What do you believe? Atheism and Religion

Kristen Weir

Monitor on Psychology

Vol. 51, No. 5, p. 52

Here is an excerpt:

Good health isn’t the only positive outcome attributed to religion. Research also suggests that religious belief is linked to prosocial behaviors such as volunteering and donating to charity.

But as with health benefits, Galen’s work suggests such prosocial benefits have more to do with general group membership than with religious belief or belonging to a specific religious group (Social Indicators Research, Vol. 122, No. 2, 2015). In fact, he says, while religious people are more likely to volunteer or give to charitable causes related to their beliefs, atheists appear to be more generous to a wider range of causes and dissimilar groups.

Nevertheless, atheists and other nonbelievers still face considerable stigma, and are often perceived as less moral than their religious counterparts. In a study across 13 countries, Gervais and colleagues found that people in most countries intuitively believed that extreme moral violations (such as murder and mutilation) were more likely to be committed by atheists than by religious believers. This anti-atheist prejudice also held true among people who identified as atheists, suggesting that religious culture exerts a powerful influence on moral judgments, even among non­believers (Nature Human Behaviour, Vol. 1, Article 0151, 2017).

Yet nonreligious people are similar to religious people in a number of ways. In the Understanding Unbelief project, Farias and colleagues found that across all six countries they studied, both believers and nonbelievers cited family and freedom as the most important values in their own lives and in the world more broadly. The team also found evidence to counter a common assumption that atheists believe life has no purpose. They found the belief that the universe is “ultimately meaningless” was a minority view among non­believers in each country.

“People assume that [non­believers] have very different sets of values and ideas about the world, but it looks like they probably don’t,” Farias says.

For the nonreligious, however, meaning may be more likely to come from within than from above. Again drawing on data from the General Social Survey, Speed and colleagues found that in the United States, atheists and the religiously unaffiliated were no more likely to believe that life is meaningless than were people who were religious or raised with a religious affiliation. 

Model-based decision making and model-free learning

Drummond, N. & Niv, Y.

Current Biology

Volume 30, Issue 15, 3 August 2020, 

Pages R860-R865

Summary

Free will is anything but free. With it comes the onus of choice: not only what to do, but which inner voice to listen to — our ‘automatic’ response system, which some consider ‘impulsive’ or ‘irrational’, or our supposedly more rational deliberative one. Rather than a devil and angel sitting on our shoulders, research suggests that we have two decision-making systems residing in the brain, in our basal ganglia. Neither system is the devil and neither is irrational. They both have our best interests at heart and aim to suggest the best course of action calculated through rational algorithms. However, the algorithms they use are qualitatively different and do not always agree on which action is optimal. The rivalry between habitual, fast action and deliberative, purposeful action is an ongoing one.

The info is here.

Beliefs have a social purpose. Does this explain delusions?

Anna Greenburgh

psyche.co

Originally published 

Here is an excerpt:

Of course, just because a delusion has logical roots doesn’t mean it’s helpful for the person once it takes hold. Indeed, this is why delusions are an important clinical issue. Delusions are often conceptualised as sitting at the extreme end of a continuum of belief, but how can they be distinguished from other beliefs? If not irrationality, then what demarcates a delusion?

Delusions are fixed, unchanging in the face of contrary evidence, and not shared by the person’s peers. In light of the social function of beliefs, these preconditions have added significance. The coalitional model underlines that beliefs arising from adaptive cognitive processes should show some sensitivity to social context and enable successful social coordination. Delusions lack this social function and adaptability. Clinical psychologists have documented the fixity of delusional beliefs: they are more resistant to change than other types of belief, and are intensely preoccupying, regardless of the social context or interpersonal consequences. In both ‘The Yellow Wallpaper’ and the novel Don Quixote (1605-15) by Miguel de Cervantes, the protagonists’ beliefs about their surroundings are unchangeable and, if anything, become increasingly intense and disruptive. It is this inflexibility to social context, once they take hold, that sets delusions apart from other beliefs.

