Discussing the works of Tversky and Kahneman;  Stanovich, 2009, stated that “being
rational means acting to achieve one’s own life goals using the best means
possible”. A long history of
research has looked into the mystery of rational human thought and decision
making – Tverky and Kahneman, 1973, proposed that humans use a set of simple
steps known as heuristics to obtain the answer to a difficult problem.  Rationality is regarded as one of the most
valued human traits and many psychologists (such as Stanovich, 2009) believe
that a Rationality Quotient (RQ) should be as important in assessing
psychological domains, as the Intelligence Quotient (IQ). Individuals certainly
have different patterns of cognition to each other, which means that some may
think and make decisions more rationally than others. However, as Tverksy and
Kahneman have shown, the basic structure of human cognition means that all of
us are susceptible to making errors in judgement – but, on occasion,
individuals are able to override these errors and make rational decisions. Whether
humans are capable of rational thought – is a subjective question which should
be investigated by means of various theories and previous experiments

The Classical Decision
Theory is a collection of the earliest models of decision making. One of these
is the Model of the Economic Man and Woman. It assumes three things: that
decision makers are fully informed about the topic, that they are aware and
sensitive to the most minor distinctions between the different options and that
they make a rational choice.  An
alternative theory, the Subjective Utility Theory, states that when people make
decisions their ultimate objective is to bring about pleasure (positive utility) and to avoid pain (negative utility). They calculate the subjective utility, which is based on
the utility or value of the choice, rather than criteria and the subjective probability, which is a
person’s estimate of possible outcomes. In comparison to the Economic Man and
Woman Model, this theory takes into account the complexity of the human mind
and subjectivity – it is not realistic that anyone would truly be fully
informed about difficult choices and be sensitive to minor differences between
each choice, (Stenberg & Stenberg 2006). 
Taking this into consideration, it is possible to say that humans are
not capable of rational thought – we don’t always make the most correct
decisions because we are not capable of calculating and distinguishing
tremendous amounts of knowledge.  

Kahneman (2011)
proposed that the mind works by means of two systems. System 1 is an automatic
and fast-responding system. It is used to answer simple questions (such as
2+2=?), reading and identifying objects. System 2 is slower and used to answer
more difficult and compelling questions. It requires attention and is used in
cases such as trying to identify a voice in a crowd or filling out a form. If
attention is lacking in these situations, the System 2 does not perform as
well. Individuals use a mixture of both systems in daily decision making.
Sometimes when individuals focus their attention too intensively, they become
blind to other stimuli. This has been shown in a study by Chabris and Simons,
2010, where people had to focus on the task of counting how many passes of a
ball has been made between basketball players. Most people missed a very
obvious stimulus – a woman dressed in a gorilla suit appearing mid-way through
the video. This demonstrates flaws in both systems, as individuals can become
blind to stimuli and be oblivious to their blindness.  Biases in cognition, such as hindsight bias
and overconfidence (Stenberg & Stenberg, 2006), may be the cause of these
mistakes.

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Deductive reasoning, which is a process of coming to conclusions
from the knowledge of general statements, gives valuable information about
rational human cognition. Conditional reasoning, a type of
deductive reasoning, is when a person comes to a conclusion using an “if-then”
proposition (Stenberg & Stenberg, 2006). It works effectively in the cases
of simple conditional arguments such as if
“p” then “q”, “p” therefore “q” (or “if it rains she gets wet, it rains
therefore she gets wet”). This is
known as the modus ponens form, which
is logically, a valid statement. Individuals usually have no problem quickly
coming to the correct conclusion when asked to finish statements in this form.
However, it takes longer to finish a statement in the modus tollens form – if “p”
then “q” and “q” is false it follows
that, therefore, “p” is false (or “if
it rains, she gets wet.  She did not get
wet, therefore it did not rain). Modus
ponens and modus tollens are two valid inferences of simple conditional
arguments, (Eysenck & Keane, 2010).

Another two inferences can
be drawn from these conditional arguments, however they are invalid
(fallacies).  One case is the “affirmation
of the consequent” – if “p” then “q”, “q”
therefore “p” (or “if it rains she gets wet, she gets wet therefore it was
raining”). This is not valid because
a conclusion cannot be drawn, the statement did not say that the reverse is
true – however, some individuals tend to finish the statement that way,
although the only “correct” conclusion would be that no conclusion can be made.
In the case of “denial of the antecedent”, some individuals tend to finish the
statement if “p” then “q”, not “p” with therefore not “q” (or “if it rains then
she gets wet, it did not rain therefore she did not get wet), which is also not valid, (Eysenck
& Keane, 2010).

