Facial recognition technology and human raters can predict political orientation from images of expressionless faces even when controlling for demographics and self-presentation.

Carefully standardized facial images of 591 participants were taken in the laboratory while controlling for self-presentation, facial expression, head orientation, and image properties. They were presented to human raters and a facial recognition algorithm: both humans (r = .21) and the algorithm (r = .22) could predict participants' scores on a political orientation scale (Cronbach's α = .94) decorrelated with age, gender, and ethnicity. These effects are on par with how well job interviews predict job success, or alcohol drives aggressiveness. The algorithm's predictive accuracy was even higher (r = .31) when it leveraged information on participants' age, gender, and ethnicity. Moreover, the associations between facial appearance and political orientation seem to generalize beyond our sample: The predictive model derived from standardized images (while controlling for age, gender, and ethnicity) could predict political orientation (r ≈ .13) from naturalistic images of 3,401 politicians from the United States, the United Kingdom, and Canada. The analysis of facial features associated with political orientation revealed that conservatives tended to have larger lower faces. The predictability of political orientation from standardized images has critical implications for privacy, the regulation of facial recognition technology, and understanding the origins and consequences of political orientation. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Large language models know how the personality of public figures is perceived by the general public.

We show that people's perceptions of public figures' personalities can be accurately predicted from their names' location in GPT-3's semantic space. We collected Big Five personality perceptions of 226 public figures from 600 human raters. Cross-validated linear regression was used to predict human perceptions from public figures' name embeddings extracted from GPT-3. The models' accuracy ranged from r = .78 to .88 without controls and from r = .53 to .70 when controlling for public figures' likability and demographics, after correcting for attenuation. Prediction models showed high face validity as revealed by the personality-descriptive adjectives occupying their extremes. Our findings reveal that GPT-3 word embeddings capture signals pertaining to individual differences and intimate traits.

Political Attitudes and Disease Threat: Regional Pathogen Stress Is Associated With Conservative Ideology Only for Older Individuals.

What environmental factors are associated with individual differences in political ideology, and do such associations change over time? We examine whether reductions in pathogen prevalence in U.S. states over the past 60 years are associated with reduced associations between parasite stress and conservatism. We report a positive association between infection levels and conservative ideology in the United States during the 1960s and 1970s. However, this correlation reduces from the 1980s onwards. These results suggest that the ecological influence of infectious diseases may be larger for older people who grew up (or whose parents grew up) during earlier time periods. We test this hypothesis by analyzing the political affiliation of 45,000 Facebook users, and find a positive association between self-reported political affiliation and regional pathogen stress for older (>40 years) but not younger individuals. It is concluded that the influence of environmental pathogen stress on ideology may have reduced over time.

Overlap in meaning is a stronger predictor of semantic activation in GPT-3 than in humans.

Modern large language models generate texts that are virtually indistinguishable from those written by humans and achieve near-human performance in comprehension and reasoning tests. Yet, their complexity makes it difficult to explain and predict their functioning. We examined a state-of-the-art language model (GPT-3) using lexical decision tasks widely used to study the structure of semantic memory in humans. The results of four analyses showed that GPT-3's patterns of semantic activation are broadly similar to those observed in humans, showing significantly higher semantic activation in related (e.g., "lime-lemon") word pairs than in other-related (e.g., "sour-lemon") or unrelated (e.g., "tourist-lemon") word pairs. However, there are also significant differences between GPT-3 and humans. GPT-3's semantic activation is better predicted by similarity in words' meaning (i.e., semantic similarity) rather than their co-occurrence in the language (i.e., associative similarity). This suggests that GPT-3's semantic network is organized around word meaning rather than their co-occurrence in text.

Human-like intuitive behavior and reasoning biases emerged in large language models but disappeared in ChatGPT.

We design a battery of semantic illusions and cognitive reflection tests, aimed to elicit intuitive yet erroneous responses. We administer these tasks, traditionally used to study reasoning and decision-making in humans, to OpenAI's generative pre-trained transformer model family. The results show that as the models expand in size and linguistic proficiency they increasingly display human-like intuitive system 1 thinking and associated cognitive errors. This pattern shifts notably with the introduction of ChatGPT models, which tend to respond correctly, avoiding the traps embedded in the tasks. Both ChatGPT-3.5 and 4 utilize the input-output context window to engage in chain-of-thought reasoning, reminiscent of how people use notepads to support their system 2 thinking. Yet, they remain accurate even when prevented from engaging in chain-of-thought reasoning, indicating that their system-1-like next-word generation processes are more accurate than those of older models. Our findings highlight the value of applying psychological methodologies to study large language models, as this can uncover previously undetected emergent characteristics.

