Psychological Science Meets a Gullible Post-Truth World

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Psychological Science Meets a Gullible Post-Truth World

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Part 1 of 2

Psychological Science Meets a Gullible Post-Truth World
by David G. Myers
Hope College (USA)
March 20, 2018

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What use are the people’s wits
who let themselves be led
by speechmakers, in crowds,
without considering
how many fools and thieves
they are among, and how few
choose the good?

-- Heraclitus, 2001 fragment 111


Highlights:

As the managing director of political messaging firm, Cambridge Analytica explained to a supposed client, things don’t “need to be true, as long as they’re believed . . . . It’s all about emotion, it’s all about emotion” (Golgowski, 2018).

When emotion trumps evidence, gullibility ensues. And like the “crafty serpent” in the creation story, said Pope Francis, fake news uses mimicry (of real news)—a “sly and dangerous form of seduction that worms its way into the heart.” One wonders if he had a certain master manipulator in mind when quoting Dostoevsky’s The Brothers Karamazov: “People who lie to themselves and listen to their own lie come to such a pass that they cannot distinguish the truth within them, or around them, and so lose all respect for themselves and for others.”...

Public gullibility ... is partly explained by the power of mere repetition. Much as mere exposure to unfamiliar stimuli breeds liking, so mere repetition can make things believable (Dechêne et al., 2010; Moons et al., 2009; Schwarz, Newman, & Leach, 2017). In elections, advertising exposure helps make an unfamiliar candidate into a familiar one, which partially explain why, in U.S. congressional elections, the candidate with the most money wins 91 percent of the time (Lowery, 2014).

Hal Arkes (1990) has called repetition’s power “scary.” Repeated lies can displace hard truths. Even repeatedly saying that a claim is false can, when discounted amid other true and false claims, lead older adults later to misremember it as true (Skurnik et al., 2005). As we forget the discounting, our lingering familiarity with a claim can also make it seem credible....

Moreover, falsehoods fly fast. On Twitter, lies have wings. In one analysis of 126,000 stories tweeted by 3 million people, falsehoods—especially false political news—“diffused significantly farther, faster, deeper, and more broadly than the truth” (Vosought, Roy, & Aral, 2018). Compared to true stories, falsehoods often are more emotionally dramatic, novel, and seemingly newsworthy. As Jonathan Swift (1710) anticipated, “Falsehood flies, and the Truth comes limping after it” (or in later renditions, “A lie can travel halfway around the world while the truth is putting on its shoes”).

Retractions of previously provided information also rarely work—people tend to remember the original story, not the retraction (Ecker 2011; Lewandowsky 2012). Courtroom attorneys understand this, which is why they will say something that might be retracted on objection, knowing the jury will remember it anyway. Better than counteracting a falsehood is providing an alternative simple story—and repeating that several times (Ecker 2011; Schwarz 2007).

Mere repetition of a statement not only increases our memory of it, but also serves to increase the ease with which it spills off our tongue. And with this increased fluency comes increased believability (McGlone & Tofighbakhsh, 2000). Other factors, such as rhyming, further increase fluency and believability. “Haste makes waste” says nothing more than “rushing causes mistakes,” but it seems more true. What makes for fluency (familiarity, rhyming) also makes for believability. O. J. Simpson’s attorney understood this when crafting his linguistic slam dunk: “If [the glove] doesn’t fit, you must acquit.”

In his astonishingly perceptive Novum Organuum, published in 1620, Francis Bacon anticipated the modern science of gullibility by identifying “idols” or fallacies of the human mind. Consider, for example, his description of what today’s psychological scientists know as the availability heuristic—the human tendency to estimate the commonality of an event based on its mental availability (often influenced by its vividness or distinctiveness):

The human understanding is most excited by that which strikes and enters the mind at once and suddenly, and by which the imagination is immediately filled and inflated. It then begins almost imperceptibly to conceive and suppose that everything is similar to the few objects which have taken possession of the mind.


As Gordon Allport (1954, p. 9) said, “Given a thimbleful of [dramatic] facts we rush to make generalizations as large as a tub.”...

Bacon’s human fallacies also included our tendency to welcome information that supports our views, and to discount what does not:

The human understanding, when any proposition has been once laid down (either from general admission and belief, or from the pleasure it affords), forces everything else to add fresh support and confirmation....


Again, Bacon foresaw the point: “The human understanding is no dry light, but receives an infusion from the will and affections. . . . For what a man had rather were true he more readily believes.”...

Human intuition has powers, but also perils. “The first principle,” said physicist Richard Feynman (1974), “is that you must not fool yourself—and you are the easiest person to fool.” In hundreds of experiments, people have overrated their eyewitness recollections, their interviewee assessments, and their stock-picking talents. Often we misjudge reality, and then we display belief perseverance when facing disconfirming information. As one unknown wag said, “It’s easier to fool people than to convince them they have been fooled.” For this gullibility, our statistical intuition is partly to blame....

“The human understanding,” said Bacon, is “prone to suppose the existence of more order and regularity in the world than it finds.” In our eagerness to make sense of our world, we see patterns. People may perceive a face on the Moon, hear Satanic messages in music played backward, or perceive Jesus’ image on a grilled cheese sandwich. It is one of the curious facts of life that even in random data, we often find order (Falk 2009; Nickerson, 2002, 2005)....

As determined pattern-seekers, we therefore sometimes fool ourselves. We see illusory correlations. We perceive causal links where there are none. We may even make sense out of nonsense, by believing that astrological predictions predict the future, that gambling strategies can defy chance, or that superstitious rituals will trigger good luck. As Pascal recognized, “All superstition is much the same . . . deluded believers observe events which are fulfilled, but neglect and pass over their failure, though it be much more common.”...

Human gullibility feeds on fake news, mere repetition, vivid anecdotes, self-confirming assessments, self-justification, and statistical misinformation, and is then further amplified as people network with like-minded others. In one of my early experiments with George Bishop, high- and low-prejudice high school students were grouped with kindred spirits for discussion of racial issues, such as a case of property rights clashing with open housing. Our finding, and that of many other experiments since, was that like minds polarize (Figure 5; Myers & Bishop, 1970). Separation + conversation [leads to] polarization....

Within this echo-chamber of the like-minded, group polarization happens. Therefore, what begins as gullibility may become toxic. Views become more extreme. Suspicion may escalate into obsession. Disagreements with the other tribe can intensify to demonization. Disapproval may inflate to loathing....

The result of gullibility-producing biases and polarization is overconfidence in one’s own wisdom. Such overconfidence—what researchers have called cognitive conceit—comes naturally. For example, when people’s answers to factual questions—“Which is longer, the Panama or the Suez Canal?” “Is absinthe a liqueur or a precious stone?”—are 60 percent of the time correct, they will typically feel 75 percent confident (Fischhoff 1977; Metcalfe, 1998).

Overconfidence—the bias that Daniel Kahneman (2015), if given a magic wand, would most like to eliminate—feeds political misjudgment. Philip Tetlock (1998, 2005) gathered 27,000+ expert predictions of world events, such as whether Quebec would separate from Canada, or the future of South Africa. His finding: Like stock brokers, gamblers, and everyday citizens, they were more confident than correct. The experts’ predictions, made with 80 percent confidence on average, were right less than 40 percent of the time.

Citizens with a shallow understanding of complex proposals, such as cap-and-trade or a flat tax, may nevertheless express strong views. As the now-famous Dunning-Krueger effect reminds us, incompetence can ironically feed overconfidence (Krueger & Dunning, 1999). The less people know, the less aware they are of their own ignorance and the more definite they may sound. Asking them to explain the details of these policies exposes them to their own ignorance, which often leads them to express more moderate views (Fernbach 2013). “No one can see his own errors,” wrote the Psalmist (19:12, GNB). But to confront one’s own ignorance is to become wiser....

Science encourages a marriage of open curiosity with skepticism. “If you are only skeptical,” noted Carl Sagan (1987), “then no new ideas make it through to you.” But a smart mind also restrains gullibility by thinking critically. It asks, “What do you mean” and “How do you know”? “Openness to new ideas, combined with the most rigorous, skeptical scrutiny of all ideas, sifts the wheat from the chaff,” Sagan (1996, p. 31) added. Education is an antidote to what Sagan (1996, p. 25) feared—a future for his grandchildren in which “our critical faculties in decline, unable to distinguish between what feels good and what’s true, we slide, almost without noticing, back into superstition and darkness.” Happily, education works. It can train people to recognize how errors and biases creep into their thinking (Nisbett, 2015; Nisbett & Ross, 1980). It can engage analytic thinking: “Activate misconceptions and then explicitly refute them,” advise Alan Bensley and Scott Lilienfeld (2017; see also Chan et al., 2017). It can harness the powers of repetition, availability, and the like to teach true information (Schwarz 2017). And thus, at the end of the day, it can and does predict decreased gullible acceptance of conspiracy theories (van Prooijen, 2017)....

