Ashley Turner
www.CNBC.com
Originally posted May 21, 2019
Here is an excerpt:
Former FDA Commissioner Scott Gottlieb said Tuesday that He’s research was a “horrible experiment and it established a horrible precedent.” Gottlieb said He’s experiment risked causing people to “rightfully” turn away from the science.
Gottlieb said he has yet to see any compelling arguments in favor of human germline editing.
Paul Dabrowski, CEO of Synthego, a genome engineering company, agreed the scientific community is not yet ready for germline editing. He wondered whether allowing parents to choose to genetically alter their future children can be ethical if they’re not the one who is having their DNA changed.
“How do you make sure you can align the person who is consenting and the person who is taking the risk?” Dabrowski asked.
Stanford’s Hurlbut said there are risks to editing DNA, as those traits can then be passed down to future generations. Editing certain genes can also cause changes in other genes, according to Hurlbut.
“We want to be very careful, nature is a profound balance and if we intervene in a way that is not profound we can upset things,” Hurlbut said.
The info is here.
Friday, June 28, 2019
Moralized memory: binding values predict inflated estimates of the group’s historical influence
Luke Churchill, Jeremy K. Yamashiro & Henry L. Roediger IIIMemory (2019)
DOI: 10.1080/09658211.2019.1623261
Abstract
Collective memories are memories or historical knowledge shared by individual group members, which shape their collective identity. Ingroup inflation, which has previously also been referred to as national narcissism or state narcissism, is the finding that group members judge their own group to have been significantly more historically influential than do people from outside the group. We examined the role of moral motivations in this biased remembering. A sample of 2118 participants, on average 42 from each state of the United States, rated their home state’s contribution to U.S. history, as well as that of ten other states randomly selected. We demonstrated an ingroup inflation effect in estimates of the group’s historical influence. Participants’ endorsement of binding values – loyalty, authority, and sanctity, but particularly loyalty – positively predicted the size of this effect. Endorsement of individuating values – care and fairness – did not predict collective narcissism. Moral motives may shape biases in collective remembering.
The research can be found here.
Thursday, June 27, 2019
The Wayfair Walkout Is a Different Kind of Tech Worker Protest
April Glaserslate.com
Originally posted June 26, 2019
Here is an excerpt:
This time, the Wayfair employees went very public—and they did so during a week of renewed public outrage over the Trump administration’s border policies, thanks to reports of appalling conditions at a facility in Clint, Texas, holding migrant children who had been separated from their families. When Wayfair employees disrupt business on Wednesday by walking out, they’ll highlight that even a company best known for cheap sofas is entangled with a system that has split up families, locked asylum-seekers in cages, and detained children who have been found sick and without access to sufficient food or places to bathe.
This isn’t a typical use of organized labor, but it’s of a piece with the methods used by white-collar workers in the technology industry over the past two years. So far, the movement to force companies to oppose various activities of the Trump administration has had mixed success. Wayfair’s case suggests it will now grow beyond the very largest tech companies—and that employees are realizing signing a petition isn’t their only move.
The Wayfair protesters aren’t fighting to improve their own working conditions: They’re organizing to change their employer’s business practices. Google employees did this in 2018 with a petition that lead to the nonrenewal of a Department of Defense contract to build software systems for drones. Microsoft and Salesforce employees were less successful last year when they sent letters to their respective CEOs demanding they stop contracting with federal immigration agencies. More than 4,200 Amazon employees recently called on the company, unsuccessfully, to reduce its carbon footprint and stop offering cloud services to the oil and gas industry.
The info is here.
This doctor is recruiting an army of medical experts to drown out fake health news on Instagram and Twitter
Christine FarrCNBC.com
Originally published June 2, 2019
The antidote to fake health news? According to Austin Chiang, the first chief medical social media officer at a top hospital, it’s to drown out untrustworthy content with tweets, pics and posts from medical experts that the average American can relate to.
Chiang is a Harvard-trained gastroenterologist with a side passion for social media. On Instagram, where he refers to himself as a “GI Doctor,” he has 20,000 followers, making him one of the most influential docs aside from TV personalities, plastic surgeons and New York’s so-called “most eligible bachelor,” Dr. Mike.
