Science through a tribal lens: A group-based account of polarization over scientific facts

Fasce, A., Adrián-Ventura, J., et al. (2023).

Group Processes & Intergroup Relations, 26(1), 3–23.

https://doi.org/10.1177/13684302211050323

Abstract

Previous research has confirmed the prominent role of group processes in the promotion and endorsement of disinformation. We report three studies on a psychological framework derived from integrated threat theory—a psychological theory which describes how perceived threat leads to group polarization and prejudice—composed of the following constructs: group belongingness, perceived threat, outgroup derogation, and intergroup anxiety. Our pilot study suggested that need to belong and intergroup anxiety predict antiscientific beliefs (pseudoscientific, paranormal, and conspiracy theories), thus justifying the general applicability of integrated threat theory. Study 1 investigates the transition from weak to strong critical thinking regarding pseudoscientific doctrines. Besides greater outgroup derogation and perceived threats among strong critical thinkers, the model does not perform well in this context. Study 2 focuses on the intergroup conflict around anthropogenic global warming, revealing the strong predictive power of the model. These results are discussed in relation to the distinctive psychological profiles of science acceptance and rejection.

From the General Discussion

Perceived Threat and the Conspiracy of Scientists

There is a wide corpus of  research highlighting the role of  group belongingness and perceived threats in conspiracy theories (Federico et al., 2018; Mashuri et al., 2016; van der Linden et al., 2020; van Prooijen, 2015). In effect, van Prooijen (2020) has developed a comprehensive inter-group threat-based model in which distressing social events stimulate conspiracism when antagonistic outgroups are salient. Believing in the existence of  secret, powerful, and evil outgroups perpetuates and exacerbates feelings of  uncertainty and existential threat (Douglas et al., 2017), so conspiracy theories tend to backfire, being a source of  threat in themselves to their own sup-porters. This situation facilitates a feedback loop that gives rise to a generalized conspiracist world-view (Imhoff  & Bruder, 2014; van der Linden et al., 2020; van Prooijen, 2020)—in fact, prior studies have found that the best predictor of belief  in one conspiracy theory is belief  in another conspiracy theory (Abalakina-Paap et al., 1999; Goertzel, 1994).

Besides its function to justify the legitimacy of  ingroup identity and values (Jolley et al., 2018), the prototypical form of  intergroup representation that lies at the root of  conspiracy theories also provides perceived epistemic justification for antiscientific conceptions of  climate change, vaccination, AIDS, and GMOs (Jolley & Douglas, 2014; Nattrass, 2013; Uscinski et al., 2017). Conspiracy theories about scientific information give rise to the kind of epistemic defense mecha-nisms that characterize self-validating belief systems (Boudry & Braeckman, 2012; Lewandowsky et al., 2015), so contrary evidence is often interpreted as evidence of  a conspiracy—for instance, conspiracy theorists typically argue that the match between the official story and the available evidence is indeed predicted by their theory, thus characterizing contradicting evidence as being, consciously or unconsciously, part of  the alleged secret plot. Accordingly, conspiracism reduces the existing dissonance between denial and expert consensus, turning contrary information into confirmatory evidence (Lewandowsky et al., 2018).

A pdf of the research is here.

The role of attention in decision-making under risk in gambling disorder: an eye-tracking study

Hoven, M., Hirmas, A., Engelmann, J. B., 

& van Holst, R. (2022, June 30).

