outweigh
the benefits.’ (Gigerenzer and Todd, 1999, section 2.2)
Therefore a solution is reached without consulting all of the evidence, in contrast
to the way models of unbounded rationality work, using all possible information.
However the requirement that at each stage the costs and benefits of containing the
search be calculated leads to a computational explosion: ‘the paradoxical approach
is to model “limited” search by assuming that the mind has essentially unlimited
time and knowledge with which to evaluate the costs and benefits of future
information search.’ (Gigerenzer and Todd, 1999, section 2.2) This means that
‘optimization under constraints can require even more knowledge and computation
than unbounded rationality.’ (op cit, section 2.2, referring to work by Vriend,
1996; Winter 1975)
As a realistic model of cognition, then, relevance theory cannot rely on
optimization under constraints; indeed it does not, but there are two reasons why
someone might suppose that it does. First, according to the communicative
principle of relevance, ‘Every ostensive stimulus conveys a presumption of its own
optimal relevance’ (Sperber and Wilson 1986/95, p 158). This means that the
hearer is licensed to search for an optimally relevant interpretation: ‘An ostensive
stimulus is optimally relevant to an audience [if] it is the most relevant one
compatible with the communicator’s abilities and preference.’ (Wilson and
Sperber, 2002, section 3) So the relevance theoretic comprehension procedure
looks for the optimal solution, given a particular stimulus in a particular context.
Thus it appears to be an optimizing procedure, but as I shall argue, it is not a kind
of optimization under constraints.
Secondly, as previously noted, relevance is a matter of effort and effects, so the
generalization ‘stop when your expectations of [optimal] relevance are satisfied’
(Wilson and Sperber, 2002, section 3) may seem to be an injunction to calculate at
each stage the costs and benefits of continuing with the search and to stop when
the projected costs in effort outweigh the prospective benefits in cognitive effects.
This is a misinterpretation, however, for two reasons. First, the hearer is licensed
to ‘stop at the first interpretation that satisfies his expectations of relevance,
because there should never be more then one.’ (Wilson and Sperber, 2002, section
3) This follows from the special nature of ostensive-inferential communication: the
speaker ‘wants her utterance to be as easy as possible to understand so that the first
interpretation to satisfy the hearer’s expectations of relevance is the one she
intended to convey.’ (op cit. , section 3) This means that there is no need to
calculate the costs and benefits of continuing the search: what is at issue is rather
whether the cognitive effects are (more than) enough at some time, t, to justify the
processing effort incurred from the beginning of the search to that time.
The second reason why the relevance theoretic comprehension procedure could
not be a species of optimization under constraints is that from the beginning
Sperber and Wilson have been clear that ‘contextual effects and processing effort
are non-representational dimensions of mental processes’ (1986/95, pp 131). We
may sometimes have intuitions about degrees of effort and effect but efforts and
effects – and therefore relevance – are not generally mentally represented and
therefore cannot be used in computations. Thus there is no possibility that future
effort and effects could in general be summed and weighed up against each other
as optimization under constraints requires. p. 77-78

The argument that the relevance theoretic comprehension procedure is a type of
satisficing procedure comes from comparing Gigerenzer’s definition, ‘satisficing
(sets) an aspiration level and ends the search for alternatives as soon as one is
found that exceeds the aspiration level’ (Gigerenzer and Todd, 1999, section 2.3,
referring to work by Simon, 1956, 1990) with the specification of the relevance
theory comprehension procedure:
(a) Follow a path of least effort…(and)
(b) Stop when your expectations of relevance are satisfied. (Wilson and
Sperber, 2002 section 3)

In the case of ostensive-inferential communication,
‘relevance theory claims that use of an ostensive stimulus may create precise and
predictable expectations of relevance not raised by other stimuli.’ (Wilson and
Sperber, 2002, section 3) This is because ‘an ostensive stimulus is designed to
attract the audience’s attention. Given the universal tendency to maximise
relevance an audience will only pay attention to a stimulus that seems relevant
enough.p. 78-79