McKay Coppins
The Atlantic
Originally posted December 7, 2017
Here is an excerpt:
For decades, the belief that private morality was essential to assessing the worthiness of politicians and public figures was an animating ideal at the core of the Christian right’s credo. As with most ideals, the movement did not always live up to its own standards. So-called “values voters” pursued a polarizing, multi-faceted agenda that was often tangled up in prejudice and partisanship. They fiercely defended Clarence Thomas when he was accused of sexually harassing Anita Hill, for example, and then excoriated Bill Clinton for his affair with Monica Lewinsky.
But even when they were failing to hold their own side accountable, they still clung to the idea that “character counts.” As recently as 2011, a poll by the Public Religion Research Institute found that only 30 percent of white evangelicals believed “an elected official who commits an immoral act in their personal life can still behave ethically and fulfill their duties in their public and professional life.” But by the time Donald Trump was running for president in 2016, that number had risen sharply to 72 percent. White evangelicals are now more tolerant of immoral behavior by elected officials than the average American. “This is really a sea change in evangelical ethics,” Robert P. Jones, the head of the institute and the author of The End of White Christian America, recently told me.
(cut)
“The way evangelicals see the world, the culture is not only slipping away—it’s slipping away in all caps, with four exclamation points after that. It’s going to you-know-what in a handbasket,” Brody told me. “Where does that leave evangelicals? It leaves them with a choice. Do they sacrifice a little bit of that ethical guideline they’ve used in the past in exchange for what they believe is saving the culture?”
The article is here.
Sunday, December 10, 2017
These are the Therapist Behaviors that are Helpful or Harmful
Christian Jarrett
Research Digest
Originally published November 23, 2017
Here is an excerpt:
The most helpful therapy moments involved specific treatment techniques, such as times the therapist gave the client a concrete strategy they could use in everyday life; instances when the therapist made connections for the client (such as identifying events that affected their depression symptoms); or helped them process their emotions. Other helpful moments involved fundamental therapist skills, such as listening and expressing empathy, offering support or praise, or when the therapist discussed the process of therapy, including what the client wants from it.
The clients said they found these moments helpful because they learned a new skill, felt heard or understood, gained insight and/or were better able to process their emotions.
In terms of hindering therapist behaviours, these often seemed the same, superficially at least, as the helpful behaviours, including instances when the therapist listened, attempted to express empathy, or attempted to structure the session. The difference seemed to be in the execution or timing of these behaviours. The clients said they found these moments unhelpful when they were off-topic (for instance, their therapist listened to them “rambling” on about irrelevant details without intervening); when they felt like they were being judged; or they felt it was too soon for them to confront a particular issue.
The article is here.
Research Digest
Originally published November 23, 2017
Here is an excerpt:
The most helpful therapy moments involved specific treatment techniques, such as times the therapist gave the client a concrete strategy they could use in everyday life; instances when the therapist made connections for the client (such as identifying events that affected their depression symptoms); or helped them process their emotions. Other helpful moments involved fundamental therapist skills, such as listening and expressing empathy, offering support or praise, or when the therapist discussed the process of therapy, including what the client wants from it.
The clients said they found these moments helpful because they learned a new skill, felt heard or understood, gained insight and/or were better able to process their emotions.
In terms of hindering therapist behaviours, these often seemed the same, superficially at least, as the helpful behaviours, including instances when the therapist listened, attempted to express empathy, or attempted to structure the session. The difference seemed to be in the execution or timing of these behaviours. The clients said they found these moments unhelpful when they were off-topic (for instance, their therapist listened to them “rambling” on about irrelevant details without intervening); when they felt like they were being judged; or they felt it was too soon for them to confront a particular issue.
The article is here.
Saturday, December 9, 2017
The Root of All Cruelty
Paul Bloom
The New Yorker
Originally published November 20, 2017
Here are two excerpts:
Early psychological research on dehumanization looked at what made the Nazis different from the rest of us. But psychologists now talk about the ubiquity of dehumanization. Nick Haslam, at the University of Melbourne, and Steve Loughnan, at the University of Edinburgh, provide a list of examples, including some painfully mundane ones: “Outraged members of the public call sex offenders animals. Psychopaths treat victims merely as means to their vicious ends. The poor are mocked as libidinous dolts. Passersby look through homeless people as if they were transparent obstacles. Dementia sufferers are represented in the media as shuffling zombies.”
The thesis that viewing others as objects or animals enables our very worst conduct would seem to explain a great deal. Yet there’s reason to think that it’s almost the opposite of the truth.
