Wednesday, March 2, 2022

In electronic interactions, on average, the public of all ethnic groups (except Blacks themselves) is less likely to respond to emails from people they believe to be Black (rather than White)

Are Americans less likely to reply to emails from Black people relative to White people? Ray Block Jr. et al. Proceedings of the National Academy of Sciences, December 20, 2021, Vol 118 (52) e2110347118.

Significance: Although previous attempts have been made to measure everyday discrimination against African Americans, these approaches have been constrained by distinct methodological challenges. We present the results from an audit or correspondence study of a large-scale, nationally representative pool of the American public. We provide evidence that in simple day-to-day interactions, such as sending and responding to emails, the public discriminates against Black people. This discrimination is present among all racial/ethnic groups (aside from among Black people) and all areas of the country. Our results provide a window into the discrimination that Black people in the United States face in day-to-day interactions with their fellow citizens.

Abstract: In this article, we present the results from a large-scale field experiment designed to measure racial discrimination among the American public. We conducted an audit study on the general public—sending correspondence to 250,000 citizens randomly drawn from public voter registration lists. Our within-subjects experimental design tested the public’s responsiveness to electronically delivered requests to volunteer their time to help with completing a simple task—taking a survey. We randomized whether the request came from either an ostensibly Black or an ostensibly White sender. We provide evidence that in electronic interactions, on average, the public is less likely to respond to emails from people they believe to be Black (rather than White). Our results give us a snapshot of a subtle form of racial bias that is systemic in the United States. What we term everyday or “paper cut” discrimination is exhibited by all racial/ethnic subgroups—outside of Black people themselves—and is present in all geographic regions in the United States. We benchmark paper cut discrimination among the public to estimates of discrimination among various groups of social elites. We show that discrimination among the public occurs more frequently than discrimination observed among elected officials and discrimination in higher education and the medical sector but simultaneously, less frequently than discrimination in housing and employment contexts. Our results provide a window into the discrimination that Black people in the United States face in day-to-day interactions with their fellow citizens.

People were better at detecting Twitter bots when they came from the opposite political camp, while greater experience with social media had a detrimental effect on the hit rate

Duped by Bots: Why Some are Better than Others at Detecting Fake Social Media Personas. Ryan Kenny et al. Human Factors: The Journal of the Human Factors and Ergonomics Society, February 24, 2022.


Objective: We examine individuals’ ability to detect social bots among Twitter personas, along with participant and persona features associated with that ability.

Background: Social media users need to distinguish bots from human users. We develop and demonstrate a methodology for assessing those abilities, with a simulated social media task.

Method: We analyze performance from a signal detection theory perspective, using a task that asked lay participants whether each of 50 Twitter personas was a human or social bot. We used the agreement of two machine learning models to estimate the probability of each persona being a bot. We estimated the probability of participants indicating that a persona was a bot with a generalized linear mixed-effects model using participant characteristics (social media experience, analytical reasoning, and political views) and stimulus characteristics (bot indicator score and political tone) as regressors.

Results: On average, participants had modest sensitivity (d’) and a criterion that favored responding “human.” Exploratory analyses found greater sensitivity for participants (a) with less self-reported social media experience, (b) greater analytical reasoning ability, and (c) who were evaluating personas with opposing political views. Some patterns varied with participants' political identity.

Conclusions: Individuals have limited ability to detect social bots, with greater aversion to mistaking bots for humans than vice versa. Greater social media experience and myside bias appeared to reduce performance, as did less analytical reasoning ability.

Application: These patterns suggest the need for interventions, especially when users feel most familiar with social media.

Keywords: signal detection theory, social bots, social media, analytical reasoning, myside bias

Storytelling is inter alia an entertainment technology used as recruitment tool: Allows to attract and potentially cooperate with those that matter to the story creator by signaling one’s qualities & enhancing one's reputation as a cooperative partner

Why and How Did Narrative Fictions Evolve? Fictions as Entertainment Technologies. Edgar Dubourg and Nicolas Baumard. Front. Psychol., March 1 2022.

