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At long last, artificial intelligence (AI)—and its main subset, machine learning—is beginning to fulfill its promise. When fed massive amounts of data, computers can discern patterns (as in speech recognition) and make predictions or decisions. AlphaZero, a Google-related computer system, started playing chess, shogi (Japanese chess), and GO against itself. Before long, thanks to machine learning, AlphaZero progressed from no knowledge of each game to “the best player, human or computer, the world has ever seen.”

 

DrAfter123/DigitalVision Vectors/Getty Images

 

I’ve had recent opportunities to witness the growing excitement about machine learning in the human future, through conversations with

  • Adrian Weller (a Cambridge University scholar who is program director for the UK’s national institute for data science and AI).
  • Andrew Briggs (Oxford’s Professor of Nanomaterials, who is using machine learning to direct his quantum computing experiments and, like Weller, is pondering what machine learning portends for human flourishing).
  • Brian Odegaard (a UCLA post-doc psychologist who uses machine learning to identify brain networks that underlie human consciousness and perception).

 

Two new medical ventures (to which—full disclosure—my family foundation has given investment support) illustrate machine learning’s potential:

  • Fifth Eye, a University of Michigan spinoff, has had computers mine data on millions of heartbeats from critically ill hospital patients—to identify invisible, nuanced signs of deterioration. By detecting patterns that predict patient crashes, the system aims to provide a potentially life-saving early warning system (well ahead of doctors or nurses detecting anything amiss).
  • Delphinus, which offers a new ultrasound alternative to mammography, will similarly use machine learning from thousands of breast scans to help radiologists spot potent cancer cells.

 

Other machine-learning diagnostic systems are helping physicians to identify strokes, retinal pathology, and (using sensors and language predictors) the risk of depression or suicide. Machine learning of locked-in ALS patients’ brain wave patterns associated with “Yes” and “No” answers has enabled them to communicate their thoughts and feelings. And it is enabling researchers to translate brain activity into speech.

 

Consider, too, a new Pew Research Center study of gender representation in Google images. Pew researchers first harvested an archive of 26,981 gender-labeled human faces from different countries and ethnic groups. They fed 80 percent of these images into a computer, which used machine learning to discriminate male and female faces. When tested on the other 20 percent, the system achieved 95 percent accuracy.

 

Pew researchers next had the system use its new human-like gender-discrimination ability to  identify the gender of persons shown in 10,000 Google images associated with 105 common occupations. Would the gender representation in the image search results overrepresent, underrepresent, or accurately represent their proportions, as reported by U.S. Bureau of Labor Statistics (BLS) data summaries?

 

The result? Women, relative to their presence in the working world, were significantly underrepresented in some categories and overrepresented in others. For example, the BLS reports that 57 percent of bartenders are female—as are only 29 percent of the first 100 people shown in Google image searches of “bartender” (as you can see for yourself). Searches for “medical records technician,” “probation officer,” “general manager,” “chief executive,” and “security guard” showed a similar underrepresentation. But women were overrepresented, relative to their working proportion, in Google images for “police,” “computer programmer,” “mechanic,” and “singer.” Across all 105 jobs, men are 54 percent of those employed and 60 percent of those pictured. The bottom line: Machine learning reveals (in Google users’ engagement) a subtle new form of gender bias.

 

As these examples illustrate, machine learning holds promise for helpful application and research. But it will also entail some difficult ethical questions.

 

Imagine, for example, that age, race, gender, or sexual orientation are incorporated into algorithms that predict recidivism among released prisoners. Would it be discriminatory, or ethical, to use such demographic predictors in making parole decisions?

 

Such questions already exist in human judgments, but may become more acute if and when we ask machines to make these decisions. Or is there reason to hope that it will be easier to examine and tweak the inner workings of an algorithmic system than to do so with a human mind?

 

(For David Myers’ other essays on psychological science and everyday life visit www.TalkPsych.com.)

In Intro Psych, during coverage of cognitive behavioral therapy (CBT) in the therapy chapter, give your students this one-page summary provided by Division 12 of the American Psychological Association: Society of Clinical Psychology. Walk your students through some of the highlights.

 

Next, share with your students this Tumblr post as it appeared on Fail Blog. Clearly the client had been seeing this therapist for some time. The client knew the basics of CBT – CBT is about changing how one thinks. The client had had some practice in doing this, but during this particular session, the client was not using what he’d learned.