Every few days, he’ll share a selfie or a photo of himself in scrubs along with captions about the latest research or insights from conferences he attends, or advice to patients trying to sort our real information from rumors. He’s also active on Twitter, Microsoft’s LinkedIn and Facebook (which owns Instagram).
But Chiang recognizes that his following pales in comparison to accounts like “Medical Medium,” where two million people tune in to the musings of a psychic, who raves about vegetables that will cure diseases ranging from depression to diabetes. (Gwyneth Paltrow’s Goop has written about the account’s creator glowingly.) Or on Pinterest and Facebook, where anti-vaccination content has been far more prominent than legitimate public health information. Meanwhile, on e-commerce sites like Amazon and eBay, vendors have hawked unproven and dangerous health “cures, ” including an industrial-strength bleach that is billed as eliminating autism in children.
The info is here.
Wednesday, June 26, 2019
The computational and neural substrates of moral strategies in social decision-making
Jeroen M. van Baar, Luke J. Chang & Alan G. Sanfey
Nature Communications, Volume 10, Article number: 1483 (2019)
Abstract
Individuals employ different moral principles to guide their social decision-making, thus expressing a specific ‘moral strategy’. Which computations characterize different moral strategies, and how might they be instantiated in the brain? Here, we tackle these questions in the context of decisions about reciprocity using a modified Trust Game. We show that different participants spontaneously and consistently employ different moral strategies. By mapping an integrative computational model of reciprocity decisions onto brain activity using inter-subject representational similarity analysis of fMRI data, we find markedly different neural substrates for the strategies of ‘guilt aversion’ and ‘inequity aversion’, even under conditions where the two strategies produce the same choices. We also identify a new strategy, ‘moral opportunism’, in which participants adaptively switch between guilt and inequity aversion, with a corresponding switch observed in their neural activation patterns. These findings provide a valuable view into understanding how different individuals may utilize different moral principles.
(cut)
From the Discussion
We also report a new strategy observed in participants, moral opportunism. This group did not consistently apply one moral rule to their decisions, but rather appeared to make a motivational trade-off depending on the particular trial structure. This opportunistic decision strategy entailed switching between the behavioral patterns of guilt aversion and inequity aversion, and allowed participants to maximize their financial payoff while still always following a moral rule. Although it could have been the case that these opportunists merely resembled GA and IA in terms of decision outcome, and not in the underlying psychological process, a confirmatory analysis showed that the moral opportunists did in fact switch between the neural representations of guilt and inequity aversion, and thus flexibly employed the respective psychological processes underlying these two, quite different, social preferences. This further supports our interpretation that the activity patterns directly reflect guilt aversion and inequity aversion computations, and not a theoretically peripheral “third factor” shared between GA or IA participants. Additionally, we found activity patterns specifically linked to moral opportunism in the superior parietal cortex and dACC, which are strongly associated with cognitive control and working memory.
The research is here.
Nature Communications, Volume 10, Article number: 1483 (2019)
Abstract
Individuals employ different moral principles to guide their social decision-making, thus expressing a specific ‘moral strategy’. Which computations characterize different moral strategies, and how might they be instantiated in the brain? Here, we tackle these questions in the context of decisions about reciprocity using a modified Trust Game. We show that different participants spontaneously and consistently employ different moral strategies. By mapping an integrative computational model of reciprocity decisions onto brain activity using inter-subject representational similarity analysis of fMRI data, we find markedly different neural substrates for the strategies of ‘guilt aversion’ and ‘inequity aversion’, even under conditions where the two strategies produce the same choices. We also identify a new strategy, ‘moral opportunism’, in which participants adaptively switch between guilt and inequity aversion, with a corresponding switch observed in their neural activation patterns. These findings provide a valuable view into understanding how different individuals may utilize different moral principles.