https://doi.org/10.31234/osf.io/fxd3m

Abstract

Gambling disorder (GD) is a behavioural addiction characterized by impairments in decision-making, favouring risk- and reward-prone choices. One explanatory factor for this behaviour is a deviation in attentional processes, as increasing evidence indicates that GD patients show an attentional bias toward gambling stimuli. However, previous attentional studies have not directly investigated attention during risky decision-making. 25 patients with GD and 27 healthy matched controls (HC) completed a mixed gambles task combined with eye-tracking to investigate attentional biases for potential gains versus losses during decision-making under risk. Results indicate that compared to HC, GD patients gambled more and were less loss averse. GD patients did not show a direct attentional bias towards gains (or relative to losses). Using a recent (neuro)economics model that considers average attention and trial-wise deviations in average attention, we conducted fine-grained exploratory analyses of the attentional data. Results indicate that the average attention in GD patients moderated the effect of gain value on gambling choices, whereas this was not the case for HC. GD patients with high average attention for gains started gambling at less high gain values. A similar trend-level effect was found for losses, where GD patients with high average attention for losses stopped gambling with lower loss values. This study gives more insight into how attentional processes in GD play a role in gambling behaviour, which could have implications for the development of future treatments focusing on attentional training or for the development of interventions that increase the salience of losses.

From the Discussion section

We extend the current literature by investigating the role of attention in risky decision-making using eye-tracking, which has been underexplored in GD thus far. Consistent with previous studies in HCs, subjects’ overall relative attention toward gains decreased in favor of attention toward losses when  loss  values  increased.  We  did not find group differences in attention to either  gains or losses, suggesting no direct attentional biases in GD. However, while HCs increased their attention to gains with higher gain values, patients with GD did not. Moreover, while patients with GD displayed lower loss aversion, they did not show less attention to losses, rather, in both groups, increased trial-by-trial attention to losses resulted in less gambling.

The question arises whether attention modulates the effect of gains and losses on choice behavior differently in GD relative to controls. Our exploratory analyses that differentiated between two different channels of attention indeed indicated that the effect of gain value on gambling choices was modulated by the amount of average attention on gains in GD only. In other words, patients with GD who focused more on gains exhibited a greater gambling propensity at relatively low gain values. Notably, the strength of the effect of gain value on choice only significantly differed at average and high levels of attention to gains between groups, while patients with GD and HCs with relatively low levels of average attention to gains did not differ. Moreover, patients with GD who had relatively more average attention to losses showed a reduction in gambling propensity at relatively lower loss values, but note that this was at trend level.  Since  average  attention  relates  to  goal-directed or top-down attention, this measure likely reflects one’s preferences and beliefs.  Hence,  the  current  results suggest  that  gambling  choices  in  patients  with GD, relative to HCs are more  influenced by their preferences for gains. Future studies are needed to verify if and how top-down attentional processes affect decision-making in GD.

The research is here.

Editor's note: Apparently, GD focusing primarily on gains continue to gamble.  GD and HC who focus on losses are more likely to stop.  Therefore, psychologists treating people with impulse control difficulties may want to help patient's focus on potential losses/harm, as opposed to imagined gains.

Black Bioethics in the Age of Black Lives Matter

Ray, K., Fletcher, F.E., Martschenko, D.O. et al. 

J Med Humanit (2023).

https://doi.org/10.1007/s10912-023-09783-4

Here are two excerpts:

Lessons Black Bioethics can take from BLM

BLM showed that telling Black people’s stories or giving them a space to tell their own stories is viewed as an inherently political act simply because Black people’s existence is viewed as political. At the same time, it taught us that we absolutely must take on this task because, if we do not tell our stories, other people will tell them for us and use our stories to deny us our rightful moral status and all the rights it entitles us.

BLM let Black people’s stories fuel its social justice initiatives. It used stories to put Black people at the forefront of protests and social inclusion efforts to show the extent to which Black people had been excluded from our collective social consciousness. Stories allowed us to see the total impact of anti-Black racism and the ways it infiltrates all parts of Black life. And for those who were far removed from the experience of being Black, BLM used stories to make us care about racial injustice and be so moved that we were unable to turn our backs on Black people’s suffering. In this way, stories are an act of rebellion, a way to force people to reckon with BLM’s demands that Black people ought to be treated like the full and complex human beings we are.

Black Bioethics is also a rebellion. It is a rebellion against the status quo in bioethics—a rebellion against Black people’s lives being an afterthought, particularly in issues of justice. Stories aid in this rebellion. Just as stories helped BLM show the full range of Black people’s humanity and the ways that individuals and institutions deny Black people that humanity, stories help Black Bioethics demonstrate just how our institutions contribute to Black people’s poor health and prevent them from living full lives. In Black Bioethics, stories can create the same emotional stirring that they did for BLM supporters since they share many of the same challenges and goals. And just as it would be imprudent to underestimate the role of stories in social justice, it would be imprudent of us to underestimate what stories can do for our sense of health justice for Black people.

