Meet Jack and Jill as they march up the hill to buy a new vehicle. Hoping to save gas costs and benefit the environment, they are wavering between two options: trading their 34-mpg sedan for a 56-mpg Toyota Prius Eco. trading their hefty 12-mpg pickup truck for a 14-mpg Toyota Tundra. Question: Assuming they drive both vehicles the same number of miles, which purchase would most reduce their gas consumption? Most folks—you, also?—think the Prius would save more. After all, a 34- to 56-mpg jump is a 65 percent improvement, whereas a 12- to 14-mpg jump is but a 17 percent improvement. I thought so, too, until a  mutual friend alerted me to social psychologist (and Duke business professor) Richard Larrick’s studies of the MPG illusion (see here and here ). To see the MPG illusion in action, let’s do the math, assuming that Jill and Jack drive each car 15,000 miles a year and pay $3.00 per gallon for gas: The 34-mpg sedan now consumes 15,000 ÷ 34 = 441 gallons; the new 56-mpg Prius would consume 15,000 ÷ 56 = 268 gallons. That’s 173 gallons and $519 saved. The 12-mpg pickup presently scarfs 15,000 ÷ 12 = 1250 gallons, compared with the Tundra’s 15,000 ÷ 14 = 1071 gallons. That’s 179 gallons and $537 saved. The bottom line: A 2-mpg increase when purchasing or replacing a low-mileage car is hugely more beneficial—to the environment and to one’s pocketbook—than a 2-mpg increase when purchasing a high-mileage car. As Larrick says (but most folks don’t appreciate), “small MPG improvements on inefficient cars can save a lot of gas.” We can cure the MPG illusion by reframing reported fuel efficiency as GPM—gallons per mile, rather than MPG—miles per gallon. When buying, isn’t that what we need to know: not how far can we drive on a gallon, but rather how many gallons must we buy to drive this car? MPG is also useful—it tells us whether we can make it home before needing to refuel. But when purchasing a car, it’s gas consumption, not MPG, that matters most. In recognition of the MPG illusion—the perception that equal MPG increases will represent equal gas savings—the U.S. Department of Energy now includes, albeit less prominently, GPM information on fuel economy labels (#5, below). Larrick and his colleague Jack Soll report that when people stop to consider the GPM framing, most do then make fuel-smart judgments. And when people think smarter about fuel savings—when, for example, they realize that increasing fuel efficiency from 10 to 20 mpg will save twice as much as a 20 to 40 mpg increase—public energy conservation policies can become smarter as well. GPM framing helps us prioritize getting the most fuel-inefficient vehicles out of sales rooms and off the road. P.S. For fellow data geeks, U.S. “Miles per hour” are increasing: (For David Myers’ other essays on psychological science and everyday life, visit TalkPsych.com .) ... View more

The history of Americans' health is, first, a good news story. Thanks to antibiotics, vaccines, better nutrition, and diminished infant mortality, life expectancy-at-birth has doubled since 1880—from 38 to 79 years. For such a thin slice of human history, that is a stunning achievement. Even amid a pandemic, be glad you are alive today. The recent not-good news is that, despite doubled per-person health-care spending compared to other rich countries, U.S. life expectancy is lower—and has been declining since 2014. Can you guess why Americans, despite spending more on their health, are dying sooner? Our World in Data founder, Max Roser, sees multiple explanations. Smoking. While the COVID-19 pandemic has claimed 2.4 million lives in the past year, cigarette smoking kills 8.1 million people annually—and it kills more in the U.S. than in other wealthy countries. Of those people who are still smokers when they die, two-thirds die because of their smoking. Still, there’s some good news: The plunging smoking rate is reducing both smoking-caused deaths and the smoking fatality gap between the U.S. and other rich countries. Obesity. While smoking has declined, obesity—a risk factor for heart disease, stroke, diabetes, and some cancers—has increased: 36 percent of Americans are now obese. Compared to the other rich (but less obese) nations, the U.S. has a much higher rate of premature deaths attributed to obesity (five times that of Japan, more than double that of France, and nearly 60 percent greater than Canada). Homicides. As a gun-owning culture, Americans much more often kill each other—four times more often than the next most murderous rich nation (peaceful Canada). Opioid overdoses. Like homicides, America’s much greater opioid overdose death rate, though causing less than 2 percent of all deaths, affects life expectancy because so many victims are young. Road accidents. A surprise to me—and you?—is the U.S. having, compared to other rich nations, a roughly doubled rate of vehicle-related accidents (again, often involving the young, and thus contributing to the life expectancy gap). Inequality and poverty. Although the U.S. enjoys higher average income than most other rich countries, its lower-income citizens are poorer. This greater inequality and poverty predicts less access to health care and also greater infant mortality, which, among the rich nations, is highest in the U.S. And how might we expect the pandemic to affect the U.S. life expectancy standing? The half-million U.S. COVID-19 deaths in the pandemic’s first year have, per capita, been matched by the UK and Italy, but are roughly double those of other European nations, and many times more than collectivist East Asian countries.   