Thursday, March 18, 2021

From 2017... Who Wants To Live Forever? Explaining the Cross-Cultural Recurrence of Reincarnation Beliefs

Who Wants To Live Forever? Explaining the Cross-Cultural Recurrence of Reincarnation Beliefs. Claire White. Journal of Cognition and Culture, vol 17, issue 5, pp 419–436. Nov 2017. https://doi.org/10.1163/15685373-12340016

Abstract: Around 30% of world cultures endorse reincarnation and 20% of contemporary Americans think that reincarnation is plausible. This paper addresses the question of why belief in reincarnation is so pervasive across geographically disparate contexts. While social scientists have provided compelling explanations of the particularistic aspects of reincarnation, less is known about the psychological foundations of such beliefs. In this paper, I review research in the cognitive science of religion to propose that selected panhuman cognitive tendencies contribute to the cross-cultural success of basic ideas in reincarnation. Together, this research suggests that extraordinary convictions, including those associated with postmortem survival, are underpinned by some of the same processes that govern mundane social cognition.

Keywords: Reincarnation, Cognitive Science of Religion, Social cognition, the afterlife.

Check also, from 2018... Contemporary Post-mortem Survival Narratives are popular & convincing, in part, because they meet default cognitive assumptions about what human survival would look like if it were possible:

How to Know You’ve Survived Death: A Cognitive Account of the Popularity of Contemporary Post-mortem Survival Narratives. Claire White, Michael Kinsella, Jesse Bering. Method & Theory in the Study of Religion, Volume 30, Issue 3, Pages 279–299. Jul 24 2018. https://www.bipartisanalliance.com/2021/03/contemporary-post-mortem-survival.html


59 societies: In individualistic societies, passion predicts a larger gain & explains more variance in achievement; in contrast, in collectivistic societies, parental support predicts achievement over & above passion

Passion matters but not equally everywhere: Predicting achievement from interest, enjoyment, and efficacy in 59 societies. Xingyu Li, Miaozhe Han, Geoffrey L. Cohen, and  Hazel Rose Markus. Proceedings of the National Academy of Sciences, March 16, 2021 118 (11) e2016964118; https://doi.org/10.1073/pnas.2016964118

Significance: In three large-scale datasets representing adolescents from 59 societies across the globe, we find evidence of a systematic cultural variation in the relationship between passion and achievement. In individualistic societies, passion better predicts achievement and explains more variance in achievement outcomes. In collectivistic societies, passion still positively predicts achievement, but it is a much less powerful predictor. There, parents’ support predicts achievement as much as passion. One implication of these findings is that if admission officers, recruiters, and managers rely on only one model of motivation, a Western independent one, they may risk passing over and mismanaging talented students and employees who increasingly come from sociocultural contexts where a more interdependent model of motivation is common and effective.

Abstract: How to identify the students and employees most likely to achieve is a challenge in every field. American academic and lay theories alike highlight the importance of passion for strong achievement. Based on a Western independent model of motivation, passionate individuals—those who have a strong interest, demonstrate deep enjoyment, and express confidence in what they are doing—are considered future achievers. Those with less passion are thought to have less potential and are often passed over for admission or employment. As academic institutions and corporations in the increasingly multicultural world seek to acquire talent from across the globe, can they assume that passion is an equally strong predictor of achievement across cultural contexts? We address this question with three representative samples totaling 1.2 million students in 59 societies and provide empirical evidence of a systematic, cross-cultural variation in the importance of passion in predicting achievement. In individualistic societies where independent models of motivation are prevalent, relative to collectivistic societies where interdependent models of motivation are more common, passion predicts a larger gain (0.32 vs. 0.21 SD) and explains more variance in achievement (37% vs. 16%). In contrast, in collectivistic societies, parental support predicts achievement over and above passion. These findings suggest that in addition to passion, achievement may be fueled by striving to realize connectedness and meet family expectations. Findings highlight the risk of overweighting passion in admission and employment decisions and the need to understand and develop measures for the multiple sources and forms of motivation that support achievement.