Across the field of mental health, research showing the importance of the social environment has spurred a great shift in the way that clinicians interact with patients. For example, research exposing the link between trauma and psychosis has resulted in more compassionate, person-centred approaches. The coalitional model of delusions can now contribute to this movement. It opens up promising new avenues of research, which integrate our fundamental social nature and the social function of belief formation. It can also deepen how people experiencing delusions are understood – instead of contributing to stigma by dismissing delusions as irrational, it considers the social conditions that gave rise to such intensely distressing beliefs.

The info is here.

New Texas rule lets social workers turn away clients who are LGBTQ or have a disability

Edgar Walters

Texas Tribune

Originally posted 14 Oct 2020

Texas social workers are criticizing a state regulatory board’s decision this week to remove protections for LGBTQ clients and clients with disabilities who seek social work services.

The Texas State Board of Social Work Examiners voted unanimously Monday to change a section of its code of conduct that establishes when a social worker may refuse to serve someone. The code will no longer prohibit social workers from turning away clients on the basis of disability, sexual orientation or gender identity.

Gov. Greg Abbott’s office recommended the change, board members said, because the code’s nondiscrimination protections went beyond protections laid out in the state law that governs how and when the state may discipline social workers.

“It’s not surprising that a board would align its rules with statutes passed by the Legislature,” said Abbott spokesperson Renae Eze. A state law passed last year gave the governor’s office more control over rules governing state-licensed professions.

The nondiscrimination policy change drew immediate criticism from a professional association. Will Francis, executive director of the Texas chapter of the National Association of Social Workers, called it “incredibly disheartening.”

He also criticized board members for removing the nondiscrimination protections without input from the social workers they license and oversee.

The info is here.

Note: All psychotherapy services are founded on the principle of beneficence: the desire to help others and do right by them.  This decision from the Texas State Board of Social Work Examiners is terrifyingly unethical.  The unanimous decision demonstrates the highest levels of incompetence and bigotry.

When eliminating bias isn’t fair: Algorithmic reductionism and procedural justice in human resource decisions

Newman, D., Fast, N. and Harmon, D.

Organizational Behavior and 

Human Decision Processes

Volume 160, September 2020, Pages 149-167

Abstract

The perceived fairness of decision-making procedures is a key concern for organizations, particularly when evaluating employees and determining personnel outcomes. Algorithms have created opportunities for increasing fairness by overcoming biases commonly displayed by human decision makers. However, while HR algorithms may remove human bias in decision making, we argue that those being evaluated may perceive the process as reductionistic, leading them to think that certain qualitative information or contextualization is not being taken into account. We argue that this can undermine their beliefs about the procedural fairness of using HR algorithms to evaluate performance by promoting the assumption that decisions made by algorithms are based on less accurate information than identical decisions made by humans. Results from four laboratory experiments (N = 798) and a large-scale randomized experiment in an organizational setting (N = 1654) confirm this hypothesis. Theoretical and practical implications for organizations using algorithms and data analytics are discussed.

Highlights

• Algorithmic decisions are perceived as less fair than identical decisions by humans.

• Perceptions of reductionism mediate the adverse effect of algorithms on fairness.

• Algorithmic reductionism comes in two forms: quantification and decontextualization.

• Employees voice lower organizational commitment when evaluated by algorithms.

• Perceptions of unfairness mediate the adverse effect of algorithms on commitment.

Conclusion

Perceived unfairness notwithstanding, algorithms continue to gain increasing influence in human affairs, not only in organizational settings but throughout our social and personal lives. How this influence plays out against our sense of fairness remains to be seen but should undoubtedly be of central interest to justice scholars in the years ahead.  Will the compilers of analytics and writers of algorithms adapt their

methods to comport with intuitive notions of morality? Or will our understanding of fairness adjust to the changing times, becoming inured to dehumanization in an ever more impersonal world? Questions

such as these will be asked more and more frequently as technology reshapes modes of interaction and organization that have held sway for generations. We have sought to contribute answers to these questions,

and we hope that our work will encourage others to continue studying these and related topics.