For its often mask-defying rugged individualism, the U.S. has paid a heavy price. Moreover, as Nathan DeWall and I report in our forthcoming Exploring Psychology, 12th Edition (with data from Carnegie Mellon University), there has been a striking -.85 correlation across states between mask wearing and COVID-19 symptoms. Less mask wearing—as in the mask-resisting Dakotas, Wyoming, Idaho, and the Southern states—predicts more COVID-19. The Centers for Disease Control observed the same correlation across U.S. counties during 2020: COVID-19 cases and deaths increased in U.S. counties that reinstated in-person dining or not requiring masks.   As Max Roser notes, the factors that predict Americans’ dying sooner—smoking, obesity, violence, opioids, poverty, and likely COVID-19—are less about better healthcare for the sick than about averting health problems in the first place. As Benjamin Franklin anticipated, “An ounce of prevention is worth a pound of cure.”   (For David Myers’ other essays on psychological science and everyday life, visit TalkPsych.com; follow him on Twitter: @DavidGMyers.)   ... View more

German medical statistics expert (and psychologist) Gerd Gigerenzer can regale you with stories of ill-fated health-risk communications. He tells , for example, of the 1990s British press report that women taking a particular contraceptive pill had a 100 percent increased chance of developing potentially fatal blood clots. That massive-sounding risk caused thousands of horrified women to stop taking the pill—leading to a wave of unwanted pregnancies and some 13,000 additional abortions (which, ironically, entail a blood clot risk of their own). So, was the press report wrong? Well, yes and no. The risk did double. But it remained infinitesimal: increasing from 1 in 7000 to 2 in 7000. Fast forward to today’s dilemma for those contemplating getting a COVID-19 vaccine: Are the vaccines both safe enough and effective enough to warrant becoming vaccinated? How protective are they? Consider two possibly misleading reports: NPR invites us to imagine a 50 percent effective vaccine: “If you vaccinate 100 people, 50 people will not get disease.” The famed   Cleveland Clinic   reports that a 95 percent effective vaccine gives you a “95% level of protection…[meaning that] about 95% of the population would develop immunity in a fashion that would protect them from getting sick if exposed to the virus.” So, with a 50 percent effective vaccine, we have a 50 percent chance of contracting COVID-19, and with a 95 percent effective vaccine, we have a 5 percent chance…right? Actually, the news is much better. Consider what that “95 percent effective” statistic actually means. As the New York Times' Katie Thomas explained , the Pfizer/BioNTech clinical trial engaged nearly 44,000 people, half of whom received its vaccine, and half a placebo. The results? “Out of 170 cases of COVID-19, 162 were in the placebo group, and eight were in the vaccine group.” So, there was a 162 to 8 (95 percent to 5 percent) ratio by which those contracting the virus were unvaccinated (albeit with the infected numbers surely rising in the post-study months). Therein lies the “95 percent effective” news we’ve all read about. So, if you receive the Pfizer or equally effective Moderna vaccine, do you have a 5 percent chance of catching the virus? No. That chance is far, far smaller: Of those vaccinated in the Pfizer trial, only 8 of nearly 22,000 people—less than 1/10th of one percent (not 5 percent)—were found to have contracted the virus during the study period. And of the 32,000 people who received either the Moderna or Pfizer vaccine, how many experienced severe symptoms? The grand total, noted David Leonhardt in a follow-up New York Times report : One. Gigerenzer tells me that his nation suffers from the same under-appreciation of vaccine efficacy. “I have pointed t his misinterpretation out in the German media,” he notes, “and gotten quite a few letters from directors of clinics who did not even seem to understand what’s wrong.” “Be assured that YOU ARE SAFE after vaccine from what matters—disease and spreading,” tweeted Dr. Monica Gandhi of the University of California, San Francisco. Although we await confirmation that the vaccines do, as expected, reduce transmission, she adds that “ Two vaccinated people can be as close as 2 spoons in [a] drawer!” The near 100 percent efficacy is “ridiculously encouraging,” adds Paul Offit , the Vaccine Education Center director at Children’s Hospital of Philadelphia. Moreover, notes stats geek Nate Silver , “T elling people they can't change their behavior even once they get a vaccine is a disincentive for them to get vaccinated.” With other vaccines and virus variants the numbers will, of course, vary. And as one of the newly vaccinated, I will continue—for as long as the pandemic persists—to honor and support the needed norms, by masking and distancing. I will strive to model protective hygiene. But my personal fear of COVID-19 will be no greater than the mild fear and resulting caution that accompanies my biking and driving. Moreover, for all of us, vaccine statistical literacy—and the need to accurately convey health risks and benefits— matters. In this case, it matters a lot. [2/20/2021 P.S. In a follow-up twitter thread, David Leonhardt offered this table, showing that of 74,000+ participants in one of the five vaccine trials, the number of vaccinated people who then died of COVID was zero. The number hospitalized with COVID was also zero.}   (For David Myers’ other essays on psychological science and everyday life, visit TalkPsych.com; follow him on Twitter: @DavidGMyers.) ... View more