(cut)
From the Discussion
We also report a new strategy observed in participants, moral opportunism. This group did not consistently apply one moral rule to their decisions, but rather appeared to make a motivational trade-off depending on the particular trial structure. This opportunistic decision strategy entailed switching between the behavioral patterns of guilt aversion and inequity aversion, and allowed participants to maximize their financial payoff while still always following a moral rule. Although it could have been the case that these opportunists merely resembled GA and IA in terms of decision outcome, and not in the underlying psychological process, a confirmatory analysis showed that the moral opportunists did in fact switch between the neural representations of guilt and inequity aversion, and thus flexibly employed the respective psychological processes underlying these two, quite different, social preferences. This further supports our interpretation that the activity patterns directly reflect guilt aversion and inequity aversion computations, and not a theoretically peripheral “third factor” shared between GA or IA participants. Additionally, we found activity patterns specifically linked to moral opportunism in the superior parietal cortex and dACC, which are strongly associated with cognitive control and working memory.
The research is here.
The evolution of human cooperation
Coren Apicella and Joan Silk
Current Biology, Volume 29 (11), pp 447-450.
Darwin viewed cooperation as a perplexing challenge to his theory of natural selection. Natural selection generally favors the evolution of behaviors that enhance the fitness of individuals. Cooperative behavior, which increases the fitness of a recipient at the expense of the donor, contradicts this logic. William D. Hamilton helped to solve the puzzle when he showed that cooperation can evolve if cooperators direct benefits selectively to other cooperators (i.e. assortment). Kinship, group selection and the previous behavior of social partners all provide mechanisms for assortment (Figure 1), and kin selection and reciprocal altruism are the foundation of the kinds of cooperative behavior observed in many animals. Humans also bias cooperation in favor of kin and reciprocating partners, but the scope, scale, and variability of human cooperation greatly exceed that of other animals. Here, we introduce derived features of human cooperation in the context in which they originally evolved, and discuss the processes that may have shaped the evolution of our remarkable capacity for cooperation. We argue that culturally-evolved norms that specify how people should behave provide an evolutionarily novel mechanism for assortment, and play an important role in sustaining derived properties of cooperation in human groups.
Here is a portion of the Summary
Cooperative foraging and breeding provide the evolutionary backdrop for understanding the evolution of cooperation in humans, as the returns from cooperating in these activities would have been high in our hunter-gatherer ancestors. Still, explaining how our ancestors effectively dealt with the problem of free-riders within this context remains a challenge. Derived features of human cooperation, however, give us some indication of the mechanisms that could lead to assortativity. These derived features include: first, the scope of cooperation — cooperation is observed between unrelated and often short-term interactors; second, the scale of cooperation — cooperation extends beyond pairs to include circumscribed groups that vary in size and identity; and third, variation in cooperation — human cooperation varies in both time and space in accordance with cultural and social norms. We argue that this pattern of findings is best explained by cultural evolutionary processes that generate phenotypic assortment on cooperation via a psychology adapted for cultural learning, norm sensitivity and group-mindedness.
The info is here.
Current Biology, Volume 29 (11), pp 447-450.
Darwin viewed cooperation as a perplexing challenge to his theory of natural selection. Natural selection generally favors the evolution of behaviors that enhance the fitness of individuals. Cooperative behavior, which increases the fitness of a recipient at the expense of the donor, contradicts this logic. William D. Hamilton helped to solve the puzzle when he showed that cooperation can evolve if cooperators direct benefits selectively to other cooperators (i.e. assortment). Kinship, group selection and the previous behavior of social partners all provide mechanisms for assortment (Figure 1), and kin selection and reciprocal altruism are the foundation of the kinds of cooperative behavior observed in many animals. Humans also bias cooperation in favor of kin and reciprocating partners, but the scope, scale, and variability of human cooperation greatly exceed that of other animals. Here, we introduce derived features of human cooperation in the context in which they originally evolved, and discuss the processes that may have shaped the evolution of our remarkable capacity for cooperation. We argue that culturally-evolved norms that specify how people should behave provide an evolutionarily novel mechanism for assortment, and play an important role in sustaining derived properties of cooperation in human groups.
