DEFINITION & HISTORY
Ambiguity aversion is defined as our preference for known risks over unknown risks. The ambiguity or uncertainty may arise from either missing information, insufficient understanding of information and its implications, or undifferentiated options that are equally attractive or unattractive (Lipshitz & Strauss, 1997). This bias is observed most commonly in situations where there are moderate to high chances of a desirable outcome or low chances of an undesirable outcome. But in some situations, the pattern may be reversed and people may actually prefer uncertainty (Kocher et al., 2018). This is due to the fact that when the probability of an outcome is extreme i.e. very high or very low, it is easier to imagine that further information will make it less extreme than more extreme. Therefore, in cases of very low chances of desirable outcomes, ambiguity gives people hope that the unknown information will improve their chances, and in cases of very high probabilities of undesirable outcomes, ambiguity gives them hope that the chances of undesirable outcome are lower than they seem (Frisch & Baron, 1988).
Awareness about people’s aversion to uncertainty has existed in all cultures and in all eras. As the old Irish proverb goes - ‘Better the devil you know than the devil you don't know’. This tendency was first recorded in an experimental setup in 1961 by the American economist, Daniel Ellsberg. Ellsberg offered his participants a choice between two urns each of which contained 100 balls. Urn A contained 50 red and 50 black balls, while Urn B contained an unknown mixture of red and black balls. A significant majority of the participants chose Urn A, the one with an equal number of red and black balls, over Urn B for which they did not have complete information. This result is paradoxical to the economic theory of rational decision making, because a rational person, given no further information, should behave as if the probability for red and black balls in Urn B are equal i.e. 50% each, which is same as Urn A, and therefore should have no clear preference between the 2 urns (Ellsberg, 1961). Other studies have found that people are even more averse to real world ambiguity, such as outcomes of elections or sporting events, than ambiguity in experimental setups (Kelsey & le Roux, 2015).
COGNITIVE CAUSES
Cognitive causes are the psychological mechanisms that explain the bias. It is likely that no one of the multiple explanations can explain every instance of the bias, and each explanation is valid in some cases and invalid in others.
Firstly, people fear that if they choose an ambiguous option and receive a bad outcome, then they will be criticized by others. This is known as fear of negative evaluation. Ambiguity increases with the number of people watching a decision as well as with the competence and the intelligence of the observers (Trautmann et al., 2008).
Next, people are motivated to avoid the regret they may experience if the outcome of their decisions reveals that their decision-making was flawed. Therefore, while making decisions, we anticipate the possibility of future regret, and choose the option that minimizes such possibilities (Zeelenberg, 1999).
And finally, ambiguity and uncertainty can evoke a number of very different emotions based on our evaluations and interpretations of the situation. These emotions influence our attitude and response to ambiguity. Uncertainty can cause anxiety if it is a barrier to effective decision making and fear if it threatens well-being and safety. Extreme threat can result in panic or torment, and personal acknowledgement of uncertainty can lead to insecurity. On the flipside, people who are uncertain, yet believe that a bright future is a possibility, feel hope or optimism. And when uncertainty represents elements of both danger and opportunity, the emotional response may be thrill (a combination of excitement and fear), which characterizes high-risk activities like adventure sports (Brashers, 2001).
BIOLOGICAL CAUSES
The level of ambiguity in choices is associated with increased activation in the amygdala, which is involved in processing emotional information, and orbitofrontal cortex which is involved in integration of emotional and cognitive input from other parts of the brain (Hsu et al., 2005). While these 2 regions may be involved in emotional and motivational components of decision-making under uncertainty, lateral prefrontal cortex, insula and parietal cortex may support calculations involved in evaluating uncertain future possibilities (Platt & Huettel, 2008). Ambiguity seeking is associated with activation in the lateral prefrontal cortex, which is involved in analytical component of decision-making and inhibiting impulsive responses, whereas ambiguity aversion is associated with activation in the posterior parietal cortex, which is involved in integration of inputs from other brain regions to represent value assigned to each option (Huettel et al., 2006). Ambiguity is also associated with reduced activation in striatum which is implicated in risk-reward perception, thus lowering the anticipated rewards for ambiguous options. The final result of all these cognitive processes is that under uncertainty, the brain recognizes the fact that information is missing, and that choices based on the information available therefore carry more unknown consequences, some of which may be undesirable (Hsu et al., 2005). How we interpret this information gap and what outcomes we anticipate influence our emotional and motivational responses to ambiguity.
DECISION ADVANTAGES
For the bias to be passed down genetically or culturally to us from our ancestors, it must be beneficial in certain conditions.
Firstly, ambiguity in most cases is subjective, so while we may not have complete information in a situation, others may know more than us. If we perceive the other to be adversarial or competing with us, we may fear that they will have an advantage in the situation or bias the situation to our disadvantage. As many of our decisions and behaviors are embedded in social contexts, and commonly the intentions of others are not known, ambiguity aversion may be a useful heuristic (Frisch & Baron, 1988).
Next, ambiguity aversion may reflect the survival pressures that influenced the evolution of our decision making framework. From an evolutionary perspective, uncertainty becomes an existential threat as organisms need to make decisions based on incomplete and uncertain information from their environment, and their survival depends on these decisions. In our ancestral environment, the impact of uncertainty may have been lopsided towards negative outcomes i.e. choosing ambiguous options may have done more cumulative harm than good to our ancestors (Trimmer et al., 2011).
DECISION RISKS
Firstly, ambiguity distorts our perception of risks. For low probability risks, e.g. a disease like cancer, incomplete information can increase risk perceptions. On the other hand, for high and medium probability risks, e.g. a global pandemic like COVID-19, incomplete information can lead to lower risk perceptions (Viscusi & Chesson, 1999).