In an experiment
(Marcus & Rips, 1979), 100% of the subjects made the modus ponens
inference, only around 50% made the modus tollens inference and even less
subjects made the affirmation of the consequent and denial of the antecedent
inferences. The suppression of these fallacies suggests that human reasoning
does not follow a logical pattern. That being said, individuals don’t always
make the modus ponens and modus tollens inferences while suppressing the
affirmation of the consequent and denial of the antecedent inferences –
sometimes people fail to make the correct inferences and conclude these
conditional arguments with fallacies.  It
is interesting to note, that when an alternative condition is given, very few
subjects make affirmation of the consequent or denial of the antecedent
inferences. An example of this is if “p”
then “q”, if “r” then “q”, “q” therefore …? (Or “if it rains, she gets wet. If it snows she gets wet. She got wet
therefore…?”).  Individuals are more
likely to say that no conclusion can be made, when they are given a clear
alternative condition – thus extra information can aid the improvement of
logical reasoning, (Eysenck & Keane, 2010). 
This can also be observed in the Wason Selection Task: the subjects of
the experiment are given four cards with numbers and letters (A, B, 2, 3), and
told that every card has a letter on one side and a number on the other. The
task was to select a card that would prove that all of the cards were following
a condition (if a card has the letter A on one side, then it has the number 2
on the other side). Most people select either the A card, the 2 card or both to
prove that this condition was met. The correct card to select was 3, because if
it had an A then condition could not be met. When a more realistic context was
given to the subjects (such as using envelopes and stamps instead of cards),
they were more likely to give the correct answer, (Wason, 1966).

Mental heuristics are
effective for humans; they are fast and decrease thinking efforts while usually
giving the correct answer. Heuristics allow us to process less information and
keep our cognition working efficiently. Sometimes they are affected by various
biases however, which causes mistakes to happen when trying to reason
rationally. Simon (1957), proposed that sometimes people think rationally and
sometimes we do not – we show bounded
rationality. Unlike the Classical Decision Theory, the assumption that we
have bounded rationality takes into account that we are limited and don’t use
every piece of information available to make decisions, but instead come close
to it by using heuristics.

 Satisficing
(Simon, 1957), is one of the first heuristics introduced by researchers,
which suggests that reasoners first make a list of options and consider them
one by one, until they come to an option that they are most satisfied with.
Individuals tend to compare the benefits of getting more information (about
each choice) against the added costs, time and effort needed to get this
information. A lot of moral behaviour is interconnected with bounded
rationality, in particular with satisficing. When faced with a difficult moral
decision, people depend on satisficing rather on maximising (which means
finding the provably best course of action) because maximising would only work
in a world that is less full of various unpredictable possibilities. In fact,
satisficing can reach better results than maximising (Gigerenzer, 2010).  Another way of coming to a decision is
eliminating different choices based on their characteristics, until the last
choice is left – which ends up meeting the decision maker’s criteria. This is
called elimination by aspects. For
example, when buying a new car, the buyer’s main criteria could be automatic
transmission; this would eliminate all cars that do not have automatic
transmission, (Tversky, 1972).

The use of mental
shortcuts can lead to biased decisions that are not rational, because
individuals often have distorted views of probability. Sometimes we believe
that one event has a bearing on another, even when the probability of that
event happening, or not happening, does not change. “Gambler’s Fallacy” is the
name given to this problem, which often happens when people believe that the
occurrence of one random event has a bearing on another event. The opposite of
this, is the “hot hand”, where individuals think that an event is more likely
to occur again if it has occurred already, (Stenberg & Stenberg, 2006).
This fallacy is often linked with the representativeness
heuristic, which involves estimating the probability of an event “by the
degree to which it is (i) similar in essential properties to its parent
population and (ii) reflects the salient features of the process by which it is
generated”, (Kahneman & Tversky, 1972, p.431). We rely on this heuristic a
great deal and quite often, because it works. For example, we base our
judgement of what the weather will be like on a particular day, by looking at
other characteristics of weather – such as time of the year, the area, presence
of clouds etc. We may then correctly or wrongly formulate the probability that
it will rain, on that particular day, (Stenberg & Stenberg, 2006). We also
use the representativeness heuristic because we’re inclined to believe that the
characteristics of a small sample apply to and represent an entire population,
(Tversky & Kahneman, 1971). Base rates, which refer to the occurrence of an
event within its population, are often ignored in every-day decision making,
but they are vital in effective decision-making, (Stenberg & Stenberg,
2006). Mistakes made due to the representativeness heuristic do not mean that
people are incapable of rational thought, as there are times when this
cognition process is very useful.

Individuals also tend
to estimate the probability of events using the availability heuristic. Information about certain events is more
readily available for us when those events occur more frequently than others,
thus when assessing the probability of an event, individuals use the
information which comes most easily to them. However, the availability
heuristic does not solely rely on frequency, which means that the use of this
heuristic sometimes gives rise to systematic biases, (Tversky & Kahneman,
1973). When asked whether there are more words beginning with the letter “r” or
words that have “r” as the third letter, most individuals say the first option
– because words that begin with “r” come to the mind more readily than words
that have “r” as the third letter. There are actually more words that have “r”
as the third letter, so this is an example of where the heuristic leads to the conjunction fallacy,  (Tversky & Kahneman, 1983).