(cut)
But “Virtuous Violence: Hurting and Killing to Create, Sustain, End, and Honor Social Relationships” (Cambridge), by the anthropologist Alan Fiske and the psychologist Tage Rai, argues that these standard accounts often have it backward. In many instances, violence is neither a cold-blooded solution to a problem nor a failure of inhibition; most of all, it doesn’t entail a blindness to moral considerations. On the contrary, morality is often a motivating force: “People are impelled to violence when they feel that to regulate certain social relationships, imposing suffering or death is necessary, natural, legitimate, desirable, condoned, admired, and ethically gratifying.” Obvious examples include suicide bombings, honor killings, and the torture of prisoners during war, but Fiske and Rai extend the list to gang fights and violence toward intimate partners. For Fiske and Rai, actions like these often reflect the desire to do the right thing, to exact just vengeance, or to teach someone a lesson. There’s a profound continuity between such acts and the punishments that—in the name of requital, deterrence, or discipline—the criminal-justice system lawfully imposes. Moral violence, whether reflected in legal sanctions, the killing of enemy soldiers in war, or punishing someone for an ethical transgression, is motivated by the recognition that its victim is a moral agent, someone fully human.
The article is here.
The New Yorker
Originally published November 20, 2017
Here are two excerpts:
Early psychological research on dehumanization looked at what made the Nazis different from the rest of us. But psychologists now talk about the ubiquity of dehumanization. Nick Haslam, at the University of Melbourne, and Steve Loughnan, at the University of Edinburgh, provide a list of examples, including some painfully mundane ones: “Outraged members of the public call sex offenders animals. Psychopaths treat victims merely as means to their vicious ends. The poor are mocked as libidinous dolts. Passersby look through homeless people as if they were transparent obstacles. Dementia sufferers are represented in the media as shuffling zombies.”
The thesis that viewing others as objects or animals enables our very worst conduct would seem to explain a great deal. Yet there’s reason to think that it’s almost the opposite of the truth.
(cut)
But “Virtuous Violence: Hurting and Killing to Create, Sustain, End, and Honor Social Relationships” (Cambridge), by the anthropologist Alan Fiske and the psychologist Tage Rai, argues that these standard accounts often have it backward. In many instances, violence is neither a cold-blooded solution to a problem nor a failure of inhibition; most of all, it doesn’t entail a blindness to moral considerations. On the contrary, morality is often a motivating force: “People are impelled to violence when they feel that to regulate certain social relationships, imposing suffering or death is necessary, natural, legitimate, desirable, condoned, admired, and ethically gratifying.” Obvious examples include suicide bombings, honor killings, and the torture of prisoners during war, but Fiske and Rai extend the list to gang fights and violence toward intimate partners. For Fiske and Rai, actions like these often reflect the desire to do the right thing, to exact just vengeance, or to teach someone a lesson. There’s a profound continuity between such acts and the punishments that—in the name of requital, deterrence, or discipline—the criminal-justice system lawfully imposes. Moral violence, whether reflected in legal sanctions, the killing of enemy soldiers in war, or punishing someone for an ethical transgression, is motivated by the recognition that its victim is a moral agent, someone fully human.
The article is here.
Evidence-Based Policy Mistakes
Kausik Basu
Project Syndicate
Originally published November 30, 2017
Here is an excerpt:
Likewise, US President Donald Trump cites simplistic trade-deficit figures to justify protectionist policies that win him support among a certain segment of the US population. In reality, the evidence suggests that such policies will hurt the very people Trump claims to be protecting.
Now, the chair of Trump’s Council of Economic Advisers, Kevin Hassett, is attempting to defend Congressional Republicans’ effort to slash corporate taxes by claiming that, when developed countries have done so in the past, workers gained “well north of” $4,000 per year. Yet there is ample evidence that the benefits of such tax cuts accrue disproportionately to the rich, largely via companies buying back stock and shareholders earning higher dividends.
It is not clear whence Hassett is getting his data. But chances are that, at the very least, he is misinterpreting it. And he is far from alone in failing to reach accurate conclusions when assessing a given set of data.
Consider the oft-repeated refrain that, because there is evidence that virtually all jobs over the last decade were created by the private sector, the private sector must be the most effective job creator. At first glance, the logic might seem sound. But, on closer examination, the statement begs the question. Imagine a Soviet economist claiming that, because the government created virtually all jobs in the Soviet Union, the government must be the most effective job creator. To find the truth, one would need, at a minimum, data on who else tried to create jobs, and how.
The article is here.
Project Syndicate
Originally published November 30, 2017
Here is an excerpt:
Likewise, US President Donald Trump cites simplistic trade-deficit figures to justify protectionist policies that win him support among a certain segment of the US population. In reality, the evidence suggests that such policies will hurt the very people Trump claims to be protecting.
