The role of the working memory storage component in a random-like series generation.

People are not equipped with an internal random series generator. When asked to produce a random series they simply try to reproduce an output of known random process. However, this endeavor is very often limited by their working memory capacity. Here, we investigate the model of random-like series generation that accounts for the involvement of storage and processing components of working memory. In two studies, we used a modern, robust measure of randomness to assess human-generated series. In Study 1, in the experimental design with the visibility of the last generated elements as a between-subjects variable, we tested whether decreasing cognitive load on working memory would mitigate the decay in the level of randomness of the generated series. Moreover, we investigated the relationship between randomness judgment and algorithmic complexity of human-generated series. Results showed that when people did not have to solely rely on their working memory storage component to maintain active past choices they were able to prolongate their high-quality performance. Moreover, people who were able to better distinguish more complex patterns at the same time generated more random series. In Study 2, in the correlational design, we examined the relationship between working memory capacity and the ability to produce random-like series. Results revealed that individuals with longer working memory capacity also were to produce more complex series. These findings highlight the importance of working memory in generating random-like series and provide insights into the underlying mechanisms of this cognitive process.

Subjective consistency increases trust.

Trust is foundational for social relations. Current psychological models focus on specific evaluative and descriptive content underlying initial impressions of trustworthiness. Two experiments investigated whether trust also depends on subjective consistency-a sense of fit between elements. Experiment 1 examined how consistency of simple verbal characterizations influences trust judgments. Experiment 2 examined how incidental visual consistency impacts trust judgments and economic decisions reflecting trust. Both experiments show that subjective consistency positively and uniquely predicts trust judgments and economic behavior. Critically, subjective consistency is a unique predictor of trust that is irreducible to the content of individual elements, either on the dimension of trust or the dimension of valence. These results show that trust impressions are not a simple sum of the contributing parts, but reflect a "gestalt". The results fit current frameworks emphasizing the role of predictive coding and coherence in social cognition.

The effect of the pandemic on European narratives on smart cities and surveillance.

This article presents an analysis of European smart city narratives and how they evolved under the pressure of the COVID-19 pandemic. We start with Joss et al.'s observation that the smart-city discourse is presently in flux, engaged in intensive boundary-work and struggling to gain wider support. We approach this process from the critical perspective of surveillance capitalism, as proposed by Zuboff, to highlight the growing privacy concerns related to technological development. Our results are based on analysing 184 articles regarding smart-city solutions, published on social media by five European journals between 2017 and 2021. We adopted both human and machine coding processes for qualitative and quantitative analysis of our data. As a result, we identified the main actors and four dominant narratives: regulation of artificial intelligence and facial recognition, technological fight with the climate emergency, contact tracing apps and the potential of 5G technology to boost the digitalisation processes. Our analysis shows the growing number of positive narratives underlining the importance of technology in fighting the pandemic and mitigating the climate emergency, but the latter is often mentioned in a tokenistic fashion. Right to privacy considerations are central for two out of four discovered topics. We found that the main rationale for the development of surveillance technologies relates to the competitiveness of the EU in the global technological rivalry, while ambitions like increasing societal well-being or safeguarding the transparency of new policies are nearly non-existent.

The Effect of Context and Individual Differences in Human-Generated Randomness.

Many psychological studies have shown that human-generated sequences are hardly ever random in the strict mathematical sense. However, what remains an open question is the degree to which this (in)ability varies between people and is affected by contextual factors. Herein, we investigated this problem. In two studies, we used a modern, robust measure of randomness based on algorithmic information theory to assess human-generated series. In Study 1 ( N=183 ), in a factorial design with task description as a between-subjects variable, we tested the effects of context and mental fatigue on human-generated randomness. In Study 2 ( N=266 ), in online research, in experimental design, we further investigated the effect of mental fatigue on the randomness of human-generated series and the relationship between the need for cognition (NFC) and the ability to produce random-like series. Results of Study 1 show that the activation of the ability to produce random-like series depends on the relevance of the contextual cues ( χ2(2)=7.9828,p=.0192 ), whether they activate known representations of a random series generator and consequently help to avoid the production of trivial sequences. Our findings from both studies on the effect of mental fatigue (Study 1 - t(47,529.5568)=-18.62,p<.001 ; Study 2 - F(edf=3.587,Ref.df=3.587)=11.863,p<.0001 ) and cognitive motivation ( t(180)=2.66,p=.009 ) demonstrate that regardless of the context or task's novelty people quickly lose interest in the random series generation. Therefore, their performance decreases over time. However, people high in the NFC can maintain the cognitive motivation for a longer period and consequently on average generate more random series. In general, our results suggest that when contextual cues and intrinsic constraints are in optimal interaction people can temporarily escape the structured and trivial patterns and produce more random-like sequences.