Truth matters.

-- Psychological Science Meets a Gullible Post-Truth World, by David G. Myers


Abstract

For us researcher-educators, the spread of misinformation is troubling. In the United States, for example, we feel distressed when public understandings radically diverge from reality—when voters believe, contrary to evidence, that crime is rising, that new immigrants are often criminals, that under Obama unemployment rose, and that climate change is a hoax.

Such gullibility crosses partisan lines. Most U.S. Democrats wrongly believed inflation had risen under Republican president Ronald Reagan. And most Republicans believed that taxes and unemployment had increased under Democratic president Barack Obama.

Some misinformation is intentional fake news—“lies in the guise of news.” But social-cognitive dynamics also feed gullibility. There is persuasive power to mere repetition, the availability heuristic, confirmation bias, self-justification, statistical illiteracy, group polarization, and overconfidence. And there is counteracting, truth-supportive power to evidence-based scientific scrutiny, education into critical thinking, and the religious mandate for humility.

“Trust me, Wilbur. People are very gullible.

They’ll believe anything they see in print.”

― E.B. White, Charlotte’s Web


Gullibility, the great enemy of wisdom, poisons and polarizes today’s public life. We live, declared the 2016 Oxford Dictionary with their word of the year, in a “post-truth” age. The Collins Dictionary seemingly concurred, by naming “fake news”—false information disseminated under the guise of news—its 2017 word of the year. “Is Truth Dead?,” pondered a 2017 TIME cover, set on a stark black background. And in 2018, the Rand Corporation offered a 326 page report on Truth Decay, exploring “the diminishing role of facts and analysis” in public life. But then some, such as Dilbert creator Scott Adams, an admirer of Donald Trump persuasion tactics, see opportunity, as conveyed by the title of his Win Bigly: Persuasion in a World Where Facts Don’t Matter.

In the United States, concerns for citizen gullibility cross party lines. From the Democratic Party side, Senator Al Franken (2017) used his parting Senate address to warn that “We’re losing the war for truth” and Hillary Clinton (2018) agreed: “We are in the midst of war on truth, facts and reason.” In his farewell address, President Obama (2017) warned that a “threat to democracy” was growing from the lack of a “common baseline of facts” and from underappreciating “that science and reason matter.” We have become, he lamented, “so secure in our bubbles that we start accepting only information, whether it’s true or not, that fits our opinions, instead of basing our opinions on the evidence that is out there.”

His one-time opponent, Republican Senator John McCain (2017) expressed comparable alarm about “the growing inability, and even unwillingness, to separate truth from lies.” McCain’s fellow Arizona Republican colleague, Senator Jeff Flake (2018), concurred: “2017 was a year which saw the truth—objective, empirical, evidence-based truth—more battered and abused than at any time in the history of our country.”

Concerns about gullibility and misinformation extend beyond political partisans. Is eating genetically modified (GM) foods safe? Yes, say 37 percent of U.S. adults, and 88 percent of 3,447 American Association for the Advance of Science members—both in Pew Research Center surveys (Funk & Rainie, 2015). Is climate change “mostly due to human activity?” Yes, say 50 percent of U.S. adults and 97 percent of climate experts (Cook et al., 2016).

“This is not about Republicans versus Democrats,” observed National Institutes of Health former director Harold Varmus (2017). “It is about a more fundamental divide, between those who believe in evidence . . . and those who adhere unflinchingly to dogma.” And that divide is hugely important, reflected British historian Simon Schama (2017): “Indifference about the distinction between truth and lies is the precondition of fascism.”

Gullibility and Misinformation Writ Large: The U.S. Example

In Enlightenment Now, Steven Pinker (2018) reminds us that human gullibility is longstanding: Unlike our medieval ancestors, few folks today “believe in werewolves, unicorns, witches, alchemy, astrology, bloodletting, miasmas, animal sacrifice, the divine right of kings, or supernatural omens in rainbows and eclipses.” Yet gullibility endures. Its enduring extent and impact—and the impetus for this symposium—appear in Americans’ striking misperceptions of social reality, with people’s beliefs often divorced from facts. “Between the idea/and the reality/ . . . falls the shadow” (T. S. Eliot). Some examples:

Perception: Crime is rising.

“The murder rate in our country is the highest it’s been in 47 years,” said Donald Trump (2017) shortly after his inauguration. Rising crime “is a dangerous permanent trend,” echoed his Attorney General, Jeff Sessions (2017)—both amplifying public fears that had helped put them in office. And most Americans nod their heads in agreement. Each year, right up to the present, 7 in 10 Americans have told Gallup they believe that the U.S. has suffered more crime than in the previous year (Figure 1, from Swift, 2016).

Image

Reality: Crime is falling.

But FBI violent crime data (aggregated from crimes reported to local law enforcement) reveals an alternative (actual) reality. Violent crime has plummeted since the early 1990s (2017; Figure 2). This reality of decreasing crime is confirmed in people’s self-reports for the Bureau of Justice Statistics’ National Crime Victimization Surveys (2016; Figure 3). Moreover, property crime rates and reports have similarly declined. Ergo, belief and fact have traveled in opposite directions. And when fear and fact conflict, fearmongering often wins—a phenomenon long ago recognized by Lord Chesterfield (1693–1773): “The best way to compel weak-minded people to adopt our opinion, is to frighten them from all others, by magnifying their danger.”

Image

Image

Perception: Many immigrants are criminals.

 “On the issue of crime,” a Gallup survey (McCarthy, 2017) reveals, “Americans are five times more likely to say immigrants make the situation worse rather than better (45% to 9%, respectively).” The National Academy of Sciences (2015) reports that this perception of crime-prone immigrants “is perpetuated by ‘issue entrepreneurs’ who promote the immigrant-crime connection in order to drive restrictionist immigration policy.”

Horrific rare incidents feed the narrative, as in the oft retold story of the Mexican national killing a young woman in San Francisco. Donald Trump’s (2015) words epitomized the perception: “When Mexico sends its people . . . they’re bringing drugs. They’re bringing crime. They’re rapists.” A January, 2018 Trump campaign ad extended this immigrants-as-killers theme with images of an illegal-immigrant murderer while a narrator referred to “evil, illegal immigrants who commit violent crimes,” noting that “Democrats who stand in our way will be complicit in every murder committed by illegal immigrants” (DonaldJTrump.com, 2018). His 2018 State of the Union address focused on the teary parents of two daughters said to have been murdered by a gang with illegal immigrant members. “If we don’t get rid of these loopholes where killers are allowed to come into our country and continue to kill … if we don’t change it, let’s have a shutdown,” Trump (2018) said two weeks later.

Reality: Immigrants are not crime-prone.

Immigrants who are poor and less educated may fit our image of criminals. Yet some studies find that, compared with native-born Americans, immigrants commit less violent crime (Butcher & Piehl, 2007; Riley, 2015). “Immigrants are less likely than the native-born to commit crimes,” confirms a National Academy of Sciences report (2015). After analyzing incarceration rates, the conservative Cato Institute (2017) confirmed that “immigrants are less likely to be incarcerated than natives relative to their shares of the population. Even illegal immigrants are less likely to be incarcerated than native-born Americans.” Noncitizens are reportedly 7 percent of the U.S. population and 6 percent of state and federal prisoners (KFF, 2018; Rizzo, 2018). Moreover, as the number of unauthorized immigrants has tripled since 1990 (Krogstad et al., 2017), the crime rate, as we have seen, plummeted.

Perception: Unemployment worsened during the Obama presidency.

In his presidential-bid announcement speech, Trump (2015) declared that “Our real unemployment is anywhere from 18 to 20 percent.” His voters heard and believed the repeated message, with 67 percent of them telling Public Policy Polling (2016) that unemployment had increased during the Obama years.

Reality: Following the recession-era doldrums that carried into Obama’s first year, unemployment steadily and substantially dropped (Figure 4; BLS, 2017).

By the time he left office, unemployment was down to 4.9 percent and some industries were facing a worker shortage.

Image

Perception: The stock market fell during the Obama presidency.

In the same Public Policy survey, Trump supporters were equally divided on whether the stock market had risen or fallen during the Obama years (4 in 10 believed each, with the remainder being unsure).

Reality: The stock market (S&P 500) nearly tripled during the Obama years.