Now, the chair of Trump’s Council of Economic Advisers, Kevin Hassett, is attempting to defend Congressional Republicans’ effort to slash corporate taxes by claiming that, when developed countries have done so in the past, workers gained “well north of” $4,000 per year. Yet there is ample evidence that the benefits of such tax cuts accrue disproportionately to the rich, largely via companies buying back stock and shareholders earning higher dividends.
It is not clear whence Hassett is getting his data. But chances are that, at the very least, he is misinterpreting it. And he is far from alone in failing to reach accurate conclusions when assessing a given set of data.
Consider the oft-repeated refrain that, because there is evidence that virtually all jobs over the last decade were created by the private sector, the private sector must be the most effective job creator. At first glance, the logic might seem sound. But, on closer examination, the statement begs the question. Imagine a Soviet economist claiming that, because the government created virtually all jobs in the Soviet Union, the government must be the most effective job creator. To find the truth, one would need, at a minimum, data on who else tried to create jobs, and how.
The article is here.
Friday, December 8, 2017
University could lose millions from “unethical” research backed by Peter Thiel
Beth Mole
ARS Technica
Originally published November 14, 2017
Here is an excerpt:
According to HHS records, SIU (Southern Illinois University) had committed to following all HHS regulations—including safety requirements and having IRB approval and oversight—for all clinical trials, regardless of who funded the trials. If SIU fails to do so, it could jeopardize the $15 million in federal grant money the university receives for its other research.
Earlier, an SIU spokesperson had claimed that SIU didn’t need to follow HHS regulations in this case because Halford was acting as an independent researcher with Rational Vaccines. Thus, SIU had no legal responsibility to ensure proper safety protocols and wasn’t risking its federal funding.
In her e-mail, Buchanan asked for the “results of SIU’s evaluation of its jurisdiction over this research.”
In his response, Kruse noted that SIU was not aware of the St. Kitts trial until October 2016, two months after the trial was completed. But, he wrote, the university had opened an investigation into Halford’s work following his death in June of this year. The decision to investigate was also based on disclosures from American filmmaker AgustÃn Fernández III, who co-founded Rational Vaccines with Halford, Kruse noted.
The article is here.
ARS Technica
Originally published November 14, 2017
Here is an excerpt:
According to HHS records, SIU (Southern Illinois University) had committed to following all HHS regulations—including safety requirements and having IRB approval and oversight—for all clinical trials, regardless of who funded the trials. If SIU fails to do so, it could jeopardize the $15 million in federal grant money the university receives for its other research.
Earlier, an SIU spokesperson had claimed that SIU didn’t need to follow HHS regulations in this case because Halford was acting as an independent researcher with Rational Vaccines. Thus, SIU had no legal responsibility to ensure proper safety protocols and wasn’t risking its federal funding.
In her e-mail, Buchanan asked for the “results of SIU’s evaluation of its jurisdiction over this research.”
In his response, Kruse noted that SIU was not aware of the St. Kitts trial until October 2016, two months after the trial was completed. But, he wrote, the university had opened an investigation into Halford’s work following his death in June of this year. The decision to investigate was also based on disclosures from American filmmaker AgustÃn Fernández III, who co-founded Rational Vaccines with Halford, Kruse noted.
The article is here.
Autonomous future could question legal ethics
Becky Raspe
Cleveland Jewish News
Originally published November 21, 2017
Here is an excerpt:
Northman said he finds the ethical implications of an autonomous future interesting, but completely contradictory to what he learned in law school in the 1990s.
“People were expected to be responsible for their activities,” he said. “And as long as it was within their means to stop something or more tellingly anticipate a problem before it occurs, they have an obligation to do so. When you blend software over the top of that this level of autonomy, we are left with some difficult boundaries to try and assess where a driver’s responsibility starts or the software programmers continues on.”
When considering the ethics surrounding autonomous living, Paris referenced the “trolley problem.” The trolley problem goes as this: there is an automated vehicle operating on an open road, and ahead there are five people in the road and one person off to the side. The question here, Paris said, is should the vehicle consider traveling on and hitting the five people or will it swerve and hit just the one?
“When humans are driving vehicles, they are the moral decision makers that make those choices behind the wheel,” she said. “Can engineers program automated vehicles to replace that moral thought with an algorithm? Will they prioritize the five lives or that one person? There are a lot of questions and not too many solutions at this point. With these ethical dilemmas, you have to be careful about what is being implemented.”
The article is here.
Cleveland Jewish News
Originally published November 21, 2017
Here is an excerpt:
Northman said he finds the ethical implications of an autonomous future interesting, but completely contradictory to what he learned in law school in the 1990s.
