Choice in experiential learning: True preferences or experimental artifacts?

The Future of Decisions From Experience: Connecting Real-World Decision Problems to Cognitive Processes

In many important real-world decision domains, such as finance, the environment, and health, behavior is strongly influenced by experience. Renewed interest in studying this influence led to important advancements in the understanding of these decisions from experience (DfE) in the last 20 years. Building on this literature, we suggest ways the standard experimental design should be extended to better approach important real-world DfE. These extensions include, for example, introducing more complex choice situations, delaying feedback, and including social interactions. When acting upon experiences in these richer and more complicated environments, extensive cognitive processes go into making a decision. Therefore, we argue for integrating cognitive processes more explicitly into experimental research in DfE. These cognitive processes include attention to and perception of numeric and nonnumeric experiences, the influence of episodic and semantic memory, and the mental models involved in learning processes. Understanding these basic cognitive processes can advance the modeling, understanding and prediction of DfE in the laboratory and in the real world. We highlight the potential of experimental research in DfE for theory integration across the behavioral, decision, and cognitive sciences. Furthermore, this research could lead to new methodology that better informs decision-making and policy interventions.

Sample decisions with description and experience

Decision makers weight small probabilities differently when sampling them and when seeing them stated. We disentangle to what extent the gap is due to how decision makers receive information (through description or experience), the literature’s prevailing focus, and what information they receive (population probabilities or sample frequencies), our novel explanation. The latter determines statistical confidence, the extent to which one can know that a choice is superior in expectation. Two lab studies, as well as a review of prior work, reveal sample decisions to respond to statistical confidence. More strongly, in fact, than decisions based on population probabilities, leading to higher payoffs in expectation. Our research thus not only offers a more robust method for identifying description-experience gaps. It also reveals how probability weighting in decisions based on samples — the typical format of real-world decisions — may actually come closer to an unbiased ideal than decisions based on fully specified probabilities — the format frequently used in decision science.

The Role of Personal Experience and Prior Beliefs in Shaping Climate Change Perceptions: A Narrative Review

Global climate change is increasing the frequency and intensity of extreme weather events such as heatwaves, droughts, and flooding. This is the primary way many individuals experience climate change, which has led researchers to investigate the influence of personal experience on climate change concern and action. However, existing evidence is still limited and in some cases contradictory. At the same time, behavioral decision research has highlighted the importance of pre-existing values and beliefs in shaping how individuals experience changes in environmental conditions. This is in line with theories of motivated reasoning, which suggest that people interpret and process information in a biased manner to maintain their prior beliefs. Yet, the evidence for directional motivated reasoning in the context of climate change beliefs has recently been questioned. In the current paper, we critically review the literature on the interrelationships between personal experience of local weather anomalies, extreme weather events and climate change beliefs. Overall, our review shows that there is some evidence that local warming can generate climate change concern, but the capacity for personal experience to promote action may rely upon the experience first being attributed to climate change. Rare extreme weather events will likely have limited impact on judgments and decisions unless they have occurred recently. However, even recent events may have limited impact among individuals who hold strong pre-existing beliefs rejecting the reality of climate change. We identify limitations of existing research and suggest directions for future work.

Choice rates are independent from perceived patterns (when patterns are not obvious): A reply to Plonsky and Teodorescu

In Ashby, Konstantinidis, and Yechiam (2017) we argued that the variance in people's choices in decisions from experience stems from uncertainty about preferences. This was confirmed by high correlations between the variance in experiential choices and subsequent one-shot policy decisions: both showing considerable diversification. In the present paper we address a comment regarding our paper by Plonsky and Teodorescu (2020). These authors suggested that variance in experiential choices is driven by responses to perceived patterns in prior outcomes (rather than individuals' preferences), and that these responses can also drive subsequent policy decisions. This was supported by an apparent "wavy recency" effect in our data indicatory of responses to patterns, and by an experiment showing that outcome patterns affected subsequent policy decisions. We demonstrate that our study results do not in fact show a significant wavy recency. We do find positive recency but it is very poorly correlated with the overall choice rates. Hence, we contend that the variance in choice rates mostly reflects one's preferences when there are no obvious patterns. Moreover, we argue that because Plonsky and Teodorescu's experimental manipulation was confounded with the frequency of relatively positive/negative outcomes, their results do not conclusively show an effect of response to patterns on subsequent policies.