Image

These recent U.S. examples have a partisan tinge. And it’s true that several analyses found that the top fake news stories of the recent U.S. election, some planted by Russians, were similarly partisan (Hachman, 2017; Lee, 2016). Thus, all evidence to the contrary, President Obama finished his time in office with 42 percent of Republicans still believing he was born in Kenya, making him ineligible to have been president (Zorn, 2017). And in 2018, a conspiracy theory flourished that the FBI harbored a dark secret society that was plotting against the Trump presidency (Cillizza, 2018).

Much gullibility is not so overtly partisan (NASA faked the moon landing; crashed UFO spacecraft are stored at Nevada’s Area 51; the Holocaust is a myth). Some bias is fostered by social scientists’ eagerness to believe claims that suit their (mostly) progressive values (Crawford & Jussim, 2018). And much political bias is bipartisan. Peter Ditto and his colleagues (2015, 2018) meta-analyzed the political bias literature and “found clear evidence of partisan bias in both liberals and conservatives, and at virtually identical levels.” Thus, both Democrats and Republicans tend to believe that, when their party holds the presidency, the president cannot control gas prices; but when the opposing party is in power they believe the president can do so (Vedantam, 2012). Or consider Democratic partisan bias in Larry Bartels’ analysis (reported by FiveThirtyEight.com) of

a 1988 survey that asked “Would you say that compared to 1980, inflation has gotten better, stayed about the same, or gotten worse?” Amazingly, over half of the self-identified strong Democrats in the survey said that inflation had gotten worse and only 8% thought it had gotten much better, even though the actual inflation rate dropped from 13% to 4% during Reagan’s eight years in office (Gelman, 2009).


Other research teams have confirmed mirror image bias (Brandt, 2017; Chambers, Schlenker & Collisson, 2013; Crawford, Kay, & Duke, 2015). Whatever supports our views, we tend to believe; whatever contradicts our views, we tend to dismiss. This humbling finding is a reminder to us all of how easy it is (paraphrasing Jesus) to “see the speck in our neighbor’s eye” while not noticing the sometimes bigger speck in our own.

Explaining Gullibility and Misinformation

“When people are bewildered they tend to become credulous,” warned Calvin Coolidge (1930). In a world of bewildering change, what explains the power of master manipulators and the striking embrace of false information regarding crime, immigration, the economy, Obama’s birth, and various conspiracy theories?

Fake News

Some credulity feeds on plain fake news—what Nicholas Kristof (2016) called “lies in the guise of news” as he described how Macedonian teens built fake websites to attract links and advertising dollars. Other times, fake news is motivated by politics rather than profit. France, Britain, and the United States, among other countries, have all accused Russia of aiming to sway public opinion and elections with legitimate-looking websites that tout falsehoods. Hence, shortly after the 2016 election, Barack Obama (2016) warned that “If we can’t discriminate between serious arguments and propaganda, then we have problems.” Facebook has taken steps to help identify fake news posts. But with new technology enabling hackers to place a head on another’s body, or to manipulate one’s words, tomorrows fake political videos may be a large problem (Farrell & Perlstein, 2018).

In the United States, considerable fake news has targeted Democrats, as with one chain e-mail that was “distinguished by its longevity and implausibility” (PolitiFact, 2009). Democratic House Speaker

Nancy Pelosi wants to put a Windfall Tax on all stock market profits (including Retirement fund, 401Ks and Mutual Funds!) Alas, it is true—all to help the 12 Million Illegal Immigrants and other unemployed minorities!


“Given the number of times we’ve been asked about this particular bit of bunk,” reported FactCheck.org (2009), “a lot of gullible people are indeed sending it on to their friends.”

But some fake news has sought to tarnish Republicans, as in reports of Donald Trump’s supposed 1998 People interview:

If I were to run, I’d run as a Republican. They’re the dumbest group of voters in the country. They believe anything on Fox News. I could lie and they’d still eat it up.


Although this interview comment never appeared in People, it became a Facebook news feed item that “just wouldn’t die” (Feldman, 2016; Snopes, 2017).

Pope Francis (2018) has deplored the infectious viral spread of fake news—“false information . . . meant to deceive and manipulate . . . by appealing to stereotypes and common social prejudices, and exploiting instantaneous emotions like anxiety, contempt, anger, and frustration.” As the managing director of political messaging firm, Cambridge Analytica explained to a supposed client, things don’t “need to be true, as long as they’re believed . . . . It’s all about emotion, it’s all about emotion” (Golgowski, 2018).

When emotion trumps evidence, gullibility ensues. And like the “crafty serpent” in the creation story, said Pope Francis, fake news uses mimicry (of real news)—a “sly and dangerous form of seduction that worms its way into the heart.” One wonders if he had a certain master manipulator in mind when quoting Dostoevsky’s The Brothers Karamazov: “People who lie to themselves and listen to their own lie come to such a pass that they cannot distinguish the truth within them, or around them, and so lose all respect for themselves and for others.”


Some fake news spreads not from demagoguery, but less maliciously from mere satire that gullible people misinterpret, as in the Borowitz headline that “Trump Threatens to Skip Remaining Debates if Hillary is There,” which Snopes (2016) felt compelled to explain was a spoof. Snopes has also felt compelled to discount other satirical reports, some from The Onion, that, for example,

• “Mike Pence said that he was disappointed in husbands and fathers for allowing women to participate in the Women’s March,”

• “The Secret Service has launched an ‘emotional protection’ unit for President Trump,” and

• “Donald Trump announced plans to convert the USS Enterprise into a ‘floating hotel and casino.’”

Mere Repetition

“Vaccines cause autism.” “Climate change is a hoax.” “Muslim terrorists pose a grave threat.” Never mind the facts—that, for example, of 230,000 murders on U.S. soil since September 11, 2001, an infinitesimal proportion—123 by 2017—were terrorist acts by Muslim Americans, with none committed by terrorists born in the seven nations covered by Donald Trump’s proposed anti-terrorist travel ban (Kristof, 2017). In 2015 and again in 2016, toddlers (with guns) killed more Americans than terrorists (Ingraham, 2016; Snopes, 2015).

Public gullibility about such myths is partly explained by the power of mere repetition. Much as mere exposure to unfamiliar stimuli breeds liking, so mere repetition can make things believable (Dechêne et al., 2010; Moons et al., 2009; Schwarz, Newman, & Leach, 2017). In elections, advertising exposure helps make an unfamiliar candidate into a familiar one, which partially explain why, in U.S. congressional elections, the candidate with the most money wins 91 percent of the time (Lowery, 2014).

Hal Arkes (1990) has called repetition’s power “scary.” Repeated lies can displace hard truths. Even repeatedly saying that a claim is false can, when discounted amid other true and false claims, lead older adults later to misremember it as true (Skurnik et al., 2005). As we forget the discounting, our lingering familiarity with a claim can also make it seem credible.


In the political realm, repeated misinformation can have a seductive influence (Bullock, 2006; Nyhan & Reifler, 2008). Recurring clichés (“Crooked Hillary”) can displace complex realities. George Orwell’s Nineteen Eighty-Four harnessed the power of repeated slogans: “Freedom is slavery.” “Ignorance is strength.” “War is peace.”

Moreover, falsehoods fly fast. On Twitter, lies have wings. In one analysis of 126,000 stories tweeted by 3 million people, falsehoods—especially false political news—“diffused significantly farther, faster, deeper, and more broadly than the truth” (Vosought, Roy, & Aral, 2018). Compared to true stories, falsehoods often are more emotionally dramatic, novel, and seemingly newsworthy. As Jonathan Swift (1710) anticipated, “Falsehood flies, and the Truth comes limping after it” (or in later renditions, “A lie can travel halfway around the world while the truth is putting on its shoes”).

Retractions of previously provided information also rarely work—people tend to remember the original story, not the retraction (Ecker 2011; Lewandowsky 2012). Courtroom attorneys understand this, which is why they will say something that might be retracted on objection, knowing the jury will remember it anyway. Better than counteracting a falsehood is providing an alternative simple story—and repeating that several times (Ecker 2011; Schwarz 2007).

Mere repetition of a statement not only increases our memory of it, but also serves to increase the ease with which it spills off our tongue. And with this increased fluency comes increased believability (McGlone & Tofighbakhsh, 2000). Other factors, such as rhyming, further increase fluency and believability. “Haste makes waste” says nothing more than “rushing causes mistakes,” but it seems more true. What makes for fluency (familiarity, rhyming) also makes for believability. O. J. Simpson’s attorney understood this when crafting his linguistic slam dunk: “If [the glove] doesn’t fit, you must acquit.”


