Shi Xian Liew’s research while affiliated with University of Melbourne and other places

The ability to generate new concepts and ideas is among the most fascinating aspects of human cognition, but we do not have a strong understanding of the cognitive processes and representations underlying concept generation. Previous work in this domain has focused on how the statistical structure of known categories generalizes to generated categories, overlooking whether (and if so, how) contrast between the known and generated categories is a factor. In this paper, we explore a different factor: contrast from known categories. We propose two novel approaches to modeling category contrast: one focused on exemplar dissimilarity and another based on the representativeness heuristic. Across three behavioral experiments, we find that people generate new categories that contrast from observed categories and distribute exemplars acoss “unoccupied” regions of stimulus space. The model based on the representativeness heuristic captured human category generation better when the known category was well captured by a Gaussian distribution. Conversely, the exemplar-based model captured human-generated categories better when the known category was not Gaussian distributed. Our results suggest contrast is a fundamental principle used in generating exemplars of a new category.

Investigations of information-seeking often highlight people’s tendency to forgo financial reward in return for advance information about future outcomes. Most of these experiments use tasks in which reward contingencies are described to participants. The use of such descriptions leaves open the question of whether the opportunity to obtain such noninstrumental information influences people’s ability to learn and represent the underlying reward structure of an experimental environment. In two experiments, participants completed a two-armed bandit task with monetary incentives where reward contingencies were learned via trial-by-trial experience. We find, akin to description-based tasks, that participants are willing to forgo financial reward to receive information about a delayed, unchangeable outcome. Crucially, however, there is little evidence this willingness to pay for information is driven by an inaccurate representation of the reward structure: participants’ representations approximated the underlying reward structure regardless of the presence of advance noninstrumental information. The results extend previous conclusions regarding the intrinsic value of information to an experience-based domain and highlight challenges of probing participants’ memories for experienced rewards.

Many investigations of information-seeking highlight a tendency to forgo financial reward in return for advance information that cannot be used to change future outcomes. Most of these experiments use tasks in which reward contingencies are described to participants. The use of such descriptions leaves open the question of whether the opportunity to obtain such non-instrumental information influences people’s ability to learn and represent the underlying reward structure of an experimental environment. In two experiments, participants completed a two-armed bandit task with monetary incentives in which reward contingencies were learned via trial-by-trial experience. We find, akin to description-based tasks, that participants are willing to forgo financial reward to receive information about a delayed, unchangeable outcome. Crucially, however, there is little evidence this willingness to pay for information is driven by an inaccurate representation of the reward structure: participants’ representations approximated the underlying reward structure regardless of the presence of advance non-instrumental information. The results extend previous conclusions regarding the intrinsic value of information to an experience-based domain and highlight challenges of probing participants’ memories for experienced rewards.

Factors affecting information-seeking behaviour can be task-endogenous (e.g., probability of winning a gamble), or task-exogenous (e.g., personality trait measures). Various task-endogenous factors affecting non-instrumental information-seeking behaviour have been identified, but it is unclear how task-exogenous factors affect such behaviour, and if they interact with task-endogenous factors. In an online information seeking experiment (N = 279), we focus on the role that outcome probability, as a task-endogenous factor, has on information preferences. We find reliable preference for advance information on highly probable gains and low preference for highly probable losses. Comparisons with individual trait measures of information preference (e.g., intolerance of uncertainty scale, obsessive-compulsive inventory, information preferences scale) reveal minimal association between these task-exogenous factors with choice task performance. We also find minimal interaction between outcome probability and individual trait measures. Despite the choice task and trait measures purportedly tapping the same (or similar) construct, the absence of clear relationships ultimately suggests a multi-dimensional nature of information preference.

Individuals differ in their sensitivity to the adverse consequences of their actions, leading some to persist in maladaptive behaviors. Two pathways have been identified for this insensitivity: a motivational pathway based on excessive reward valuation and a behavioral pathway based on autonomous stimulus-response mechanisms. Here, we identify a third, cognitive pathway based on differences in punishment knowledge and use of that knowledge to suppress behavior. We show that distinct phenotypes of punishment sensitivity emerge from differences in what people learn about their actions. Exposed to identical punishment contingencies, some people (sensitive phenotype) form correct causal beliefs that they use to guide their behavior, successfully obtaining rewards and avoiding punishment, whereas others form incorrect but internally coherent causal beliefs that lead them to earn punishment they do not like. Incorrect causal beliefs were not inherently problematic because we show that many individuals benefit from information about why they are being punished, revaluing their actions and changing their behavior to avoid further punishment (unaware phenotype). However, one condition where incorrect causal beliefs were problematic was when punishment is infrequent. Under this condition, more individuals show punishment insensitivity and detrimental patterns of behavior that resist experience and information-driven updating, even when punishment is severe (compulsive phenotype). For these individuals, rare punishment acted as a "trap," inoculating maladaptive behavioral preferences against cognitive and behavioral updating.