The conservative New York Times columnist Ross Douthat spoke for many in being astounded by “the sheer scale of the belief among conservatives that the [2020 presidential] election was really stolen,” which he attributed partly to “A strong belief [spurring] people to go out in search of evidence” for what they suppose. Douthat alluded to confirmation bias—our well-established tendency, when assessing our beliefs, to seek information that supports rather than challenges them. What’s the basis for this big idea, which has become one of social psychology’s gifts to public awareness? And should appreciating its power to sustain false beliefs cause us to doubt our own core beliefs? In a pioneering study that explored our greater eagerness to seek evidence for rather than against our ideas, psychologist Peter Wason gave British university students a set of three numbers (2-4-6) and told them that the series illustrated a rule. Their task was to discover the rule by generating their own three-number sequences, which Wason would confirm either did or didn’t conform to the rule. After the students tested enough to feel certain they had the rule, they were to announce it. Imagine being one of Wason’s study participants. What might you suppose the rule to be, and what number strings might you offer to test it? The outcome? Most participants, though seldom right, were never in doubt. Typically, they would form a wrong idea (such as “counting by twos?”) and then test it by searching for confirming evidence: “4-6-8?” “Yes, that conforms.” “20-22-24?” “Yes.” “200-202-204?” “Yes again.” “Got it. It’s counting by twos.” To discover Wason’s actual rule (any three ascending numbers), the participants should also have attempted to disconfirm their hunch by imagining and testing alternative ideas. Confirmation bias also affects our social beliefs. In several experiments , researchers Mark Snyder and William Swann tasked participants with posing questions to someone that would reveal whether that person was extraverted. The participants’ typical strategy was to seek information that would confirm extraversion. They would more likely ask “What would you do if you wanted to liven things up at a party?” than “What factors make it hard for you to really open up to people?” Vice versa for those assessing introversion. Thus, participants typically would detect in a person whatever trait they were assessing. Seek and ye shall find. In everyday life, too, once having formed a belief—that vaccines cause autism, that people can choose or change their sexual orientation, that the election was rigged—we prefer and seek information that verifies our belief. The phenomenon is politically bipartisan. Across various issues, both conservatives and liberals avoid learning the other side’s arguments about topics such as climate change, guns, and same-sex marriage. If we believe that systemic racism is (or is not) rampant, we will gravitate toward news sources, Facebook friends, and evidence that confirms our view, and away from sources that do not. Robert Browning understood: “As is your sort of mind, / So is your sort of search: you’ll find / What you desire.” Confirmation bias supplements another idea from social psychology—belief perseverance, a sister sort of motivated reasoning. In one provocative experiment, a Stanford research team led by Craig Anderson invited students to consider whether risk-takers make good or bad firefighters. Half viewed cases of a venturesome person succeeding as a firefighter, and a cautious person not succeeding; the other half viewed the reverse. After the students formed their conclusion, the researchers asked them to explain it. “Of course,” one group reflected, “risk-takers are braver.” To the other group, the opposite explanation seemed equally obvious: “Cautious people have fewer accidents.” When informed that the cases they’d viewed were fake news made up for the experiment, did the students now return to their pre-experiment neutrality? No—because after the fake information was discredited, the students were left with their self-generated explanations of why their initial conclusion might be true. Their new beliefs, having grown supporting legs, thus survived the discrediting. As the researchers concluded, “People often cling to their beliefs to a considerably greater extent than is logically or normatively warranted.” So, does confirmation bias + belief perseverance preclude teaching an old dogma new tricks? Does pondering our beliefs, and considering why they might be true, close us to dissonant truths? Mindful of the self-confirming persistence of our beliefs (whether true or false), should we therefore doubt everything? Once formed, it does take more compelling persuasion to change a belief (“election fraud was rampant”) than it did to create it. But there are at least two reasons we need not succumb to a nihilistic belief in nothing. First, evidence-based critical thinking works. Some evidence will change our thinking. If I believe that Reno is east of Los Angeles, that Atlanta is east of Detroit, and that Rome is south of New York, a look at a globe