Collective Intelligence Under a Volatile Task Environment: a Behavioral Experiment Using Social Networks and Computer Simulations

Collective intelligence in our highly-connected world is a topic of interdisciplinary interest. Previous research has demonstrated that social network structures can affect collective intelligence, but the potential network impact is unknown when the task environment is volatile (i.e., optimal behavioral options can change over time), a common situation in modern societies. Here, we report a laboratory experiment in which a total of 250 participants performed a “restless” two-armed bandit task either alone, or collectively in a centralized or decentralized network. Although both network conditions outperformed the solo condition, no sizable performance difference was detected between the centralized and decentralized networks. To understand the absence of network effects, we analyzed participants’ behavior parametrically using an individual choice model. We then conducted exhaustive agent-based simulations to examine how different choice strategies may underlie collective performance in centralized or decentralized networks under volatile or stationary task environments. We found that, compared to the stationary environment, the difference in network structure had a much weaker impact on collective performance under the volatile environment across broad parametric variations. These results suggest that structural impacts of networks on collective intelligence may be constrained by the degree of environmental volatility.

Liquiritin Alleviates Depression-Like Behavior in CUMS Mice by Inhibiting Oxidative Stress and NLRP3 Inflammasome in Hippocampus

Objective. Central inflammation is generally accepted to be involved in the pathology of depression. We investigated whether liquiritin exerts antidepressant effects by inhibiting central NLRP3 inflammasomes. Results. The behavioral despair model and chronic unpredictable mild stress (CUMS) model in mice were established to evaluate the antidepressant action of liquiritin. In the despair model study, liquiritin (40 mg/kg) administration reduced immobility time in tail suspension test (TST) and forced swimming test (FST) without affecting locomotion activity. In CUMS model study, liquiritin (40 mg/kg, once daily for 4 weeks) significantly increased sucrose consumption and body weight of CUMS mice. The behavioral experiment results showed that liquiritin reduced the immobile time of CUMS mice in TST and FST, respectively, and increased the time spent and open arm entries in the elevated plus-maze (EPM) test. Further, the hippocampal superoxide dismutase (SOD) activity was increased in liquiritin-treated group, while malonaldehyde (MDA) decreased. Additionally, the hippocampal cytokines interleukin-18 (IL-18) and interleukin-1 beta (IL-1β) contents were reduced in the liquiritin-treated group. Further, liquiritin downregulated the expression of NLRP3 in the hippocampus of CUMS mice rather than TLR4. Besides, NLRP3 inflammasome-associated proteins caspase-1 and ASC were also downregulated. However, liquiritin did not alter the thermal stability of NLRP3 in the cellular thermal shift assay (CETSA), suggesting that its inhibition of NLPR3 was not by direct targeting of NLRP3 protein. Conclusions. Liquiritin attenuates depression-like behavior of CUMS mice and inhibited cytokines levels triggered by NLRP3 inflammasome, suggesting the antidepressant action is, at least partially, associated with antioxidant stress and inhibition of NLRP3 inflammasome activation.

Discovering Rational Heuristics for Risky Choice

For computationally limited agents such as humans, perfectly rational decision-making is almost always out of reach. Instead, people may rely on computationally frugal heuristics that usually yield good outcomes. Although previous research has identified many such heuristics, discovering good heuristics and predicting when they will be used remains challenging. Here, we present a machine learning method that identifies the best heuristics to use in any given situation. To demonstrate the generalizability and accuracy of our method, we compare the strategies it discovers against those used by people across a wide range of multi-alternative risky choice environments in a behavioral experiment that is an order of magnitude larger than any previous experiments of its type. Our method rediscovered known heuristics, identifying them as rational strategies for specific environments, and discovered novel heuristics that had been previously overlooked. Our results show that people adapt their decision strategies to the structure of the environment and generally make good use of their limited cognitive resources, although they tend to collect too little information and their strategy choices do not always fully exploit the structure of the environment.

Valid and Reliable Measures of Generalized Trust: Evidence from a Nationally Representative Survey and Behavioral Experiment

Across the social sciences, generalized trust has been one of the most frequently examined constructs since researchers first introduced measures of it in the 1950s. Despite its significance, there is growing consensus that conventional measures of generalized trust are prone to measurement invalidity and non-equivalence, which places sociological knowledge about generalized trust in serious doubt. In this article, I advance trust research in sociology by (1) refining two new self-report measures of generalized trust—the Stranger Face Trust scale (SFT) and the Imaginary Stranger Trust scale (IST)—and (2) assessing their empirical performance on a nationally representative probability sample (N = 1,264). I compare the reliability and validity of SFT, IST, and traditional measures of generalized trust across a number of measurement validation tests (convergent validity, discriminant validity, known-groups validity, and predictive validity). Results suggest that SFT provides the most accurate and consistent measure of generalized trust. I conclude by discussing the implications of my findings for sociological knowledge.