Here is a portion of the Summary
Cooperative foraging and breeding provide the evolutionary backdrop for understanding the evolution of cooperation in humans, as the returns from cooperating in these activities would have been high in our hunter-gatherer ancestors. Still, explaining how our ancestors effectively dealt with the problem of free-riders within this context remains a challenge. Derived features of human cooperation, however, give us some indication of the mechanisms that could lead to assortativity. These derived features include: first, the scope of cooperation — cooperation is observed between unrelated and often short-term interactors; second, the scale of cooperation — cooperation extends beyond pairs to include circumscribed groups that vary in size and identity; and third, variation in cooperation — human cooperation varies in both time and space in accordance with cultural and social norms. We argue that this pattern of findings is best explained by cultural evolutionary processes that generate phenotypic assortment on cooperation via a psychology adapted for cultural learning, norm sensitivity and group-mindedness.
The info is here.
Tuesday, June 25, 2019
Truth by Repetition: Explanations and Implications
Unkelbach, C., Koch, A., Silva, R. R., & Garcia-Marques, T. (2019).
Current Directions in Psychological Science, 28(3), 247–253. https://doi.org/10.1177/0963721419827854
Current Directions in Psychological Science, 28(3), 247–253. https://doi.org/10.1177/0963721419827854
Abstract
People believe repeated information more than novel information; they show a repetition-induced truth effect. In a world of “alternative facts,” “fake news,” and strategic information management, understanding this effect is highly important. We first review explanations of the effect based on frequency, recognition, familiarity, and coherent references. On the basis of the latter explanation, we discuss the relations of these explanations. We then discuss implications of truth by repetition for the maintenance of false beliefs and ways to change potentially harmful false beliefs (e.g., “Vaccination causes autism”), illustrating that the truth-by-repetition phenomenon not only is of theoretical interest but also has immediate practical relevance.
Here is a portion of the closing section:
No matter which mental processes may underlie the repetition-induced truth effect, on a functional level, repetition increases subjective truth. The effect’s robustness may be worrisome if one considers that information nowadays is not randomly but strategically repeated. For example, the phenomenon of the “filter bubble” (Pariser, 2011) suggests that people get verbatim and paraphrased repetition only of what they already know and believe. As discussed, logically, this should not strengthen information’s subjective truth. However, as discussed above, repetition does influence subjective truth psychologically. In combination with phenomena such as selective exposure (e.g., Frey, 1986), confirmation biases (e.g., Nickerson, 1998), or failures to consider the opposite (e.g., Schul, Mayo, & Burnstein, 2004), it becomes apparent how even blatantly false information may come “to fix itself in the mind in such a way that it is accepted in the end as a demonstrated truth” (Le Bon, 1895/1996). For example, within the frame of a referential theory, filter bubbles repeat information and thereby add supporting coherent references for existing belief networks, which makes them difficult to change once they are established. Simultaneously, people should also process such information more fluently. In the studies reviewed here, statement content was mostly trivia. Yet, even for this trivia, participants evaluated contradictory information as being less true compared with novel information, even when they were explicitly told that it was 100% false (Unkelbach & Greifeneder, 2018). If one considers how many corresponding references the information that “vaccination leads to autism” may instigate for parents who must decide whether to vaccinate or not, the relevance of the truth-by-repetition phenomenon becomes apparent.
Monday, June 24, 2019
Not so Motivated After All? Three Replication Attempts and a Theoretical Challenge to a Morally-Motivated Belief in Free Will
Andrew E. Monroe and Dominic Ysidron
Preprint
Abstract
AbstractFree will is often appraised as a necessary input to for holding others morally or legally responsible for misdeeds. Recently, however,Clark and colleagues (2014), argued for the opposite causal relationship. They assert that moral judgments and the desire to punish motivate people’s belief in free will. In three experiments—two exact replications (Studies 1 & 2b) and one close replication(Study 2a)we seek to replicate these findings. Additionally, in a novel experiment (Study 3) we test a theoretical challenge derived from attribution theory, which suggests that immoral behaviors do not uniquely influence free will judgments. Instead, our non-violation model argues that norm deviations, of any kind—good, bad, or strange—cause people to attribute more free will to agents, and attributions of free will are explained via desire inferences.Across replication experiments we found no evidence for the original claim that witnessing immoral behavior causes people to increase their belief in free will, though we did replicate the finding that people attribute more free will to agents who behave immorally compared to a neutral control (Studies 2a & 3). Finally, our novel experiment demonstrated broad support for our norm-violation account, suggesting that people’s willingness to attribute free will to others is malleable, but not because people are motivated to blame.Instead, this experiment shows that attributions of free will are best explained by people’s expectations for norm adherence, and when these expectations are violated people infer that an agent expressed their free will to do so.
