Implications for Research

In chapter 2 of this thesis, I put forward three areas that appear to be closely intertwined with the false feedback acceptance effects discussed in this thesis; introspection, error detection and preferential choice. I will now briefly discuss how the findings reported in this thesis contribute to such phenomena.

The very nature of accepting false feedback that contradicts the information we recently provided about the self, questions our ability to be introspective, or access the information about our own attitudes, actions and what brought them about. Across the experiments presented here, we provide further evidence that false feedback is indeed often accepted, therefore questioning our introspective abilities. Nonetheless, the research also shows some hope for the knowledge of ourselves by demonstrating that some conditions can increases mismatch detections which in turn suggests higher introspective access. For example, chapters 4 and 5 show that if feedback provided is not advantageous and negatively affects our self-image we are likely to detect its inaccuracy. Furthermore, if the feedback encountered does not seem probable, for example, if we do not remember considering it (chapter 3), we also have a heightened ability to detect its falsehood.

This suggests that whilst we may not hold a precise description of our personality profiles, or preference order as a precise list, we must have the ability to access relevant past experiences and emotional associations. For example, in order to reject negative feedback, we need to access information that suggests ‘this is bad for me’, or when we reject feedback that was not a

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part of the choice, we must be able to compare to it to the knowledge of what we had seen in the past. Perhaps the research outlined does not call for labelling introspective information unreliable, but instead a reconsideration of what it means to be introspective.

This further has important implications for error detection. The support for the notion that people tend to accept false feedback can be viewed as a demonstration of failure to detect errors regardless of whether we treat that information as suggestive that we made an error or that some external factor has led to an error being made. The research, however, is also reassuring as it suggests that by defining tasks in a particular way can maximise our ability to detect mismatches between our intentions and the environment. For example, at this stage we can suggest that extending decision sets to three instead of two choices can increase our ability to monitor the choice that was made (chapter 5), similarly it appears that when dealing with choosing from a small set of alternatives we are better off phrasing the task in a positive manner (i.e., which one do you prefer; chapter 6), whilst past research indicates that when rejecting alternatives to narrow down the item pool asking people to reject the unwanted alternatives can result in a higher choice consistency (Kogut, 2011). Another positive finding comes from chapter 4 of this thesis, as it suggests that even when we fail to detect an error it does not mean that error is necessarily incorporated into our beliefs system, or that it will impact how we treat information at a later date.

It must be noted that in many instances it is unclear why we fail to detect errors, given that we have evolved specialised neural systems to do so (see Holroyd & Coles, 2002; Yeung et al., 2004). However, by clarifying circumstances in which error detection is high or low we are making a step in the right direction to determine how the human mind adapts to dealing with the imprecise and error-prone world. Perhaps now that we have built up some understanding using behavioural data, we can start introducing biological measures to decipher what this means. For instance, an EEG study measuring error-related negativity (Gehring, 1992) produced during the Barnum procedure or choice blindness can inform us whether not invalid information is detected as error at all, or whether this is simply not transferred to our

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consciousness. This can, in turn, be used to understand why some circumstances are more prone to error than others (as discussed in chapters 5 through 7) and help identify how to maximise error detection. Alternatively, monitoring the activity in the anterior cingulate cortex during the choice blindness task can tell us if a person is experiencing discomfort, or dissonance (van Veen, Krug, Schooler & Carter, 2009), and help us test the cognitive dissonance explanation of choice blindness. Whilst continuing behavioural research that identifies situational factors that can improve choice monitoring and is no doubt of value in academic and practical application settings alike, expanding the approach can aid the interpretation of the behavioural data and help formulate a comprehensive model of feedback acceptance.