will persuade me that I am wrong, wrong, and wrong. I may once have supposed that child-rearing techniques shape children’s personalities, that the crime rate has been rising for years, or that traumatic experiences get repressed, but evidence has shown me otherwise. Recognizing that none of us are infallible little gods, we all, thankfully, have at least some amount of intellectual humility. Moreover, seeking evidence that might disconfirm our convictions sometimes strengthens them. I once believed that close, supportive relationships predict happiness, that aerobic exercise boosts mental health, and that wisdom and emotional stability grow with age—and the evidence now enables me to believe these things with even greater confidence. Curiosity is not the enemy of conviction. Second, explaining a belief does not explain it away. Knowing why you believe something needn’t tell us anything about your belief’s truth or falsity. Consider: If the psychology of belief causes us to question our own beliefs, it can also cause others to question their opposing beliefs, which are themselves prone to confirmation bias and belief perseverance. Psychological science, for example, offers both a psychology of religion and a “psychology of unbelief” (an actual book title). If both fully complete their work—by successfully explaining both religion and irreligion—that leaves open the question of whether theism or atheism is true. Archbishop William Temple recognized the distinction between explaining a belief and explaining it away when he was challenged after an Oxford address: “Well, of course, Archbishop, the point is that you believe what you believe because of the way you were brought up.” To which the archbishop replied, “That is as it may be. But the fact remains that you believe that I believe what I believe because of the way I was brought up, because of the way you were brought up.” Finally, let’s remember: If we are left with uncertainty after welcoming both confirming and disconfirming evidence, we can still venture a commitment. As French author Albert Camus reportedly said, sometimes life beckons us to make a 100 percent commitment to something about which we are 51 percent sure—to a cause worth embracing, or even to a belief system that helps make sense of the universe, gives meaning to life, connects us in supportive communities, provides a mandate for morality and selflessness, and offers hope in the face of adversity and death. So yes, belief perseverance solidifies newly formed ideas as invented rationales outlast the evidence that inspired them. And c onfirmation bias then sustains our beliefs as we seek belief-confirming evidence. Nevertheless, evidence-based thinking can strengthen true beliefs, or at least give us courage, amid lingering doubt, to make a reasoned leap of faith. As St. Paul advised , “Test everything; hold fast to what is good.” (For David Myers’ other essays on psychological science and everyday life, visit TalkPsych.com ; follow him on Twitter: @DavidGMyers.) ... View more

A powerful psychological phenomenon is deflecting public approval of Donald Trump and Joe Biden, a phenomenon that is surfacing in polls and may influence the outcome of Georgia’s special Senate election. Social psychologists have repeatedly observed our human tendency to assume that we live in a just world, a world where people get what they deserve—where good is rewarded and evil is punished. Things happen for a reason, we surmise. From this “just-world” assumption it is but a short leap to assume that those who succeed must be good and those who suffer must be bad. The rich, we may think, have earned their wealth, even as the poor’s misfortune is similarly deserved. Those who viewed Donald Trump as an exceptionally successful business person would, in a just world, naturally assume that he possessed exceptional business acumen and leadership skills. At the other extreme, American slaveholders tended to view enslaved people as lazy and irresponsible—as having the very traits that justified their slavery. In both cases, folks presumed, people deserved what they got. The just-world phenomenon has played out in experiments . For example, people who were randomly assigned to receive supposed electric shocks for wrong answers on a memory test were later perceived as somehow deserving their fate. Juvenal, the Roman satirist, observed the phenomenon: “The Roman mob follows after Fortune . . . and hates those who have been condemned.” In other experiments people who read about a man and woman’s interaction judged the woman differently depending on whether the story ends with a happy ending or a rape—even when in both cases her behavior was the same. Thus the phenomenon can blind us to injustice, as people presume rape victims must have been seductive, battered spouses may have elicited their beating, and sick people as responsible for what ails them. “You reap what you sew.” So it happened in the Old Testament story of the undeserved suffering Job, whose friends judged that he must have merited his lot. Linking fortune with virtue and misfortune with moral failure sustains injustice. It enables the fortunate to feel pride in their just rewards and to avoid responsibility for the unfortunate. Just-world thinking is enabled by after-the-face narratives that explain victory or defeat. When a basketball game ends with a winning shot that rolls around the rim and falls in, fans and commentators explain