Moral Leadership in the 2016 U.S. Presidential Election

W. Kidd & J. A. Vitriol

Political Psychology

First published: 27 September 2021

Abstract

Voters commonly revise their political beliefs to align with the political leaders with whom they strongly identify, suggesting voters lack a coherent ideological structure causally prior to their political loyalties. Alternatively, voters may organize their preferences around nonideological concepts or values, such as moral belief. Using a four-wave panel study during the 2016 election, we examine the relationship between voters' own moral foundations and their perceptions of the candidates' moral beliefs. We observed a bidirectional relationship among Republicans, who revised both their own moral beliefs and their perceptions of Donald Trump to reduce incongruities. In contrast, Democrats revised their perceptions of Hillary Clinton to align with their own moral beliefs. Importantly, consistency between voters' and political candidates' moral beliefs was more common among partisans and led to polarized evaluations of the two candidates on Election Day.

The research is here.

From a PsyPost interview:

Trump supporters also appeared to adjust their moral foundations from to align more closely with their perceptions of Trump’s moral foundations. Perceptions of Trump at wave two changed how his supporters perceived their own moral beliefs at wave three. But this pattern was not found among Clinton supporters, who did not adjust their own moral beliefs.

“Political leadership is moral leadership,” the researchers told PsyPost. “Many voters revise even their fundamental views of what they describe as right and wrong based on their perceptions of the candidates they support. Ideas and positions that might have seemed out of bounds can become normalized very quickly if they receive support from political leaders.”

“That voters adjust their ‘perceptions’ of the candidates is also likely a reason partisan conflict often seems so intractable, as voters from each party may not even share a common understanding of the candidates in question, limiting any form of reasoned debate.”

This information is here.

Experts Are Ringing Alarms About Elon Musk’s Brain Implants

Noah Kirsch

Daily Beast

Posted 25 Jan 2021

Here is an excerpt:

“These are very niche products—if we’re really only talking about developing them for paralyzed individuals—the market is small, the devices are expensive,” said Dr. L. Syd Johnson, an associate professor in the Center for Bioethics and Humanities at SUNY Upstate Medical University.

“If the ultimate goal is to use the acquired brain data for other devices, or use these devices for other things—say, to drive cars, to drive Teslas—then there might be a much, much bigger market,” she said. “But then all those human research subjects—people with genuine needs—are being exploited and used in risky research for someone else’s commercial gain.”

In interviews with The Daily Beast, a number of scientists and academics expressed cautious hope that Neuralink will responsibly deliver a new therapy for patients, though each also outlined significant moral quandaries that Musk and company have yet to fully address.

Say, for instance, a clinical trial participant changes their mind and wants out of the study, or develops undesirable complications. “What I’ve seen in the field is we’re really good at implanting [the devices],” said Dr. Laura Cabrera, who researches neuroethics at Penn State. “But if something goes wrong, we really don't have the technology to explant them” and remove them safely without inflicting damage to the brain.

There are also concerns about “the rigor of the scrutiny” from the board that will oversee Neuralink’s trials, said Dr. Kreitmair, noting that some institutional review boards “have a track record of being maybe a little mired in conflicts of interest.” She hoped that the high-profile nature of Neuralink’s work will ensure that they have “a lot of their T’s crossed.”

The academics detailed additional unanswered questions: What happens if Neuralink goes bankrupt after patients already have devices in their brains? Who gets to control users’ brain activity data? What happens to that data if the company is sold, particularly to a foreign entity? How long will the implantable devices last, and will Neuralink cover upgrades for the study participants whether or not the trials succeed?

Dr. Johnson, of SUNY Upstate, questioned whether the startup’s scientific capabilities justify its hype. “If Neuralink is claiming that they’ll be able to use their device therapeutically to help disabled persons, they’re overpromising because they’re a long way from being able to do that.”

Neuralink did not respond to a request for comment as of publication time.

The info is here.

Public Deliberation about Gene Editing in the Wild

M. K. Gusmano, E. Kaebnick, et al. (2021).

Hastings Center Report

10.1002/hast.1318, 51, S2, (S34-S41).