 

The therapist had very likely seen this behavior from the client before and had been thinking about ways to call the client’s attention to his negative thinking without interrupting the client’s train of thought. At the therapy session described in the Tumblr post, the therapist unveiled his new CBT tool: a Nerf gun. For the rest of the therapy session, every time the client voiced “unhelpful ways of thinking,” his therapist shot him with a Nerf gun. The client stopped, thought about what he said, and revised it. Saying “what a stupid issue, I’m an idiot” was revised to this issue is “frustrating me and I don’t want it to be a problem I’m having.”

 

If you’d like to expand this coverage, you can add information about attribution. Making global (vs. specific), stable (vs. unstable), and internal (vs. external) attributions about negative events is associated with depression.

For example, after a relationships ends, a person may make the following attributions.

 

Global: “I can’t do anything right.”

 

Stable: “I’ll never have a successful relationship.”

 

Internal: “I’m not good enough to have a successful relationship.”

 

In CBT, the client is encouraged to make different attributions, attributions that are specific (vs. global), unstable (vs. stable), and external (vs. internal).

 

Specific: “This relationship wasn’t good.”

 

Unstable: “While this relationship didn’t work out, the next one could.”

 

External: “It takes two people to have a relationship. My boyfriend bears some responsibility.”

 

Interestingly, the reverse is true for positive events. Making specific, unstable, and external attributions for positive events is associated with depression. People who are not depressed are more likely to make global, stable, and internal attributions for positive events.

 

Class demonstration

 

If you’ve been waiting all term for an opportunity to peg your students with Nerf balls, here’s the demonstration for you.

Ask your students to imagine that they have received a poor grade on an exam. Ask student volunteers to give a global attribution for the failing grade. Hit them with a Nerf ball (aim low, you don’t want anyone to lose an eye!), and then ask for a specific attribution instead. After students have given several global attributions, ask for stable attributions – and for those to be changed to unstable attributions. Lastly, ask for internal attributions – and for those to be changed to external attributions.

Judith Rich Harris’ December 29th death took my mind to her remarkable life and legacy. Among all the people I’ve never met, she was the person I came to know best. Across 243 emails she shared her draft writings, her critical assessment of others’ thinking (including my own), and the progress of her illness.

 

Our conversation began after the publication of her cogent Psychological Review paper, which changed my thinking and led me to send a note of appreciation. The paper’s gist was delivered by its first two sentences: “Do parents have any important long-term effects on the development of their child’s personality? This article examines the evidence and concludes that the answer is no.”

 

Her argument: Behavior genetics studies (of twins and adoptees) show that genes predispose our individual traits, and that siblings’ “shared environment” has a shockingly small influence. Peers also matter—they transmit culture. Show her some children who hear English spoken with one accent at home, and another accent at school and in the neighborhood, and—virtually without exception—she will show you children who talk like their peers.

 

Judy Harris was a one-time Harvard psychology graduate student who was dismissed from its doctoral program because, as George Miller explained to her, she lacked “originality and independence.”

 

But she persisted. In her mid-fifties, without any academic affiliation and coping with debilitating autoimmune disorders, she had the chutzpah to submit her evidence-based ideas to Psychological Review, then as now psychology’s premier theoretical journal. To his credit, the editor, Daniel Wegner, welcomed this contribution from this little-known independent scholar. Moreover, when her great encourager Steven Pinker and I each nominated her paper for the annual award for “outstanding paper on general psychology,” the judges selected her as co-recipient of the—I am not making this up—George A. Miller Award. (To his credit, Miller later termed the irony “delicious.”)

 

The encouraging lesson (in Harris’ words): “‘Shut in’ does not necessarily mean ‘shut out.’” Truth will out. Although biases are real, excellence can get recognized. So, wherever you are, whatever your big idea or passion, keep on.

 

Her fame expanded with the publication of her 1998 book The Nurture Assumption, which was profiled by Malcolm Gladwell in a New Yorker feature article, made into a Newsweek cover story, and named as a Pulitzer Prize finalist.

 

Her argument was controversial, and a reminder that important lessons are often taught by those who fearlessly push an argument to its limit. (Surely child-rearing does have some direct influence on children’s values, religiosity, and politics—and not just via the peer culture to which parents expose children. And surely the loving versus abusive extremes of parenting matter.)