the brilliant play and smart coaching that enabled the victory. Let the shot roll off, and everything remains the same—except now, the Monday morning narrative itemizes the player mistakes and coaching failures. Already we see the phenomenon operating writ large, with the expected post-election analyses of Mr. Trump’s flaws and Mr. Biden’s virtues. Losers we devalue. Winners we admire. Runoff and special elections historically have elicited more Republican turnout. This seemingly is reflected in the betting markets, which, as I write, estimate a 73 percent chance that Republicans will retain control of the Senate by winning at least one of the Georgia seats. Moreover, notes election modeler Nate Silver , “It’s easy to imagine Republicans being more motivated to turn out than Democrats, who may feel like they’ve done their duty.” But surely there is an alternative scenario: In this interim before the January 5th Georgia Senate runoff elections involving two Trump-supporting Republicans, we can anticipate further decline in Donald Trump’s public approval, which will be mirrored by rising approval of Joe Biden. If it’s a just world, both got what they deserved. And sure enough: A new Gallup Poll finds Biden’s favorability rating up six points six the election and Trump’s down three. Trump’s absence from the January ballot and his falling approval will likely weigh on the Trump-associated Senators Perdue and Loeffler. Moreover, if Mr. Biden’s public esteem rises, if the election becomes issue-focused (on allowing Biden to legislate majority-supported livable wages, climate protection, and affordable health care), and if Democratic voters are more motivated to enable Biden to govern than are dispirited Republicans motivated to block his initiatives, then the results may surprise us. (For David Myers’ other essays on psychological science and everyday life, visit TalkPsych.com or follow him on Twitter: @DavidGMyers.)   ... View more

In a pre-election essay, I contrasted the prognostications of poll-influenced prediction models with the wisdom of the betting crowd. I suspected that bettors—many of whom believed their candidate would win—were overly influenced by the false consensus effect (the presumption that most others see the world as we do). But score this round for the wisdom of the betting crowd, which better anticipated the election closeness, including Trump’s Florida victory. That’s a contrast with Britain’s Brexit vote, where polls indicated a toss-up (a half percent edge for “Remain”) while the betting markets wrongly estimated a 90+ percent Remain chance. The U.S. polls had a rougher-than-usual year, with the final Biden margin likely near 4.5 percent rather than the predicted 8 percent. The pollsters also struggled in key states. On election eve, the average poll gave Trump a 0.8 percent edge in Ohio; he won by 8 percent. In Florida, the polls gave Biden a 2.5 percent edge; he lost by about 3 percent. In Wisconsin, the polls favored Biden by 8.4 percent; he won by less than a percent. With so few people now responding to pollster calls and texts, precision is increasing a challenge (even with pollster adjusting results to match the voting demographics). But lest we dismiss the polls and sophisticated forecasters, let’s grant them three points. First, they got many of the specifics right. FiveThirtyEight, for example, correctly anticipated 48 of the 50 presumed state outcomes. Some of its correct predictions even surprised its creator: Second, polls, as Silver has said , could be worse and they would still greatly exceed conventional seat-of-the-pants wisdom. In a University of Michigan national survey in September, 4 in 5 Republicans incorrectly anticipated a Trump victory. Third, although the models missed on some details, credit them with the big picture. “Biden’s Favored in Our Final Presidential Forecast, but It’s a Fine Line Between a Landslide and a Nail-Biter,” headlined FiveThirtyEight in its final election forecast. And Biden did win. As I write, though, the betting markets —mindful of fraud allegations and legal challenges—still give Donald Trump a 12 percent chance of victory. But this, says Silver , “ is basically a market saying there's a 12% chance that the sky isn't blue.” Consider, say the media analysts who have called the election: How would widespread voter fraud account for Donald Trump’s doing much better than predicted by the historically reliable polls (and for down ballot Republicans doing better yet)? And how could that be so across America in countless local municipalities, including those with Republican-elected officials? Take my community—Holland, Michigan, a historically Republican town where Betsy DeVos grew up and has a home just a bike ride from my own. With a changing demography that now closely mirrors the nation, our last three presidential elections have been razor close, with Donald Trump narrowly edging Hillary Clinton in 2016 . . . but with Biden defeating Trump by 11 percent. Likewise, our surrounding county—one of the nation’s most reliably Republican counties—voted Trump by 30.2 percent in 2016 but only 21.5 percent in 2020. Neighboring Kent County, also leans Republican and is the home of Republican-turned-Libertarian Congressman Justin Amash, gave Biden 50,000 more votes than Clinton received four years ago. Is it conceivable that the Republican-friendly voting officials in countless such places across the U.S. consistently committed Biden-supporting fraud? All in all, it was not the best of years for pollsters and modelers, though it was a worse year for John and Joan Q. Public’s expectations of their candidate’s triumphant success. Winston Churchill once called democracy “the worst form of Government except for all those other forms.” To borrow his sentiment, polls and models are the worst forms of prediction, except for all the other forms. (For David Myers’ other essays on psychological science and everyday life, visit TalkPsych.com .) ... View more