Being male and having higher arousal in response to erotic stimuli, however, was associated with a greater willingness to engage in coercive sex

Sex, sexual arousal, and sexual decision making: An evolutionary perspective. Courtney L. Crosby, David M. Buss, Lawrence K. Cormack, Cindy M. Meston. Personality and Individual Differences, Volume 177, July 2021, 110826., https://doi.org/10.1016/j.paid.2021.110826

Abstract: Sexual arousal is conceptualized as a motivational system that prioritizes mating and minimizes the perceived risks associated with sex. Previous studies show that when sexually aroused, individuals are more likely to endorse engaging in risky sexual behaviors. A majority of these studies examine a restricted number of sexual behaviors or do not test evolutionarily-relevant sex differences. Due to gender asymmetries in the minimum obligatory costs of parental investment, the costs of injudicious sexual decisions tend to be greater for women. As such, men and women may respond in disparate ways when sexually aroused. We extend previous research by investigating the effect of experimentally manipulated sexual arousal on sexual decision-making in men and women (N = 140). We found no significant difference between individuals exposed to neutral or erotic stimuli on the willingness to engage in experimental or coercive sex. Being male and having higher arousal in response to erotic stimuli, however, was associated with a greater willingness to engage in coercive sex. Results suggest that individual differences in sexual arousal following exposure to erotic stimuli may be critical for understanding sexual strategies, particularly those pertaining to sexual coercion.

Keywords: Sexual arousalSexual decision makingSexual coercionSexual behaviorEvolutionary theory


Project Debater, an autonomous debating system that can engage in a competitive debate with humans

An autonomous debating system. Noam Slonim et al. Nature volume 591, pp379–384, Mar 17 2021. https://www.nature.com/articles/s41586-021-03215-w

Abstract: Artificial intelligence (AI) is defined as the ability of machines to perform tasks that are usually associated with intelligent beings. Argument and debate are fundamental capabilities of human intelligence, essential for a wide range of human activities, and common to all human societies. The development of computational argumentation technologies is therefore an important emerging discipline in AI research1. Here we present Project Debater, an autonomous debating system that can engage in a competitive debate with humans. We provide a complete description of the system’s architecture, a thorough and systematic evaluation of its operation across a wide range of debate topics, and a detailed account of the system’s performance in its public debut against three expert human debaters. We also highlight the fundamental differences between debating with humans as opposed to challenging humans in game competitions, the latter being the focus of classical ‘grand challenges’ pursued by the AI research community over the past few decades. We suggest that such challenges lie in the ‘comfort zone’ of AI, whereas debating with humans lies in a different territory, in which humans still prevail, and for which novel paradigms are required to make substantial progress.

Popular version: https://www.nature.com/articles/d41586-021-00539-5


Discussion

Research in AI and in natural language processing is often focused on so called ‘narrow AI’, consisting of narrowly defined tasks. The preference for such tasks has several reasons. They require less resources to pursue; typically have clear evaluation metrics; and are amenable to end-to-end solutions such as those stemming from the rapid progress in the study of deep learning techniques37. Conversely, ‘composite AI’ tasks—namely, tasks associated with broader human cognitive activities, which require the simultaneous application of multiple skills—are less frequently tackled by the AI community. Here, we break down such a composite task into a collection of tangible narrow tasks and develop corresponding solutions for each. Our results demonstrate that a system that properly orchestrates such an arsenal of components can meaningfully engage in a complex human activity, one which we presume is not readily amenable to a single end-to-end solution. Since the 1950s AI has advanced in leaps and bounds, thanks, in part, to the ‘grand challenges’, in which AI technologies performed tasks of growing complexity. Often, this was in the context of competing against humans in games which were thought to require intuitive or analytic skills that are particular to humans. Examples range from chequers38, backgammon39, and chess40, to Watson winning in Jeopardy!41 and Alpha Zero winning at Go and shogi42. We argue that all these games lie within the ‘comfort zone’ of AI, whereas many real-world problems are inherently more ambiguous and fundamentally different, in several ways. First, in games there is a clear definition of a winner, facilitating the use of reinforcement learning techniques39,42. Second, individual game moves are clearly defined, and the value of such moves can often be quantified objectively (for example, see ref. 43), enabling the use of game-solving techniques. Third, while playing a game an AI system may come up with any tactic to ensure winning, even if the associated moves could not be easily interpreted by humans. Finally, for many AI grand challenges, such as Watson41 and Alpha Star44, massive amounts of relevant structured data (for example, in the form of complete games played by humans) was available and imperative for the development of the system. These four characteristics do not hold in competitive debate, which requires an advanced form of using human language, one with much room for subjectivity and interpretation. Correspondingly, often there is no clear winner. Moreover, even if we had a computationally efficient ‘oracle’ to determine the winner of a debate, the sheer complexity of a debate—such as the amount of information required to encode the ‘board state’ or to enumerate all possible ‘moves’—prohibits the use of contemporary game-solving techniques. In addition, it seems implausible to win a debate using a strategy that humans can fail to follow, especially if it is the human audience which determines the winner. And finally, structured debate data are not available at the scale required for training an AI system. Thus, the challenge taken by Project Debater seems to reside outside the AI comfort zone, in a territory where humans still prevail, and where many questions are yet to be answered.