 

Harris was kind and generous (she supportively critiqued my writing, even as I did hers) but also had the self-confidence to take on all critics and to offer challenges to other widely accepted ideas. One was the “new science” of birth order, which, as she wrote me, was “neither new nor science.” An August 24, 1997, email gives the flavor of her wit and writing:

Birth order keeps coming back. In their 1996 book on birth order and political behavior, Albert Somit, Alan Arwine, and Steven A. Peterson spoke of the “inherent non-rational nature of deeply held beliefs” and mused that “permanently slaying a vampire”—the belief in birth order effect—may require “that a stake of gold be driven through his/her heart at high noon” (p. vi).
            Why is it so difficult to slay this vampire? Why, in spite of all the telling assaults that have been made on it, does it keep coming back? The answer is that the belief in birth order effects fits so well into the basic assumptions of our profession and our culture. Psychologists and nonpsychologists alike take it for granted that a child’s personality, to the degree that it is shaped by the environment, receives that shaping primarily at home. And since we know (from our own memories and introspections) that a child’s experiences at home are very much affected by his or her position in the family—oldest, youngest, or in the middle—we expect birth order to leave permanent marks on the personality.
            The belief in birth order effects never dies; it just rests in its coffin until someone lifts the lid again.

 

Alas, the disease that shut her in has, as she anticipated, claimed her. In her last email sent my way on September 6, 2018, she reported that

I’m not doing so well. This is the normal course of the disorder I have—pulmonary arterial hypertension. It is incurable and eventually progresses to heart failure and death. I’m in the heart failure stage now. It’s progressing very slowly, but makes remaining alive not much fun. 

            Because I can’t actually DO anything anymore, it’s a treat to get your mail. I can’t do any more than I’ve already done, but maybe what I’ve already done is enough. Who would have thought that 20 years after its publication, people would still be talking about The Nurture Assumption!

 

Or that The New York Times would replay its message at length, in your well-deserved obituary, Judy.

 

(For David Myers’ other essays on psychological science and everyday life visit www.TalkPsych.com.)

Crows are smart. Never underestimate a crow.

 

Comparative psychology is “the study of nonhuman animal behavior with the dual objective of understanding the behavior for its own sake and furthering the understanding of human behavior” (American Psychological Association, n.d.). The better that we understand how crows behave, think, communicate, and solve problems, the better we will understand both crows and ourselves.

 

I have a short written assignment that my Intro Psych students do. After its completion, students have a greater appreciation for the crows around them.

 

John Marzluff, a University of Washington zoologist, has made studying crows his life’s work. In his 22-minute TEDx talk, Marzluff shares what he thinks everyone should know about crows. I assign this during the thinking chapter in Intro Psych, after we’ve covered neuroscience and learning. It makes for a nice review of previously covered content.

 

Here are the questions I ask my students to address:

  • What three factors does Marzluff cite for the crow's problem-solving ability? Explain how each contributes to problem-solving skills.
  • How do the brain areas of crows map onto the human brain? What do those brain areas do and why are they important? How do their brains differ from those of humans?
  • Give an example from his talk of how the birds' behavior changed due to positive reinforcement.
  • Give an example from his talk of how the birds' behavior changed due to observational learning.
  • What is your reaction to this video? 

 

 

 

Reference

American Psychological Association. (n.d.). Comparative psychology. Retrieved December 26, 2018, from https://dictionary.apa.org/comparative-psychology

As Pope Francis has said, “Everyone’s existence is deeply tied to that of others.” We are social animals. We need to belong. We flourish when supported by close relationships. Finding a supportive confidante, we feel joy.

 

Longing for acceptance and love, Americans spend $86 billion annually on cosmetics, fragrances, and personal care products—and billions more on clothes, hair styling, and diets. Is that money well spent? Will it help us find and form meaningful relationships?

 

Consider one of social psychology’s most provocative, and simplest, experiments. Cornell University students were asked to don a Barry Manilow T-shirt (at the behest of researcher Thomas Gilovich and colleagues) and were then shown into a room where several others were completing questionnaires. Afterwards they were asked to guess how many of the others noticed their dorky attire. Their estimate? About half. Actually, only 23 percent did.

 

Other experiments confirm this spotlight effect—an overestimation of others’ noticing us, as if a spotlight is shining on us.