Secondly, uncertainty leads to anxiety, which causes a desire for the uncertainty to be resolved as soon as possible. But in many situations, there is a delay between the decision being made and the resolution of uncertainty. The expected time for resolution of uncertainty may influence decisions, as people may prefer options with swift resolution to avoid prolonged periods of anxiety e.g. given a choice between a test for a disease that is more accurate but has a significant wait time for results and another which is less accurate, but produces results immediately, a number of people may prefer the latter (Wu, 1999).
Next, people don’t sufficiently think about all the possibilities before making decisions in ambiguous situations - a phenomenon known as the “disjunction effect”. In a study, participants were first asked to imagine having passed an exam, failed an exam, or being still unaware about the result, and then asked to indicate their willingness to purchase an exotic vacation. Participants in the fail and pass condi-tions were eager to purchase the vacation, but not those who were still unaware of their results. Now, as the preference for the vacation was unlikely to change for either passing or failing the exam, if the participants unaware of their results had thought about their preferences in the 2 possibilities, they also would have purchased the vacation, which tells us that they didn’t think it through in the experiment (Van Dijk & Zeelenberg, 2007).
Next, ambiguity aversion causes people to be unwilling to act or procrastinate decisions, if they perceive a possibility of waiting and obtaining more information. Yet collecting information often requires forgoing more immediate rewards. This tension between seeking new information and choosing the best option, given what is already known, is called the ‘explore-exploit’ dilemma (Platt & Huettel, 2008).
Lastly, important decisions, such as financial decisions, often suffer due to ambiguity aversion. People tend to invest and trade more in their own country than would be expected given the gains from international diversification. People feel less knowledgeable and unfamiliar about the more distant options, therefore they perceive more uncertainty (Trautmann at al., 2008).
DE-BIASING STRATEGIES
An effective antidote to ambiguity aversion is curiosity. Curiosity, if strong enough, can override the anticipation of regret and fear of negative evaluation that accompanies ambiguity and uncertainty (Van Dijk & Zeelenberg, 2007).
Next, according to the emotional appraisal theory, our evaluations and interpretations of events, rather than events per se, determine our emotional responses to the events. Therefore, reinterpreting uncertain situations to imagine desirable possibilities that may result from it, can lead to hope, instead of anxiety and fear, in face of uncertainty (Roseman et al., 1990).
FInally, a critical requirement for successfully dealing with ambiguity is behavioral flexibility. Decision makers use different strategies to cope with different types of uncertainty. Inadequate understanding is primarily managed by collecting additional information, seeking support of others who may have a better understanding or deferring the decision till more information is available; incomplete information is primarily managed by making reasonable assumption based on evidence and revising them with additional evidence; and conflict among alternatives was primarily managed by comparing the pros and cons of the alternatives. In all uncertain situations, it is advisable to acknowledge ambiguity and preparing to avoid or confront potential risks - preempt, prevent, prepare. Lastly, denial of uncertainty can help us deal with the negative emotions that accompany it, but is ill-advised (Lipshitz & Strauss, 1997).
REFERENCES
Lipshitz, R., & Strauss, O. (1997). Coping with uncertainty: A naturalistic decision-making analysis. Organizational behavior and human decision processes, 69(2), 149-163.
Kocher, M. G., Lahno, A. M., & Trautmann, S. T. (2018). Ambiguity aversion is not universal. European Economic Review, 101, 268-283.
Frisch, D., & Baron, J. (1988). Ambiguity and rationality. Journal of Behavioral Decision Making, 1(3), 149-157.
Ellsberg, D. (1961). Risk, ambiguity, and the Savage axioms. The quarterly journal of economics, 643-669.
Kelsey, D., & le Roux, S. (2015). An experimental study on the effect of ambiguity in a coordination game. Theory and Decision, 79(4), 667–688.
Trautmann, S.T., Vieider, F.M. & Wakker, P.P. Causes of ambiguity aversion: Known versus unknown preferences. J Risk Uncertainty 36, 225–243 (2008).
Zeelenberg, M. (1999). Anticipated regret, expected feedback and behavioral decision making. Journal of Behavioral Decision Making, 12(2), 93–106.
Brashers, D. E. (2001). Communication and Uncertainty Management. Journal of Communication, 51(3), 477–497.
Hsu, M., Bhatt, M., Adolphs, R., Tranel, D., & Camerer, C. F. (2005). Neural systems responding to degrees of uncertainty in human decision-making. Science, 310(5754), 1680-1683.
Platt, M. L., & Huettel, S. A. (2008). Risky business: the neuroeconomics of decision making under uncertainty. Nature neuroscience, 11(4), 398–403.
Huettel, S. A., Stowe, C. J., Gordon, E. M., Warner, B. T., & Platt, M. L. (2006). Neural signatures of economic preferences for risk and ambiguity. Neuron, 49(5), 765-775.
Trimmer, P. C., Houston, A. I., Marshall, J. A., Mendl, M. T., Paul, E. S., & McNamara, J. M. (2011). Decision-making under uncertainty: biases and Bayesians. Animal cognition, 14(4), 465-476.
Viscusi, W. K., & Chesson, H. (1999). Hopes and fears: the conflicting effects of risk ambiguity. Theory and decision, 47(2), 157-184.
Wu, G. (1999). Anxiety and decision making with delayed resolution of uncertainty. Theory and Decision, 46(2), 159-199.
Van Dijk, E., & Zeelenberg, M. (2007). When curiosity killed regret: Avoiding or seeking the unknown in decision-making under uncertainty. Journal of Experimental Social Psychology, 43(4), 656–662.
Roseman, I. J., Spindel, M. S., & Jose, P. E. (1990). Appraisals of emotion-eliciting events: Testing a theory of discrete emotions. Journal of personality and social psychology, 59(5), 899.