Abstract: Narrative fictions have surely become the single most widespread source of entertainment in the world. In their free time, humans read novels and comics, watch movies and TV series, and play video games: they consume stories that they know to be false. Such behaviors are expanding at lightning speed in modern societies. Yet, the question of the origin of fictions has been an evolutionary puzzle for decades: Are fictions biological adaptations, or the by-products of cognitive mechanisms that evolved for another purpose? The absence of any consensus in cognitive science has made it difficult to explain how narrative fictions evolve culturally. We argue that current conflicting hypotheses are partly wrong, and partly right: narrative fictions are by-products of the human mind, because they obviously co-opt some pre-existing cognitive preferences and mechanisms, such as our interest for social information, and our abilities to do mindreading and to imagine counterfactuals. But humans reap some fitness benefits from producing and consuming such appealing cultural items, making fictions adaptive. To reconcile these two views, we put forward the hypothesis that narrative fictions are best seen as entertainment technologies that is, as items crafted by some people for the proximate goal to grab the attention of other people, and with the ultimate goal to fulfill other evolutionary-relevant functions that become easier once other people’s attention is caught. This hypothesis explains why fictions are filled with exaggerated and entertaining stimuli, why they fit so well the changing preferences of the audience they target, and why producers constantly make their fictions more attractive as time goes by, in a cumulative manner.

See also Why imaginary worlds? Exploratory preferences explain the cultural success of fictions with imaginary worlds in modern societies. Edgar Dubourg. Human Behavior & Evolution Society HBES 2021, Jun-Jul 2021.


A Specific Kind of Technologies: Entertainment Technologies

The Centrality of Entertainment in Fictions

Literary theorists and historians have long noticed the cross-culturally recurrent and entertaining features of fictions (which have also been called “themes,” “tropes,” or “patterns”) such as adventures, conflicts, love stories, imaginary worlds, monsters, gossip, authority, success, and the search of social status (Kato and Saunders, 1985, p. 232; Pavel, 1986, pp. 147–148; Campbell, 1993Schaeffer, 1999, p. 241; Huang, 2001, pp. 60–61; Hogan, 2003Booker, 2004). Evolutionary critics in the humanities and evolutionary social scientists brought evidence that such universal fictional features are influenced by the evolutionary history of the human mind (Carroll, 1995Gottschall, 2008Fisher and Salmon, 2012Saad, 2012Grodal, 2017). More recently, as we have seen in section The By-product Hypothesis (and the Problem of Fitness Benefits), these cross-cultural features have been linked to specific cognitive preferences (Table 1). In all, there seems to be a large and interdisciplinary consensus to say that narrative fictions include attractive and entertaining features. The question therefore is: Why are such features attractive and entertaining to the human mind?

We contend that such pleasurable features of fictions are very close to what evolutionary biologists called superstimuli (Tinbergen, 1969Barrett, 2010). Many studies show that some species, in the course of their evolutionary history, recycled pre-existing attractive traits for new evolutionary relevant functions such as attracting mates (Lorenz, 1966Krebs and Dawkins, 1978Basolo, 1990Ryan et al., 1990). For instance, because the female frog Physalaemus pustulosus had developed preferences for lower-frequency chuck sounds, males evolved the ability to produce such sounds to tap into this sensory preference (Ryan et al., 1990).

In nonhuman animals, this recycling of preexisting preferences usually emerges through biological selection. In humans, it can emerge through cultural evolution: producers use their expertise to target and refine stimuli that are already appealing to consumers (Lightner et al., 2022), so as to fulfill fitness relevant goals (Singh, 2020). We will explain what these goals are in the next sub-section.

We therefore argue that content features in fictions are superstimuli: they are crafted to resemble stimuli that were already appealing to the human mind, because of the natural selection of attention-orienting cognitive mechanisms, and of the pleasure systems rewarding the behavior of paying attention to such stimuli. This is a form of what psychologists have called “content-based attraction,” when the attraction and prevalence of a cultural item is favored by its content (Sperber, 1996Claidière and Sperber, 2007Scott-Phillips et al., 2018).

A question follows: Why are such stimuli attention-grabbing in the first place (in the real world)? This is where we fall back on the by-product hypothesis: such preferences for some stimuli (e.g., social information) evolved because humans endowed with them survived and reproduced better in the ancestral environments when the human cognition evolved.