 

The phenomenon extends to our secret emotions. Thanks to an illusion of transparency we presume that our attractions, our disgust, and our anxieties leak out and become visible to others. Imagine standing before an audience: If we’re nervous and we know it, will our face surely show it? Not necessarily. Even our lies and our lusts are less transparent than we imagine.

 

There’s bad news here: Others notice us less than we imagine (partly because they are more worried about the impressions they are making).

 

But there’s also good news: Others notice us less than we imagine. And that good news is liberating: A bad hair day hardly matters. And if we wear yesterday’s clothes again today, few will notice. Fewer will care. Of those, fewer still will remember. 

 

If normal day-to-day variations in our appearance are hardly noticed and soon forgotten, what does affect the impressions we make and the relationships we hope to form and sustain?

 

Proximity. Our social ecology matters. We tend to like those nearby—those who sit near us in class, at work, in worship. Our nearest become our dearest as we befriend or marry people who live in the same town, attend the same school, share the same mail room, or visit the same coffee shop. Mere exposure breeds liking. Familiar feels friendly. Customary is comfortable. So look around.

 

Similarity. Hundreds of experiments confirm and reconfirm that likeness leads to liking (and thus the challenge of welcoming the benefits of social diversity). The more similar another’s attitudes, beliefs, interests, politics, income, and on and on, the more disposed we are to like the person and to stay connected. And the more dissimilar another’s attitudes, the greater the odds of disliking.  Opposites retract.

 

If proximity and similarity help bonds form, what can we do to grow and sustain relationships?

 

Equity. One key to relationship endurance is equity, which occurs when friends perceive that they receive in proportion to what they give. When two people share their time and possessions, when they give and receive support in equal measure, and when they care equally about one another, their prospects for long-term friendship or love are bright. This doesn’t mean playing relational ping pong—balancing every invitation with a tit-for-tat response. But over time, each friend or partner invests in the other about as much as he or she receives.

 

Self-disclosure. Relationships also grow closer and stronger as we share our likes and dislikes, our joys and hurts, our dreams and worries. In the dance of friendship or love, one reveals a little and the other reciprocates. And then the first reveals more, and on and on. As the relationship progresses from small talk to things that matter, the increasing self-disclosure can elicit liking, which unleashes further self-disclosure.

 

Mindful of the benefits of equity and mutual self-disclosure, we can monitor our conversations: 

  • Are we listening as much as we are talking?
  • Are we drawing others out as much as we disclosing about ourselves?

 

In his classic How to Win Friends and Influence People, Dale Carnegie offered kindred advice. To win friends, he advised, “become genuinely interested in other people. . . . You can make more friends in two months by being interested in them, than in two years by making them interested in you.” Thus, “Be a good listener. Encourage others to talk about themselves.”

 

So, looking our best may help a little, initially, though less than we suppose. What matters more is being there for others—focusing on them, encouraging them, supporting them—and enjoying their support in return. Such is the soil that feeds satisfying friendships and enduring love.

 

(For David Myers’ other weekly essays on psychological science and everyday life, visit www.TalkPsych.com)

Sue Frantz

Gaming disorder: Discuss

Posted by Sue Frantz Jan 2, 2019

"Wes, 21, an Eagle Scout and college student from Michigan, played video games 80 hours a week, only stopping to eat every two to three days. He lost 25 pounds and failed his classes" (Irvine, 2018).

 

The World Health Organization (WHO) recently announced the addition of “gaming disorder” to the next edition of the International Classification of Diseases.

 

Gaming disorder is defined in the 11th Revision of the International Classification of Diseases (ICD-11) as a pattern of gaming behavior (“digital-gaming” or “video-gaming”) characterized by impaired control over gaming, increasing priority given to gaming over other activities to the extent that gaming takes precedence over other interests and daily activities, and continuation or escalation of gaming despite the occurrence of negative consequences (World Health Organization, 2018).