Abstract

Genetic editing technologies have long been used to modify domesticated nonhuman animals and plants. Recently, attention and funding have also been directed toward projects for modifying nonhuman organisms in the shared environment—that is, in the “wild.” Interest in gene editing nonhuman organisms for wild release is motivated by a variety of goals, and such releases hold the possibility of significant, potentially transformative benefit. The technologies also pose risks and are often surrounded by a high uncertainty. Given the stakes, scientists and advisory bodies have called for public engagement in the science, ethics, and governance of gene editing research in nonhuman organisms. Most calls for public engagement lack details about how to design a broad public deliberation, including questions about participation, how to structure the conversations, how to report on the content, and how to link the deliberations to policy. We summarize the key design elements that can improve broad public deliberations about gene editing in the wild.

Here is the gist of the paper:

We draw on interdisciplinary scholarship in bioethics, political science, and public administration to move forward on this knot of conceptual, normative, and practical problems. When is broad public deliberation about gene editing in the wild necessary? And when it is required, how should it be done? These questions lead to a suite of further questions about, for example, the rationale and goals of deliberation, the features of these technologies that make public deliberation appropriate or inappropriate, the criteria by which “stakeholders” and “relevant publics” for these uses might be identified, how different approaches to public deliberation map onto the challenges posed by the technologies, how the topic to be deliberated upon should be framed, and how the outcomes of public deliberation can be meaningfully connected to policy-making.

The info is here.

Robot performs first laparoscopic surgery without human help (and outperformed human doctors)

Johns Hopkins University. (2022, January 26). 

ScienceDaily. Retrieved January 28, 2022

A robot has performed laparoscopic surgery on the soft tissue of a pig without the guiding hand of a human -- a significant step in robotics toward fully automated surgery on humans. Designed by a team of Johns Hopkins University researchers, the Smart Tissue Autonomous Robot (STAR) is described today in Science Robotics.

"Our findings show that we can automate one of the most intricate and delicate tasks in surgery: the reconnection of two ends of an intestine. The STAR performed the procedure in four animals and it produced significantly better results than humans performing the same procedure," said senior author Axel Krieger, an assistant professor of mechanical engineering at Johns Hopkins' Whiting School of Engineering.

The robot excelled at intestinal anastomosis, a procedure that requires a high level of repetitive motion and precision. Connecting two ends of an intestine is arguably the most challenging step in gastrointestinal surgery, requiring a surgeon to suture with high accuracy and consistency. Even the slightest hand tremor or misplaced stitch can result in a leak that could have catastrophic complications for the patient.

Working with collaborators at the Children's National Hospital in Washington, D.C. and Jin Kang, a Johns Hopkins professor of electrical and computer engineering, Krieger helped create the robot, a vision-guided system designed specifically to suture soft tissue. Their current iteration advances a 2016 model that repaired a pig's intestines accurately, but required a large incision to access the intestine and more guidance from humans.

The team equipped the STAR with new features for enhanced autonomy and improved surgical precision, including specialized suturing tools and state-of-the art imaging systems that provide more accurate visualizations of the surgical field.

Soft-tissue surgery is especially hard for robots because of its unpredictability, forcing them to be able to adapt quickly to handle unexpected obstacles, Krieger said. The STAR has a novel control system that can adjust the surgical plan in real time, just as a human surgeon would.

The info is here.

I See Color

Khama Ennis

On The Flip Side

Original date: February 13, 2020

9 minutes worth watching: Patient biases versus professional obligations

Copy the In-group: Group Membership Trumps Perceived Reliability, Warmth, and Competence in a Social-Learning Task

Montrey, M., & Shultz, T. R. (2022). 

Psychological Science, 33(1), 165–174. 

https://doi.org/10.1177/09567976211032224

Abstract

Surprisingly little is known about how social groups influence social learning. Although several studies have shown that people prefer to copy in-group members, these studies have failed to resolve whether group membership genuinely affects who is copied or whether group membership merely correlates with other known factors, such as similarity and familiarity. Using the minimal-group paradigm, we disentangled these effects in an online social-learning game. In a sample of 540 adults, we found a robust in-group-copying bias that (a) was bolstered by a preference for observing in-group members; (b) overrode perceived reliability, warmth, and competence; (c) grew stronger when social information was scarce; and (d) even caused cultural divergence between intermixed groups. These results suggest that people genuinely employ a copy-the-in-group social-learning strategy, which could help explain how inefficient behaviors spread through social learning and how humans maintain the cultural diversity needed for cumulative cultural evolution.