In evolutionary and cognitive approaches to fictional content, superstimuli have already been studied in fictional texts (Jobling, 2001Nettle, 2005a,bSingh, 2019), in movies (Cutting et al., 2011Andrews, 2012Clasen, 2012Cutting, 20162021Sobchuk and Tinits, 2020), in video games (Jansz and Tanis, 2007Mendenhall et al., 2010), in artistic representations (Verpooten and Nelissen, 20102012), and in cross-media approaches to fiction (Grodal, 2010Barrett, 2016Dubourg and Baumard, 2021). Let us note that such fictional superstimuli can be narrative superstimuli (e.g., how Marcel in Search of Lost Time reaches prestige), visual superstimuli (e.g., the form of Mickey), auditory superstimuli (e.g., the terrifying sounds in horror films), and other sensory superstimuli (e.g., the sense of control in open-world video games or in virtual reality games). Producers of fictions use any means available to them to make the most attention-grabbing superstimuli and therefore the most entertaining fictions.

Of course, the pleasure-inducing effect elicited by superstimuli in fictions is also elicited by some other cultural behavior and products, such as sport and news (Barrett, 20102016). This is because the fiction industry is not the only one to target entertainment. However, the presence of superstimuli successfully isolate fiction from non-fiction, because superstimuli are never included in non-fictional narratives: the obligation to (try to) stick to real facts prevent, to a large extent, producers of non-fictional narratives to invent and exaggerate any feature (or else their epistemic reputation might suffer, and the benefits of attracting other people’s attention would be overweighted by the reputational costs of having deceived their audience). We contend that such a distinction is intuitive to consumers: they will continue to consume and positively evaluate fictions that they take pleasure from, while they will either stop consuming or negatively evaluate fictions that deceive the expectation to be entertained. Conversely, when they consume non-fictional narratives, such as a philosophical treatise, a political essay, or an history documentary, their primary goal is to learn things, so that they will not stop consuming the non-fiction if they are not entertained, and they will not base their evaluation on this criterion.

The Fitness Consequences of Entertainment Technologies

Why would producing fictions be adaptive? With the entertainment hypothesis, this question is the same as the following one: Why would attracting the attention of other people by inventing entertaining cultural items should bring any fitness benefit? We propose that, because they are highly attractive and entertaining, fictions can be used to fulfill any evolutionary relevant goal that needs others’ attention to be caught, be it signaling one’s values to potential mates (Miller, 2001) or cooperative partners (Bourdieu, 2010André et al., 2020André and Baumard, 2020Dubourg et al., 2021bLightner et al., 2022), transmitting knowledge (Schniter et al., 2018Nakawake and Sato, 2019Sugiyama, 2021b), communicating social norms (Mar and Oatley, 2008Ferrara et al., 2019), or selling products (Saad and Gill, 2000Saad, 2012).

Consistently, narrative fictions seem to have been used (1) as recruitment technologies: they allow the producers of fictions to attract and potentially cooperate with individuals that matter to them, by signaling one’s qualities (e.g., their competence, their moral sense, and their intelligence) and therefore enhancing one’s reputation as a cooperative partner (Sperber and Baumard, 2012). For instance, in many countries at most time in history, cultural institutions and organizations aimed at spotlighting the producers of fictions, from the poetry contests (uta-awase) in Japan from the Heian period to the modern Nobel Prize in Literature and movie Academy Awards. Narrative fictions are also obviously used to (2) derive economic or material gains. This is clearly pictured in the form fiction production and fiction consumption took in large-scale societies, that of a massive (and highly lucrative) contract-based market.

Crucially, such adaptive goals need not be conscious or deliberate. They need not be the only motivations either: drawing on adaptive hypotheses that we reviewed in section State of the Current Hypotheses, producers of fictions can have other goals, such as transmitting knowledge (Sugiyama, 2021a). The association between both motivations of educating and entertaining people has produced a new form of cultural devices called “Edutainment” (Singhal, 2004Anikina and Yakimenko, 2015), which we argue has emerged far back in human cultural history, embedding not only recent fictions (e.g., Dora the Explorer), but also ancient folktales (Sugiyama, 2021b) and other literary forms such as pre-17th century European fairy tales.

According to this hypothesis, narrative fictions are sustained because they confer fitness benefits to the consumers too. First, let us note that the opportunity costs of fiction consumption seem rather low because people do not seem to consume fictions at the expense of other more “evolutionary relevant” activities such as sleeping, eating, and parenting. On the other hand, consumers can use fictions they liked to signal their skills (Veblen, 1899Bourdieu, 1979Lizardo, 20062013). They can also use more culturally successful fictions they liked to signal their personality traits (Dubourg et al., 2021a), or to share cultural focal points for social coordination (Dubourg et al., 2021b,c). Besides, human minds have evolved specialized cognitive mechanisms to detect and use social markers for coordination (Nettle and Dunbar, 1997Boyer, 2018). We propose that preferences for fictions have become relatively important markers in the ecology of modern cultural diversity, because of their signaling potential.