What Does Women’s Facial Attractiveness Signal? Implications for an Evolutionary Perspective on Appearance Enhancement

What Does Women’s Facial Attractiveness Signal? Implications for an Evolutionary Perspective on Appearance Enhancement. Benedict C. Jones, Alex L. Jones, Victor Shiramizu & Claire Anderson. Archives of Sexual Behavior, Mar 17 2021. https://rd.springer.com/article/10.1007/s10508-021-01955-4

Abstract: In their Target Article, Davis and Arnocky (2020) suggest that evolutionary theories of mate preferences can contribute to our understanding of why appearance-enhancement behaviors are seemingly ubiquitous. We support their argument that an interdisciplinary approach, in which evolutionary and other perspectives are fully integrated, will give us a more complete understanding of appearance-enhancement behaviors. We also agree that evolutionary theories of mate preferences have the potential to provide new insights into why such behaviors are so common. Here, we use the literature on women’s facial attractiveness to highlight an important limitation of this argument: uncertainty about precisely what is signalled by physical attractiveness.

Check also Marcinkowska, Urszula M., Benedict C. Jones, and Anthony J. Lee. 2021. “Self-rated Attractiveness Predicts Preferences for Sexually Dimorphic Facial Characteristics: Evidence from a Culturally Diverse Sample.” PsyArXiv. March 10. https://www.bipartisanalliance.com/2021/03/self-rated-attractiveness-predicts.html


Our results suggest that compressing a neural circuit through the "genomic bottleneck" serves as a regularizer, enabling evolution to select simple circuits that can be readily adapted to important real-world tasks

Encoding innate ability through a genomic bottleneck. Alexei Koulakov, Sergey Shuvaev, Anthony Zador. bioRxiv Mar 16 2021. https://doi.org/10.1101/2021.03.16.435261

Abstract: Animals are born with extensive innate behavioral capabilities, which arise from neural circuits encoded in the genome. However, the information capacity of the genome is orders of magnitude smaller than that needed to specify the connectivity of an arbitrary brain circuit, indicating that the rules encoding circuit formation must fit through a "genomic bottleneck" as they pass from one generation to the next. Here we formulate the problem of innate behavioral capacity in the context of artificial neural networks in terms of lossy compression of the weight matrix. We find that several standard network architectures can be compressed by several orders of magnitude, yielding pre-training performance that can approach that of the fully-trained network. Interestingly, for complex but not for simple test problems, the genomic bottleneck algorithm also captures essential features of the circuit, leading to enhanced transfer learning to novel data sets. Our results suggest that compressing a neural circuit through the genomic bottleneck serves as a regularizer, enabling evolution to select simple circuits that can be readily adapted to important real-world tasks. The genomic bottleneck also suggests how innate priors can complement conventional approaches to learning in designing algorithms for artificial intelligence.