Availability of Vivid (and Sometimes Misleading) Anecdotes

In his astonishingly perceptive Novum Organuum, published in 1620, Francis Bacon anticipated the modern science of gullibility by identifying “idols” or fallacies of the human mind. Consider, for example, his description of what today’s psychological scientists know as the availability heuristic—the human tendency to estimate the commonality of an event based on its mental availability (often influenced by its vividness or distinctiveness):

The human understanding is most excited by that which strikes and enters the mind at once and suddenly, and by which the imagination is immediately filled and inflated. It then begins almost imperceptibly to conceive and suppose that everything is similar to the few objects which have taken possession of the mind.


As Gordon Allport (1954, p. 9) said, “Given a thimbleful of [dramatic] facts we rush to make generalizations as large as a tub.” To persuade people of the perils of immigration and the need to “build the wall,” Donald Trump repeatedly told the vivid story of the previously deported homeless Mexican who fired a gun killing a San Francisco woman. (The bullet actually ricocheted off the ground, and the man was found not guilty.) The political use of dramatic anecdotes is bipartisan, as illustrated when the wrongful detaining of Australian children’s author Mem Fox at Los Angeles Airport triggered progressive’s outrage over Trump administration border policies. But with 51 million nonresident tourists entering the U.S. each year, it behooved us to remember that “the plural of anecdote is not data.” The staying power of vivid images contributes to misperception that crime has been increasing. In 2015, six of the top ten Associated Press news stories were about gruesome violence (Bornstein & Rosenberg, 2016). “If it bleeds, it leads.” Small wonder that Americans grossly overestimate their vulnerability to crime and terror.

In other ways, too, we fear the wrong things. We exhibit probability neglect as we worry about unlikely possibilities while ignoring higher probabilities. As Bacon observed, “Things which strike the sense outweigh things which do not immediately strike it, though they be more important.” Thanks to cognitively-available images of airplane crashes, we may feel more at risk in airplanes than in cars. In reality, from 2010 through 2014, U.S. travelers were nearly 2,000 times more likely to die in a car crash than on a commercial flight covering the same distance (National Safety Council, 2017). In 2017, there were no fatal commercial jet crashes anywhere in the entire world (BBC, 2018). For most air travelers, the most dangerous part of the journey is the un-scary drive to the airport.

After 9/11, as many people forsook air travel for driving, I estimated that if Americans flew 20 percent less (as airline data indicated) and instead drove half those unflown miles, we could expect an additional 800 traffic deaths in the ensuing year (Myers, 2001). Gerd Gigerenzer (2004, 2010) later checked that prediction against U.S. traffic accident data. The data confirmed an excess (compared to the prior five years) of some 1,595 deaths in the year following 9/11—people who “lost their lives on the road by trying to avoid the risk of flying.” Ergo, the terrorists appear to have killed, unnoticed, six times more people on America’s roads than they did with the 265 fatalities of those flying on those four planes.

In 2018, school shootings understandably captured attention. When an unarmed stranger wandered into the girls’ bathroom in my 2nd grade granddaughter’s school complex in the opposite corner of the country from Parkland, Florida, police surrounded the schools, helicopters flew overhead, and frightened children were ushered onto school buses overseen by guards with assault rifles. In schools elsewhere, children practiced huddling in closets during active shooter drills. Protecting children is appropriately a high priority. Yet Harvard risk expert David Ropeik (2018) calculates that the likelihood of any given school student being killed by a gun on any given day is incomprehensibly small—1 in 614,000,000—“far lower than almost any other mortality risk a kid faces, including traveling to and from school” or playing sports. Compared to the evil and emotions of a school shooting (or being eaten by a shark), “Statistics seem cold and irrelevant,” acknowledges Ropeik. But, he argues, exaggerated fears of an “extraordinarily rare risk” do their own form of harm to children’s security and well-being.

When estimating risks, reasonable people should, of course, seek data. Yet cognitive availability often predominates, as was illustrated one morning after I awoke at an airport hotel where I had been waylaid after a flight delay. The nice woman working the breakfast bar explained how, day after day, she met waylaid passengers experiencing weather problems, crew delays, and mechanical problems. Her conclusion (from her mentally available sample): Flying so often goes awry that if she needed to travel she would never fly.

Not-gullible people should likewise seek data when assessing global climate change: “Over time, are the planet air and seas warming? Are the polar ice caps melting? Are vegetation patterns changing? And should accumulating atmospheric CO2 lead us to expect such changes?” Yet thanks to the availability heuristic, dramatic weather events make us gasp, while such global data we hardly grasp. Thus, people’s recent weather experience contaminates their beliefs about the reality and threat of climate change (Kaufman 2017). People express more belief in global warming, and more willingness to donate to a global warming charity, on warmer-than-usual days than on cooler-than-usual days (Li 2011; Zaval 2014). A hot spell increases people’s worry about global warming, while a cold day reduces their concern. In one survey, 47 percent of Americans agreed that “The record snowstorms this winter in the eastern United States make me question whether global warming is occurring” (Leiserowitz 2011a). But then, after an ensuing blistering summer, 67 percent agreed that global warming helped explain the “record high summer temperatures in the U.S. in 2011” (Leiserowitz, 2011b). A tweet from Comedian Stephen Colbert (2014) gets it: “Global warming isn’t real because I was cold today! Also great news: world hunger is over because I just ate.”

Confirmation Bias and Self-Justification

Bacon’s human fallacies also included our tendency to welcome information that supports our views, and to discount what does not:

The human understanding, when any proposition has been once laid down (either from general admission and belief, or from the pleasure it affords), forces everything else to add fresh support and confirmation.


Reflecting on his experiments demonstrating this human yen to seek self-supporting evidence (the confirmation bias), Paul Wason (1981) concludes that “Ordinary people evade facts, become inconsistent or systematically defend themselves against the threat of new information relevant to the issue.” So, having formed a belief—that climate change is real (or a hoax), that gun control does (or does not) save lives, that people can (or cannot) change their sexual orientation—people selectively expose themselves to belief-supportive information. Our minds vacuum up supportive information. To believe is to see.

Confirmation bias and selective exposure give insight into the striking result of a May, 2016 Public Policy Polling survey. Among voters with a favorable view of Donald Trump (a subset of Republicans), most believed Barack Obama was Muslim rather than Christian (65 percent versus 13 percent). Among voters with an unfavorable view of Trump, the numbers were reversed (13 percent versus 64 percent). Since both can’t be right, the survey again displays gullibility writ large. And in the year after Trump’s inauguration, anti- and pro-Trump people could read reports of Trump campaign contacts with Russia and reach similarly opposite conclusions of either “collusion” or “a nothing burger.”

A sister phenomenon, self-justification, further sustains misinformation. To believe is also to justify one’s beliefs. This was dramatically evident in U.S. national surveys surrounding the Iraq war. As the war began, 4 in 5 Americans supported the war—on the assumption that Iraq had weapons of mass destruction, though only 38 percent said the war would be justified if there were no such weapons (Duffy, 2003; Newport 2003). When the war was completed without any discovery of WMDs, 58 percent now justified the war even without such weapons (Gallup, 2003). “Whether or not they find weapons of mass destruction doesn’t matter,” suggested Republican pollster Frank Luntz (2003), “because the rationale for the war changed.” As Daniel Levitin (2017, p. 14) observed in Weaponized Lies, “The brain is a very powerful self-justifying machine.”

Confirmation bias and self-justification are both driven by people’s motives. Motives matter, emphasize Stephen Lewandowsky and Klaus Oberauer (2016): “Scientific findings are rejected . . . because the science is in conflict with people’s worldviews, or political or religious opinions.” Thus, a conservative libertarian who cherishes the unregulated free market may be motivated to ignore evidence that government regulations serve the common good—that gun control saves lives, that mandated livable wages and social security support human flourishing, that future generations need climate-protecting regulations. A liberal may be likewise motivated to discount science regarding the toxicity of teen pornography exposure, the benefits of stable co-parenting, or the innovations incentivized by the free market. Again, Bacon foresaw the point: “The human understanding is no dry light, but receives an infusion from the will and affections. . . . For what a man had rather were true he more readily believes.”

Statistical Illiteracy

Our human powers of automatic information processing feed our intuition. As car mechanics and physicians accumulate experience, their intuitive expertise often allows them to quickly diagnose a problem. Chess masters, with one glance at the board, intuitively know the right move. Japanese chicken sexers use acquired pattern recognition to separate newborn pullets and cockerels with instant accuracy. And for all of us, social experience enables us, when shown but a “thin slice” of another’s behavior, to gauge their energy and warmth.

Human intuition has powers, but also perils. “The first principle,” said physicist Richard Feynman (1974), “is that you must not fool yourself—and you are the easiest person to fool.” In hundreds of experiments, people have overrated their eyewitness recollections, their interviewee assessments, and their stock-picking talents. Often we misjudge reality, and then we display belief perseverance when facing disconfirming information. As one unknown wag said, “It’s easier to fool people than to convince them they have been fooled.” For this gullibility, our statistical intuition is partly to blame.