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Toward an intersectional bioethics

Bioethics is well-positioned to foster antiracism in scholarship, training, and advocacy (Danis et al. 2016). Although the field focuses on ethical issues in biomedical research and clinical care specifically, Danis et al. (2016) point out that many ethical dilemmas that impact health and well-being lie outside of healthcare settings. For instance, there are significant ethical dilemmas posed by the social determinants of health and complex disease. Social factors such as poverty, unequal access to healthcare, lack of education, stigma, and racism are underlying and contributing factors to health inequalities. These inequalities, in turn, generate the ethical dilemmas that bioethics grapples with (Danis et al. 2016). If the field genuinely values the just conduct of biomedical research and the just provision of clinical care, then it will need to draw upon intersectionality to understand and effectively analyze the many interlocking complexities in our world and in human experiences. Social activist movements like BLM and their use of intersectionality offer several lessons to those in the field working to secure justice in biomedicine, clinical care, and society.

First, as an analytic tool, intersectionality recognizes and understands that different social forces conjoin to produce and maintain privilege and marginalization. Therefore, intersectionality clarifies instances in which real lives and experiences are being erased. Bioethics cannot afford to “neglect entire ways of being in the world,” though it has and continues to do so (Wallace 2022, S79). Social activist movements like BLM are drawing attention to ways of being that are unjust yet largely ignored by mainstream hegemonic interests. For instance, BLM directly acknowledges within its movement “those who have been marginalized within [other] Black liberation movements” (Black Lives Matter n.d.). Using intersectionality, BLM heightens awareness of the ways in which Black queer and trans individuals, undocumented individuals, and people with disabilities have different experiences with White supremacy and advance colonialism. In doing so, it centers rather than erases real lives and experiences. Learning from this movement, bioethical scholarship grounded in the principle of justice will need to find ways to center the experiences of Black-identifying individuals without treating the Black community as a homogenous entity.

The info is here.

Rational learners and parochial norms

Partington, S. Nichols, S., & Kushnir, T.

Cognition

Volume 233, April 2023, 105366

Abstract

Parochial norms are narrow in social scope, meaning they apply to certain groups but not to others. Accounts of norm acquisition typically invoke tribal biases: from an early age, people assume a group's behavioral regularities are prescribed and bounded by mere group membership. However, another possibility is rational learning: given the available evidence, people infer the social scope of norms in statistically appropriate ways. With this paper, we introduce a rational learning account of parochial norm acquisition and test a unique prediction that it makes. In one study with adults (N = 480) and one study with children ages 5- to 8-years-old (N = 120), participants viewed violations of a novel rule sampled from one of two unfamiliar social groups. We found that adults judgments of social scope – whether the rule applied only to the sampled group (parochial scope), or other groups (inclusive scope) – were appropriately sensitive to the relevant features of their statistical evidence (Study 1). In children (Study 2) we found an age difference: 7- to 8-year-olds used statistical evidence to infer that norms were parochial or inclusive, whereas 5- to 6-year olds were overall inclusive regardless of statistical evidence. A Bayesian analysis shows a possible inclusivity bias: adults and children inferred inclusive rules more frequently than predicted by a naïve Bayesian model with unbiased priors. This work highlights that tribalist biases in social cognition are not necessary to explain the acquisition of parochial norms.

From the General discussion

The widespread prevalence of parochial norms across history and cultures have led some to suggest parochialism is itself a human universal (Clark et al., 2019; Greene, 2013) in part owing to evolved, group-based biases in social norm acquisition (Chalik & Rhodes, 2020; Chudek & Henrich, 2011; Roberts et al., 2017). In this paper, we investigated whether a rational learning process can also explain this phenomenon. In Study 1, we found that adults can acquire distinctions of social scope in a statistically appropriate manner, and this finding was robust across two forms of measurement (rule judgments and open response). In Study 2, older children displayed the adult-like statistical sensitivity in their rule judgments, and even younger children did so in their open responses. Computational analyses suggests that rule judgments were inclusively biased: compared to an unbiased Bayesian learner, children tended to assume that novel rules apply to everyone in a candidate population. Adults also displayed an inclusive bias, albeit to a lesser extent than children.