To many observers, the election was a clash of two Americas—a war between two increasingly partisan identities, each of which is incredulous at what the other supports. As the Pew Research Center documents , the gulf between them is enormous. For example, 74 percent of Biden supporters told the Pew Research Center that “it is a lot more difficult” to be a Black person in this country than to be a White person, a view shared by a mere 9% of Trump supporters. Likewise, 68 percent of Biden supporters said climate change was important to their vote—as was the case for but 11 percent of Trump supporters (who scored this last among 12 issues of possible concern). Many Republicans, having believed Donald Trump would win, are aghast at the defeat of their pro-life, law-and-order supporting, free-enterprise-buttressing, patriotic values-embracing leader. Democrats had hoped the massive turnout heralded a massive blue wave repudiation of Trump’s bigotry, divisiveness, and climate unfriendly actions. Thus, many are stunned that all this barely moved the needle—from a 2016 electoral vote margin of 2.1 percent to about 5 percent—despite improved Democratic party demographics, increased fund-raising, and a better-liked candidate. In Why We’re Polarized , journalist Ezra Klein draws on social science research to document how Americans now view politics through the lens of their strongly held partisan identities—who “we” are versus who “they” are. Klein describes how our political tribal identities engage what we psychologists call “motivated reasoning.” Whatever our party and its leaders do—even when it clashes with what we formerly believed—we rationalize. Even morality and religion have become subservient to politics. In the latest issue of Science , an interdisciplinary team of 15 scholars, led by social psychologist Eli Finkel, further describe today’s “political sectarianism” and the rise of out-party hate. They document the growing contempt that today’s partisans feel for the other party, which greatly exceeds the love they have for their own. Recall, too, the power of the availability heuristic—our tendency to estimate the commonality of events based on their mental availability. Whatever information pops readily into mind—often vivid images—can hijack our thinking. Thus, potent memes (“defund the police”) and scenes (rampaging protesters) can define those we associate with them, even if the meme represents no political party and the scene represents an infinitesimal proportion of otherwise peaceful demonstrators. In the post-Trump era to come, both parties will be debating and massaging their brand identities in hopes of drawing more people in while retaining their base. Partisans on both sides could, methinks, benefit from a reading of Peter Wehner’s prescient The Death of Politics: How to Heal Our Frayed Republic After Trump —a guidebook to seeking a more perfect union (a book acclaimed, remarkably, by both Democratic strategist David Axelrod and Republican strategist Karl Rove). (For David Myers’ other essays on psychological science and everyday life, visit TalkPsych.com .) ... View more

I see you. My psychic powers enable me, from a great distance, to peer into your heart and to sense your unease. Regardless of your political leanings, you understand the upcoming U.S. election to be momentous, world-changing, the most important of your lifetime. Part of you is hopeful, but a larger part of you is feeling tense. Anxious. Fearing a future that would follow the outcome you dread. Hungering for indications of the likely outcome, you read the latest commentary and devour the latest polls. You may even glean insight from the betting markets (here and here) , which offer “the wisdom of the crowd.” They are akin to stock markets, in which people place bets on future stock values, with the current market value—the midpoint between those expecting a stock to rise and those expecting it to fall—representing the distillation of all available information and insight. As stock market booms and busts remind us, the crowd sometimes displays an irrational exuberance or despair. Yet, as Princeton economist Burton Malkiel has repeatedly demonstrated , no individual stock picker (or mutual fund) has had the smarts to consistently outguess the efficient marketplace. You may also, if you are a political geek, have welcomed clues to the election outcome from prediction models ( here and here ) that combine historical information, demographics, and poll results to forecast the result. But this year, the betting and prediction markets differ sharply. The betting markets see a 34 percent chance of a Trump victory, while the prediction models see but a 5 to 10 percent chance. So who should we believe? Skeptics scoff that the poll-influenced prediction models erred in 2016. FiveThirtyEight’s final election forecast gave Donald Trump only a 28 percent chance of winning. So, was it wrong? Consider a