Probability neglect.

Consider, for example, how statistical illiteracy and misinformation feed health scares (Gigerenzer, 2010). In the 1990s, the British press reported that women taking a particular contraceptive pill had a 100 percent increased risk of stroke-risking blood clots. This caused thousands of women to stop taking the pill, leading to many unwanted pregnancies and 13,000 additional abortions (which were also linked with increased blood-clot risk). A study indeed had found a 100 percent increased risk—but a nominal increase from 1 in 7000 to 2 in 7000.

In one study, Gigerenzer (2010) showed how gullibility crosses educational levels. He invited people to estimate the odds that a woman had breast cancer, given these facts: Among women in her age group, 1 percent had breast cancer. If a woman had breast cancer, the odds were 90 percent that a mammogram would show a positive result. Now imagine a woman had a positive mammogram. What is the probability that she had breast cancer? This simple question stymied even physicians, who greatly overestimated her risk.

But consider the same information framed with more transparent natural numbers: Of every 1000 women in this age group, 10 had breast cancer. Of these 10, 9 will have a positive mammogram. Among the other 990 who don’t have breast cancer, some 90 will have a false positive mammogram. So, again, what is the probability that a woman with a positive mammogram had cancer? Given the natural numbers, it becomes easier to see that among the 100 or so women receiving a positive result, only 10, or about 1 in 10, actually had breast cancer.
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Re: Psychological Science Meets a Gullible Post-Truth World

Postby admin » Sun Dec 05, 2021 2:51 am

Part 2 of 2

Perceiving order in random events.

“The human understanding,” said Bacon, is “prone to suppose the existence of more order and regularity in the world than it finds.” In our eagerness to make sense of our world, we see patterns. People may perceive a face on the Moon, hear Satanic messages in music played backward, or perceive Jesus’ image on a grilled cheese sandwich. It is one of the curious facts of life that even in random data, we often find order (Falk 2009; Nickerson, 2002, 2005).

Random sequences seldom look random because, more than people expect, they contain streaks. Coin tosses have more runs of heads and of tails than people expect from random coin tosses. Likewise, basketball-shooting and baseball-hitting outcomes that mimic random coin tossing appear to have “hot” or “cold” streaks for which sports fans have ready explanations—as if there were something to explain (Gilovich 1985; Reifman, 2011). And as Burton Malkiel’s many editions of A Random Walk Down Wall Street document, stock pickers are similarly tempted to see patterns in random data and to overestimate their ability to beat the efficient marketplace.

As determined pattern-seekers, we therefore sometimes fool ourselves. We see illusory correlations. We perceive causal links where there are none. We may even make sense out of nonsense, by believing that astrological predictions predict the future, that gambling strategies can defy chance, or that superstitious rituals will trigger good luck. As Pascal recognized, “All superstition is much the same . . . deluded believers observe events which are fulfilled, but neglect and pass over their failure, though it be much more common.”

Misinterpreting regression toward the mean.

Another common source of gullibility is our natural underappreciation of statistical regression. Because average results are more typical than extreme results, we may expect that, after an unusual event, things will tend to regress (return) toward their average level. Extraordinary events tend to be followed by more ordinary ones.

It seems obvious, yet we often miss it: We sometimes attribute what may be a normal regression (the expected return to normal) to something special. For example, students who score much lower or higher on an exam than they usually do will tend, when next tested, to return to their average. And unusual ESP subjects who defy chance when first tested nearly always lose their “psychic powers” when retested (a phenomenon parapsychologists have called the decline effect).

Failure to recognize such regression feeds superstitions and ineffective practices. When day-to-day behavior contains chance fluctuation, we may notice that others’ behavior improves (regresses toward average) after we criticize them for an unusually bad performance, and that it worsens (regresses toward average) after we praise them for an exceptionally fine performance. Ironically, then, regression toward the average can mislead us into feeling rewarded for having criticized others and into feeling punished for having praised them (Tversky & Kahneman, 1974). Coaches who berate their teams at halftime after an exceptionally bad performance will tend to feel rewarded with a more normal second half performance, and vice versa for those who lavish praise after an outstanding first half performance.

The inverse fallacy.

“Nearly 3 in 4 individuals convicted of terrorism-related charges are foreign-born,” tweeted Donald Trump on January 16, 2018. Trump’s assertion—supporting increased restrictions on immigration—was supported by his Justice and Homeland Security Departments’ report of data from U.S. federal courts: from 9/11/2001 through 2016, 402 of the 549 people convicted of international terrorism-related charges were foreign born. The implied message: fear immigrants.

For two reasons, the statistic is “deeply misleading,” reported Leaf Van Boven and Paul Slovic (2018). First, the “3 in 4” statistic was inflated by excluding domestic terrorism, which is what Americans most fear, and including terrorism-related activities such as perjury and petty theft that were tenuously related to terrorist acts.

Second, the report exploited people’s statistical gullibility by committing the inverse fallacy. People often assume that the probability that A has happened given B implies the probability of B given A. If informed that heroin addicts have used marijuana, we may then assume that marijuana users are at high risk for heroin addiction.

People are especially prone to the inverse fallacy when it confirms their preexisting belief, but not when they know enough to know better. Consider: Among the some 450 National Basketball Association players, about 3 in 4 are African-American. Even so, “a vanishingly small” percentage of African-American men—less than 0.01 percent—play in the NBA. Thus, note Van Boven and Slovic, if you know only that a man is African-American you can confidently predict he is not an NBA player.

Similarly, if you know someone in the U.S. is foreign born, you can be virtually certain the individual has not engaged even in terrorist-related international activities—as did but 402 of 41 million people born outside the U.S.—less than .001 percent. The likelihood of a domestic terrorist being an immigrant is extremely low. But vastly lower still is the inverse likelihood of an immigrant being a domestic terrorist. To intentionally conflate the two is malignant misinformation that exploits people’s statistical gullibility.

When combined with vivid, emotion-eliciting anecdotes of killer immigrants, such lying with statistics amplifies people’s fears. People understand the infinitesimal chance that an African-American plays in the NBA, yet may succumb to “fear-based inverse fallacy tactics” that fit their preexisting anxieties about immigrants. And so it is that statistical lies oppress human lives.

Group Polarization

Human gullibility feeds on fake news, mere repetition, vivid anecdotes, self-confirming assessments, self-justification, and statistical misinformation, and is then further amplified as people network with like-minded others. In one of my early experiments with George Bishop, high- and low-prejudice high school students were grouped with kindred spirits for discussion of racial issues, such as a case of property rights clashing with open housing. Our finding, and that of many other experiments since, was that like minds polarize (Figure 5; Myers & Bishop, 1970). Separation + conversation [leads to] polarization.

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This group polarization phenomenon—discussion magnifying a group’s preexisting leanings—helps fuel both public good (when benevolent tendencies strengthen) and evil (from gang delinquency to terrorism). As with hot coals, like minds strengthen one another.

In communities, like minds are segregating more and more. Progressive places have attracted progressive people, and become more progressive. Ditto conservative places. Thus the percent of Americans living in landslide counties—those with 60+ percent voting for the same presidential candidate—rose from 38 percent in 1992 to 60 percent in 2016 (Aisch, Pearce, & Yourish, 2016). And the proportion of entering collegians describing themselves as politically “middle of the road” dropped from 60 percent in 1983 to 42 percent in 2016—with corresponding increases in those with “far left” and “far right” identities (Eagan 2017; Twenge 2016).

As I cut my eye teeth in social psychology with studies of group polarization, I did not foresee the creative possibilities or potential dangers of polarization enabled by social media, with liberal and conservative websites linking people mostly to kindred sites (Figure 6; Lazer et al., 2009). The internet enables cancer survivors and conspiracy schemers to congregate with like-minded others and to share support for their shared aspirations and suspicious. With customized news feeds, retweets, and self-selections from a varied news buffet, we devour information—and misinformation (Bakshy 2015; Barberá, 2015). “Dear Satan,” tweeted Steve Martin (2016), “thank you for having my internet news feed tailed especially for ME!”

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Within this echo-chamber of the like-minded, group polarization happens. Therefore, what begins as gullibility may become toxic. Views become more extreme. Suspicion may escalate into obsession. Disagreements with the other tribe can intensify to demonization. Disapproval may inflate to loathing.

Overconfidence

The result of gullibility-producing biases and polarization is overconfidence in one’s own wisdom. Such overconfidence—what researchers have called cognitive conceit—comes naturally. For example, when people’s answers to factual questions—“Which is longer, the Panama or the Suez Canal?” “Is absinthe a liqueur or a precious stone?”—are 60 percent of the time correct, they will typically feel 75 percent confident (Fischhoff 1977; Metcalfe, 1998).