 

For your reference, internet gaming disorder appeared in DSM-V in the section identifying areas in need of research. While it’s called internet gaming disorder, the internet part is not required. As it’s currently written, a person would need five of these symptoms to be diagnosed:

 

  • Preoccupation with gaming
  • Withdrawal symptoms when gaming is taken away or not possible (sadness, anxiety, irritability)
  • Tolerance, the need to spend more time gaming to satisfy the urge
  • Inability to reduce playing, unsuccessful attempts to quit gaming
  • Giving up other activities, loss of interest in previously enjoyed activities due to gaming
  • Continuing to game despite problems
  • Deceiving family members or others about the amount of time spent on gaming
  • The use of gaming to relieve negative moods, such as guilt or hopelessness
  • Risk, having jeopardized or lost a job or relationship due to gaming (“Internet gaming,” 2018)

 

The symptoms, as it true for (almost?) all DSM-V diagnoses, must cause “significant impairment or distress” (“Internet gaming,” 2018).

 

Following WHO’s announcement, 25 researchers co-authored a short and freely-available paper published in the Journal of Behavioral Addictions (Aarseth et al., 2017) outlining their concerns with the inclusion of gaming disorder in ICD-11. Their six concerns are:

 

  1. “The quality of the research base is low.”
  2. “The current operationalization of the construct leans too heavily on substance use and gambling criteria.”
  3. “There is no consensus on the symptomatology and assessment of problematic gaming.”
  4. “Moral panics around the harm of video gaming might result in premature application of a clinical diagnosis and the treatment of abundant false-positive cases, especially among children and adolescents.”
  5. “Research will be locked into a confirmatory approach rather than an exploration of the boundaries of normal versus pathological.”
  6. “The healthy majority of gamers will be affected by stigma and perhaps even changes in policy.”

 

In the same journal volume, also freely-available, a couple researchers (Király & Demetrovics, 2017) address each of those concerns.

 

Discussion

 

After your coverage of psychological disorders, divide your students into six groups – or if you have a large class, divide students into groups that are multiples of six. Give each group a copy of both articles.  Assign one of the six concerns to each group. The group is to:

  1. Summarize the concern as it was raised in the Aarseth article.
  2. Summarize the response to that concern given by Király and Demetrovics.
  3. Decide, as a group, which of the two arguments is more persuasive. In other words, based on that concern alone, should ICD-11 include gaming disorder? Explain the group’s reasoning.

 

Ask three different group members to take on the responsibility of being prepared to speak to the class about one of those three tasks. In other words, one student would address #1, another would address #2, and another would address #3.

 

Following discussion, ask the group that was assigned the first concern to offer their responses to the three questions. If you have more than one group looking at the first concern, ask the other groups for their response to the third question.

Repeat with the remaining five concerns.

 

Conclude this activity with a summary of how difficult it is to determine if a set of behaviors rises to the point of a diagnosable disorder and that there are real consequences for creating a diagnosis.

 

Expansion

 

If you would like to expand this exploration, the journal volume, September 2017 issue of the Journal of Behavioral Addictions, these two articles came from has another 10 articles on the topic, all freely available. Create 11 groups. Give each group the Aarseth article that opens the volume, plus one additional article from the remaining 11 commentaries. To start the discussion, you can summarize the Aarseth article. This will ensure everyone starts on the same page, and this will model what their summaries should look like. After the groups have had time to discuss the commentary article they’ve been given, ask each group to report out. After all the groups have reported, by a show of hands (or through an audience response system), ask students to decide if gaming disorder should be included in ICD-11. Ask volunteers to share their reasoning.

 

References

 

Aarseth, E., Bean, A. M., Boonen, H., Colder Carras, M., Coulson, M., Das, D., … Van Rooij, A. J. (2017). Scholars’ open debate paper on the World Health Organization ICD-11 Gaming Disorder proposal. Journal of Behavioral Addictions, 6(3), 267–270. https://doi.org/10.1556/2006.5.2016.088

 

Internet gaming. (2018, June). https://doi.org/10.1176/appi.pn.2018.12a20

 

Irvine, M. (2018). ‘Hi, my name is ___, and I’m addicted to tech’. Retrieved December 27, 2018, from https://www.seattletimes.com/seattle-news/hes-a-tech-addict-who-works-in-the-tech-industry/

 

Király, O., & Demetrovics, Z. (2017). Inclusion of Gaming Disorder in ICD has more advantages than disadvantages. Journal of Behavioral Addictions, 6(3), 280–284. https://doi.org/10.1556/2006.6.2017.046

 

World Health Organization. (2018). WHO | Gaming disorder. Retrieved December 25, 2018, from https://www.who.int/features/qa/gaming-disorder/en/