simple prediction model that predicted a baseball player’s chance of a hit based on the player’s batting average. If a .280 hitter came to the plate and got a hit, would we discount our model? Of course not, because we understand the model’s prediction that sometimes (28% of the time, in this case), the less likely outcome will happen. (If it never does, the model errs.) But why do the current betting markets diverge from the prediction models? FiveThirtyEight modeler Nate Silver has an idea: The Dunning-Kruger effect, as psychology students know, is the repeated finding that incompetence tends not to recognize itself. As one person explained to those unfamiliar with Silver’s allusion: Others noted that the presidential betting markets, unlike the stock markets, are drawing on limited (once every four years) information—with people betting only small amounts on their hunches, and without the sophisticated appraisal that informs stock investing. And what are their hunches? Surely, these are informed by the false consensus effect—our tendency to overestimate the extent to which others share our views. Thus, in the University of Michigan’s July Survey of Consumers, 83 percent of Democrats and 84 percent of Republicans predicted that voters would elect their party’s presidential candidate. Ergo, bettors are surely, to some extent, drawing on their own preferences, which—thanks to the false consensus effect—inform their predictions. What we are, we see in others. So, if I were a betting person, I would wager based on the prediction models. Usually, there is wisdom to the crowd. But sometimes . . . we shall soon see . . . the crowd is led astray by the whispers of its own inner voices. ----- P.S. At 10:30 a.m. on election day, the Economist model projects a 78 percent chance of a Biden Florida victory, FiveThirtyEight.com projects a Biden Florida victory with a 2.5 percent vote margin, and electionbettingodds.com betting market average estimates a 62% chance of a Trump Florida victory. Who's right--the models or the bettors? Stay tuned! P.S.S. on November 4: Mea culpa. I was wrong. Although the models--like weather forecasts estimating the percent change of rain--allow for unlikely possibilities, the wisdom of the betting crowd won this round--both in Florida and in foreseeing a closer-than-expected election. (For David Myers’ other essays on psychological science and everyday life, visit TalkPsych.com .)   ... View more

At a May 26 Rose Garden press conference, President Trump asked a face-masked reporter: “Can you take it off, because I cannot hear you.” On this matter, I can empathize with our president. At a recent dental appointment, I could understand but half my hygienist’s and dentist’s spoken words. Despite being a person with hearing loss, I normally hear them both with ease, thanks to our proximity. But when muffled by their masks and face shields, their words became indistinct. One speech researcher explains that the thicker fabrics of many home-made masks are especially likely to “significantly block the airstream, diminishing the acoustic energy.” Although I wouldn’t have it otherwise—they and other caregivers are protecting their patients, and protecting themselves from their patients—masks do impede accessibility. More than we realize, we are all natural lip readers. Even a normal-hearing friend, visiting an ice cream shop, could not make out the masked clerk’s words: “Cup or cone”? Another acquaintance, during a hospital ER visit, reporting understanding only about half of what the masked nurses and doctors said to her. In the fully masked classrooms of my campus, colleagues tell me that, for example, “I have found myself asking students to repeat their questions.” Another colleague says “I am using my outside voice,” which takes more energy (and which other colleagues report leaves them drained). Another reports that “It is frustrating to continue to ask a student to repeat something and I fear it will shut down discussion and make most classes a lecture performance—in which case I might as well go completely online.” Another has, while the weather allows, taken his class outdoors where, socially distanced, they can see facial expressions and lip-read one another, mask-free. The essential lesson: There is more to hearing than meets the ears. What our eyes see influences what our brain hears. That phenomenon, which you can experience here , is called the McGurk effect. Moreover, thanks to our powers of instantly reading facial expressions, much of our communication is nonverbal. We share our emotions through our words but also through our smiles, our tight lips, our gaping mouths. Even our emojis vary the mouth: :- ( and :- ) . One colleague explains: “It adds a barrier that feels formal and inaccessible when you can't shake someone's hand, and then you can't smile at them to say ‘but I still want to get to know you.’” Cut off from facial expression, our communication is hampered. So is face recognition. With students’ faces masked, colleagues report becoming partially face-blind. They’re not only having more difficultly immediately knowing which student is speaking, but also recognizing their obscured faces: “I cannot call on a familiar student by name, because I can't tell who anyone is.” Add to this the depletion of normal emotional display and mimicry and the natural result will be weakened social bonds, including those between teacher and student, argues German psychiatrist