Rugged American Individualism is a Myth, and It’s Killing Us

Katherine Wasson

Hastings Center

Originally published 4 June 21

The starkest picture of rugged American individualism is one we learned in school. A family moves West to settle the land and struggles with the elements.  Yet, even in these depictions, settlers needed help to raise a barn or harvest crops. They drew on the help of others and reciprocated in return. In the 21st century few Americans live in any way close to this largely self-sustaining lifestyle. Yet, the myth of rugged individualism is strong and persistent.

The reality for all of us is that none survive or flourish without the help of others. Whether it is within a family, peer group, school, religious institution, or wider community, all of us have been helped by others. Someone somewhere encouraged us, gave us a break or an opportunity, however small.  Some have experienced random acts of kindness from strangers. The myth of rugged individualism, which often means “pulling yourself up by your own bootstraps,” is outdated, was never completely accurate, and is harming us.

Holding tightly to this myth leads to the misperception that an individual can do (or not do) whatever they want in society and no person or, perhaps especially, government entity can tell them otherwise. People say, “As long as my choice doesn’t harm anyone else, I should be able to do what I want.” How they know their action does not harm anyone else is unclear and there are examples from the pandemic where personal choice does harm others. In bioethics we recognize this view as an expression of individual autonomy; the freedom to govern oneself.  Yet, such blinkered views of individual autonomy are misguided and inaccurate. Everyone’s autonomy is limited in society to avoid harm to the self or others. We enforce seatbelt and drunk driving laws to these ends. Moreover, that we rely on others to function in society has been made very clear during the pandemic. We need others to provide food and education, collect our garbage, and conduct the scientific research that informs our knowledge of the virus. These contributions support the common good.

We have seen rugged individualism on full display during the coronavirus pandemic. It can lead to a disregard for the worth and value of others. While many people observed public health restrictions and guidelines, others, including some elected officials, refused to wear masks and are now refusing vaccination. Those who cling to their individualism seem to view such restrictions as unnecessary or unacceptable, an infringement on their individual rights and freedoms. They are not willing to sacrifice a degree of their freedom to protect themselves or others. The result has been 33,264,650 cases and 594,568 deaths in the United States and counting. 

The info is here.

Updated Physician-Aid-in-Dying Law Sparks Controversy in Canada

Richard Karel

Psychiatric News

Originally posted 27 May 21

Here is an excerpt:

Addressing the changes for people who may be weighing MAID for severe mental illness, the government stated the following:

“If you have a mental illness as your only medical condition, you are not eligible to seek medical assistance in dying. … This temporary exclusion allows the Government of Canada more time to consider how MAID can safely be provided to those whose only medical condition is mental illness.

“To support this work, the government will initiate an expert review to consider protocols, guidance, and safeguards for those with a mental illness seeking MAID and will make recommendations within a year (by March 17, 2022).

“After March 17, 2023, people with a mental illness as their sole underlying medical condition will have access to MAID if they are eligible and the practitioners fulfill the safeguards that are put in place for this group of people. …”

While many physicians and others have long been sympathetic to allowing medical professionals to help those with terminal illness die peacefully, the fear has been that medically assisted death could become a substitute for adequate—and more costly—medical care. Those concerns are growing with the expansion of MAID in Canada.

The info is here.

Experimental Regulations for AI: Sandboxes for Morals and Mores

Ranchordas, Sofia

Morals and Machines (vol.1, 2021)

Available at SSRN: 

https://ssrn.com/abstract=3839744

Abstract

Recent EU legislative and policy initiatives aim to offer flexible, innovation-friendly, and future-proof regulatory frameworks. Key examples are the EU Coordinated Plan on AI and the recently published EU AI Regulation Proposal which refer to the importance of experimenting with regulatory sandboxes so as to balance innovation in AI against its potential risks. Originally developed in the Fintech sector, regulatory sandboxes create a testbed for a selected number of innovative projects, by waiving otherwise applicable rules, guiding compliance, or customizing enforcement. Despite the burgeoning literature on regulatory sandboxes and the regulation of AI, the legal, methodological, and ethical challenges of regulatory sandboxes have remained understudied. This exploratory article delves into the some of the benefits and intricacies of employing experimental legal instruments in the context of the regulation of AI. This article’s contribution is twofold: first, it contextualizes the adoption of regulatory sandboxes in the broader discussion on experimental approaches to regulation; second, it offers a reflection on the steps ahead for the design and implementation of AI regulatory sandboxes.

(cut)

In conclusion, AI regulatory sandboxes are not the answer to more innovation in AI. They are part of the path to a more forward-looking approach to the interaction between law and technology. This new approach will most certainly be welcomed with reluctance in years to come as it disrupts existing dogmas pertaining to the way in which we conceive the principle of legal certainty and the reactive—rather than anticipatory—nature of law. However, traditional law and regulation were designed with human agents and enigmas in mind. Many of the problems generated by AI (discrimination, power asymmetries, and manipulation) are still human but their scale and potential for harms (and benefits) have long ceased to be. It is thus time to rethink our fundamental approach to regulation and refocus on the new regulatory subject before us.