From the Discussion

In fact, if people are predisposed to copy in-group members, perhaps even when their perceived competence is low, this could help explain the spread of inefficient or even deleterious behaviors. For example, opposition to vaccination is often disseminated through highly clustered and enclosed online communities (Yuan & Crooks, 2018) who use in-group-focused language (Mitra et al., 2016). Likewise, fake news tends to spread among politically aligned individuals (Grinberg et al., 2019), and the most effective puppet accounts prefer to portray themselves as in-group members rather than as knowledgeable experts (Xia et al., 2019). Our research also sheds light on why social media platforms seem especially prone to spreading misinformation. By offering such fine-grained control over whom users observe, these platforms may spur the creation of homogeneous social networks, in which individuals are more inclined to copy others because they belong to the same social group.

The research is here.

Fast response times signal social connection in conversation

Templeton, E. M. et al.

Proceedings of the National Academy of Sciences 

Jan 2022, 119 (4) e2116915119

Abstract

Clicking is one of the most robust metaphors for social connection. But how do we know when two people "click"? We asked pairs of friends and strangers to talk with each other and rate their felt connection. For both friends and strangers, speed in response was a robust predictor of feeling connected. Conversations with faster response times felt more connected than conversations with slower response times, and within conversations, connected moments had faster response times than less-connected moments. This effect was determined primarily by partner responsivity: People felt more connected to the degree that their partner responded quickly to them rather than by how quickly they responded to their partner. The temporal scale of these effects (<250 ms) precludes conscious control, thus providing an honest signal of connection. Using a round-robin design in each of six closed networks, we show that faster responders evoked greater feelings of connection across partners. Finally, we demonstrate that this signal is used by third-party listeners as a heuristic of how well people are connected: Conversations with faster response times were perceived as more connected than the same conversations with slower response times. Together, these findings suggest that response times comprise a robust and sufficient signal of whether two minds “click.”

Significance

Social connection is critical for our mental and physical health yet assessing and measuring connection has been challenging. Here, we demonstrate that a feature intrinsic to conversation itself—the speed with which people respond to each other—is a simple, robust, and sufficient metric of social connection. Strangers and friends feel more connected when their conversation partners respond quickly. Because extremely short response times (<250 ms) preclude conscious control, they provide an honest signal that even eavesdroppers use to judge how well two people “click.”

The research is here.

The Pervasive Impact of Ignorance

Kirfel, L., & Phillips, J. S. 

(2022, January 16). 

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

Abstract

Norm violations have been demonstrated to impact a wide range of seemingly non-normative judgments. Among other things, when agents' actions violate prescriptive norms they tend to be seen as having done those actions more freely, as having acted more intentionally, as being more of a cause of subsequent outcomes, and even as being less happy. The explanation of this effect continues to be debated, with some researchers appealing to features of actions that violate norms, and other researchers emphasizing the importance of agents' mental states when acting. Here, we report the results of two large-scale experiments that replicate and extend twelve of the studies that originally demonstrated the pervasive impact of norm violations. In each case, we build on the pre-existing experimental paradigms to additionally manipulate whether the agents knew that they were violating a norm while holding fixed the action done. We find evidence for a pervasive impact of ignorance: the impact of norm violations on non-normative judgments depends largely on the agent knowing that they were violating a norm when acting. Moreover, we find evidence that the reduction in the impact of normality is underpinned by people's counterfactual reasoning: people are less likely to consider an alternative to the agent’s action if the agent is ignorant. We situate our findings in the wider debate around the role of normality in people's reasoning.

General Discussion

Motivated Moral Cognition

On the one hand, blame-based accounts may try and use this discovery to their ad-vantage by arguing that an agent’s knowledge is directly relevant to whether they should be blamed (Cushman et al., 2008; Cushman, Sheketoff, Wharton, & Carey, 2013; Laurent, Nuñez, & Schweitzer, 2015; Yuill & Perner, 1988), and thus that these effects reflect that theimpact of normality arises from the motivation to blame or hold agents responsible for theiractions (Alicke & Rose, 2012; Livengood et al., 2017; Samland & Waldmann, 2016). For example, the tendency to report that agents who bring about harm acted intentionally may serve to corroborate people’s desire to judge the agent’s behaviour negatively (Nadelhoffer, 2004; Rogers et al., 2019). Motivated accounts differ in terms of exactly which moral judgment is argued to be at stake, i.e. whether norm-violations elicit a desire to punish (Clarket al., 2014), to blame (Alicke & Rose, 2012; Hindriks et al., 2016), to hold accountable (Samland & Waldmann, 2016) or responsible (Sytsma, 2020a), and whether its influence works in form of a cognitive bias (Alicke, 2000), or a more affective response (Nadelhoffer,2004). Common to all, however, is the assumption that it is the impetus to morally condemn the norm-violating agent that underlies exaggerated attributions of specific properties, from free will to intentional action.