Perceived patterns in decisions from experience and their influence on choice variability and policy diversification: A response to Ashby, Konstantinidis, & Yechiam, 2017

Searching for and acting upon perceived patterns of regularity is a fundamental learning process critical for adapting to changes in the environment. Yet in more artificial, static settings, in which patterns do not exist, this mechanism could interfere with choice maximization and manifest as unexplained choice variability in later trials. Recently however, Ashby et al. (2017) found that choice variability in later trials of a repeated choice setting is correlated with levels of diversification in policy tasks, in which patterns can never be exploited. They concluded that in repeated choice tasks, choice-variability in later trials is unlikely the result of following perceived patterns. Here, we demonstrate that correlations between choice variability and policy diversification can actually be the result of pattern seeking, rather than serving as evidence against it. We review evidence for the robustness of pattern seeking mechanisms in repeated choices and explain how such mechanisms could in fact create the results observed by Ashby et al. To examine our interpretation for their results, we conducted a sequential dependencies analysis of their data and find evidence that many participants behaved as if they believed trials are inter-dependent, even though they were explicitly instructed that the environment is stationary. The results of a new experiment in which sequential patterns are directly manipulated support our interpretation: Experiencing patterns affected both choice variability in later trials and policy diversification. Finally, we argue that decisions from experience tasks are a valid tool to examine the generation of preferences via fundamental learning processes.

The effect of switching costs on choice-inertia and its consequences

In two studies we provide a novel investigation into the effects of monetary switching costs on choice-inertia (i.e., selection of the same option on consecutive choices). Study 1 employed a static decisions-from-feedback task and found that the introduction of, as well as larger, monetary switching costs led to increases in choice-inertia. While experience and decreases in the similarity of options average payouts (expected value: EV) increased choice-inertia for the option with a higher EV (the EV maximizing option), switching costs increased choice-inertia for the inferior option (the lower EV option): The proportion of total participants showing choice-inertia for the EV maximizing option also increased with switching costs. Study 2 employed a dynamic decisions-from-feedback task where halfway through the task the EV maximizing option became the inferior option. The effect of switching costs increasing choice-inertia for both the EV maximizing and the inferior option was replicated with little impact of the change in options values being detected. In sum, decision makers appear to be sensitive to switching costs, and this sensitivity can bias them towards inferior or superior options, revealing the good and the bad of choice-inertia.

Task complexity moderates the influence of descriptions in decisions from experience

Decisions-makers often have access to a combination of descriptive and experiential information, but limited research so far has explored decisions made using both. Three experiments explore the relationship between task complexity and the influence of descriptions. We show that in simple experience-based decision-making tasks, providing congruent descriptions has little influence on task performance in comparison to experience alone without descriptions, since learning via experience is relatively easy. In more complex tasks, which are slower and more demanding to learn experientially, descriptions have stronger influence and help participants identify their preferred choices. However, when the task gets too complex to be concisely described, the influence of descriptions is reduced hence showing a non-monotonic pattern of influence of descriptions according to task complexity. We also propose a cognitive model that incorporates descriptive information into the traditional reinforcement learning framework, with the impact of descriptions moderated by task complexity. This model fits the observed behavior better than previous models and replicates the observed non-monotonic relationship between impact of descriptions and task complexity. This research has implications for the development of effective warning labels that rely on simple descriptive information to trigger safer behavior in complex environments.

‘Tis better to choose and lose than to never choose at all

When decisions involve opting in or out of competition many decision makers will opt-in even when doing so leads to losses on average. In the current paper, we examine the generality of this effect in risky choices not involving competition. We found that re-framing a sure (certain) zero option as an option to observe the results of the other options without choosing would lead to increased consequential choice (i.e., increased selection of risky options rather than the zero option). Specifically, in two studies we compared the rate of consequential choice in a novel paradigm where decision makers decide to observe or to choose with consequence from a set of risky options (decisions-to-engage) to a full-feedback decisions-from-feedback paradigm where the choice set included a labeled sure zero option. Compared to decisions-from-feedback, participants were more likely to choose from mixed (risky) gambles with consequence (over a zero outcome) in decisions-to-engage. This occurred irrespective of whether doing so was advantageous (i.e., when choice led to monetary gains on average) or disadvantageous (i.e., when choice led to monetary losses on average), and when descriptions of the options outcomes and probabilities were provided (Study 2). These findings provide an important boundary condition for the positive effects of experience on the quality of choice, and suggest that decision makers’ preference for agency can sometimes induce poorer choices.