Dreamers and the Trump Base

September 15, 2017
Posted by Jay Livingston

People whose life is in politics develop a firm ideology. Ordinary voters have no such need for consistency.

“Word of Deal Bewilders and Angers Trump’s Base,” says a subhead in today’s New York Times about DACA.  The deal in question was Trump’s agreement with his new friends Chuck and Nancy to let the Dreamers keep dreaming for at least another half year. Over on the right, the loud voices are getting shrill. The Times story quotes people like Ann Coulter (“At this point, who DOESN’T want Trump impeached?”), Rep. Steve King, and some talk-radio conservatives. 

But the people who voted for Trump are more loyal to him. Also more ideologically flexible. It’s Trump the person they want, not any particular policy. On some matters, their ardor for Trump has led them to change their long-held views. Russia is no longer a terrible villain. A politician’s private peccadilloes now mean little for his performance in office. Obamacare isn’t so terrible after all.

Given Trump’s campaign rhetoric and the “Build the Wall” chant, you might expect his supporters to be more adamant on immigration. But even before Trump’s change of heart on DACA, his base was soft on Dreamers, though the polls on this are not consistent. A YouGov poll taken September 3 -5 asked Trump voters.

Do you favor or oppose DACA, Deferred Action for Childhood Arrivals, which is a policy that grants temporary legal status to “dreamers,” otherwise law-abiding children and young adults who were brought into the United States at a very young age by parents who were illegal immigrants?

(Click on an image for a larger view.)

The DACA glass is half empty. A third of the Trumpistas are firm opponents. But on the other side a third of the Trump voters actually support DACA, and the rest aren’t sure.

A Morning Consult Poll for Politico taken a few days earlier found Trump voters to be still more accepting of Dreamers and even non-dreamers.
“As you may know, Dreamers are young people who were brought to the United States illegally when they were children, often with their parents. Which of the following do you think is the best way to handle Dreamers?” The poll also about the best way to handle “immigrants currently living in the United States illegally.” The choices were”

• They should beallowed to stay and become citizens if they meet certain requirements 
• They should be allowed to stay and become legal sidents, but NOT citizens, if they meet certain requirements
• They should be removed or deported from the United States
• Don’t Know / No Opinion           

Two-thirds of Trump voters wanted to allow the Dreamers to stay. Slightly more than half were OK with granting residence (22%) or even citizenship (33%) to all immigrants now living in the US illegally.

When Trump took office, his net approval was +4 (45% Approve, 41% Disapprove). Since then, he has managed to drive that figure to – 14 (39 - 55). His recent change on DACA may have cost him cred with Coulter and other people deeply involved in politics. But it seems unlikely that his support with the public at large or even his base will fall any farther.

Algorithms and False Positives

September 13, 2017
Posted by Jay Livingston

Can face-recognition software tell if you’re gay?

Here’s the headline from The Guardian a week ago.

Yilun Wang and Michal Kosinski at Stanford’s School of Business have written an article showing that artificial intelligence – machines that can learn from their experiences – can develop algorithms to distinguish the gay from the straight. Kosinski goes farther. According to Business Insider,

He predicts that self-learning algorithms with human characteristics will also be able to identify:

• a person’s political beliefs
• whether they have high IQs
• whether they are predisposed to criminal behaviour

When I read that last line, something clicked. I remembered that a while ago I had blogged about an Israeli company, Faception, that claimed its face recognition software could pick out the faces of terrorists, professional poker players, and other types. It all reminded me of Cesare Lombroso, the Italian criminologist. Nearly 150 years ago, Lombroso claimed that criminals could be distinguished by the shape of their skulls, ears, noses, chins, etc. (That blog post, complete with pictures from Lombroso’s book, is here.) So I was not surprised to learn that Kosinski had worked with Faception.

For a thorough (3000 word) critique of the Wang-Kosinski paper, see Greggor Mattson’s post at Scatterplot. The part I want to emphasize here is the problem of False Positives.

