Preferential Choice

Preferences are inherently subjective, varying from person to person depending on emotions, goals, past experiences and even biological differences. For most domains, it is, therefore, impossible to determine what constitutes a ‘good’ or rational choice. Consider for example the scenario outlined in the introduction (Chapter 1), where one is faced with the task of selecting a person they would like to date from a range of potential candidates. Whether they prefer a person who is tall or short, or blond or brunette, there is no objectively correct answer – only one that best matches the person’s subjective criteria. However, whilst one choice in isolation is hard to evaluate, a set of preferences in aggregate is expected to follow a certain pattern, which has long been of interest to psychologists and economists alike. This pattern is, in turn, thought to provide a benchmark against which the quality of choices can be evaluated.

A term that best captures what we have come to expect from preferences is consistency (Rieskamp, Busemeyer & Mellers, 2006). Any sets of preferences held by a decision maker are widely assumed to be stable (consistent over time), and to have a stable order, where if alternative A is preferred to B, and B is preferred to C, A must also be preferred to C (consistent across alternatives – Houthakker, 1950; Arrow, 1959). It is further commonly accepted that subjects’ choices reflect this underlying preference order (Samuelson, 1938). For example, if we choose item A over item B when both items have the same associated costs we are thought to prefer item A, and unless some learning process takes place to alter this preference, repeating the task should yield the same result. These presuppositions have formed the basis of many influential theories (e.g., Samuelson, 1938; von Neumann & Morgenstern, 1944), and are often applied in real world practice areas (e.g., marketing, consumer sales; see Jacoby, 2000).

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The expectation that our preferences are broadly consistent is natural. After all, in other, more objective, forms of decision making inconsistent outcomes signal a problem. Even outside of the decision context, consistency is thought to play a fundamental part in attitude formation (e.g., Festinger, 1957) and human behaviour more broadly (e.g., Ouellette & Wood, 1998). The stable and ordered model of preferences has also proven useful in describing how a rational agent should act if they are to avoid being open to manipulation. Consider the ‘money pump’ example commonly quoted in economics to illustrate the importance of preference stability, where a person prefers option A over option B, option B over option C, yet option C over option A. In this example, we would expect a person to be willing to pay a small amount to upgrade option A to B, B to C and C to A, which would result in the end product being no different to that at the start, whilst the person would have made a loss. With a stable set of ordered preferences on the other hand, such manipulation should not be possible.

Whilst a stable, ordered set of preferences provide a good description of how a completely rational agent would think, how far they describe real human behaviour has come into question over the past few decades. Research has increasingly shown that people’s choices are consistently affected by seemingly irrelevant aspects of the environment. Let us consider the violation of procedural invariance to illustrate this. Procedural invariance states that as far as we have a stable preference order, the method used to elicit preferences should have no impact on the person’s apparent preferential order (Slovic & Lichtenstein, 1968). However, in one scenario studied by Shafir (1993), the participants were given a choice between two ice creams; ice-cream one is very tasty but very high in cholesterol and ice-cream two is just moderately tasty. When participants were presented with the task of choosing their preferred option 72% selected the tasty alternative, however, when they were required to give up one of the choices only 55% rejected the non-tasty alternative, whereas the ordered preference approach would predict equivalent proportions in the two conditions. Similarly, Tversky and Kahneman (1981) demonstrated that people are equally easily swayed by the way the alternatives themselves are presented. The most commonly cited

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example of this is that choices involving gains are often risk averse and choices involving losses are often risk seeking. Consider the scenario of preparing for an outbreak of a deadly Asian disease, which is expected to kill 600 people. Here the participants are given a choice of saving 200 people for certain versus a 1 in 3 chance of saving everyone and 2 in 3 chance that no one will be saved. In this scenario, the majority of people selected the certain option. However, when faced with the choice of 400 people dying for certain versus 1 in 3 chance that no one will die and 2 in 3 chance that everyone will die, only a minority selected the first alternative. Mathematically the two sets of choices are identical, but merely described differently, yet the elicited preferences for two courses of action appear to change depending on how the alternatives are presented or ‘framed’.