Individuals differ in sensitivity to the adverse consequences of their actions, leading some to persist in maladaptive behaviours. Two pathways have been identified for this insensitivity: a motivational pathway based on reward valuation and a behavioural pathway based on stimulus–response mechanisms. Here we identify a third, cognitive pathway based on differences in punishment knowledge. Exposed to identical punishment contingencies, some people (Sensitive) form correct causal beliefs that guide their behaviour to avoid punishment, whereas others form incorrect causal beliefs that lead them to earn punishment. Incorrect causal beliefs were not inherently problematic, many individuals benefited from information about why punishment was occurring, revaluing their actions and changing their behaviour (Unaware). However, we identify one condition where incorrect causal beliefs can be problematic: when punishment is infrequent. Under this condition, more individuals showed detrimental patterns of behaviour that resisted information-driven updating (Compulsive). For these individuals, rare punishment inoculated behavioural preferences against cognitive and behavioural updating.

The samples of evidence we use to make inferences in everyday and formal settings are often subject to selection biases. Two property induction experiments examined group and individual sensitivity to one type of selection bias: sampling frames - causal constraints that only allow certain types of instances to be sampled. Group data from both experiments indicated that people were sensitive to the effects of such frames, showing narrower generalization when sample instances were selected because they shared a target property (property sampling) than when instances were sampled because they belonged to a particular group (category sampling). Group generalization patterns conformed to the predictions of a Bayesian model of property induction that incorporates a selective sampling mechanism. In each experiment, however, there was considerable individual variation, with a nontrivial minority showing little sensitivity to sampling frames. Experiment 2 examined correlates of frames sensitivity. A composite measure of working memory capacity predicted individual sensitivity to sampling frames. These results have important implications for current debates about people's ability to factor sample selection mechanisms into their inferences and for the development of formal models of inductive inference. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Standard theories suggest that humans should seek information only when it can help them make better decisions. However, recent work suggests that people choose to seek information even when it cannot influence the outcome of a choice. Across three experiments, we examined how this preference for non‐instrumental information was related to the risk, regret, and rejoice associated with different choices. Experiment 1 examined how risk preference informed the appetite for non‐instrumental information and tested how risk and information preference in a gamble‐task related to the desire for knowledge across a range of hypothetical real‐world scenarios. In Experiment 2, we tested how risk, operationalized as variance, related to non‐instrumental information seeking when allowing participants to mentally simulate the potential outcomes of gambles. In Experiment 3, we provided explicit feedback about forgone options, intending to make the potential for regret or rejoice more salient. Taken together, our results show a consistent appetite for information that was robust to changes across all experimental manipulations. We found some evidence of a positive correlation between the desire for knowledge and the level of anticipated regret (Experiment 1), but overall, our data appear more consistent with the idea that non‐instrumental information seeking is driven by a general aversion to uncertainty than by an attempt to regulate specific future emotions.

Proposed psychological mechanisms generating noninstrumental information seeking in humans can be broadly categorized into two competing accounts: the maximization of anticipating rewards versus an aversion to uncertainty. We compare three separate formalizations of these theories on their ability to track the dependency of information-seeking behavior on increasing levels of cue-outcome delay as well as their sensitivity to outcome valence. Across three experiments using a variety of different stimuli, we observe a flat to monotonically increasing pattern of delay dependency and minimal evidence of sensitivity to outcome valence––patterns which are better predicted, qualitatively and quantitatively, by an uncertainty aversion information model.

People’s desire to seek or avoid information is not only influenced by the possible outcomes of an event, but the probability of those particular outcomes occurring. There are competing explanations however as to how and why people’s desire for non-instrumental information is affected by factors including expected value, probability of outcome, and a unique formulation of outcome uncertainty. Over two experiments, we find that people’s preference for noninstrumental information is positively correlated with probability when the outcome is positive (i.e., winning money) and negatively correlated when the outcome is negative (i.e., losing money). Furthermore, at the aggregate level, we find the probability of an outcome to be a better predictor of information preference than the expected value of the event or its outcome uncertainty.