“People were expected to be responsible for their activities,” he said. “And as long as it was within their means to stop something or more tellingly anticipate a problem before it occurs, they have an obligation to do so. When you blend software over the top of that this level of autonomy, we are left with some difficult boundaries to try and assess where a driver’s responsibility starts or the software programmers continues on.”
When considering the ethics surrounding autonomous living, Paris referenced the “trolley problem.” The trolley problem goes as this: there is an automated vehicle operating on an open road, and ahead there are five people in the road and one person off to the side. The question here, Paris said, is should the vehicle consider traveling on and hitting the five people or will it swerve and hit just the one?
“When humans are driving vehicles, they are the moral decision makers that make those choices behind the wheel,” she said. “Can engineers program automated vehicles to replace that moral thought with an algorithm? Will they prioritize the five lives or that one person? There are a lot of questions and not too many solutions at this point. With these ethical dilemmas, you have to be careful about what is being implemented.”
The article is here.
Thursday, December 7, 2017
Social media threat: People learned to survive disease, we can handle Twitter
Glenn Harlan Reynolds
USA Today
Originally posted November 20, 2017
Here is an excerpt:
Hunters and gatherers were at far less risk for infectious disease because they didn’t encounter very many new people very often. Their exposure was low, and contact among such bands was sporadic enough that diseases couldn’t spread very fast.
It wasn’t until you crowded thousands, or tens of thousands of them, along with their animals, into small dense areas with poor sanitation that disease outbreaks took off. Instead of meeting dozens of new people per year, an urban dweller probably encountered hundreds per day. Diseases that would have affected only a few people at a time as they spread slowly across a continent (or just burned out for lack of new carriers) would now leap from person to person in a flash.
Likewise, in recent years we’ve gone from an era when ideas spread comparatively slowly, to one in which social media in particular allow them to spread like wildfire. Sometimes that’s good, when they’re good ideas. But most ideas are probably bad; certainly 90% of ideas aren’t in the top 10%. Maybe we don’t know the mental disease vectors that we’re inadvertently unleashing.
It took three things to help control the spread of disease in cities: sanitation, acclimation and better nutrition. In early cities, after all, people had no idea how diseases spread, something we didn’t fully understand until the late 19th century. But rule-of-thumb sanitation made things a lot better over time. Also, populations eventually adapted: Diseases became endemic, not epidemic, and usually less severe as people developed immunity. And finally, as Scott notes, surviving disease was always a function of nutrition, with better-nourished populations doing much better than malnourished ones.
The article is here.
USA Today
Originally posted November 20, 2017
Here is an excerpt:
Hunters and gatherers were at far less risk for infectious disease because they didn’t encounter very many new people very often. Their exposure was low, and contact among such bands was sporadic enough that diseases couldn’t spread very fast.
It wasn’t until you crowded thousands, or tens of thousands of them, along with their animals, into small dense areas with poor sanitation that disease outbreaks took off. Instead of meeting dozens of new people per year, an urban dweller probably encountered hundreds per day. Diseases that would have affected only a few people at a time as they spread slowly across a continent (or just burned out for lack of new carriers) would now leap from person to person in a flash.
Likewise, in recent years we’ve gone from an era when ideas spread comparatively slowly, to one in which social media in particular allow them to spread like wildfire. Sometimes that’s good, when they’re good ideas. But most ideas are probably bad; certainly 90% of ideas aren’t in the top 10%. Maybe we don’t know the mental disease vectors that we’re inadvertently unleashing.
It took three things to help control the spread of disease in cities: sanitation, acclimation and better nutrition. In early cities, after all, people had no idea how diseases spread, something we didn’t fully understand until the late 19th century. But rule-of-thumb sanitation made things a lot better over time. Also, populations eventually adapted: Diseases became endemic, not epidemic, and usually less severe as people developed immunity. And finally, as Scott notes, surviving disease was always a function of nutrition, with better-nourished populations doing much better than malnourished ones.
The article is here.
Attica: It’s Worse Than We Thought
Heather Ann Thompson
The New York Times
Originally posted November 19, 2017
Here is an excerpt:
As the fine print of that 1972 article read: “We are indebted to the inmates of the Attica Correctional Facility who participated in this study and to the warden and his administration for their help and cooperation.” This esteemed physician, a man working for two of New York’s most respected hospitals and receiving generous research funding from the N.I.H., was indeed conducting leprosy experiments at Attica.