Summary of the Hypothesis

In all, we propose that humans did not specifically evolve the capacity to tell fictional stories, but they rather produce fictions thanks to a range of other adaptations (e.g., language, the capacity to simulate, Theory of Mind, and communicative inferences; Zunshine, 2006Mellmann, 2012Wilson, 2018). Yet, we do not consider fictions as “by-products,” because they clearly confer fitness benefits to the producers (André et al., 2020). We argue that fictions are “entertainment technologies” (Dubourg and Baumard, 2021): they are crafted by storytellers to artificially attract the attention of other people and then fulfill evolutionary-relevant goals (Singh, 2020). Obviously, fictions are not the only example of entertainment technologies. Sport, TV shows (Barrett, 20102016), music (Dubourg et al., 2021a), and performing arts (Verpooten and Nelissen, 20102012) are also entertainment technologies in the sense that they are created to trigger people’s attention, and are consumed because they exaggerate the features of phenomena (e.g., human voice and interindividual competition) that humans evolved to be interested in.

The election of a new non-Democratic school board member causes home values in their neighborhood to rise about 4pct on average relative to those of losing Democratic candidates

Self-Interest in Public Service: Evidence from School Board Elections. Stephen B. Billings, Hugh Macartney, Geunyong Park & John D. Singleton. NBER Working Paper 29791. Feb 2022. DOI 10.3386/w29791

Abstract: In this paper, we show that the election of a new school board member causes home values in their neighborhood to rise. This increase is identified using narrowly-decided contests and is driven by non-Democratic members, whose neighborhoods appreciate about 4% on average relative to those of losing candidates. We find that student test scores in the neighborhood public schools of non-Democratic winners also relatively increase, but this effect is driven by changing student composition, including via the manipulation of attendance zones, rather than improvements in school quality (as measured by test score value-added). Notably, we detect no differential changes when comparing neighborhood or scholastic outcomes between winning and losing Democratic school board candidates. These results suggest that partisan affiliation is correlated with private motivations for seeking public office.

Rolf Degen summaring... Although "nice" personality traits are beneficial in many areas of life, there is no correlation with physical health or career success

Agreeableness and Its Consequences: A Quantitative Review of Meta-Analytic Findings. Michael P. Wilmot, Deniz S. Ones. Personality and Social Psychology Review, February 28, 2022.

Abstract: Agreeableness impacts people and real-world outcomes. In the most comprehensive quantitative review to date, we summarize results from 142 meta-analyses reporting effects for 275 variables, which represent N > 1.9 million participants from k > 3,900 studies. Arranging variables by their content and type, we use an organizational framework of 16 conceptual categories that presents a detailed account of Agreeableness’ external relations. Overall, the trait has effects in a desirable direction for 93% of variables (grand mean ˉρM=.16). We also review lower order trait evidence for 42 variables from 20 meta-analyses. Using these empirical findings, in tandem with existing theory, we synthesize eight general themes that describe Agreeableness’ characteristic functioning across variables: self-transcendence, contentment, relational investment, teamworking, work investment, lower results emphasis, social norm orientation, and social integration. We conclude by discussing potential boundary conditions of findings, contributions and limitations of our review, and future research directions.

Keywords: agreeableness, personality, meta-analysis, second-order meta-analysis, consequences, Big Five, HEXACO

It’s complicated: People emotionally tied to robots can undermine relationships with co-workers

Subgroup formation in human–robot teams: A multi-study mixed-method approach with implications for theory and practice. Sangseok You,Lionel P. Robert. Journal of the Association for Information Science and Technology, February 10 2022.

Abstract: Human–robot teams represent a challenging work application of artificial intelligence (AI). Building strong emotional bonds with robots is one solution to promoting teamwork in such teams, but does this come at a cost in the form of subgroups? Subgroups—smaller divisions within teams—in all human teams can undermine teamwork. Despite the importance of this question, it has received little attention. We employed a mixed-methods approach by conducting a lab experiment and a qualitative online survey. We (a) examined the formation and impact of subgroups in human–robot teams and (b) obtained insights from workers currently adapting to robots in the workplace on mitigating impacts of subgroups. The experimental study (Study 1) with 44 human–robot teams found that robot identification (RID) and team identification (TID) are associated with increases and decreases in the likelihood of a subgroup formation, respectively. RID and TID moderated the impacts of subgroups on teamwork quality and subsequent performance in human–robot teams. Study 2 was a qualitative study with 112 managers and employees who worked collaboratively with robots. We derived practical insights from this study that help situate and translate what was learned in Study 1 into actual work practices.