Broadly, these findings suggest that rational learning processes can indeed explain the acquisition of parochial norms and highlight an important sense in which children's norm learning can be biased in the opposite direction of tribalism. At the least, the finding that children and adults are inclusively biased serves as an existence proof that deep-rooted tribal biases in social learning are not necessary to explain the acquisition of parochial norms. Rather, if children and adults are rational learners, they can acquire a parochial norm when presented with evidence that is consistent with parochialism. However, tribalism can still play a role in norm acquisition, for example, by influencing the sort of evidence that adults seek out, or the evidence to which children are exposed.

The research is here.

Drowning in Debris: A Daughter Faces Her Mother’s Hoarding

Deborah Derrickson Kossmann

Psychotherapy Networker

March/April 2023

Here is an excerpt:

My job as a psychologist is to salvage things, to use the stories people tell me in therapy and help them understand themselves and others better. I make meaning out of the joy and wreckage of my own life, too. Sure, I could’ve just hired somebody to shovel all my mother’s mess into a dumpster, but I needed to be my family’s archaeologist, excavating and preserving what was beautiful and meaningful. My mother isn’t wrong to say that holding on to some things is important. Like her, I appreciate connections to the past. During the cleaning, I found photographs, jewelry passed down over generations, and my bronzed baby shoes. I treasure these things.

“Maybe I failed by not following anything the psychology books say to do with a hoarding client,” I tell my sister over the phone. “Sometimes I still feel like I wasn’t compassionate enough.”

“You handled it as best you could as her daughter,” my sister says. “You’re not her therapist.”

After six years, my mother has finally stopped saying she’s a “prisoner” at assisted living. She tells me she’s part of a “posse” of women who eat dinner together. My sister decorated her studio apartment beautifully, but the cluttering has begun again. Piles of magazines and newspapers sit in corners of her room. Sometimes, I feel the rage and despair these behaviors trigger in me. I still have nightmares where I drive to my mother’s house, open the door, and see only darkness, black and terrifying, like I’m looking into a deep cave. Then, I’m fleeing while trying to wipe feces off my arm. I wake up feeling sadness and shame, but I know it isn’t my own.

A few weeks ago, I pulled up in front of my mother’s building after taking her to the cardiologist. We turned toward each other and hugged goodbye. She opened the car door with some effort and determinedly waved off my help before grabbing the bag of books I’d brought for her.

“I can do it, Deborah,” she snapped. But after taking a few steps toward the building entrance, she turned around to look at me and smiled. “Thank you,” she said. “I really appreciate all you do for me.” She added, softly, “I know it’s a lot.”

The article is here.

The article is an important reminder that practicing psychologists cope with their own stressors, family dynamics, and unpleasant emotional experiences.  Psychologists are humans with families, value systems, emotions, beliefs, and shortcomings.

Why do we focus on trivial things? Bikeshedding explained

The Decision Lab

An Explainer

Originally posted: No idea

What is Bikeshedding?

Bikeshedding, also known as Parkinson’s law of triviality, describes our tendency to devote a disproportionate amount of our time to menial and trivial matters while leaving important matters unattended.

Where does this bias occur?

Do you ever remember sitting in class and having a teacher get off track from a lesson plan? They may have spent a large portion of your biology class time telling you a personal story and skimmed over important scientific theory. In such an instance, your teacher may have been a victim of bikeshedding, where they spent too long discussing something minor and lost track of what was important. Even though it may have been more entertaining to listen to their story, it did not help you acquire important information.