These examples of framing are by no means unique in challenging the notion of stable, ordered and revealed preferences, and many factors which should be irrelevant from a rational choice perspective have now been identified that can alter the elicited preferences of an individual, including the order of presentation (e.g., Nisbett & Wilson, 1977), perceptual fluency (e.g., Reber, Winkielman & Schwarz, 1998) and the presence of a third, however, irrelevant, alternative (e.g., Huber, Payne & Puto, 1982) to name a few. Furthermore, even under a controlled environment when presented with a similar choice on two different occasions, people tend to change their minds around 25% of the time (e.g., Camerer, 1989; Hey, 2001; Loomes & Sugden, 1998).

Whilst problematic for rational choice theory, the study of choice inconsistencies and preference have allowed us to make considerable progress in describing real, human behaviours. The newly emerging descriptive models of choice have become more inclusive of variable and context dependent choices. The predominant themes to emerge have included recognising that decision are made under limited cognitive resources (bounded rationality – e.g., Simon, 1956), in a probabilistic rather than discrete manner (probabilistic choice – e.g., Block & Marschak, 1960; Rieskamp, 2008), and are at least to some extent constructed from the information in the surrounding environment (constructed preferences – e.g.,

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Payne, Bettman & Johnson, 1992; Slovic, 1995). Nonetheless, there is still no single model that perfectly describes all aspects of choice. Although research has shown that the rational choice approach fails to accurately describe human behaviour, some argue that we are still to create a theory powerful and comprehensive enough to put in its place (Posner, 1993, p367). In order to formulate comprehensive models and test the proposed governing rules of preferential choice, we need to provide more data that will allow us to test these models against real behaviours, and identify any choices that may deviate from what we would expect.

Choice blindness provides one of the latest, and most striking, examples of violations of stable preference assumptions, what is more, is that it appears to do so within one choice. If we were to assume stable and accessible preferences, the occurrence of choice blindness seems very unlikely as we would be able to detect a mismatch between what we prefer and what we are presented with. Furthermore, if we fail to initially detect that the presented face is the wrong one, the action of providing a justification for choosing the wrong face should serve as an additional alert (i) as it would require us to attend to the stimulus at hand and (ii) as we would not be able to provide the justification, because we actually prefer the other alternative. Indeed, the implications of choice blindness present an important challenge that needs to be addressed if we are to progress in our understanding and description of human behaviour (Hall et al., 2010; Somerville & McGowan, 2016).

Choice blindness undoubtedly contributes to the bulk of research that has put the notion of a master list of preferences into question, it does not, however, negate the existence of preference altogether. Although the effect has been demonstrated across a wide range of domains (e.g., personal finance – McLaughlin & Somerville, 2013; haptic stimuli – Steenfeldt-Kristensen & Thornton, 2013; eyewitness testimony – Sagana et al., 2013), in some instances the levels of choice blindness have been found to be very low. For example, when presented with choices in a domain we are already familiar with less than a fifth of participants fail to report a mismatch between their choice and the feedback provided (Somerville & McGowan, 2016). This will

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be further discussed in Chapter 3 of this thesis, however, situations where choice blindness would seem extremely unlikely are not hard to imagine – such as choosing between being tortured and receiving a huge sum of money for example. Of course, this is speculative, but even strong proponents of the constructed preference approach agree that some preference are very stable, even from birth (Lichtenstein & Slovic, 2006), making mistaking a large reward for detrimental punishment unlikely (although I expect there would be one or two exceptions).

One significant contribution provided by the choice blindness paradigm is a new tool that can help us better understand when, and hopefully more broadly why, we can detect a mismatch in exhibited behaviour and feedback available in our environment. As Payne et al. (1992) suggest, ‘common sense dictates that consistent decisions are good decision’, and since it has been established with reasonable certainty that preferences are highly malleable by their environment the use of choice blindness allows us to establish in what circumstances choice consistency is best elicited. In the next chapter I will attempt to outline which factors in the environment can impact the likelihood of choice blindness being elicited, as well as the factors that affect the likelihood of accepting other forms of false information as demonstrated in the Barnum effect. This will be followed by a discussion of the role of false feedback in determining later behaviours, as well as the cognitive mechanisms put forward for explaining why false feedback acceptance occurs.

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