Our Minds Aren’t Equipped for This Kind of Reopening

TessWilkinson-Ryan
The Atlantic
Originally published 6 July 20

Here is the conclusion:

At the least, government agencies must promulgate clear, explicit norms and rules to facilitate cooperative choices. Most people congregating in tight spaces are telling themselves a story about why what they are doing is okay. Such stories flourish under confusing or ambivalent norms. People are not irrevocably chaotic decision makers; the level of clarity in human thinking depends on how hard a problem is. I know with certainty whether I’m staying home, but the confidence interval around “I am being careful” is really wide. Concrete guidance makes challenges easier to resolve. If masks work, states and communities should require them unequivocally. Cognitive biases are the reason to mark off six-foot spaces on the supermarket floor or circles in the grass at a park.

For social-distancing shaming to be a valuable public-health tool, average citizens should reserve it for overt defiance of clear official directives—failure to wear a mask when one is required—rather than mere cases of flawed judgment. In the meantime, money and power are located in public and private institutions that have access to public-health experts and the ability to propose specific behavioral norms. The bad judgments that really deserve shaming include the failure to facilitate testing, failure to protect essential workers, failure to release larger numbers of prisoners from facilities that have become COVID-19 hot spots, and failure to create the material conditions that permit strict isolation. America’s half-hearted reopening is a psychological morass, a setup for defeat that will be easy to blame on irresponsible individuals while culpable institutions evade scrutiny.

The info is here.

Amazon Halts Police Use Of Its Facial Recognition Technology

Bobby Allyn
www.npr.org
Originally posted 10 June 20

Amazon announced on Wednesday a one-year moratorium on police use of its facial-recognition technology, yielding to pressure from police-reform advocates and civil rights groups.

It is unclear how many law enforcement agencies in the U.S. deploy Amazon's artificial intelligence tool, but an official with the Washington County Sheriff's Office in Oregon confirmed that it will be suspending its use of Amazon's facial recognition technology.

Researchers have long criticized the technology for producing inaccurate results for people with darker skin. Studies have also shown that the technology can be biased against women and younger people.

IBM said earlier this week that it would quit the facial-recognition business altogether. In a letter to Congress, chief executive Arvind Krishna condemned software that is used "for mass surveillance, racial profiling, violations of basic human rights and freedoms."

And Microsoft President Brad Smith told The Washington Post during a livestream Thursday morning that his company has not been selling its technology to law enforcement. Smith said he has no plans to until there is a national law.

The info is here.

Moral Molecules: Morality as a combinatorial system

Curry, O. S., Alfano, M.,
Brandt, M. J., & Pelican, C. (2020, June 9).
https://doi.org/10.31219/osf.io/xnstk

Abstract

Is morality a combinatorial system in which a small number of simple moral ‘elements’ combine to form a large number of complex moral ‘molecules’? According to the theory of morality-as-cooperation, morality is a collection of biological and cultural solutions to the problems of cooperation recurrent in human social life. As evolutionary game theory has shown, there are many types of cooperation; hence, the theory explains many types of morality, including: family values, group loyalty, reciprocity, heroism, deference, fairness and property rights. As with any set of discrete items, these seven ‘elements’ can, in principle, be combined in multiple ways. But are they in practice? In this paper, we show that they are. For each combination of two elements, we hypothesise candidate moral molecules; and we successfully locate examples of them in the professional and popular literature. These molecules include: fraternity, blood revenge, family pride, filial piety, gavelkind, primogeniture, friendship, patriotism, tribute, diplomacy, common ownership, honour, confession, turn taking, restitution, modesty, mercy, munificence, arbitration, mendicancy, and queuing. Thus morality – like many other physical, biological, psychological and cultural systems – is indeed a combinatorial system. And morality-as-cooperation provides a principled and systematic taxonomy that has the potential to explain all moral ideas, possible and actual. Pursuing the many implications of this theory will help to place the study of morality on a more secure scientific footing.

Why Do People Avoid Facts That Could Help Them?

Francesca Gino
Scientific American
Originally posted 16 June 20

In our information age, an unprecedented amount of data are right at our fingertips. We run genetic tests on our unborn children to prepare for the worst. We get regular cancer screenings and monitor our health on our wrist and our phone. And we can learn about our ancestral ties and genetic predispositions with a simple swab of saliva.