Overconfidence—the bias that Daniel Kahneman (2015), if given a magic wand, would most like to eliminate—feeds political misjudgment. Philip Tetlock (1998, 2005) gathered 27,000+ expert predictions of world events, such as whether Quebec would separate from Canada, or the future of South Africa. His finding: Like stock brokers, gamblers, and everyday citizens, they were more confident than correct. The experts’ predictions, made with 80 percent confidence on average, were right less than 40 percent of the time.

Citizens with a shallow understanding of complex proposals, such as cap-and-trade or a flat tax, may nevertheless express strong views. As the now-famous Dunning-Krueger effect reminds us, incompetence can ironically feed overconfidence (Krueger & Dunning, 1999). The less people know, the less aware they are of their own ignorance and the more definite they may sound. Asking them to explain the details of these policies exposes them to their own ignorance, which often leads them to express more moderate views (Fernbach 2013). “No one can see his own errors,” wrote the Psalmist (19:12, GNB). But to confront one’s own ignorance is to become wiser.


Conclusion: Gullibility and Humility

This enumeration of the roots of gullibility could be extended with explanations of the anchoring effect, belief perseverance, the false consensus phenomenon, issue framing, the fundamental attribution error, hindsight bias, illusory correlations, implicit associations, in-group bias, the just-world phenomenon, memory construction, mood-congruent memories, perceptual illusions, self-serving perceptions, implicit associations, in-group bias, the representativeness heuristic, and more. But this has been enough to appreciate that Pascal was right: “The human understanding is like a false mirror.” We can acknowledge human gullibility while still respecting our remarkable information-processing powers—appreciating, with Shakespeare’s Hamlet, “in apprehension how like a god!” Our species is smart enough to have invented talking computers, cracked our genetic code, and traveled to the moon. Three cheers for our human brilliance.

Or maybe two cheers, because our mind’s premium on efficiency enables us, with striking ease, to adapt successfully but also to form and sustain false beliefs. “The naked intellect,” observed novelist Madeline L’Engle (1973), “is an extraordinarily inaccurate instrument.”

For this, science, education, and religion each offer remedies.

Science encourages a marriage of open curiosity with skepticism. “If you are only skeptical,” noted Carl Sagan (1987), “then no new ideas make it through to you.” But a smart mind also restrains gullibility by thinking critically. It asks, “What do you mean” and “How do you know”? “Openness to new ideas, combined with the most rigorous, skeptical scrutiny of all ideas, sifts the wheat from the chaff,” Sagan (1996, p. 31) added. Education is an antidote to what Sagan (1996, p. 25) feared—a future for his grandchildren in which “our critical faculties in decline, unable to distinguish between what feels good and what’s true, we slide, almost without noticing, back into superstition and darkness.” Happily, education works. It can train people to recognize how errors and biases creep into their thinking (Nisbett, 2015; Nisbett & Ross, 1980). It can engage analytic thinking: “Activate misconceptions and then explicitly refute them,” advise Alan Bensley and Scott Lilienfeld (2017; see also Chan et al., 2017). It can harness the powers of repetition, availability, and the like to teach true information (Schwarz 2017). And thus, at the end of the day, it can and does predict decreased gullible acceptance of conspiracy theories (van Prooijen, 2017).

Finally, religion provides a deep rationale for the humility that underlies science and critical thinking. All varieties of theism assume that 1) there is a God, and 2) it’s not you or me. As fallible creatures we should therefore hold our own beliefs tentatively (our surest conviction can be that some of our beliefs err). We should assess others’ ideas with open-minded skepticism. And when appropriate, we should use observation and experimentation to winnow truth from error. As St. Paul advised (I Thessalonians 5:21), “Test everything, hold fast to what is good.” Truth matters.

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Re: Psychological Science Meets a Gullible Post-Truth World

Postby admin » Mon Jan 03, 2022 8:09 am

The history of fraud -- art
by guardian.co.uk
2011

You would be mistaken if you thought art forgery was a recent thing. In fact, for as long as art works have been coveted, they have been forged, faked and fobbed off on untrained eyes. There are even examples of Romans forging ancient Greek sculptures to turn a fast buck.

In 1496, Michelangelo himself faked a piece of sculpture and sold it to Cardinal Riario of San Giorgio. The piece was a sleeping cupid figure, which Michelangelo treated with sour earth to make it seem ancient. When the Cardinal later learned of the fraud he demanded his money back.


For many centuries, copying another artist's work was done more for practice and as a tribute than in order to deceive a buyer. Many old masters -- Rembrandt for one -- taught their pupils by getting them to copy works in their style. In return for their tuition, the teacher was then allowed to sell those works as their own. This caused significant confusion to art historians who had to decipher which works were genuine old masters', and which merely produced under their tutelage.

The most infamous forgeries have taken place in the 20th century, for one, the "Etruscan" terracotta warriors that were sold to the New York Met between 1915 and 1921. These sculptures were passed off as work by ancient Etruscan artisans, but were in reality created by two Italian brothers and their sons.

Pio and Alfonso Ricardi began their career as art forgers when Roman art dealer Domenico Fuschini hired them to forge ancient ceramics for him to sell. They proved so adept at the techniques used by ancient civilisations that they were soon creating much larger fakes. In 1908, the British Museum bought a large bronze chariot that the brothers claimed they had found in an Etruscan fort near Orvieto.

In 1915, the Ricardis enlisted aid of sculptor Alfredo Fioravanti and created a two-metre statue of a warrior which was then sold to the New York Met. The same museum also bought their next two pieces of work, the Colossal Head, in 1916, and the Big Warrior, designed by Pio's eldest son Ricardo, in 1918 -- this piece alone cost the museum $40,000.


The three warrior statues were exhibited together in 1933, but in the years that followed various art historians voiced concern about their legitimacy. Finally, in 1960, a chemical test indicated that the black glaze used on the sculptures contained manganese, which was never used by the Etruscans. In January 1961, Alfredo Fioravanti came clean, signing a full confession at the US consulate in Rome.

One artist whose fraudulent paintings have come to light is John Myatt, whose versions of paintings by artists such as Marc Chagall, Le Corbusier, Jean Dubuffet, Alberto Giacometti, Matisse, Ben Nicholson and Graham Sutherland were sold at major auction houses.

What made these fakes difficult to spot was the paper trail that was created by Myatt's associates to lend credence to their genuineness, including certificates of authenticity and invoices of previous sales. Erroneous material -- letters, pages of art catalogues featuring fakes was even inserted into archives in case anyone checked up on what was being offered for sale. He was caught and convicted, but now however, you can buy one of his "genuine fakes" from his own website.

The era of the forgery may now be over, however, due to the complex methods now available to art historians charged with ascertaining the legitimacy of a piece of work. Carbon dating, pigment analysis and X-ray fluorescence are all used to date paintings and sculpture, and the materials of which them comprise. It's hard to fool a carbon dating test, even if forgers source original materials to construct their fabrication. It is even possible to take fingerprint scans from dried paint on the canvass - and there's no better proof of legitimacy than that.

These techniques have made the life of a forger much harder, but they've also been used to prove the provenance of works previously branded forgeries. In 2004, Vermeer's Young Woman Seated at the Virginals was declared genuine, having been labelled a forgery back in 1947.
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Re: Psychological Science Meets a Gullible Post-Truth World

Postby admin » Tue Jan 04, 2022 10:46 am

Is Sanskrit really the best language for computer programming?
by techzoworld
April 24, 2018
https://techzoworld.wordpress.com/2018/ ... ogramming/

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I spend a lot of time on the internet searching for interesting things to learn. The search isn’t specific and neither is the inflow of information. I take what I get. Sadly some of it is utter nonsense. I happened upon a few articles recently that suggest Sanskrit, the ancient nigh dead Indian language, is good for computer programming and that NASA uses it to program artificial intelligence. A peek at the headlines triggered my bullshit alarm -– we should all have one -– but, in those moments of curiosity, I perused their contents. They were so very devoid of rationality, I had to search for a fun little activity to take my mind off it. Betteridge’s law of headlines did the trick. Betteridge’s law: If the headline to an article is a question, the answer is always no.

What it’s all about

There was a paper by Rick Briggs, a NASA researcher, published in the spring issue of Artificial Intelligence magazine in 1985 (Volume 6 Number 1), entitled ‘Knowledge Representation in Sanskrit and Artificial Intelligence’. It can be found here on AAAI’s website. Noteworthy: ‘Rick Briggs’ at best is a pseudonym. There are absolutely no other works in related fields attributed to this name. Another less likely plausible inference is that Rick Briggs just doesn’t exist -– there are no publicly available records of him ever having worked for RIACS, NASA. That, however, in no way impacts the merit of his arguments.