The research is here.

Active shooter drills may do more harm than good, study shows

Katie Camero
Miami Herald

Originally posted 3 September 20

Here is an except:

The research team discovered that social media posts alone displayed a 42% increase in anxiety and stress from the 90 days before active shooter drills to the 90 days after them. The frequent use of words such as “afraid, struggling and nervous” served as evidence, according to the report.

Signs of depression increased by 39% based on posts that featured the words “therapy, cope, irritability and suicidal” following drill events. Concerns about friends grew by 33%, concerns about social situations rose by 14% and concerns about work soared by 108%, the researchers found.

“I can tell you personally, just as an educator, we were not okay [after drills]. We were in bathrooms crying, shaking, not sleeping for months. The consensus from my friends and peers is that we are not okay,” one anonymous K-12 teacher wrote on social media, according to the report.

Worries over health also jumped by 23% while fears about death rose by 22%. “The analysis revealed words like blood, pain, clinics, and pills came up with jarring frequency, suggesting that drills may have a direct impact on participants’ physical health or, at the very least, made it a persistent topic of concern,” the researchers wrote.

An anonymous parent tweeted, “my kindergartener was stuck in the bathroom, alone, during a drill and spent a year in therapy for extreme anxiety. in a new school even, she still has to use the bathroom in the nurses office because she has ptsd from that event.”

The info is here.

‘Disorders of consciousness’: Understanding ‘self’ might be the greatest scientific challenge of our time

Joel Frohlich

Genetic Literacy report

Originally published 18 Sept 20

Here are two excerpts:

Just as life stumped biologists 100 years ago, consciousness stumps neuroscientists today. It’s far from obvious why some brain regions are essential for consciousness and others are not. So Tononi’s approach instead considers the essential features of a conscious experience. When we have an experience, what defines it? First, each conscious experience is specific. Your experience of the colour blue is what it is, in part, because blue is not yellow. If you had never seen any colour other than blue, you would most likely have no concept or experience of colour. Likewise, if all food tasted exactly the same, taste experiences would have no meaning, and vanish. This requirement that each conscious experience must be specific is known as differentiation.

But, at the same time, consciousness is integrated. This means that, although objects in consciousness have different qualities, we never experience each quality separately. When you see a basketball whiz towards you, its colour, shape and motion are bound together into a coherent whole. During a game, you’re never aware of the ball’s orange colour independently of its round shape or its fast motion. By the same token, you don’t have separate experiences of your right and your left visual fields – they are interdependent as a whole visual scene.

Tononi identified differentiation and integration as two essential features of consciousness. And so, just as the essential features of life might lead a scientist to infer the existence of DNA, the essential features of consciousness led Tononi to infer the physical properties of a conscious system.

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Consciousness might be the last frontier of science. If IIT continues to guide us in the right direction, we’ll develop better methods of diagnosing disorders of consciousness. One day, we might even be able to turn to artificial intelligences – potential minds unlike our own – and assess whether or not they are conscious. This isn’t science fiction: many serious thinkers – including the late physicist Stephen Hawking, the technology entrepreneur Elon Musk, the computer scientist Stuart Russell at the University of California, Berkeley and the philosopher Nick Bostrom at the Future of Humanity Institute in Oxford – take recent advances in AI seriously, and are deeply concerned about the existential risk that could be posed by human- or superhuman-level AI in the future. When is unplugging an AI ethical? Whoever pulls the plug on the super AI of coming decades will want to know, however urgent their actions, whether there truly is an artificial mind slipping into darkness or just a complicated digital computer making sounds that mimic fear.

The info is here.