Yet there’s some information that many of us do not want to know. A study of more than 2,000 people in Germany and Spain by Gerd Gigerenzer of the Max Planck Institute for Human Development in Berlin and Rocio Garcia-Retamero of the University of Granada in Spain found that 90 percent of them would not want to find out, if they could, when their partner would die or what the cause would be. And 87 percent also reported not wanting to be aware of the date of their own death. When asked if they’d want to know if, and when, they’d get divorced, more than 86 percent said no.

Related research points to a similar conclusion: We often prefer to avoid learning information that could cause us pain. Investors are less likely to log on to their stock portfolios on days when the market is down. And one laboratory experiment found that subjects who were informed that they were rated less attractive than other participants were willing to pay money not to find out their exact rank.

More consequentially, people avoid learning certain information related to their health even if having such knowledge would allow them to identify therapies to manage their symptoms or treatment. As one study found, only 7 percent of people at high risk for Huntington’s disease elect to find out whether they have the condition, despite the availability of a genetic test that is generally paid for by health insurance plans and the clear usefulness of the information for alleviating the chronic disease’s symptoms. Similarly,participants in a laboratory experiment chose to forgo part of their earnings to avoid learning the outcome of a test for a treatable sexually transmitted disease. Such avoidance was even greater when the disease symptoms were more severe.

The info is here.

Aging in an Era of Fake News

Brashier, N. M., & Schacter, D. L. (2020).
Current Directions in 
Psychological Science, 29(3), 316–323.

Abstract

Misinformation causes serious harm, from sowing doubt in modern medicine to inciting violence. Older adults are especially susceptible—they shared the most fake news during the 2016 U.S. election. The most intuitive explanation for this pattern lays the blame on cognitive deficits. Although older adults forget where they learned information, fluency remains intact, and knowledge accumulated across decades helps them evaluate claims. Thus, cognitive declines cannot fully explain older adults’ engagement with fake news. Late adulthood also involves social changes, including greater trust, difficulty detecting lies, and less emphasis on accuracy when communicating. In addition, older adults are relative newcomers to social media and may struggle to spot sponsored content or manipulated images. In a post-truth world, interventions should account for older adults’ shifting social goals and gaps in their digital literacy.

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The focus on “facts” at the expense of long-term trust is one reason why I see news organizations being ineffective in preventing, and in some cases facilitating, the establishment of “alternative narratives”. News reporting, as with any other type of declaration, can be ideologically, politically, and emotionally contested. The key differences in the current environment involve speed and transparency: First, people need to be exposed to the facts before the narrative can be strategically distorted through social media, distracting “leaks”, troll operations, and meme warfare. Second, while technological solutions for “fake news” are a valid effort, platforms policing content through opaque technologies adds yet another disruption in the layer of trust that should be reestablished directly between news organizations and their audiences.

A pdf can be found here.

Addiction, Identity, Morality

Earp, B.D., Skorburg, J.A. Everett, J. & Savulescu, J.
(2019) AJOB Empirical Bioethics, 10:2, 136-153.
DOI: 10.1080/23294515.2019.1590480

Background: Recent literature on addiction and judgments about the characteristics of agents has focused on the implications of adopting a “brain disease” versus “moral weakness” model of addiction. Typically, such judgments have to do with what capacities an agent has (e.g., the ability to abstain from substance use). Much less work, however, has been conducted on the relationship between addiction and judgments about an agent’s identity, including whether or to what extent an individual is seen as the same person after becoming addicted.

Methods: We conducted a series of vignette-based experiments (total N = 3,620) to assess lay attitudes concerning addiction and identity persistence, systematically manipulating key characteristics of agents and their drug of addiction.

Conclusions: In Study 1, we found that U.S. participants judged an agent who became addicted to drugs as being closer to “a completely different person” than “completely the same person” as the agent who existed prior to the addiction. In Studies 2–6, we investigated the intuitive basis for this result, finding that lay judgments of altered identity as a consequence of drug use and addiction are driven primarily by perceived negative changes in the moral character of drug users, who are seen as having deviated from their good true selves.

The research is here.