But which of Attica’s nearly 2,400 prisoners, I wondered, was the subject of experiments relating to this crippling disease, without, as Dr. Brandriss admitted, adequate consent? Might it have been the 19-year-old who was at Attica because he had sliced the top of a neighbor’s convertible? Or a man imprisoned there for more serious offenses? Either way, no jury had sentenced them to being a guinea pig in any experiment relating to a disease as painful and disfiguring as leprosy.
And what about the hundreds of corrections officers and civilian employees working at Attica? Even if no one in this extremely crowded facility was actually exposed to this dreaded disease, one in which “prolonged close contact” with an infected patient is a most serious risk factor, were these state employees at all informed that medical experiments being conducted on the men in their charge?
This is not the first time prisons have allowed secret medical experiments on those locked inside. A 1998 book on Holmesburg Prison in Pennsylvania revealed that a doctor there, Albert Kligman, had been experimenting on prisoners for years. After the book appeared, nearly 300 former prisoners sued him, the University of Pennsylvania and the manufacturers of the substances to which they had been exposed, but none of the defendants was held accountable.
The article is here.
The New York Times
Originally posted November 19, 2017
Here is an excerpt:
As the fine print of that 1972 article read: “We are indebted to the inmates of the Attica Correctional Facility who participated in this study and to the warden and his administration for their help and cooperation.” This esteemed physician, a man working for two of New York’s most respected hospitals and receiving generous research funding from the N.I.H., was indeed conducting leprosy experiments at Attica.
But which of Attica’s nearly 2,400 prisoners, I wondered, was the subject of experiments relating to this crippling disease, without, as Dr. Brandriss admitted, adequate consent? Might it have been the 19-year-old who was at Attica because he had sliced the top of a neighbor’s convertible? Or a man imprisoned there for more serious offenses? Either way, no jury had sentenced them to being a guinea pig in any experiment relating to a disease as painful and disfiguring as leprosy.
And what about the hundreds of corrections officers and civilian employees working at Attica? Even if no one in this extremely crowded facility was actually exposed to this dreaded disease, one in which “prolonged close contact” with an infected patient is a most serious risk factor, were these state employees at all informed that medical experiments being conducted on the men in their charge?
This is not the first time prisons have allowed secret medical experiments on those locked inside. A 1998 book on Holmesburg Prison in Pennsylvania revealed that a doctor there, Albert Kligman, had been experimenting on prisoners for years. After the book appeared, nearly 300 former prisoners sued him, the University of Pennsylvania and the manufacturers of the substances to which they had been exposed, but none of the defendants was held accountable.
The article is here.
Wednesday, December 6, 2017
What the heck is machine learning, and why is it everywhere these days?
Luke Dormehl
Digital Trends
Originally published November 18, 2017
Here is an excerpt:
Which programming languages to machine learners use?
Like the question above, there’s no one answer to this. Machine learning is a big field and, with so much ground to cover, there’s no one language that does absolutely everything.
Due to its simplicity, and the availability of deep learning libraries such as TensorFlow and PyTorch, Python is currently the number one language. If you’re thinking about delving into machine learning for the first time, it’s also one of the most accessible languages — and there are loads of online resources available.
Java is a good option, too, and comes with a great community of its own, while C++ and R are also worth checking out.
Is machine learning the perfect solution to all our AI problems?
You can probably guess where we’re going with this. No, machine learning isn’t infallible. Algorithms can still be subject to human biases, and the rule of “garbage in, garbage out” holds as true here as it does to any other data-driven field.
There are also questions about transparency, particularly when you’re dealing with the kind of “black boxes” that are an essential part of neural networks.
But as a tool that’s helping to revolutionize technology as we know it, and making AI available to the masses? You bet that it’s a great tool!
The article is here.
Digital Trends
Originally published November 18, 2017
Here is an excerpt:
Which programming languages to machine learners use?
Like the question above, there’s no one answer to this. Machine learning is a big field and, with so much ground to cover, there’s no one language that does absolutely everything.
Due to its simplicity, and the availability of deep learning libraries such as TensorFlow and PyTorch, Python is currently the number one language. If you’re thinking about delving into machine learning for the first time, it’s also one of the most accessible languages — and there are loads of online resources available.
Java is a good option, too, and comes with a great community of its own, while C++ and R are also worth checking out.
Is machine learning the perfect solution to all our AI problems?
You can probably guess where we’re going with this. No, machine learning isn’t infallible. Algorithms can still be subject to human biases, and the rule of “garbage in, garbage out” holds as true here as it does to any other data-driven field.
There are also questions about transparency, particularly when you’re dealing with the kind of “black boxes” that are an essential part of neural networks.
But as a tool that’s helping to revolutionize technology as we know it, and making AI available to the masses? You bet that it’s a great tool!
The article is here.
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