Against Empathy Bias: The Moral Value of Equitable Empathy

Fowler, Z., Law, K. F., & Gaesser, B.

Psychological Science

Volume: 32 issue: 5, page(s): 766-779

Abstract

Empathy has long been considered central in living a moral life. However, mounting evidence has shown that empathy is often biased towards (i.e., felt more strongly for) close and similar others, igniting a debate over whether empathy is inherently morally flawed and should be abandoned in efforts to strive towards greater equity. This debate has focused on whether empathy limits the scope of our morality, with little consideration of whether it may be our moral beliefs limiting our empathy. Across two studies conducted on Amazon’s Mechanical Turk (N= 604), we investigate moral judgments of biased and equitable feelings of empathy. We observed a moral preference for empathy towards socially close over distant others. However, feeling equal empathy for all is seen as the most morally and socially valuable. These findings provide new theoretical insight into the relationship between empathy and morality with implications for navigating towards a more egalitarian future.

General Discussion

The present studies investigated moral judgments of socially biased and equitable feelings of empathy in hypothetical vignettes. The results showed that moral judgments of empathy are biased towards preferring more empathy for a socially close over socially distant individual. Despite this bias in moral judgments, however, people consistently judged feeling equal empathy as the most morally right. These findings generalized from judgments of others’ empathy for targets matched on objective social distance to judgments of one’s own empathy for targets that were personally-tailored and matched on subjective social distance across subjects.  Further, participants most desired to affiliate with someone who felt equal empathy. We also found that participants’ desire to affiliate with the actor in the vignette mirrored their moral judgments of empathy.

A pdf is here.

Drug Overdose Deaths Up 30% in Pandemic Year, Government Data Show

Joyce Frieden

MedPage Today 

Originally published 1 June 2021

Mortality from all types of drug overdoses increased by a whopping 30% over a 1-year period, Nora Volkow, MD, director of the National Institute on Drug Abuse (NIDA), reported at the FDA Science Forum.

Data from the National Center for Health Statistics from October 2019 to October 2020 shows that mortality from overdoses from all types of drugs increased 30%, from 70,669 deaths in October 2019 to 91,862 deaths in October 2020, "and I think that that is a number that is very, very chilling," Volkow said at the forum. Among those overdose deaths in both years, more than half came from synthetic opiates -- "the most notable presence is fentanyl," she said. There was also a 46% increase in overdose deaths from other psychostimulants, mainly methamphetamine, and a 38% increase in deaths from cocaine overdoses.

Having any kind of substance use disorder (SUD) also affects the risk of getting COVID-19, she continued. According to a study done by Volkow and colleagues, "Regardless of the specific type of substance use disorder -- legal or illegal -- there was a significant increase in the likelihood of people that have a substance use disorder to become infected," she said. Their study, which included electronic health records from 7.5 million patients with an SUD diagnosis, found that patients with a recent SUD diagnosis -- within the past year -- were nearly nine times more likely to contract COVID-19 than patients without that diagnosis; for those with opioid use disorder in particular, their odds of contracting COVID were 10 times higher.

The info is here.

How relationships bias moral reasoning: Neural and self-report evidence

Berg, M. K., Kitayama, S., & Kross, E.

Journal of Experimental Social Psychology

Volume 95, July 2021, 104156

Abstract

Laws govern society, regulating people's behavior to create social harmony. Yet recent research indicates that when laws are broken by people we know and love, we consistently fail to report their crimes. Here we identify an expectancy-based cognitive mechanism that underlies this phenomenon and illustrate how it interacts with people's motivations to predict their intentions to report crimes. Using a combination of self-report and brain (ERP) measures, we demonstrate that although witnessing any crime violates people's expectations, expectancy violations are stronger when close (vs. distant) others commit crimes. We further employ an experimental-causal-chain design to show that people resolve their expectancy violations in diametrically opposed ways depending on their relationship to the transgressor. When close others commit crimes, people focus more on the individual (vs. the crime), which leads them to protect the transgressor. However, the reverse is true for distant others, which leads them to punish the transgressor. These findings highlight the sensitivity of early attentional processes to information about close relationships. They further demonstrate how these processes interact with motivation to shape moral decisions. Together, they help explain why people stubbornly protect close others, even in the face of severe crimes.

Highlights

• We used neural and self-report methods to explain people's reluctance to punish close others who act immorally.

• Close others acting immorally, and severe immoral acts, are highly unexpected.

• Expectancy violations interact with motivation to drive attention.

• For close others, people focus on the transgressor, which yields a more lenient response.

• For distant others, people focus on the immoral act, which yields a more punitive response.

A pdf is here.