Regional personality assessment through social media language.

OBJECTIVE: We explore the personality of counties as assessed through linguistic patterns on social media. Such studies were previously limited by the cost and feasibility of large-scale surveys; however, language-based computational models applied to large social media datasets now allow for large-scale personality assessment. METHOD: We applied a language-based assessment of the five factor model of personality to 6,064,267 U.S. Twitter users. We aggregated the Twitter-based personality scores to 2,041 counties and compared to political, economic, social, and health outcomes measured through surveys and by government agencies. RESULTS: There was significant personality variation across counties. Openness to experience was higher on the coasts, conscientiousness was uniformly spread, extraversion was higher in southern states, agreeableness was higher in western states, and emotional stability was highest in the south. Across 13 outcomes, language-based personality estimates replicated patterns that have been observed in individual-level and geographic studies. This includes higher Republican vote share in less agreeable counties and increased life satisfaction in more conscientious counties. CONCLUSIONS: Results suggest that regions vary in their personality and that these differences can be studied through computational linguistic analysis of social media. Furthermore, these methods may be used to explore other psychological constructs across geographies.

Facial recognition technology can expose political orientation from naturalistic facial images.

Ubiquitous facial recognition technology can expose individuals' political orientation, as faces of liberals and conservatives consistently differ. A facial recognition algorithm was applied to naturalistic images of 1,085,795 individuals to predict their political orientation by comparing their similarity to faces of liberal and conservative others. Political orientation was correctly classified in 72% of liberal-conservative face pairs, remarkably better than chance (50%), human accuracy (55%), or one afforded by a 100-item personality questionnaire (66%). Accuracy was similar across countries (the U.S., Canada, and the UK), environments (Facebook and dating websites), and when comparing faces across samples. Accuracy remained high (69%) even when controlling for age, gender, and ethnicity. Given the widespread use of facial recognition, our findings have critical implications for the protection of privacy and civil liberties.

ATP and spontaneous calcium oscillations control neural stem cell fate determination in Huntington's disease: a novel approach for cell clock research.

Calcium, the most versatile second messenger, regulates essential biology including crucial cellular events in embryogenesis. We investigated impacts of calcium channels and purinoceptors on neuronal differentiation of normal mouse embryonic stem cells (ESCs), with outcomes being compared to those of in vitro models of Huntington's disease (HD). Intracellular calcium oscillations tracked via real-time fluorescence and luminescence microscopy revealed a significant correlation between calcium transient activity and rhythmic proneuronal transcription factor expression in ESCs stably expressing ASCL-1 or neurogenin-2 promoters fused to luciferase reporter genes. We uncovered that pharmacological manipulation of L-type voltage-gated calcium channels (VGCCs) and purinoceptors induced a two-step process of neuronal differentiation. Specifically, L-type calcium channel-mediated augmentation of spike-like calcium oscillations first promoted stable expression of ASCL-1 in differentiating ESCs, which following P2Y2 purinoceptor activation matured into GABAergic neurons. By contrast, there was neither spike-like calcium oscillations nor responsive P2Y2 receptors in HD-modeling stem cells in vitro. The data shed new light on mechanisms underlying neurogenesis of inhibitory neurons. Moreover, our approach may be tailored to identify pathogenic triggers of other developmental neurological disorders for devising targeted therapies.

Spouses' faces are similar but do not become more similar with time.

The widely disseminated convergence in physical appearance hypothesis posits that long-term partners' facial appearance converges with time due to their shared environment, emotional mimicry, and synchronized activities. Although plausible, this hypothesis is incompatible with empirical findings pertaining to a wide range of other traits-such as personality, intelligence, attitudes, values, and well-being-in which partners show initial similarity but do not converge over time. We solve this conundrum by reexamining this hypothesis using the facial images of 517 couples taken at the beginning of their marriages and 20 to 69 years later. Using two independent methods of estimating their facial similarity (human judgment and a facial recognition algorithm), we show that while spouses' faces tend to be similar at the beginning of marriage, they do not converge over time, bringing facial appearance in line with other personal characteristics.