Work teams relying on AI-enabled technology such as robots will increase along with efforts to design them to elicit strong emotional bonds from humans (Vreede & Briggs, 2019). Our results underline the need for a more cautious and considerate approach when attempting to elicit such responses. Next, we discuss implications for theory and work.

6.1 Theoretical implications

Our findings have several implications for theory and research. First, Study 1 highlighted the overall need to extend theories of subgroup formation to include AI-enabled technologies. Study 1 found evidence of subgroup formation in human–robot teams and its negative impacts. Previous research demonstrated that strong bonds with technology could benefit individuals (K.-K. Kim et al., 2010; Read et al., 2011). Our work goes beyond this by demonstrating whether and when such strong bonds can be problematic. In doing so, we highlight the need for greater theoretical attention. There is a vast body of research on subgroup formation, and it is not clear how much of it is directly applicable to human–robot teams.

Second, Study 1's findings contribute to the existing theories on subgroups. We found that subgroups positively impact teamwork quality when robot identification is low, but these subgroups become problematic when robot identification is high. However, subgroup formation led to increased teamwork quality when TID was high. Our findings identified the particular mechanisms that can help dictate when subgroups are likely to increase/decrease teamwork quality. These findings answer recent calls to identify moderators that constrain the impacts of subgroups (Meyer et al., 2015; Thatcher & Patel, 2012).

6.2 Work practice implications

First, it is clear that the inclusion of robots can lead to subgroups. The surveyed workers had either already seen evidence of subgroups in human–robot work collaborations or were genuinely afraid they would see them. To address these concerns, many of the workers suggested ways to promote communication, training, and team-building that could all be labeled as approaches to promote TID. This seems to align with our findings from Study 1 regarding the importance of TID in reducing the negative impacts of subgroups. Study 2 goes beyond Study 1 by situating and translating the TID construct to changes in actual work practices.

Second, it was interesting that workers' comments were primarily directed at promoting human relationships rather than reducing human-to-robot bonds. It is possible that the workers' suggestions relating to the promotion of TID could be viewed as ways to reduce RID, but this was not directly suggested by workers. Instead, workers might actually see the value of strong RID and not want to undermine it but instead were more concerned with promoting TID through stronger human bonds. If so, this finding aligns well with Study 1's finding that RID can actually have a positive impact as long as it is coupled with strong TID.

Third, there was an emphasis on leadership in addressing issues associated with subgroups. On the one hand, workers thought that strong leadership was needed to help workers understand the value of robots while promoting strong bonds among human coworkers. On the other hand, managers indicated that strong leadership was needed to determine who should be assigned what tasks. That being said, the importance of leadership in human–robot teams is a relatively unexplored area. Despite this, Study 2's findings seem to imply that human–robot team scholars need to broaden their research agenda to include leadership.

Finally, it seems that as AI and the world of work are reshaping the meaning of work, employees would rather not lose what it means to be a human. More specifically, workers indicated the need to emphasize human contributions as distinct and separate from robot contributions. They also thought it was important to draw clear lines between robots and humans and to remind their coworkers of these distinctions. In doing so, workers latently suggested that organizations must highlight the uniqueness of being a human and instill this value through training, communication, and evaluation. To this point, our results have broader implications for our understanding of how AI reshapes the world of work.

6.3 Limitations and future research

The study has several limitations. This study employed one method to measure subgroup formation among other possible approaches. We used cohesion between humans and robots to measure subgroups because this aligns with the paper's definition of subgroups. However, previous research has employed many different subgroup measures (Polzer et al., 2006; Thatcher & Patel, 2012). Future research could investigate different measures. Second, while the experimental study found evidence of subgroups, the brief interaction is a limitation. Future research could examine how emotional bonds evolve over time (Björling et al., 2020). Third, robots used in Study 1 were not fully autonomous, representing many of the robots used in workplaces today (i.e., cobots). Future studies could vary the robot's autonomy to determine its importance in understanding subgroup formation and its impacts. Finally, our experimental study was designed to ensure internal validity at the expense of external validity. Future studies should examine the phenomena in field settings to qualitatively unpack the bonding process over time.