Wang-Kosinski tested their algorithm by showing a series of paired pictures from a dating site. In each pair, one person was gay, the other straight. The task was to guess which was which. The machine’s accuracy was roughly 80% – much better than guessing randomly and better than the guesses made by actual humans, who got about 60% right. (These are the numbers for photos of men only. The machine and humans were not as good at spotting lesbians. In my hypothetical example that follows, assume that all the photos are of men.)

But does that mean that the face-recognition algorithm can spot the gay person? The trouble with Wang-Kosinki’s gaydar test was that it created a world where half the population was gay. For each trial, people or machine saw one gay person and one straight.

Let’s suppose that the machine had an accuracy rate of 90%. Let’s also present the machine with a 50-50 world. Looking at the 50 gays, the machine will guess correctly on 45. These are “True Positives.” It identified them as gay, and they were gay. But it will also classify 5 of the gay people as not-gay. These are the False Negatives.

It will have the same ratio of true and false for the not-gay population. It will correctly identify 45 of the not-gays (True Negatives), but it will guess incorrectly that 5 of these straight people are gay (False Positive).

It looks pretty good. But how well will this work in the real world, where the gay-straight ratio is nowhere near 50-50? Just what that ratio is depends on definitions. But to make the math easier, I’m going to use 5% as my estimate. In a sample of 1000, only 50 will be gay. The other 950 will be straight.

Again, let’s give the machine an accuracy rate of 90%. For the 50 gays, it will again have 45 True Positives and 5 False Negatives. But what about the 950 not-gays. It will be correct 90% of the time and identify 885 of them as not-gay (True Negatives). But it will also guess incorrectly that 10% are gay. That’s 95 False Positives.

The number of False Positives is more than double the number of True Positives. The overall accuracy may be 90%, but when it comes to picking out gays, the machine is wrong far more often than it’s right.

The rarer the thing that you’re trying to predict, the greater the ratio of False Positives to True Positives. And those False Positives can have bad consequences. In medicine, a false positive diagnosis can lead to unnecessary treatment that is physically and psychologically damaging. As for politics and policy, think of the consequences if the government goes full Lomborso and uses algorithms for predicting “predisposition to criminal behavior.”

Smartphones and Teen Existential Angst

September 12, 2017
Posted by Jay Livingston

I’ve been wondering about America’s youth, mostly because of the Atlantic article by Jean Twenge: “Have Smartphones Destroyed a Generation?”  (Previous posts are here  and here .)
As the title of the article suggests, we’ve got trouble.

Around 2012, I noticed abrupt shifts in teen behaviors and emotional states. The gentle slopes of the line graphs became steep mountains and sheer cliffs . . . At first I presumed these might be blips, but the trends persisted, across several years and a series of national surveys. The changes weren’t just in degree, but in kind.

Twenge shows how kids differ from those of just a few years ago in how they spend their time – less dating, driving, and hanging out with peers, and more time on their phones, tablets, and computers. These changes in behavior, Twenge claims, have psychological consequences.

The biggest difference between the Millennials and their predecessors was in how they viewed the world. . . . There is compelling evidence that the devices we’ve placed in young people’s hands are having profound effects on their lives—and making them seriously unhappy.

I went to the archives of Monitoring the Future, the only source of systematic data that Twenge mentions. It surveys kids in 8th, 10th, and 12th grades. I looked only at the data on 12th graders. One of the MTF questions asks kids whether they agree with the statement, “It feels good to be alive.” The choices are Agree, Mostly Agree, Neither, Mostly Disagree, Disagree.” So few kids chose either of the Disagree categories ( 4- 6 %) that I combined them with Neither.

(Click on a graph for a larger view.)

In the most recent year, these depressive categories accounted for only 18% of 12th graders. All the others agreed – 51% gave unqualified agreement, another 20% “mostly” agreed. More important for Twenge’s argument, the graph lines do not fall off a cliff in 2012 or in any other year. There’s a slow decline 2012-2015, but the numbers in the most recent year are very similar to what they were in before smartphones and social media.

Monitoring the Future also asks a question that would seem to tap depression, or at least existential despair*: “Life often seems meaningless.” The levels of agreement are the same ones as for “Good to be alive,” but the distribution of answers is more even.