From the Discussion Section:
Together these findings argue for a non-moral explanation for free will judgments with norm-violation as the key driver. This account explains people’s tendency to attribute more free will to behaving badly agents because people generally expect others to follow moral norms, and when they don’t, people believe that there must have been a strong desire to perform the behavior. In addition, a norm-violation account is able to explain why people attribute more free will to agents behaving in odd or morally positive ways. Any deviation from what is expected causes people to attribute more desire and choice (i.e., free will)to that agent.Thus our findings suggest that people’s willingness to ascribe free will to others is indeed malleable, but considerations of free will are being driven by basic social cognitive representations of norms, expectations, and desire. Moreover, these data indicate that when people endorse free will for themselves or for others, they are not making claims about broad metaphysical freedom. Instead, if desires and norm-constraints are what affect ascriptions of free will, this suggests that what it means to have (or believe) in free willis to be rational (i.e., making choices informed by desires and preferences) and able to overcome constraints.
A preprint can be found here.
Preprint
Abstract
AbstractFree will is often appraised as a necessary input to for holding others morally or legally responsible for misdeeds. Recently, however,Clark and colleagues (2014), argued for the opposite causal relationship. They assert that moral judgments and the desire to punish motivate people’s belief in free will. In three experiments—two exact replications (Studies 1 & 2b) and one close replication(Study 2a)we seek to replicate these findings. Additionally, in a novel experiment (Study 3) we test a theoretical challenge derived from attribution theory, which suggests that immoral behaviors do not uniquely influence free will judgments. Instead, our non-violation model argues that norm deviations, of any kind—good, bad, or strange—cause people to attribute more free will to agents, and attributions of free will are explained via desire inferences.Across replication experiments we found no evidence for the original claim that witnessing immoral behavior causes people to increase their belief in free will, though we did replicate the finding that people attribute more free will to agents who behave immorally compared to a neutral control (Studies 2a & 3). Finally, our novel experiment demonstrated broad support for our norm-violation account, suggesting that people’s willingness to attribute free will to others is malleable, but not because people are motivated to blame.Instead, this experiment shows that attributions of free will are best explained by people’s expectations for norm adherence, and when these expectations are violated people infer that an agent expressed their free will to do so.
From the Discussion Section:
Together these findings argue for a non-moral explanation for free will judgments with norm-violation as the key driver. This account explains people’s tendency to attribute more free will to behaving badly agents because people generally expect others to follow moral norms, and when they don’t, people believe that there must have been a strong desire to perform the behavior. In addition, a norm-violation account is able to explain why people attribute more free will to agents behaving in odd or morally positive ways. Any deviation from what is expected causes people to attribute more desire and choice (i.e., free will)to that agent.Thus our findings suggest that people’s willingness to ascribe free will to others is indeed malleable, but considerations of free will are being driven by basic social cognitive representations of norms, expectations, and desire. Moreover, these data indicate that when people endorse free will for themselves or for others, they are not making claims about broad metaphysical freedom. Instead, if desires and norm-constraints are what affect ascriptions of free will, this suggests that what it means to have (or believe) in free willis to be rational (i.e., making choices informed by desires and preferences) and able to overcome constraints.
A preprint can be found here.
Motivated free will belief: The theory, new (preregistered) studies, and three meta-analyses
Clark, C. J., Winegard, B. M., & Shariff, A. F. (2019).
Manuscript submitted for publication.