It begins with Briggs describing the then current state of events surrounding artificial intelligence. It had been quite an undertaking to design unambiguous representations of natural languages for the purpose of computer processing. Natural languages -– the way humans communicate with each other -– had not been easy to parse and transform into information that a machine could understand. Even if they could overcome that barrier, there was the issue of ambiguity -– statements could mean different unrelated things, depending on the context. A human who spoke the language wouldn’t find it hard to understand what was actually meant, but computers would. It led to the belief that there might not be a way to effectively exchange information with machines without the help of an artificial language.

Briggs, in his paper, challenged that belief by drawing attention to the fact that there has existed at least one natural language which could, in theory, be used as an artificial language. It had a logical structure that mapped on to certain knowledge representation schemes perfectly. That language, of course, was Sanskrit.


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The contents

The paper provides a whole lot of compelling arguments that show it is indeed possible for a natural language to work as an artificial one. That’s it. It does not at all claim that Sanskrit has to be that language. Sure, it uses Sanskrit as a case study, but that’s all there is to it. A quick read of the 8 page piece should make that clear.

If you’ve haven’t time for that, or are unable to comprehend the piece (likelier, but we’ll pretend it’s the former), here’s a gist of the points he tried to make. I’ve used my natural intelligence to summarise it. It’s not chronological but exhaustive.

1. A perfect natural language must have these characteristics.
• A statement should be easy to break down into a semantic net or an array of semantic data. (He referred to the array as series of triplets.)
• It should be easy to compile a natural language statement from the data array. It should be human readable and comprehensible.
• The statements coming out should be about the same as the ones going in. It shouldn’t sound weird, nor should it lose or gain information.
• Deviations if any should be minimum.

2. Sanskrit, as it turns out, does all of that. It has an extremely logical structure. It’s grammar rules allow a kind of precision unmatched by other languages. It has a near unchanging syntax.

3. The computer readable data representation of a Sanskrit statement can be obtained by simply placing the individual words of the sentence in an array. This is aided by the fact that word order simply makes no difference in Sanskrit.

4. That very sentence can be reconstructed by putting together the contents of the array.

5. The language is extremely concise. It has perhaps the highest information to word count ratio. There are no redundancies.

Brilliant stuff, isn’t it? The following is an excerpt from the last paragraph of Briggs’ work.

It is interesting to speculate as to why the Indians found it worthwhile to pursue studies into unambiguous coding of natural language into semantic elements. It is tempting to think of them as computer scientists without the hardware, but a possible explanation is that a search for clear, unambiguous understanding is inherent in the human being.


Make a note. The conclusion of the paper was that humans are capable of using an extremely precise unambiguous language. That should save you some back and forth when we debunk baseless claims.

A few truths

Sanskrit is a brilliant language. I’m not kidding and neither am I being sarcastic. It really is the most precise language in existence, with Latin being a close second. However, it isn’t a perfect language and it isn’t natural either.

Sanskrit’s efficiency

Sanskrit makes use of declensions in nearly every part of speech. This means the ends of words, every single one of them, change depending on the part of speech they’re supposed to be. Even proper nouns aren’t exempt. The ends of people’s names change in a sentence depending on whether they’re the subject or the object. This is a bit of a problem for people whose names don’t end in a vowel as there is no provision for that in Sanskrit.

The rules of inflections are precise. Just by knowing the ends of a word, one could know its role in a sentence. This makes word order a non issue. A three word sentence could be written six different ways and a four word sentence in twenty four. None of the permutations would alter their meaning.

Because of the use of declensions, a lot of information is packed in fewer words. This makes transmission of information extremely efficient in speech. Sanskrit is not the only language that can do this though. Latin, an equally dead language, also allowed word order independent sentences in a similar way. Latin too had quite a complicated set of grammar rules. It, like Sanskrit, isn’t spoken very much because humans naturally tend to deviate toward simplicity.


Storage issues

Despite the arguably best verbal efficiency, there are a few issues with the language in actual knowledge representation. Sanskrit has a glyph based script rather than the alphabet based script as with Latin and its derivatives.

Latin alphabets take one byte of space each. Sanskrit written in the current character set for the Devanagari script is however not an efficient way of storing information. Here’s a list of why that is.


• Vowels or consonant glyphs with the inherent vowel takes up 2 bytes of space each.
• The combination of a consonant glyph and a different vowel takes 4 bytes.
• A consonant with a suppressed vowel is 4 bytes.
• A double consonant glyph is 6 bytes.
• A double consonant glyph combined with a vowel is 8 bytes.

Latin script, on the other hand, is consistent. You spend exactly the same number of bytes in conveying a message as the number of letters it contains. My name, ‘Denver’, takes up 6 characters, 6 keystrokes and 6 bytes in the Latin script. The crude and borderline terrible Devanagari transliteration, ‘डेन्वर्’, takes 3 glyphs (in some renditions, it might look like four -– in that case, the two in the middle are a single glyph), 7 careful keystrokes and 14 bytes.

If the character set were redone to start with Devanagari characters rather than the Latin ones, they could reduce space consumption to about a half. Unfortunately, that would mean I’ll be spending a byte more to write my name in the wrong script and still have it screw up the pronunciation. Sanskrit is phonemically precise in that the pronunciation of words don’t deviate. It does not have a universal phonology. A native speaker of a Sanskrit derived language will find it hard to sound in other languages.


Sanskrit’s naturalness

The fact is that Sanskrit, unlike other languages, hasn’t had a natural evolution. Nearly everything about Sanskrit, as is known today, was codified sometime around the year 500 BCE by one person, Panini, who was bent on making it as precise and concise as was humanly possible. Sanskrit didn’t simply happen to have the required characteristics of an artificial language by coincidence. It’s there by design. It is indeed the work of a primitive computer scientist without the hardware. This is not to say Panini intended for his language to be used with machines. At best, his work caught the eye of a pattern seeking human in need of an answer to a difficult, perhaps unsolvable problem -– it was bound to happen sooner or later.

The Sanskrit of today, the one reportedly spoken by a few tens of thousands, is about the same as that codified two and a half millennia ago. The language doesn’t evolve, it can’t evolve. Unlike natural languages, speakers of Sanskrit cannot be classified as proficient or eloquent as its precision does not allow gradations. You either speak the language or you don’t; there is no grey. Even artificial languages do not suffer that restriction.

Sanskrit was never widely spoken. During the past two and a half millennia, Sanskrit scholarship was an exclusive club. None other than the Brahmins were allowed to use it. That all literary works in Sanskrit was made accessible only to the Brahmins, spelt its doom. The thing about languages is that, like living organisms, languages too evolve by natural selection.

Natural languages thrive by fitting the need of the era. The flexible of the lot flourish organically forcing the less prominent ones to wither away. Sanskrit’s resistance to change was the reason of its demise. This is essentially why every attempt to revive the language will fail, no exceptions.


The argument of "brahmanical fantasy" has been used in other areas as well. Cf. Mill's statement on the Brahmins above. Also, in connection with the Dhatupatha, a list of some two thousand verbal roots of which more than half have not been met with in Sanskrit literature, it has been suggested that it was "concocted" by the Indian grammarians (Whitney 1884; reprinted in Staal 1992: 142). In fact, the Indian pandits have been accused of inventing the Sanskrit language (Dugald Stewart and Christoph Meiners, quoted in Rosane Rocher 1983: 78).

-- Chapter 4: Law Books in an Oral Culture: The Indian Dharmasastras, Excerpt from "Studies in Hindu Law and Dharmaśastra", by Ludo Rocher


The actual point

The paper does not at all contain any claim, mention or indication that Sanskrit can be used as a programming language. In fact, the one and only instance of the word ‘program’ was in an example sentence meant to illustrate semantic nets. (The subject was a programmer.) Every single use of the word ‘code’ or variations thereof have been used to describe sentence construction rules or grammatical syntax. Notice that in my systematic summarisation of Briggs’ piece, the word ‘program’ doesn’t appear once.

The question Briggs tried to answer was whether it was possible for one to create a perfect language for knowledge representation. If a computer scientist were to codify a new language humans could use just as well as a machine, what would the end result look like? He then shows how Sanskrit manages to fulfil all of those requirements
. To him, it was astonishing to find that someone who lived a long while ago could accomplish such a feat of brilliance; the entire piece is a recurring acknowledgement of that fact.