Again, the sunnier choices carry the day. Those who “Disagree” categorically out number all others, followed by those who disagree but with some reservations. And again, the MTF data shows no dramatic changes.

So, “Have Smartphones Destroyed a Generation?” As I said in a previous post on this topic,

Whenever the title of a book or article is phrased as a question, two things are almost certain

• The author thinks that the answer to the question is “Yes.”
• The more accurate answer is “No.”

When it comes to finding life meaningful or worth living, teens today are no different from those teens twenty years ago who were sans iPhones, sans Facebook, sans Instagram, sans cyber-everything.
----------------------------
*

In the view of the existentialist, the individual's starting point is characterized by what has been called "the existential attitude", or a sense of disorientation, confusion, or dread in the face of an apparently meaningless or absurd world. Existentialism - Wikipedia https://en.wikipedia.org/wiki/Existentialism

America’s Not-So-Lost Youth

September 10, 2017
Posted by Jay Livingston

It seems that we never tire of experts like Prof. Harold Hill, the con artist in “The Music Man,” warning us about the temptations that threaten to lead our children astray. That musical was set in Iowa a century ago, and when Prof. Hill told the good people of River City, “Ya got trouble, my friends,” the culprit was a pool table. I’m old enough to remember when the menace was comic books. Today it’s social media. All those kids spending so much time on Facebook, Instagram, and iPhones – surely that can’t be good.

Last month, The Atlantic ran an article in full Music Man mode – “Have Smartphones Destroyed a Generation?” by Jean Twenge .

I blogged my skepticism (here). Twenge’s previous alarmist reports – The Narcissism Epidemic, for example – had not held up well against the evidence. But I had not been able to deal with the data sets from Monitoring the Future (MTF) that Twenge used for evidence about the destruction supposedly being wrought by iPhones. I didn’t know it at the time, but Alexandra Samuel had already done some of the work. (Her article is at JStor – here)

Twenge acknowledges that kids today cause far less trouble than did their counterparts of earlier generations. Juvenile crime is way down. The same goes for pregnancy, drugs, and abortion. But, says Twenge, the kids are not all right. They are desperately unhappy. Or as the Atlantic sub-head puts it, they are “on the brink of a mental-health crisis.”  Ya got trouble my friends.

According to Twenge, the crucial year is 2012. “Around 2012, I noticed abrupt shifts in teen behaviors and emotional states.” It turns out that the MTF survey of kids does not have many mental-health items – nothing about anxiety or depression. It does ask about happiness. Here is a graph from Alexandra Samuel’s article. The survey asks kids how happy they are generally – Very Happy, Pretty Happy, or Not Too Happy.

(Click on an image for a larger view.)

The biggest winner by far is Pretty Happy, chosen by 60-65%, a proportion that has not changed much since the first years of the survey. Since 2012, the percent reporting that they are Very Happy has decreased by perhaps 4 percentage points. Not Too Happy has increased by 2-3 percentage points. This hardly seems like the leading edge of a mental-health crisis.

As for the insidious effects of Facebook, Instagram and the rest, Samuel has a graph comparing kids who spend more time with social media (> 10 hours a week) and those who spend less. This too doesn’t do much to support Twenge’s claim that iPhones and the like are making kids “seriously unhappy.”

I don’t doubt that social media and smartphones have changed the way kids live their lives. Twenge presents evidence that kids are spending less time hanging out with peers, that they feel less pressure to drive a car, and that dating and sex are on the decline. I’d like to check the MTF data, but assuming Twenge’s report is accurate, are these trends a sign of a pending crisis in mental health? I seem to remember Harold Hill types warning about the dangers of peer groups, cars (remember those warnings about hot rodders?), and of course sex.  The Twenge types of a few decades ago were warning that kids were spending too much time with peers, unsupervised by adults. “Peer pressure” was always the source of bad behavior, never good. And adults fretted that this pressure was forcing kids to “grow up too fast ” (cars, sex). So if social media has made it easier for kids to escape these peer groups,  become less invested in cars, and have less premarital sex, maybe these trends are not harbingers of a coming crisis in the mental health of America’s youth.