Abstract
Do desires to punish lead people to attribute more free will to individual actors (motivated free will attributions) and to stronger beliefs in human free will (motivated free will beliefs) as suggested by prior research? Results of 14 new (7 preregistered) studies (n=4,014) demonstrated consistent support for both of these. These findings consistently replicated in studies (k=8) in which behaviors meant to elicit desires to punish were rated as equally or less counternormative than behaviors in control conditions. Thus, greater perceived counternormativity cannot account for these effects. Additionally, three meta-analyses of the existing data (including eight vignette types and eight free will judgment types) found support for motivated free will attributions (k=22; n=7,619; r=.25, p<.001) and beliefs (k=27; n=8,100; r=.13, p<.001), which remained robust after removing all potential moral responsibility confounds (k=26; n=7,953; r=.12, p<.001). The size of these effects varied by vignette type and free will belief measurement. For example, presenting the FAD+ free will belief subscale mixed among three other subscales (as in Monroe and Ysidron’s [2019] failed replications) produced a smaller average effect size (r=.04) than shorter and more immediate measures (rs=.09-.28). Also, studies with neutral control conditions produced larger effects (Attributions: r=.30; Beliefs: rs=.14-.16) than those with control conditions involving bad actions (Attributions: r=.05; Beliefs: rs=.04-.06). Removing these two kinds of studies from the meta-analyses produced larger average effect sizes (Attributions: r=.28; Beliefs: rs=.17-.18). We discuss the relevance of these findings for past and future research and the significance of these findings for human responsibility.
From the Discussion Section:
We suspect that motivated free will beliefs have become more common as society has become more humane and more concerned about proportionate punishment. Many people now assiduously reflect upon their own society’s punitive practices and separate those who deserve to be punished from those who are incapable of being fully responsible for their actions. Free will is crucial here because it is often considered a prerequisite for moral responsibility (Nichols & Knobe, 2007; Sarkissian et al., 2010; Shariff et al., 2014). Therefore, when one is motivated to punish another person, one is also motivated to inflate free will beliefs and free will attributions to specific perpetrators as a way to justify punishing the person.
A preprint can be downloaded here.
Manuscript submitted for publication.
Abstract
Do desires to punish lead people to attribute more free will to individual actors (motivated free will attributions) and to stronger beliefs in human free will (motivated free will beliefs) as suggested by prior research? Results of 14 new (7 preregistered) studies (n=4,014) demonstrated consistent support for both of these. These findings consistently replicated in studies (k=8) in which behaviors meant to elicit desires to punish were rated as equally or less counternormative than behaviors in control conditions. Thus, greater perceived counternormativity cannot account for these effects. Additionally, three meta-analyses of the existing data (including eight vignette types and eight free will judgment types) found support for motivated free will attributions (k=22; n=7,619; r=.25, p<.001) and beliefs (k=27; n=8,100; r=.13, p<.001), which remained robust after removing all potential moral responsibility confounds (k=26; n=7,953; r=.12, p<.001). The size of these effects varied by vignette type and free will belief measurement. For example, presenting the FAD+ free will belief subscale mixed among three other subscales (as in Monroe and Ysidron’s [2019] failed replications) produced a smaller average effect size (r=.04) than shorter and more immediate measures (rs=.09-.28). Also, studies with neutral control conditions produced larger effects (Attributions: r=.30; Beliefs: rs=.14-.16) than those with control conditions involving bad actions (Attributions: r=.05; Beliefs: rs=.04-.06). Removing these two kinds of studies from the meta-analyses produced larger average effect sizes (Attributions: r=.28; Beliefs: rs=.17-.18). We discuss the relevance of these findings for past and future research and the significance of these findings for human responsibility.
From the Discussion Section:
We suspect that motivated free will beliefs have become more common as society has become more humane and more concerned about proportionate punishment. Many people now assiduously reflect upon their own society’s punitive practices and separate those who deserve to be punished from those who are incapable of being fully responsible for their actions. Free will is crucial here because it is often considered a prerequisite for moral responsibility (Nichols & Knobe, 2007; Sarkissian et al., 2010; Shariff et al., 2014). Therefore, when one is motivated to punish another person, one is also motivated to inflate free will beliefs and free will attributions to specific perpetrators as a way to justify punishing the person.
A preprint can be downloaded here.
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