Bone Defect Repair Using a Bone Substitute Supported by Mesenchymal Stem Cells Derived from the Umbilical Cord.

OBJECTIVE: Bone defects or atrophy may arise as a consequence of injury, inflammation of various etiologies, and neoplastic or traumatic processes or as a result of surgical procedures. Sometimes the regeneration process of bone loss is impaired, significantly slowed down, or does not occur, e.g., in congenital defects. For the bone defect reconstruction, a piece of the removed bone from ala of ilium or bone transplantation from a decedent is used. Replacement of the autologous or allogenic source of the bone-by-bone substitute could reduce the number of surgeries and time in the pharmacological coma during the reconstruction of the bone defect. Application of mesenchymal stem cells in the reconstruction surgery may have positive influence on tissue regeneration by secretion of angiogenic factors, recruitment of other MSCs, or differentiation into osteoblasts. Materials and Methods. Mesenchymal stem cells derived from the umbilical cord (Wharton's jelly (WJ-MSC)) were cultured in GMP-grade DMEM low glucose supplemented with heparin, 10% platelet lysate, glucose, and antibiotics. In vitro WJ-MSCs were seeded on the bone substitute Bio-Oss Collagen® and cultured in the StemPro® Osteogenesis Differentiation Kit. During the culture on the 1st, 7th, 14th, and 21st day (day in vitro (DIV)), we analyzed viability (confocal microscopy) and adhesion capability (electron microscopy) of WJ-MSC on Bio-Oss scaffolds, gene expression (qPCR), and secretion of proteins (Luminex). In vivo Bio-Oss® scaffolds with WJ-MSC were transplanted to trepanation holes in the cranium to obtain their overgrowth. The computed tomography was performed 7, 14, and 21 days after surgery to assess the regeneration. RESULTS: The Bio-Oss® scaffold provides a favourable environment for WJ-MSC survival. WJ-MSCs in osteodifferentiation medium are able to attach and proliferate on Bio-Oss® scaffolds. Results obtained from qPCR and Luminex® indicate that WJ-MSCs possess the ability to differentiate into osteoblast-like cells and may induce osteoclastogenesis, angiogenesis, and mobilization of host MSCs. In animal studies, WJ-MSCs seeded on Bio-Oss® increased the scaffold integration with host bone and changed their morphology to osteoblast-like cells. CONCLUSIONS: The presented construct consisted of Bio-Oss®, the scaffold with high flexibility and plasticity, approved for clinical use with seeded immunologically privileged WJ-MSC which may be considered reconstructive therapy in bone defects.

Individual-Level Analyses of the Impact of Parasite Stress on Personality: Reduced Openness Only for Older Individuals.

The parasite stress hypothesis predicts that individuals living in regions with higher infectious disease rates will show lower openness, agreeableness, and extraversion, but higher conscientiousness. This article, using data from more than 250,000 U.S. Facebook users, reports tests of these predictions at the level of both U.S. states and individuals and evaluates criticisms of previous findings. State-level results for agreeableness and conscientiousness are consistent with previously reported cross-national findings, but others (a significant positive correlation with extraversion and no correlation with openness) are not. However, effects of parasite stress on conscientiousness and agreeableness are not found when analyses account for the data's hierarchical structure and include controls. We find that only openness is robustly related to parasite stress in these analyses, and we also find a significant interaction with age: Older, but not younger, inhabitants of areas of high parasite stress show lower openness. Interpretations of the findings are discussed.

Privacy in the age of psychological targeting.

Psychological targeting describes the practice of extracting people's psychological profiles from their digital footprints (e.g. their Facebook Likes, Tweets or credit card records) in order to influence their attitudes, emotions or behaviors through psychologically informed interventions at scale. We discuss how the increasingly blurred lines between public and private information, and the continuation of the outdated practices of notice and consent, challenge traditional conceptualizations of privacy in the context of psychological targeting. Drawing on the theory of contextual integrity, we argue that it is time to rethink privacy and move beyond the questions of who collects what data to how the data are being used. Finally, we suggest that regulations of psychological targeting should be accompanied by a mindset that fosters (1) privacy by design to make it easy for individuals to act in line with their privacy goals, as well as (2) disclosure by choice, to allow individuals to freely decide whether and when they might be willing to forsake their privacy for better service.