Lastly, I would like to touch on the impact my findings may have on our understanding of preferential choice. In chapter 3, I discussed how understanding violations of rational choice theory is crucial to developing descriptive models of how the mind operates, which has been a challenge academics have been trying to tackle for the last half a century (e.g., Kahneman & Tversky, 1979). Choice blindness (Johansson et al., 2005) was one of the latest of such violations, demonstrating that we are unable to access a stable representation of our preference, or even to use a recently made choice to inform the task of justifying a decision (that we did not make). Beyond demonstrating that we fail to think like rational agents, choice blindness has also provided us with a way to measure choice stability, or the extent to which a stated preference is likely to remain the same regardless of external influences.

In the past, choice stability has been measured through choice consistency, or the elicitation of the same outcome across different points in time, with research often reporting that people fail to remain consistent across two choices on about 25% of trials (Camerer, 1989; Hey, 2001; Loomes & Sugden, 1998). Here I compared the detection of invalid feedback, to the rates of consistency across trials reported in past literature. Specifically, I investigated whether increasing the number of choice alternatives, as well as whether negative framing of the task, can improve choice stability demonstrated through the choice blindness task, as would be hypothesised

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from past literature using choice consistency to measure stability (DeShazo & Fermo, 2002; Collins & Vossler, 2009, Kogut, 2011). In comparing the rate of choice blindness for two and three-alternative tasks, I find that ternary choice is indeed more stable than binary, however, this effect only occurs when the alternatives presented are of different visual similarity and level of attractiveness. Nonetheless, since past research fails to control for such characteristics of the alternatives presented, it is possible that the same effect would be observed for choice consistency, suggesting that choice blindness and choice consistency are likely to reflect the same inherent characteristics of choice processes.

On the other hand, in exploring how framing impacts the level of choice blindness, I find that people are more likely to detect invalid feedback when both the choice and justification elements of the task are framed positively, contrary to what we would expect from Kogut’s (2011) work on choice consistency. However, there are also a number of procedural differences that could have led to the discrepancy in conclusions, including the difference in number of alternatives presented and selected, and the fact that Kogut (2011) measured consistency of choices with previously stated opinions, and the current research attempts to measure the consistency between a choice and its direct outcome (for detailed discussion of the differences see chapter 6). Whether it is the procedural difference that led to this discrepancy, or that choice blindness and choice consistency do indeed reflect different cognitive mechanisms remains unclear, and requires further research. All I conclude is that as far as the choice blindness procedure is concerned, increasing the number of alternatives and framing the choice and judgement tasks in a positive manner can increase false feedback detection, and thus improve at least some form of choice stability.

Chapter 4 provides another interesting contribution to how we perceive preferential choice. Past research has shown false feedback acceptance can shape our preferences. For example, Johansson et al. (2014) demonstrated that accepting feedback that suggests the non-preferred alternative was, in fact, preferred results in higher likelihood of that alternative being selected in the future. Similarly, information about the self,

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such as high extraversion, has been shown to impact subsequent social interactions (Sakamoto et al., 2000). Accordingly, by integrating the two lines of research, we can hypothesise that presenting people with information about their own characteristics which are directly related to preferences, should impact actual subsequent preferences, as long as people accept the feedback presented as accurate. However, in the experiment presented in chapter 4, I find that risk preference as demonstrated in choosing between certain and risky lotteries is not affected by accepting altered information about one’s own financial risk preference. This suggests that risk preferences are not as malleable, as one would hypothesise based on previous research, at least in some circumstances.

Overall, it seems clear that false feedback acceptance can help us decipher when choices are more stable, allowing us to more accurately describe and predict preferential choice behaviours. I have attempted to outline the small contribution my own work presents for the broader understanding, however, there is still a long way to go before we have a comprehensive theory of preferential choice. Personally, I feel that it may be time to pause and reflect on how the breadth of knowledge we have accumulated over the last century combines together and whether approaches from other disciplines, such as Barnum effect as a product of psychometric evaluation literature, can come together. Such a task is not, however, in the scope of this PhD thesis. Before concluding this thesis, I will now briefly discuss one last area to which the empirical work presented here is relevant, the potential for practical applications.