A Normative Approach to Artificial Moral Agency

Behdadi, D., Munthe, C.
Minds & Machines (2020). 
https://doi.org/10.1007/s11023-020-09525-8

Abstract

This paper proposes a methodological redirection of the philosophical debate on artificial moral agency (AMA) in view of increasingly pressing practical needs due to technological development. This “normative approach” suggests abandoning theoretical discussions about what conditions may hold for moral agency and to what extent these may be met by artificial entities such as AI systems and robots. Instead, the debate should focus on how and to what extent such entities should be included in human practices normally assuming moral agency and responsibility of participants. The proposal is backed up by an analysis of the AMA debate, which is found to be overly caught in the opposition between so-called standard and functionalist conceptions of moral agency, conceptually confused and practically inert. Additionally, we outline some main themes of research in need of attention in light of the suggested normative approach to AMA.

Conclusion

We have argued that to be able to contribute to pressing practical problems, the debate on AMA should be redirected to address outright normative ethical questions. Specifically, the questions of how and to what extent artificial entities should be involved in human practices where we normally assume moral agency and responsibility. The reason for our proposal is the high degree of conceptual confusion and lack of practical usefulness of the traditional AMA debate. And this reason seems especially strong in light of the current fast development and implementation of advanced, autonomous and self-evolving AI and robotic constructs.

Can COVID-19 re-invigorate ethics?

Louise Campbell
BMJ Blogs
Originally posted 26 May 20

The COVID-19 pandemic has catapulted ethics into the spotlight.  Questions previously deliberated about by small numbers of people interested in or affected by particular issues are now being posed with an unprecedented urgency right across the public domain.  One of the interesting facets of this development is the way in which the questions we are asking now draw attention, not just to the importance of ethics in public life, but to the very nature of ethics as practice, namely ethics as it is applied to specific societal and environmental concerns.

Some of these questions which have captured the public imagination were originally debated specifically within healthcare circles and at the level of health policy: what measures must be taken to prevent hospitals from becoming overwhelmed if there is a surge in the number of people requiring hospitalisation?  How will critical care resources such as ventilators be prioritised if need outstrips supply?  In a crisis situation, will older people or people with disabilities have the same opportunities to access scarce resources, even though they may have less chance of survival than people without age-related conditions or disabilities?  What level of risk should healthcare workers be expected to assume when treating patients in situations in which personal protective equipment may be inadequate or unavailable?   Have the rights of patients with chronic conditions been traded off against the need to prepare the health service to meet a demand which to date has not arisen?  Will the response to COVID-19 based on current evidence compromise the capacity of the health system to provide routine outpatient and non-emergency care to patients in the near future?

Other questions relate more broadly to the intersection between health and society: how do we calculate the harms of compelling entire populations to isolate themselves from loved ones and from their communities?  How do we balance these harms against the risks of giving people more autonomy to act responsibly?  What consideration is given to the fact that, in an unequal society, restrictions on liberty will affect certain social groups in disproportionate ways?  What does the catastrophic impact of COVID-19 on residents of nursing homes say about our priorities as a society and to what extent is their plight our collective responsibility?  What steps have been taken to protect marginalised communities who are at greater risk from an outbreak of infectious disease: for example, people who have no choice but to coexist in close proximity with one another in direct provision centres, in prison settings and on halting sites?

The info is here.

Racial bias skews algorithms widely used to guide care from heart surgery to birth, study finds

Sharon Begley
statnews.com
Originally posted 17 June 20

Here is an excerpt:

All 13 of the algorithms Jones and his colleagues examined offered rationales for including race in a way that, presumably unintentionally, made Black and, in some cases, Latinx patients less likely to receive appropriate care. But when you trace those rationales back to their origins, Jones said, “you find outdated science or biased data,” such as simplistically concluding that poor outcomes for Black patients are due to race.

Typically, developers based their algorithms on studies showing a correlation between race and some medical outcome, assuming race explained or was even the cause of, say, a poorer outcome (from a vaginal birth after a cesarean, say). They generally did not examine whether factors that typically go along with race in the U.S., such as access to primary care or socioeconomic status or discrimination, might be the true drivers of the correlation.

“Modern tools of epidemiology and statistics could sort that out,” Jones said, “and show that much of what passes for race is actually about class and poverty.”

Including race in a clinical algorithm can sometimes be appropriate, Powers cautioned: “It could lead to better patient care or even be a tool for addressing inequities.” But it might also exacerbate inequities. Figuring out the algorithms’ consequences “requires taking a close look at how the algorithm was trained, the data used to make predictions, the accuracy of those predictions, and how the algorithm is used in practice,” Powers said. “Unfortunately, we don’t have these answers for many of the algorithms.”

The info is here.