Dynamic Probabilistic Entailment. Improving on Adams' Dynamic Entailment Relation

The inferences of contraposition (A ⇒ C ∴ ¬C ⇒ ¬A), the hypothetical syllogism (A ⇒ B, B ⇒ C ∴ A ⇒ C), and others are widely seen as unacceptable for counterfactual conditionals. Adams convincingly argued, however, that these inferences are unacceptable for indicative conditionals as well. He argued that an indicative conditional of form A ⇒ C has assertability conditions instead of truth conditions, and that their assertability ‘goes with’ the conditional probability p(C|A). To account for inferences, Adams developed the notion of probabilistic entailment as an extension of classical entailment. This combined approach (correctly) predicts that contraposition and the hypothetical syllogism are invalid inferences. Perhaps less well-known, however, is that the approach also predicts that the unconditional counterparts of these inferences, e.g., modus tollens (A ⇒ C, ¬C ∴ ¬A), and iterated modus ponens (A ⇒ B, B ⇒ C, A ∴ C) are predicted to be valid. We will argue both by example and by calling to the results from a behavioral experiment (N = 159) that these latter predictions are incorrect if the unconditional premises in these inferences are seen as new information. Then we will discuss Adams’ (1998) dynamic probabilistic entailment relation, and argue that it is problematic. Finally, it will be shown how his dynamic entailment relation can be improved such that the incongruence predicted by Adams’ original system concerning conditionals and their unconditional counterparts are overcome. Finally, it will be argued that the idea behind this new notion of entailment is of more general relevance.

The effect of social identity on integration of social minorities: The case of North Korean refugees in South Korea

This paper investigates the effect of a shared social identity on social behaviors of a marginalized population by focusing on North Korean refugees in South Korea. The findings of a behavioral experiment with North Korean refugees show that the common Korean identity can promote their integration in South Korea, despite considerable differences caused by seven-decade long separation between the two countries. Perceiving ethnic unity shared with South Koreans stimulates North Koreans’ socially desirable behaviors and attitudes such as trust, cooperation, confidence, and life satisfaction in South Korea, as well as their self-confidence about North Korean origin. In addition, the effect of the shared identity is greater for women and better educated persons – the finding that stresses the importance of education and gender-specific policy to accelerate social integration of North Korean refugees.

Motivated reasoning, fast and slow

Are people more likely to (mis)interpret information so that it aligns with their ideological identity when relying on feelings compared to when engaging in analytical thinking? Or is it the other way around: Does deliberation increase the propensity to (mis)interpret information to confirm existing political views? In a behavioral experiment, participants (n = 1207, Swedish sample) assessed numerical information concerning the effects of gender quotas and immigration either under time pressure or under no time pressure. To measure trait differences in cognitive sophistication, we also collected data on numeric ability. We found clear evidence of motivated reasoning when assessing both the effects of gender quotas on companies’ financial results and the effect of refugee intake on crime rates. Subjects who prioritized equality over liberty on the labor market were 13 percentage points less likely to correctly assess numerical information depicting that companies that used gender quotas when hiring made less profit. Subjects who classified themselves as ‘Swedes’ rather than ‘World citizens’ were 14 percentage points less likely to correctly assess numerical information depicting that crime rates decreased following immigration. Time pressure did not affect the likelihood to engage in motivated reasoning, while subjects with higher numeric ability were less likely to engage in motivated reasoning when analyzing information concerning refugee intake, but more likely to engage in motivated reasoning when analyzing information regarding the effect of gender quotas. Together these results indicate that motivated reasoning is primarily driven by individual differences in analytical thinking at the trait level and not by situational factors such as time pressure, and that whether motivated reasoning is primarily driven by analysis or feelings depends on the topic at hand.

Moving beyond "nouns in the lab": Using naturalistic data to understand why infants' first words include uh-oh and hi

Why do infants learn some words earlier than others? To explain how and when words are learned, existing theories of word learning prioritize visual information and draw mainly on lab-based studies of noun-to-object mapping. However, words that are more abstract than object nouns, such as uh-oh, hi, more, up, and all-gone, are typically among the first to appear in infants' vocabularies. We combined a behavioral experiment with naturalistic observational research to explore how infants learn and represent this understudied category of high-frequency, routine-based non-nouns, which we term ‘everyday words’. In Study 1, we found that conventional eye-tracking measures of comprehension were insufficient to capture 10- to 16-month-old infants' emerging understanding of everyday words. In Study 2, we analyzed the visual and social scenes surrounding caregivers' and infants' use of everyday words in a naturalistic video corpus. This ecologically-motivated research revealed that everyday words rarely co-occurred with consistent visual referents, making their early learnability difficult to reconcile with dominant word learning theories. Our findings instead point to complex patterns in the types of situations associated with everyday words that could contribute to their early representation in infants’ vocabularies. By leveraging both experimental and observational methods, this investigation underscores the value of using naturalistic data to broaden theories of early learning.

Single target acuity in the common sunfish (Lepomis gibbosus)

Vision is considered to contribute to foraging, territorial, and reproductive behavior in sunfish. In these contexts, sunfish need to perceive single targets, such as prey items or body markings from either conspecifics or individuals of other sunfish species, from some distances. We determined the single target acuity of six common sunfish in a behavioral experiment to assess whether the visual abilities of sunfish correspond with behavioral observations or reactive distance measures and thus to assess the limits of vision regarding the mentioned behaviors. Single target acuity for full-contrast single targets amounted to 0.17 (0.13 - 0.32) deg. When contrast was reduced to Weber contrasts of 0.67 and 0.41, single target acuity dropped to 0.34 (0.31 - 0.37) deg, and finally to 0.42 (0.34 - 0.54) deg. Single target acuity would thus allow common sunfish to perceive biologically relevant stimuli at reasonable distances even when contrast is reduced.