Although that scenario is one familiar to most, bikeshedding is an issue most commonly seen as a problem in corporate and consulting environments, especially during meetings. Imagine that at work, you have a meeting scheduled to discuss two important issues. The first issue is having to come up with ways in which the company can reduce carbon emissions. The second issue is discussing the implementation of standing desks at the office. It is clear that the first issue is more important, but it is also more complex. You and your coworkers will likely find it much easier to talk about whether or not to get standing desks, and as a result, a large portion of the scheduled meeting time is devoted to this more trivial matter. This disproportionate time allocation is known as bikeshedding and causes complicated matters to receive little attention.

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How to avoid it?

An awareness of bikeshedding is vital to countering its effects. There are various techniques that can be used in order to ensure that a group or team is being efficient with the time they spend on each topic.

One method to avoid bikeshedding is to have a separate meeting for any major, complex issue. If the topic is brought into a meeting with a long agenda, it can get lost under the trivial issues. However, if it is the main and only purpose for a meeting, it is difficult to avoid talking about it. Keeping meetings specific and focused on a particular issue can help counter bikeshedding.1 It may also be a good idea to have a particular person appointed to keep the team on task and pull back focus if the discussion does get sidetracked.

Another way of pulling the focus onto particular issues is to have less people present at the meeting. Bikeshedding is a big problem in group settings because simple issues entice multiple people to speak, which can drag them out. By only having the necessary people present at a meeting, even if a trivial issue is discussed, it will take up less time since there are fewer people to voice their opinion.

The explainer is here.

This bias may occur in psychotherapy when psychologist and patient focus on trivial issues that are easier to discuss or solve, rather than addressing critical, difficult issues.  There is a difference between creating a therapeutic attachment and bikeshedding.

What Happens When AI Has Read Everything?

Ross Anderson

The Atlantic

Originally posted 18 JAN 23

Here is an excerpt:

Ten trillion words is enough to encompass all of humanity’s digitized books, all of our digitized scientific papers, and much of the blogosphere. That’s not to say that GPT-4 will have read all of that material, only that doing so is well within its technical reach. You could imagine its AI successors absorbing our entire deep-time textual record across their first few months, and then topping up with a two-hour reading vacation each January, during which they could mainline every book and scientific paper published the previous year.

Just because AIs will soon be able to read all of our books doesn’t mean they can catch up on all of the text we produce. The internet’s storage capacity is of an entirely different order, and it’s a much more democratic cultural-preservation technology than book publishing. Every year, billions of people write sentences that are stockpiled in its databases, many owned by social-media platforms.

Random text scraped from the internet generally doesn’t make for good training data, with Wikipedia articles being a notable exception. But perhaps future algorithms will allow AIs to wring sense from our aggregated tweets, Instagram captions, and Facebook statuses. Even so, these low-quality sources won’t be inexhaustible. According to Villalobos, within a few decades, speed-reading AIs will be powerful enough to ingest hundreds of trillions of words—including all those that human beings have so far stuffed into the web.

And the conclusion:

If, however, our data-gorging AIs do someday surpass human cognition, we will have to console ourselves with the fact that they are made in our image. AIs are not aliens. They are not the exotic other. They are of us, and they are from here. They have gazed upon the Earth’s landscapes. They have seen the sun setting on its oceans billions of times. They know our oldest stories. They use our names for the stars. Among the first words they learn are flow, mother, fire, and ash.

The article is here.

Intersectional implicit bias: Evidence for asymmetrically compounding bias and the predominance of target gender

Connor, P., Weeks, M., et al. (2023).

Journal of Personality and Social Psychology,

124(1), 22–48.

https://doi.org/10.1037/pspa0000314

Abstract

Little is known about implicit evaluations of complex, multiply categorizable social targets. Across five studies (N = 5,204), we investigated implicit evaluations of targets varying in race, gender, social class, and age. Overall, the largest and most consistent evaluative bias was pro-women/anti-men bias, followed by smaller but nonetheless consistent pro-upper-class/anti-lower-class biases. By contrast, we observed less consistent effects of targets’ race, no effects of targets’ age, and no consistent interactions between target-level categories. An integrative data analysis highlighted a number of moderating factors, but a stable pro-women/anti-men and pro-upper-class/anti-lower-class bias across demographic groups. Overall, these results suggest that implicit biases compound across multiple categories asymmetrically, with a dominant category (here, gender) largely driving evaluations, and ancillary categories (here, social class and race) exerting relatively smaller additional effects. We discuss potential implications of this work for understanding how implicit biases operate in real-world social settings. 