Latent human traits in the language of social media: An open-vocabulary approach.

Over the past century, personality theory and research has successfully identified core sets of characteristics that consistently describe and explain fundamental differences in the way people think, feel and behave. Such characteristics were derived through theory, dictionary analyses, and survey research using explicit self-reports. The availability of social media data spanning millions of users now makes it possible to automatically derive characteristics from behavioral data-language use-at large scale. Taking advantage of linguistic information available through Facebook, we study the process of inferring a new set of potential human traits based on unprompted language use. We subject these new traits to a comprehensive set of evaluations and compare them with a popular five factor model of personality. We find that our language-based trait construct is often more generalizable in that it often predicts non-questionnaire-based outcomes better than questionnaire-based traits (e.g. entities someone likes, income and intelligence quotient), while the factors remain nearly as stable as traditional factors. Our approach suggests a value in new constructs of personality derived from everyday human language use.

The Promotion of a Bright Future and the Prevention of a Dark Future: Time Anchored Incitements in News Articles and Facebook's Status Updates.

Background: Research suggests that humans have the tendency to increase the valence of events when these are imagined to happen in the future, but to decrease the valence when the same events are imagined to happen in the past. This line of research, however, has mostly been conducted by asking participants to value imagined, yet probable, events. Our aim was to re-examine this time-valence asymmetry using real-life data: a Reuter's news and a Facebook status updates corpus. Method: We organized the Reuter news (120,000,000 words) and the Facebook status updates data (41,056,346 words) into contexts grouped in chronological order (i.e., past, present, and future) using verbs and years as time markers. These contexts were used to estimate the valence of each article and status update, respectively, in relation to the time markers using natural language processing tools (i.e., the Latent Semantic Analysis algorithm). Results: Our results using verbs, in both text corpus, showed that valence for the future was significantly higher compared to the past (future > past). Similarly, in the Reuter year condition, valence increased approximately linear from 1994 to 1999 for texts written 1996-1997. In the Facebook year condition, the valence of the future was also significantly higher than past valence. Conclusion: Generally, the analyses of the Reuters data indicated that the past is devaluated relative to both the present and the future, while the analyses of the Facebook data indicated that both the past and the present are devaluated against the future. On this basis, we suggest that people strive to communicate the promotion of a bright future and the prevention of a dark future, which in turn leads to a temporal-valence asymmetrical phenomenon (valence = past < present < future). " I have a dream that one day this nation will rise up and live out the true meaning of its creed: "We hold these truths to be self-evident, that all men are created equal."I have a dream that one day on the red hills of Georgia, the sons of former slaves and the sons of former slave owners will be able to sit down together at the table of brotherhood.I have a dream that one day even the state of Mississippi, a state sweltering with the heat of injustice, sweltering with the heat of oppression, will be transformed into an oasis of freedom and justice.I have a dream that my four little children will one day live in a nation where they will not be judged by the color of their skin but by the content of their character.I have a dream today!"Martin Luther King, Jr., 28th of August 1963, at the Lincoln Memorial, Washington, DC, United States.

Musical Preferences Predict Personality: Evidence From Active Listening and Facebook Likes.

Research over the past decade has shown that various personality traits are communicated through musical preferences. One limitation of that research is external validity, as most studies have assessed individual differences in musical preferences using self-reports of music-genre preferences. Are personality traits communicated through behavioral manifestations of musical preferences? We addressed this question in two large-scale online studies with demographically diverse populations. Study 1 ( N = 22,252) shows that reactions to unfamiliar musical excerpts predicted individual differences in personality-most notably, openness and extraversion-above and beyond demographic characteristics. Moreover, these personality traits were differentially associated with particular music-preference dimensions. The results from Study 2 ( N = 21,929) replicated and extended these findings by showing that an active measure of naturally occurring behavior, Facebook Likes for musical artists, also predicted individual differences in personality. In general, our findings establish the robustness and external validity of the links between musical preferences and personality.

Deep neural networks are more accurate than humans at detecting sexual orientation from facial images.