Our findings challenge the role of social media in the creation of like-minded discussion; instead, we should look to the role of individual attributes, such as personality traits

The Role of Personality in Political Talk and Like-Minded Discussion. Shelley Boulianne, Karolina Koc-Michalska. The International Journal of Press/Politics, March 17, 2021. https://doi.org/10.1177/1940161221994096

Abstract: Political discussion is a key mechanism for the development of reasoned opinions and political knowledge, but online political discussion has been characterized as uncivil, intolerant, and/or ideologically homogeneous, which is detrimental to this development. In this paper, we examine the role of personality in various forms of political talk—online and offline—as well as like-minded discussion. Based on a 2017 survey conducted in the United Kingdom, United States, and France, we find that people who are open-minded and extraverted are more likely to engage in political talk but less likely to engage in like-minded discussion. Individuals who are older, less educated, introverted, and conscientious are more likely to find themselves in like-minded discussions, both online and on social media. Like-minded discussion is rare; personality, rather than ideology, predicts whether people engage in this form of political talk in online and offline modes. Our findings challenge the role of social media in the creation of like-minded discussion. Instead, we should look to the role of individual attributes, such as personality traits, which create a disposition that motivates the use of social media (and offline networks) to cultivate like-minded discussion.

Keywords: Big Five personality traits, political discussion, political talk, like-minded discussion, echo chamber

This paper examines how personality affects the filtering process related to political discussion. Personality impacts the propensity to discuss politics, use social media, and engage in like-minded discussion on social media. Several steps are required to understand like-minded discussion on social media: (1) consider the biases in who talks politics (81.57 percent of our pooled sample, as per Table 2), (2) consider the filtering of social media adoption (76.82 percent of our pooled sample), (3) consider the subset of people who talk politics on social media (43.99 percent of our pooled sample of social media users), and (4) consider the few people who engage in like-minded discussion (9.41 percent of a pooled sample of social media talkers). Approximately one in ten respondents engages in like-minded discussion; this incidence rate is consistent for offline and online forms. So we ask, what is the role of personality throughout this filtering process? This question is answered with our annotation of Figure 2.

[Figure 2. Summary of findings about personality and political discussion.]

Note. Diagonal-dashed arrows are filtering arrows and straight arrows depict causal effects among key variables in the analysis. O = openness, C = conscientious, Ex = extraversion, A = agreeable, Es = emotional stability.

Openness impacts whether an individual talks politics online and offline and whether they use social media. The filtering process has three stages. In the first stage, people who are open-minded are more likely to talk politics (any mode). In the second stage, people who are open-minded adopt social media use. In the third stage, people who are open-minded are less likely to engage in like-minded discussion. The coefficient did not reach statistical significance at the p < .05 level. Openness has a stronger and more consistent impact than ideology. The existing literature (Table 1) features ten tests of the relationship between openness and political discussion. Of these, four tests for openness on political discussion are significant, which suggests a relationship but hardly offers conclusive results (Table 1). These other studies from the existing literature do not consider the mode of discussion and few consider personality and like-minded discussion. Yet, we offer consistent findings about the importance of openness using our pooled cross-national sample.

We find that extraversion is also important. As mentioned, the existing research features ten tests of the relationship between extraversion and political discussion of which five are significant (Table 1). Extraversion has mixed support related to political discussion in general; extraversion influences talk on social media, but not offline. However, extraversion is a strong and consistent predictor of like-minded discussion on social media and offline. In terms of understanding like-minded discussion on social media, extraversion seems to be the strongest and most consistent personality trait. We replicate this finding in the country-specific results.

Existing research (Table 1) suggests that agreeableness is important (four of ten tests are significant), yet the findings are not consistently positive or negative but rather highly divergent. In our study, agreeableness matters for social media adoption but does not offer direct effects on the likelihood of talking politics. However, as mentioned, assessing agreeableness poses challenges because this trait is strongly correlated with conscientiousness and extraversion (see prior literature review and Supplementary Information file). Correlation issues with these personality traits may pose a challenge when trying to determine their independent effects. We included all traits in our models to reflect existing research (Table 1).