Our study puts an important constraint on how the normative judgment that motivated reasoning accounts assume might work. To account for our findings, motivated ac-counts cannot generally appeal to whether an agent’s action violated a clear norm, but have to take into account whether people would all-things-considered blame the agent (Driver,2017). In that sense, the mere violation of a norm must not, itself, suffice to trigger the relevant blame response. Rather, the perception of this norm violation must occur in con-junction with an assessment of the epistemic state of the agent such that the relevant motivated reasoning is only elicited when the agent is aware of the immorality of their action. For example, Alicke and Rose’s 2012 Culpable Control Model holds that immediate negative evaluative reactions of an agent’s behaviours often cause people to interpret all other agential features in a way that justifies blaming the agent. Such accounts face a challenge. On the one hand, they seem committed to the idea that people should discount the agent’s ignorance to support their immediate negative evaluation of the harm causing actions. On the other hand, they need to account for the fact that people seem to be sensitive to fine-grained epistemic features of the agent when forming their negative evaluation of the harm causing action.

The paper is here.

Meta-analysis of human prediction error for incentives, perception, cognition, and action

Corlett, P.R., Mollick, J.A. & Kober, H.

Neuropsychopharmacol. (2022). 

https://doi.org/10.1038/s41386-021-01264-3

Abstract

Prediction errors (PEs) are a keystone for computational neuroscience. Their association with midbrain neural firing has been confirmed across species and has inspired the construction of artificial intelligence that can outperform humans. However, there is still much to learn. Here, we leverage the wealth of human PE data acquired in the functional neuroimaging setting in service of a deeper understanding, using an MKDA (multi-level kernel-based density) meta-analysis. Studies were identified with Google Scholar, and we included studies with healthy adult participants that reported activation coordinates corresponding to PEs published between 1999–2018. Across 264 PE studies that have focused on reward, punishment, action, cognition, and perception, consistent with domain-general theoretical models of prediction error we found midbrain PE signals during cognitive and reward learning tasks, and an insula PE signal for perceptual, social, cognitive, and reward prediction errors. There was evidence for domain-specific error signals––in the visual hierarchy during visual perception, and the dorsomedial prefrontal cortex during social inference. We assessed bias following prior neuroimaging meta-analyses and used family-wise error correction for multiple comparisons. This organization of computation by region will be invaluable in building and testing mechanistic models of cognitive function and dysfunction in machines, humans, and other animals. Limitations include small sample sizes and ROI masking in some included studies, which we addressed by weighting each study by sample size, and directly comparing whole brain vs. ROI-based results.

Discussion

There appeared to be regionally compartmentalized PEs for primary and secondary rewards. Primary rewards elicited PEs in the dorsal striatum and amygdala, while secondary reward PEs were in ventral striatum. This is consistent with the representational transition that occurs with learning. We also found separable PEs for valence domains: caudal regions of the caudate-putamen are involved in the learning of safety signals and avoidance learning, more anterior striatum is selective for rewards, while more posterior is selective for losses. We found posterior midbrain aversive PE, consistent with preclinical findings that dopamine neurons––which respond to negative valence––are located more posteriorly in the midbrain and project to medial prefrontal regions. Additionally, we found both appetitive and aversive PEs in the amygdala, consistent with animal studies. The presence of both appetitive and aversive PE signals in the amygdala is consistent with its expanding role regulating learning based on surprise and uncertainty rather than fear per se. 

Perhaps conspicuous in its absence, given preclinical work, is the hippocampus, which is often held to be a nexus for reward PE, memory PE, and perceptual PE. This may be because the hippocampus is constantly and commonly engaged throughout task performance. Its PEs may not be resolved by the sluggish BOLD response, which is based on local field potentials and may represent the projections into a region (and therefore the striatal PE signals we observed may be the culmination of the processing in CA1, CA3, and subiculum). Furthermore, we have only recently been able to image subfields of the hippocampus (with higher field strengths and more rapid sequences); as higher resolution PE papers accrue we will revisit the meta-analysis of PEs.

The research is here.