We show that faces contain much more information about sexual orientation than can be perceived or interpreted by the human brain. We used deep neural networks to extract features from 35,326 facial images. These features were entered into a logistic regression aimed at classifying sexual orientation. Given a single facial image, a classifier could correctly distinguish between gay and heterosexual men in 81% of cases, and in 71% of cases for women. Human judges achieved much lower accuracy: 61% for men and 54% for women. The accuracy of the algorithm increased to 91% and 83%, respectively, given five facial images per person. Facial features employed by the classifier included both fixed (e.g., nose shape) and transient facial features (e.g., grooming style). Consistent with the prenatal hormone theory of sexual orientation, gay men and women tended to have gender-atypical facial morphology, expression, and grooming styles. Prediction models aimed at gender alone allowed for detecting gay males with 57% accuracy and gay females with 58% accuracy. Those findings advance our understanding of the origins of sexual orientation and the limits of human perception. Additionally, given that companies and governments are increasingly using computer vision algorithms to detect people's intimate traits, our findings expose a threat to the privacy and safety of gay men and women. (PsycINFO Database Record

In your eyes only? Discrepancies and agreement between self- and other-reports of personality from age 14 to 29.

Do others perceive the personality changes that take place between the ages of 14 and 29 in a similar fashion as the aging person him- or herself? This cross-sectional study analyzed age trajectories in self- versus other-reported Big Five personality traits and in self-other agreement in a sample of more than 10,000 individuals from the myPersonality Project. Results for self-reported personality showed maturation effects (increases in extraversion, conscientiousness, openness to experience, and emotional stability), and this pattern was generally also reflected in other-reports, albeit with discrepancies regarding timing and magnitude. Age differences found for extraversion were similar between the self- and other-reports, but the increase found in self-reported conscientiousness was delayed in other-reports, and the curvilinear increase found in self-reported openness was slightly steeper in other-reports. Only emotional stability showed a distinct mismatch with an increase in self-reports, but no significant age effect in other-reports. Both the self- and other-reports of agreeableness showed no significant age trends. The trait correlations between the self- and other-reports increased with age for emotional stability, openness, agreeableness, and conscientiousness; by contrast, agreement regarding extraversion remained stable. The profile correlations confirmed increases in self-other agreement with age. We suggest that these gains in agreement are a further manifestation of maturation. Taken together, our analyses generally show commonalities but also some divergences in age-associated mean level changes between self- and other-reports of the Big Five, as well as an age trend toward increasing self-other agreement. (PsycINFO Database Record

A Computer Adaptive Measure of Delay Discounting.

Delay discounting has been linked to important behavioral, health, and social outcomes, including academic achievement, social functioning and substance use, but thoroughly measuring delay discounting is tedious and time consuming. We develop and consistently validate an efficient and psychometrically sound computer adaptive measure of discounting. First, we develop a binary search-type algorithm to measure discounting using a large international data set of 4,190 participants. Using six independent samples ( N = 1,550), we then present evidence of concurrent validity with two standard measures of discounting and a measure of discounting real rewards, convergent validity with addictive behavior, impulsivity, personality, survival probability; and divergent validity with time perspective, life satisfaction, age and gender. The new measure is considerably shorter than standard questionnaires, includes a range of time delays, can be applied to multiple reward magnitudes, shows excellent concurrent, convergent, divergent, and discriminant validity-by showing more sensitivity to effects of smoking behavior on discounting.

Frankly, We Do Give a Damn: The Relationship Between Profanity and Honesty.

There are two conflicting perspectives regarding the relationship between profanity and dishonesty. These two forms of norm-violating behavior share common causes and are often considered to be positively related. On the other hand, however, profanity is often used to express one's genuine feelings and could therefore be negatively related to dishonesty. In three studies, we explored the relationship between profanity and honesty. We examined profanity and honesty first with profanity behavior and lying on a scale in the lab (Study 1; N = 276), then with a linguistic analysis of real-life social interactions on Facebook (Study 2; N = 73,789), and finally with profanity and integrity indexes for the aggregate level of U.S. states (Study 3; N = 50 states). We found a consistent positive relationship between profanity and honesty; profanity was associated with less lying and deception at the individual level and with higher integrity at the society level.