and psychologist Manfred Spitzer. Given that masks—and also face shields in health care—are essential to controlling the pandemic, how can we salvage hearing accessibility in a masked world? Clear hearing is helpful to everyone—our minds wander less when little cognitive effort is required--but especially for those with hearing loss. In retail contexts, where a transaction occurs with a masked person behind a clear plastic screen, a simple solution can serve most people with hearing aids. Given a microphone and an installed hearing loop , a clerk’s voice will magnetically transmit to the telecoil sensor in most aids and all cochlear implants. As I can vouch , the system also works beautifully in other venues, including auditoriums, airports, and places of worship . With the mere push of a button, my hearing aids can become in-the-ear speakers that receive PA sound and customize it for my hearing needs. But what about classrooms, where campus face-mask mandates will require teachers and students to wear mutually protective masks—and in some cases (including the classrooms of my own campus) also to speak from behind a plastic barrier? What can schools and colleges do to enable hearing accessibility while also supporting public health? Admonish clarity. Schools can admonish instructors to be mindful that their audience is experiencing some muffling of sound, without supportive lip reading. Health care workers can likewise be coached to speak more deliberately and distinctly: “Your patients, especially your older patients, are having more trouble hearing you than you suppose.” That, alas, will be only a modestly effective solution, because we soon revert to our natural speaking styles. When one experimenter asked people to act as expressive or inhibited as possible while stating opinions, the naturally expressive people—even when feigning inhibition—were less inhibited than naturally inhibited people. And inexpressive people, when feigning expressiveness, were less expressive than naturally expressive folks. It’s hard to be, for any length of time, someone you’re not. Your speaking speed and style is, once your self-consciousness subsides, irrepressible. Transparent face masks. A second solution is to equip instructors with a face mask or shield that allows people to read lips and facial expressions. One example, used by some on my campus (such as the colleague below, at left) is the ClearMask. (An alternative, germ-filtering transparent Swiss surgical mask to be available in 2021 from hmcare.ch is shown at right.) Mindful of the face’s role in communication, one colleague is hoping, with appropriate permissions, to equip all his students with face shields. Two other colleagues have, however, told me of being bothered both by breathing issues with a clear mask, and also by the altered sound of their own voice (a familiar distraction to new hearing aid wearers). Define safe distance. A third solution is to specify a safe distance at which an instructor may lower the mask while lecturing. Imagine two very different classrooms. In a small seminar, colleges would surely mandate a professor's mask wearing when seated around a table with students. When lecturing while alone as a sage on the stage of a large auditorium, the professor would be sufficiently physically distanced to make a mask superfluous. In the gradations of classrooms in between, could colleges define a minimum safe distance at which a mask could be lowered while teaching? Add PA systems. A fourth solution is to add PA systems to intermediate-size rooms. An instructor’s head-mounted mic could transmit to a class through newly installed speakers. Live captioning. Google Meet’s captioning illustrates the potential for instant, accurate captioning that rivals the speed and precision of human captioner. Not only is it, therefore, a preferred video conferencing technology for accessibility (Zoom, take note), the visual information display aids anyone whose mind has momentarily wandered. Might classrooms be similarly equipped with open captioned displays of instructors’ remarks? Hearing loops. Finally, schools could employ hearing technology. Such ranges from personal assistive technology—in which an instructor wears a mic that transmits to individual hard-of-hearing students with special receivers—to class and auditorium hearing loops that transmit to most of today’s hearing aids and cochlear implants (as I illustrate here from my Hope College campus). We want to stay healthy. And we want to hear. Let those planning for in-person, under-the-pandemic instruction aim for both—a health-protecting accessibility. [February, 2021, P.S. For data on the face mask acoustic effects, see here and here. . . and stay tuned for data on the CDC-recommended double masks. (In a recent conversation, a double-masked colleague's comments were mostly indecipherable to me.) Note: high frequency consonants, which convey so much meaning, are most impaired by dense fabric masks and, alas, clear shield masks. Perhaps the new Ford partially clear N95 mask (see here) will work better for communication, as well as not fogging up? Also, have you, too, noticed athletic coaches dutifully wearing asks, but them pulling them down when needing to communicate--at the time they're most needed, albeit in recognition that masks impair hearing accessibility?]   (For David Myers’ other essays on psychological science and everyday life, visit TalkPsych.com .) ... View more