General Discussion

Implicit bias is central to the study of social cognition. Given that people are multiply categorizable, understanding the influences of such intersectionality upon implicit bias is likely to be vital for understanding its effects in everyday social contexts. In the present research, we examined implicit evaluations of multiply categorizable social targets, testing two competing theories about intersectional intergroup bias. We also developed and tested the reliability of a novel method of measuring and modelling implicit bias at the level of individual targets.

In Study 1 we observed implicit evaluations of Black and White males to be driven solely by targets' social class with bias favoring upper-class over lower-class targets. In Study 2, we measured implicit evaluations of targets varying in race, gender, social class, and age, and found results to be primarily driven by a specific positive bias favoring upper-class female targets. In Study 3, we used similarly intersectional targets, and explored the impact of portraying targets in full-body versus upper body photographs on implicit evaluations. Here, we observed effects of targets’ race, with Asian and White targets evaluated more positively than Black targets, and of targets’ social class, with upper-class targets evaluated more positively than lower-class targets (though only when targets were displayed in full-body presentation). Most striking, however, was the dominant effect of target gender, with positive/negative evaluations of female/male targets accounting for the majority of variance in implicit bias.

In Study 4 we tested the generalizability of these results by recruiting representative samples of US adults, and measuring implicit evaluations not just via ST-IATs, but also via EPTs and AMPs. Across all measures, we observed target gender to be the largest driver of implicit evaluations, though its dominance was less pronounced in EPTs and AMPs than in ST-IATs. We also again observed effects of targets’ social class and race, though the effect of race was inconsistent across tasks, with participants displaying anti-Black bias in the ST-IAT, pro-Asian bias in the EPT, and anti-White bias in the AMP. Finally, in Study 5 we conducted an integrative data analysis to test a number of potential moderating factors. Results showed that while all groups of participants displayed pro-female implicit gender bias and pro-upper-class implicit social class bias, both biases were stronger among women than men. Results also showed the effect of race varied across racial groups, with Asians displaying a preference for Asian over White and Black targets, Black participants displaying a preference for Asian and Black targets over White targets, Latinos displaying a preference for Asian over Black targets, and Whites displaying no significant racial bias.

A pdf of the research is here.

Growth of AI in mental health raises fears of its ability to run wild

Sabrina Moreno

Axios.com

Originally posted 9 MAR 23

Here's how it begins:

The rise of AI in mental health care has providers and researchers increasingly concerned over whether glitchy algorithms, privacy gaps and other perils could outweigh the technology's promise and lead to dangerous patient outcomes.

Why it matters: As the Pew Research Center recently found, there's widespread skepticism over whether using AI to diagnose and treat conditions will complicate a worsening mental health crisis.

• Mental health apps are also proliferating so quickly that regulators are hard-pressed to keep up.
• The American Psychiatric Association estimates there are more than 10,000 mental health apps circulating on app stores. Nearly all are unapproved.

What's happening: AI-enabled chatbots like Wysa and FDA-approved apps are helping ease a shortage of mental health and substance use counselors.

• The technology is being deployed to analyze patient conversations and sift through text messages to make recommendations based on what we tell doctors.
• It's also predicting opioid addiction risk, detecting mental health disorders like depression and could soon design drugs to treat opioid use disorder.

Driving the news: The fear is now concentrated around whether the technology is beginning to cross a line and make clinical decisions, and what the Food and Drug Administration is doing to prevent safety risks to patients.

• KoKo, a mental health nonprofit, recently used ChatGPT as a mental health counselor for about 4,000 people who weren't aware the answers were generated by AI, sparking criticism from ethicists.
• Other people are turning to ChatGPT as a personal therapist despite warnings from the platform saying it's not intended to be used for treatment.

The info is here.