Artificial intelligence research may have hit a dead end

Thomas Nail

salon.com

Originally published 30 April 21

Here is an excerpt:

If it's true that cognitive fluctuations are requisite for consciousness, it would also take time for stable frequencies to emerge and then synchronize with one another in resting states. And indeed, this is precisely what we see in children's brains when they develop higher and more nested neural frequencies over time.

Thus, a general AI would probably not be brilliant in the beginning. Intelligence evolved through the mobility of organisms trying to synchronize their fluctuations with the world. It takes time to move through the world and learn to sync up with it. As the science fiction author Ted Chiang writes, "experience is algorithmically incompressible." 

This is also why dreaming is so important. Experimental research confirms that dreams help consolidate memories and facilitate learning. Dreaming is also a state of exceptionally playful and freely associated cognitive fluctuations. If this is true, why should we expect human-level intelligence to emerge without dreams? This is why newborns dream twice as much as adults, if they dream during REM sleep. They have a lot to learn, as would androids.

In my view, there will be no progress toward human-level AI until researchers stop trying to design computational slaves for capitalism and start taking the genuine source of intelligence seriously: fluctuating electric sheep.

The info is here.

Preparing for the Next Generation of Ethical Challenges Concerning Heritable Human Genome Editing

Robert Klitzman

The American Journal of Bioethics

(2021) Volume 21 (6), 1-4.

Here is the conclusion

Moving Forward

Policymakers will thus need to make complex and nuanced risk/benefit calculations regarding costs and extents of treatments, ages of onset, severity of symptoms, degrees of genetic penetrance, disease prevalence, future scientific benefits, research costs, appropriate allocations of limited resources, and questions of who should pay.

Future efforts should thus consider examining scientific and ethical challenges in closer conjunction, not separated off, and bring together the respective strengths of the Commission’s and of the WHO Committee’s approaches. The WHO Committee includes broader stakeholders, but does not yet appear to have drawn conclusions regarding such specific medical and scientific scenarios (WHO 2020). These two groups’ respective memberships also differ in instructive ways that can mutually inform future deliberations. Among the Commission’s 18 chairs and members, only two appear to work primarily in ethics or policy; the majority are scientists (National Academy of Medicine, the National Academies of Sciences and the Royal Society 2020). In contrast, the WHO Committee includes two chairs and 16 members, with both chairs and the majority of members working primarily in ethics, policy or law (WHO 2020). ASRM and other countries’ relevant professional organizations should also stipulate that physicians and healthcare professionals should not be involved in any way in the care of patients using germline editing abroad.

The Commission’s Report thus provides valuable insights and guidelines, but multiple stakeholders will likely soon confront additional, complex dilemmas involving interplays of both science and ethics that also need urgent attention.

The article is here.

Wise teamwork: Collective confidence calibration predicts the effectiveness of group discussion

Silver, I, Mellers, B.A., & Tetlock, P.E.

Journal of Experimental Social Psychology

Volume 96, September 2021.

Abstract

‘Crowd wisdom’ refers to the surprising accuracy that can be attained by averaging judgments from independent individuals. However, independence is unusual; people often discuss and collaborate in groups. When does group interaction improve vs. degrade judgment accuracy relative to averaging the group's initial, independent answers? Two large laboratory studies explored the effects of 969 face-to-face discussions on the judgment accuracy of 211 teams facing a range of numeric estimation problems from geographic distances to historical dates to stock prices. Although participants nearly always expected discussions to make their answers more accurate, the actual effects of group interaction on judgment accuracy were decidedly mixed. Importantly, a novel, group-level measure of collective confidence calibration robustly predicted when discussion helped or hurt accuracy relative to the group's initial independent estimates. When groups were collectively calibrated prior to discussion, with more accurate members being more confident in their own judgment and less accurate members less confident, subsequent group interactions were likelier to yield increased accuracy. We argue that collective calibration predicts improvement because groups typically listen to their most confident members. When confidence and knowledge are positively associated across group members, the group's most knowledgeable members are more likely to influence the group's answers.

Conclusion

People often display exaggerated beliefs about their skills and knowledge. We misunderstand and over-estimate our ability to answer general knowledge questions (Arkes, Christensen, Lai, & Blumer, 1987), save for a rainy day (Berman, Tran, Lynch Jr, & Zauberman, 2016), and resist unhealthy foods (Loewenstein, 1996), to name just a few examples. Such failures of calibration can have serious consequences, hindering our ability to set goals (Kahneman & Lovallo, 1993), make plans (Janis, 1982), and enjoy experiences (Mellers & McGraw, 2004). Here, we show that collective calibration also predicts the effectiveness of group discussions. In the context of numeric estimation tasks, poorly calibrated groups were less likely to benefit from working together, and, ultimately, offered less accurate answers. Group interaction is the norm, not the exception. Knowing what we know (and what we don't know) can help predict whether interactions will strengthen or weaken crowd wisdom.

The research is here.