 The availability heuristic has also been
associated with fears about certain risks. If a particular risk (such as
terrorism or climate change), is more “available” to a person’s cognition then
they will be more likely to fear it due to the availability heuristic, (Renn
& Rohrmann, 2000; Sunstein, 2006).  Another
heuristic which is related to availability is the anchoring-and-adjustment heuristic. Individuals modify their
estimation of things through reference points known as end-anchors. They change the end answer according to the first
value they see. The starting point may lead to a certain estimate, thus
different starting points lead to different estimates, (Tversky & Khaneman,
1974).

There is an additional
fallacy that occurs in people’s reasoning known as the “sunk-cost
fallacy”.  This is linked to the tendency
of people to be loss-averse; Kahneman (2011) proposed that early humans who
focused more on avoiding threats rather than pursuing opportunities, had
greater chances of survival – thus we evolved to be loss-averse. People tend to
invest more resources into something if they have already invested into it
before (to avoid loss), although in the end, more resources are spent in total.
An example of this is when people spend money on a holiday and realise on the
first day that they are not enjoying it, but still stay and continue spending
money to “get their money’s worth”, (Stenberg & Stenberg, 2006). The
existence of such fallacies means that people have a tendency to think
irrationally, but it does not mean we are incapable of rational thought;
sometimes heuristics work excellently in solving problems, (Cohen, 1981).

Biases and fallacies in
decision making would lead some to believe that people are not capable of
rational thought, but as discussed earlier individuals show bounded rationality
(Simon, 1957; Gigerenzer & Selten, 2002) – that is we are rational, but to
an extent. Differences in individuals show that some are more capable of
rational thought more than others, but learning to suppress biases (by taking
base rates into account, for example), can lead to better decision making
(Gigerenzer, 1996). Sometimes people make decisions that do not follow any
logical pattern; in conditional reasoning some make affirmation of the
consequent or denial of the antecedent inferences – however, fewer individuals
come to these conclusions and more individuals make the correct and logical
inferences, (Marcus & Rips, 1979). The question that remains to be answered
is whether rational thought is simply logical thought, or whether it is the
ability to make the best decision in a given situation – either way, a vast
amount of research has shown that people are, indeed, capable of making
rational decisions and the next step comes in recognising that rationality is as
valuable as intelligence in the modern world, (Stanovich, 2009)

References

Stanovich, K. E. (2009). What intelligence
tests miss: The psychology of rational thought. Yale University Press.

Tversky, A., & Kahneman, D. (1973).
Availability: A heuristic for judging frequency and probability. Cognitive
psychology, 5(2), 207-232.

Stenberg, R. J., & Stenberg, K. (2006). Decision
Making and Reasoning. Cognitive
Psychology 6th Edition, 507-509.

Kahneman, D. (2011). Thinking, fast and slow.
Macmillan.

Chabris, C., & Simons, D. (2010). The invisible gorilla: And other ways our
intuitions deceive us. Harmony.

Eysenck, M. W., & Keane, M. T. (2010). Reasoning
and Deduction. Cognitive psychology. 6th ed. Hove and New York:
Psychology Press, 571-605.

Marcus, S. L., & Rips, L. J. (1979). Conditional
reasoning. Journal of Verbal Learning and Verbal Behavior, 18(2),
199-223.

Wason, P. C. (1966). Reasoning. New Horizons in
Psychology, 135-151.

Simon, H. A. (1957).
Models of man; social and rational.

Gigerenzer, G. (2010).
Moral satisficing: Rethinking moral behavior as bounded rationality. Topics
in cognitive science, 2(3), 528-554.

Tversky, A. (1972).
Elimination by aspects: A theory of choice. Psychological Review, 79(4),
281-299.

Kahneman, D., & Tversky, A. (1972). Subjective
probability: A judgment of representativeness. Cognitive psychology, 3(3),
430-454.

Tversky, A., & Kahneman, D. (1971). Belief in
the law of small numbers. Psychological bulletin, 76(2),
105.

Tversky, A., & Kahneman, D. (1973). Availability:
A heuristic for judging frequency and probability. Cognitive psychology, 5(2),
207-232.

Tversky, A., & Kahneman, D. (1983). Extensional
versus intuitive reasoning: The conjunction fallacy in probability
judgment. Psychological review, 90(4), 293.

Renn, O., & Rohrmann, B. (2000). Cross-cultural
risk perception: State and challenges. In Cross-Cultural Risk
Perception (pp. 211-233). Springer US.

Sunstein, C. R. (2006). The availability heuristic,
intuitive cost-benefit analysis, and climate change. Climatic Change, 77(1),
195-210.

Tversky, A., & Kahneman, D. (1974). Judgment
under uncertainty: Heuristics and biases. Science, 185(4157),
1124-1131.

Cohen, L. J. (1981). Can human irrationality be
experimentally demonstrated?. Behavioral and Brain Sciences, 4(3),
317-331.

Gigerenzer, G., & Selten, R. (Eds.).
(2002). Bounded rationality: The
adaptive toolbox. MIT press.

Gigerenzer, G. (1996). On narrow norms and vague
heuristics: A reply to Kahneman and Tversky.

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