Our paper distinguishes between offline discussion and online discussion through social media. Openness predicts both modes of discussion, suggesting the two modes might be combined into a single, hybrid discussion measure (Chadwick 2013). However, combining these modes would blur some important findings about social media and the role of personality in filtering social media-based discussion. In particular, extraversion and conscientiousness predict social media use, then social media-based discussion, then like-minded discussion on social media. The effects of these personality traits might disappear if the modes are combined into a single measure of political discussion as these measures do not have the same predictive value in relation to offline discussion (general). Also, age and political ideology predict online but not offline forms of discussion. Combining these modes would hide these ideological and age differences in patterns of participation. Age is a consistent predictor of online political discussion (Brundidge 2010Evans and Ulbig 2012Huber et al. 2019Kim and Baek 2018Stromer-Galley 2002). Finally, females are more likely to participate in offline political talk, but less likely to talk on social media (also see: Evans and Ulbig 2012Huber et al. 2019Stromer-Galley 2002). These gender differences would be missed in a combined measure of political discussion. All of these differences have implications with respect to the quality and representativeness of online discussion. We still have more research to do on this topic, given the low explained variance in our models as well as those models summarized in Table 1.

Like-minded discussion may have both positive and negative impacts. Mondak (2010: 115) explains that “conversations with like-minded others may offer reassurance and support, but such conversations do nothing to broaden the person's perspectives.” Discussions with people of differing viewpoints are expected to increase political tolerance (Nir 2017) and perhaps decrease attitude polarization (Grönlund et al. 2015Mutz 2006). Personality shapes the propensity to engage in homogeneous discussion networks (Hibbing et al. 2011Kim et al. 2013Mondak et al. 2010). We have contributed to scholarship by testing the role of personality in an online discussion. Our findings suggest that like-minded discussion networks cannot be solely attributed to social media use. An individual's personality affects whether they use social media (Correa et al. 2010Jenkins-Guarnieri et al. 2012Ryan and Xenos 2011) and how they use social media. People who are introverted, close-minded, and conscientious will use social media to form discussion networks where their ideas will not be challenged. Indeed, when it comes to like-minded discussion, we find that personality matters more than political ideology.

As a final note, our data are limited to self-reports about political discussion—an issue that this field of research has addressed (Wojcieszak and Mutz 2009). We do not know if people truly abstain from political discussion, nor do we have an independently verified approach to measure the frequency of political discussion. Social media trace data would help to validate the estimates about frequency. However, social media data are limited for assessing like-minded discussion, as it is difficult to determine whether two discussion partners agree or disagree with each other's social media posts. For example, on Twitter, there is a “like” button but no “dislike” button. Facebook offers more nuances, albeit the “like” button is still the most popular response and does not suggest agreement so much as acknowledgment. Ideology is sometimes used as a proxy for this disagreement, but even ideological leanings are difficult to decipher in relation to the discussion of complex policy issues, such as immigration or the economy. Surveys are a valuable tool to supplement social media trace data as people can be asked about their agreement or disagreement with the topic. Future research should consider using a mixed-methods approach with a record of political discussion (such as social media trace data) as well as a survey of personality traits, policy positions, and reports about (dis)agreement. Our survey is an important contribution to the field, which has examined self-reports of offline discussion based on surveys or online discussion using social media trace data. We bridge these two modes but come to similar conclusions. Like-minded discussion is rare; personality, rather than ideology, predicts whether people engage in this form of political talk in online and offline modes.

Prior to proposing our research hypothesis and questions, we presented the findings of existing research. Research to date is based largely on American samples, yet international scholars have used the same theoretical claims for tests based on non-U.S. samples. Existing scholarship has not addressed whether we should expect cross-national differences in the relationship between personality and political discussion. As such, we proposed a research question, rather than a hypothesis. We find consistency in the importance of extraversion predicting like-minded discussion. Extraverts are less likely to engage in like-minded discussion. We replicate existing research about cross-national differences in political talk (Nir 2012Vaccari and Valeriani 2018), but we offer new evidence about the importance of personality and perhaps culture in political discussion.