The dark side of information proliferation

There are well-understood psychological limits on our capacity to process information. As information proliferation—the consumption and sharing of information—increases through social media and other communications technology, these limits create an attentional bottleneck, favoring information that is more likely to be searched for, attended to, comprehended, encoded, and later reproduced. In information-rich environments, this bottleneck influences the evolution of information via four forces of cognitive selection, selecting for information that is beliefconsistent, negative, social, and predictive. Selection for belief-consistent information leads balanced information to support increasingly polarized views. Selection for negative information amplifies information about downside risks and crowds out potential benefits. Selection for social information drives herding, impairs objective assessments, and reduces exploration for solutions to hard problems. Selection for predictive patterns drives overfitting, the replication crisis, and risk seeking. This article summarizes the negative implications of these forces of cognitive selection and presents eight warnings, which represent severe pitfalls for the naive informavore, accelerating extremism, hysteria, herding, and the proliferation of misinformation

The baby effect and young male syndrome : social influences on cooperative risk-taking in women and men

Parental investment theory predicts differences in risk-taking for females and males as a consequence of reproductive context, with females attempting to reduce risks in relation to their own offspring (here called the baby effect) and males taking more risks in competition with one another (young male syndrome). The experiment we report tests these predictions in a cooperative context by introducing the Social Balloon Analogue Risk Task—the Balloon Analogue Risk Task modified to include a social partner (adult male, adult female, or baby)—along with a commitment device in which participants choose among several possible social partners, with whom they will share their earnings. Results were consistent with the predictions of parental investment theory. Females did not change their levels of risk-taking when paired with adult males or females, but showed a strong reduction in risk when paired with babies. Consistent with previous research, males were strongly inclined to take more risks when paired with another male of the same age, but males showed no change in risk-taking when paired with a female of the same age or a child. The current work provides the first experimental evidence of gender differences in cooperative social risk-taking, as well as the first experimental evidence of a mediator of female risk-taking, i.e., babies

The emotional recall task : juxtaposing recall and recognition-based affect scales

Existing affect scales typically involve recognition of emotions from a predetermined emotion checklist. However, a recognition-based checklist may fail to capture sufficient breadth and specificity of an individual’s recalled emotional experiences and may therefore miss emotions that frequently come to mind. More generally, how do recalled emotions differ from recognized emotions? To address these issues, we present and evaluate an affect scale based on recalled emotions. Participants are asked to produce 10 words that best described their emotions over the past month and then to rate each emotion for how often it was experienced. We show that average weighted valence of the words produced in this task, the Emotional Recall Task (ERT), is strongly correlated with scales related to general affect, such as the PANAS, Ryff’s Scales of Psychological Well-being, the Satisfaction with Life Scale, Depression Anxiety and Stress Scales, and a few other related scales. We further show that the Emotional Recall Task captures a breadth and specificity of emotions not available in other scales but that are nonetheless commonly reported as experienced emotions. We test a general version of the ERT (the ERT general) that is language neutral and can be used across cultures. Finally, we show that the ERT is valid in a test-retest paradigm. In sum, the ERT measures affect based on emotion terms relevant to an individual’s idiosyncratic experience. It is consistent with recognition-based scales, but also offers a new direction towards enriching our understanding of individual differences in recalled and recognized emotions

Humor norms for 4,997 English words

Humor ratings are provided for 4,997 English words collected from 821 participants using an online crowd-sourcing platform. Each participant rated 211 words on a scale from 1 (humorless) to 5 (humorous). To provide for comparisons across norms, words were chosen from a set common to a number of previously collected norms (e.g., arousal, valence, dominance, concreteness, age of acquisition, and reaction time). The complete dataset provides researchers with a list of humor ratings and includes information on gender, age, and educational differences. Results of analyses show that the ratings have reliability on a par with previous ratings and are not well predicted by existing norms

Description-experience gap in choice deferral

Facing a large set of alternatives has previously been reported to lead to choice overload, including choice deferral. Recent studies, however, imply that choice deferral is more tightly associated with the difficulty in evaluating alternatives than with set size: when alternatives are difficult to evaluate, people often defer a choice. This implication is examined in the present study, using alternatives with probabilistic payoffs in 2 paradigms: the description paradigm—with full probability and payoff information provided at 1 time—and the sampling paradigm—with search revealing 1 payoff at a time and repeated search required to derive probabilities and payoffs. The results show that in both paradigms, choice deferral is less frequent when set size is large. Also, the difficulty in evaluating alternatives influences choice deferral in the description paradigm but not in the sampling paradigm: when a payoff from an alternative can take many possible values, a choice is more likely deferred in the description paradigm. In the sampling paradigm, in contrast, information search is often insufficient for people to recognize the difficulty in evaluating alternatives. These results point to a description-experience gap in choice deferral