Machine learning uncovers the most robust self-report predictors of relationship quality across 43 longitudinal couples studies

S. Joel and others
Proceedings of the National Academy of Sciences 
Aug 2020, 117 (32) 19061-19071
DOI: 10.1073/pnas.1917036117

Abstract

Given the powerful implications of relationship quality for health and well-being, a central mission of relationship science is explaining why some romantic relationships thrive more than others. This large-scale project used machine learning (i.e., Random Forests) to 1) quantify the extent to which relationship quality is predictable and 2) identify which constructs reliably predict relationship quality. Across 43 dyadic longitudinal datasets from 29 laboratories, the top relationship-specific predictors of relationship quality were perceived-partner commitment, appreciation, sexual satisfaction, perceived-partner satisfaction, and conflict. The top individual-difference predictors were life satisfaction, negative affect, depression, attachment avoidance, and attachment anxiety. Overall, relationship-specific variables predicted up to 45% of variance at baseline, and up to 18% of variance at the end of each study. Individual differences also performed well (21% and 12%, respectively). Actor-reported variables (i.e., own relationship-specific and individual-difference variables) predicted two to four times more variance than partner-reported variables (i.e., the partner’s ratings on those variables). Importantly, individual differences and partner reports had no predictive effects beyond actor-reported relationship-specific variables alone. These findings imply that the sum of all individual differences and partner experiences exert their influence on relationship quality via a person’s own relationship-specific experiences, and effects due to moderation by individual differences and moderation by partner-reports may be quite small. Finally, relationship-quality change (i.e., increases or decreases in relationship quality over the course of a study) was largely unpredictable from any combination of self-report variables. This collective effort should guide future models of relationships.

Significance

What predicts how happy people are with their romantic relationships? Relationship science—an interdisciplinary field spanning psychology, sociology, economics, family studies, and communication—has identified hundreds of variables that purportedly shape romantic relationship quality. The current project used machine learning to directly quantify and compare the predictive power of many such variables among 11,196 romantic couples. People’s own judgments about the relationship itself—such as how satisfied and committed they perceived their partners to be, and how appreciative they felt toward their partners—explained approximately 45% of their current satisfaction. The partner’s judgments did not add information, nor did either person’s personalities or traits. Furthermore, none of these variables could predict whose relationship quality would increase versus decrease over time.

The U.S. Has an Empathy Deficit—Here’s what we can do about it.

Judith Hall and Mark Leary

Scientific American

Originally poste 17 Sept 20

Here are two excerpts:

Fixing this empathy deficit is a challenge because it is not just a matter of having good political or corporate leaders or people treating each other with good will and respect. It is, rather, because empathy is a fundamentally squishy term. Like many broad and complicated concepts, empathy can mean many things. Even the researchers who study it do not always say what they mean, or measure empathy in the same way in their studies—and they definitely do not agree on a definition. In fact, there are stark contradictions: what one researcher calls empathy is not empathy to another.

When laypeople are surveyed on how they define empathy, the range of answers is wide as well. Some people think empathy is a feeling; others focus on what a person does or says. Some think it is being good at reading someone’s nonverbal cues, while others include the mental orientation of putting oneself in someone else’s shoes. Still others see empathy as the ability or effort to imagine others’ feelings, or as just feeling “connected” or “relating” to someone. Some think it is a moral stance to be concerned about other people’s welfare and a desire to help them out. Sometimes it seems like “empathy” is just another way of saying “being a nice and decent person.” Actions, feelings, perspectives, motives, values—all of these are “empathy” according to someone.

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Whatever people think empathy is, it’s a powerful force and human beings need it. These three things might help to remedy our collective empathy deficit:

Take the time to ask those you encounter how they are feeling, and really listen. Try to put yourself in their shoes. Remember that we all tend to underestimate other people’s emotional distress, and we’re most likely to do so when those people are different from us.

Remind yourself that almost everyone is at the end of their rope these days. Many people barely have enough energy to handle their own problems, so they don’t have their normal ability to think about yours.

The info is here.