Mediation centrality in adversarial policy networks

Conflict resolution often involves mediators who understand the issues central to both sides of an argument. Mediators in complex networks represent nodes that are connected to other key nodes in opposing subgraphs. Here we introduce a new metric, mediation centrality, for iden- tifying good mediators in adversarial policy networks, such as the connections between indi- viduals and their reasons for and against the support of controversial topics (e.g., state-financed abortion). Using a process-based account of reason mediation we construct bipartite adversar- ial policy networks and show how mediation defined over subgraph projections constrained to reasons representing opposing sides can be used to produce a measure of mediation centrality that is superior to centrality computed on the full network. We then empirically illustrate and test mediation centrality in a “policy fluency task,” where participants generated reasons for or against eight controversial policy issues (state-subsidized abortion, bank bailouts, forced CO2 reduction, cannabis legalization, shortened naturalization, surrogate motherhood legalization, public smoking ban, and euthanasia legalization). We discuss how mediation centrality can be extended to adversarial policy networks with more than two positions and to other centrality measures

Filling gaps in early word learning

Years of research has shown that children do not learn words at random, but in distinct patterns. Why do we observe the patterns that we do? By using network science and investigating the words that children don’t learn, researchers have potentially uncovered a general property of word learning as a process of gap forming and filling

Historical analysis of national subjective wellbeing using millions of digitized books

We develop a new way to measure national subjective well-being across the very long run where traditional survey data on well-being is not available. Our method is based on quantitative analysis of digitized text from millions of books published over the past 200 years, long before the widespread availability of consistent survey data. The method uses psychological valence norms for thousands of words in different languages to compute the relative proportion of positive and negative language for four different nations (the USA, UK, Germany and Italy). We validate our measure against existing survey data from the 1970s onwards (when such data became available) showing that our measure is highly correlated with surveyed life satisfaction. We also validate our measure against historical trends in longevity and GDP (showing a positive relationship) and conflict (showing a negative relationship). Our measure allows a first look at changes in subjective well-being over the past two centuries, for instance highlighting the dramatic fall in well-being during the two World Wars and rise in relation to longevity

Multiscale computation and dynamic attention in biological and artificial intelligence

Biological and artificial intelligence (AI) are often defined by their capacity to achieve a hierarchy of short-term and long-term goals that require incorporating information over time and space at both local and global scales. More advanced forms of this capacity involve the adaptive modulation of integration across scales, which resolve computational inefficiency and explore-exploit dilemmas at the same time. Research in neuroscience and AI have both made progress towards understanding architectures that achieve this. Insight into biological computations come from phenomena such as decision inertia, habit formation, information search, risky choices and foraging. Across these domains, the brain is equipped with mechanisms (such as the dorsal anterior cingulate and dorsolateral prefrontal cortex) that can represent and modulate across scales, both with top-down control processes and by local to global consolidation as information progresses from sensory to prefrontal areas. Paralleling these biological architectures, progress in AI is marked by innovations in dynamic multiscale modulation, moving from recurrent and convolutional neural networks—with fixed scalings—to attention, transformers, dynamic convolutions, and consciousness priors—which modulate scale to input and increase scale breadth. The use and development of these multiscale innovations in robotic agents, game AI, and natural language processing (NLP) are pushing the boundaries of AI achievements. By juxtaposing biological and artificial intelligence, the present work underscores the critical importance of multiscale processing to general intelligence, as well as highlighting innovations and differences between the future of biological and artificial intelligence

The macroscope : a tool for examining the historical structure of language

The recent rise in digitized historical text has made it possible to quantitatively study our psychological past. This involves understanding changes in what words meant, how words were used, and how these changes may have responded to changes in the environment, such as in healthcare, wealth disparity, and war. Here we make available a tool, the Macroscope, for studying historical changes in language over the last two centuries. The Macroscope uses over 155 billion words of historical text, which will grow as we include new historical corpora, and derives word properties from frequency-of-usage and co-occurrence patterns over time. Using co-occurrence patterns, the Macroscope can track changes in semantics, allowing researchers to identify semantically stable and unstable words in historical text and providing quantitative information about changes in a word’s valence, arousal, and concreteness, as well as information about new properties, such as semantic drift. The Macroscope provides information about both the local and global properties of words, as well as information about how these properties change over time, allowing researchers to visualize and download data in order to make inferences about historical psychology. Although quantitative historical psychology represents a largely new field of study, we see this work as complementing a wealth of other historical investigations, offering new insights and new approaches to understanding existing theory. The Macroscope is avail- able online at http://www.macroscope.tech