Even after all of that, he never once suggested that Sanskrit should be used for knowledge representation. He insisted however that if anyone attempted to create such a language, they would do well to follow a similar pattern of processes as Panini did with Sanskrit.

Not entirely right

Briggs did get a few things wrong in his piece. I wouldn’t say he meant to mislead; his work shows his genuine appreciation for Sanskrit. There are, however, a few fallacies he seemed to have overlooked.

A precise language, by definition, wouldn’t allow the many stylistic devices that make natural languages worth using. A language like that wouldn’t allow metaphors, innuendos, synecdoches, litotes, hyperboles, puns and personification -– they’re all inherently ambiguous. Sanskrit however is capable of all of those, its literature being a glaring proof of it. Without exactly those seven, the totality of Sanskrit works would see their volume reduced to about a quarter. On the other hand, owing to word order independence, devices like hypallages, anastrophes, hyperbatons and general inversions are baked into every statement made in the language; they thus don’t really stand out.

The degree of precision that Sanskrit affords its speakers prevents verbosity i.e. purposefully lengthening prose for effect. Attempts at verbosity leads to a redundant prose. Translating to Sanskrit from any other language would thus lead to loss of data. This data isn’t particularly useful in the context of the prose, but having it allows one to deduce information about the author -– things like their personality and state of mind while writing. A language that attains precision does so at the expense of creativity. This clearly doesn’t happen with Sanskrit considering the abundance of Sanskrit works.

Here’s the thing though. People who praise Sanskrit for its precision are the same people who suggest that works in the language need interpretation by scholars. They’re the same people who bend their scriptures to make them appear to reference newly discovered scientific facts. They say Sanskrit doesn’t need disambiguation [the act or process of distinguishing between similar things, meanings, names, etc., in order to make the meaning or interpretation more clear] while failing at translating all of the “ancient knowledge” trapped in their literature.


So what happened?

All of what we’ve discussed until now comes from a single paper in a magazine issue published a little under 30 years ago. Every single hoax about Sanskrit as programming language can be traced back to it. From the hundreds of internet articles parroting the supposed “findings” of the NASA researcher, through the thousands of derivative works attempting to explain the efficacy of Sanskrit as a computer language in their own ways, to Indian politicians claiming that knowing Sanskrit is an obligatory prerequisite for computer literacy, all of that, everything goes back to that one paper. If I wasn’t already clear (or you skipped the above sections), the paper suggests nothing of the sort.

Of course, that doesn’t in and of itself mean anything. It is possible that the paper just gets quoted a lot for having kickstarted all of that research into Sanskrit. The logical next question is, is there any research at all? So, I dedicated about two hours of my info-binging time to look up research related to Sanskrit. Almost all of the publicly accessible real academic research on the language is about its literature, its cultural impact and decoding its complex grammatical rules –- yes, that’s still a work in progress apparently. Every research that relates to both, the language and computation, are conducted under dedicated Sanskrit research academies based in India. I’m not saying research done in India is any less worthy than elsewhere. However, there is none to back the claims about Sanskrit gaining a foothold in modern computing.

So, how’s artificial intelligence been doing all those years since 1985? Well, good… pretty good actually. For instance, the most popular search engine, Google, does extremely well in guessing what it is you mean when you enter your search terms –- that is indeed an example of AI if you’re wondering. Facebook’s graph search is a semantic search engine meant to answer natural language queries pertaining to interactions on the social network. Bing’s contextual search is capable of answering your follow up queries almost as if it were a conversation. Shazam and SoundHound can tell you what song is playing around you. Genius -– a feature of Apple’s iTunes can create a playlist of songs similar to the selected one and is known to get better at predicting what a user might like. Oh Siri! How could I forget about that? Siri, Google’s voice search and Microsoft’s Cortana -– they’re AI too you know.

Besides, give it some hard thought for a moment. Let’s assume Briggs did suggest that Sanskrit must be used as an artificial language. It raises a few questions. Foremost, what exactly will that accomplish? Sure, a native Sanskrit speaker will not be disappointed when a computer understands everything they say. Would anyone on this planet be willing to learn Sanskrit just to clearly communicate their ideas to a machine? Of course not. If a fifth of the world or even a fiftieth spoke the language, it would make some sense. A fiftieth is still ten thousand times larger than the self-reported Sanskrit speaking population. See, when nearly all programs are written in English, there is little incentive for programmers to pursue exotic languages. Again, this does not mean a Sanskrit parser can never be created. It can, but the efforts will have to come from those who actually care about it. (In a Venn diagram that would be the intersection of the sets ‘people who have learnt or will learn Sanskrit’ and ‘people who have learnt or will learn programming and not just for an IT job’.)

Let’s look at that a bit differently. Sanskrit is the second official language in the Indian state of Uttarakhand. It had a population of a little over 10 million as in the 2011 census. The number of people who declared Sanskrit as their native language in the 2001 census was a bit over 14 thousand. Assuming by some miracle that number doubled in ten years and every native speaker of the language moved to Uttarakhand, it’s still a huge undertaking to make special provisions for what seems to be fewer than 0.3% of the state’s people. Yes, that can be explained by misplaced pride, extreme nationalism and a hint of idiocy. That’s some inconsistent minority appeasement, especially considering Garhwali and Kumaoni, two of the state’s most spoken languages after Hindi, do not get the same treatment despite each of them having over a hundred times more speakers than those of Sanskrit.

Another important question: Why not focus our efforts on writing AI that understands normal humans speech rather than structured speech? Yes, that will make coding a natural language parser much more difficult, but that’s a problem to solve, not to ignore. Suggesting the use of Sanskrit as an AI language is like spelling the letters in ‘nirvana’, in a spelling bee, instead of ‘liberation’ because the latter is harder. Teaching the world that language to simplify the work of developers of natural language parsers -– that would be reinventing the wheel.

Great! I’ve spent a lot of energy arguing against Sanskrit for natural language processing. How are AI researchers planning to solve that problem? Have they moved in a different direction or was all of this “Sanskrit bashing” a pointless exercise? I’m so glad you asked and yes, they have. Instead of dissecting every statement into its constituent words, natural language parsers use a statistics intensive approach to guess their actual meaning. Inputs are compared with massive databases of previously parsed information. Based on the context, the interpretation engine would determine the one that was most probably meant. This means words don’t necessarily need to each be separately analysed. The system will also have a parallel rating component that would evaluate whether it output the right thing. Over a large enough duration, by collecting and consolidating the information gained from a lot of users, the system would get better at understanding natural languages.

I would argue that English is in fact the best language to test the scope of natural language parsing simply because the evolution of English isn’t regulated by an academy like many others. It’s free to change and vary depending on the culture that speaks it. English linguists are almost exclusively descriptivists -– they don’t police one’s speech as long as everyone understands what they’ve meant. It constantly borrows words from other languages for their own use. When new non-existent words become mainstream, they embrace rather than despise. It thrives by adaptation. An AI system that adapts itself to the evolving language rather than requiring people to speak with precision -– that’s intelligence.

Here’s the best part. The approach taken by current implementations of AI ensures that natural language parsing isn’t limited to human-machine interactions [in] the English language. With some minor tweaks, the same algorithms can be adapted to every other language. This will eventually make it completely unnecessary to learn English to use an AI implementation. Ooh! Sanskrit just got out of the question altogether.
You’re still free to learn it, but if you’re doing it to save your future robot a few computation cycles, you probably need to steer clear of them as natural intelligence seems to elude you. You might have to urge software engineers, fluent in your favourite language, to contribute to the tweaking.

The hoaxes

Now that we’ve got our facts straight, let’s begin the much awaited hoax debunking. It’s going to be a bit tougher than usual; most of the Sanskrit bullshit found online are rearrangements of the same content. It’s the content that will be decimated here.

The eerily familiar intro

The extraordinary thing about Sanskrit is that it offers direct accessibility to anyone to that elevated plane where the two — mathematics and music, brain and heart, analytical and intuitive, scientific and spiritual — become one.




THE FALSIFICATION

• Adaptation: It might seem a bit off topic, but take a moment to appreciate what just happened here. Those of you with even the most rudimentary capacity for critical thinking have adapted themselves to be able to intuitively call bullshit on an article from its very first sentence. The analytical and the intuitive have unified and Sanskrit didn’t play any role in it.
This is clearly woo. Music, while being a subjective experience, is already entirely mathematical. One surely cannot be expected to believe Sanskrit would improve upon that.
• The brain and the heart always work together. You can’t have one working without the other. Of course, if you’re someone who believes thoughts and feelings originate in the heart, you probably need to be united with a biology textbook.
• Spirituality is subjective. The spirituality of one is different from the the spirituality of everyone else, regardless of the degree of similarity of their thoughts. It cannot be defined, hence science doesn’t deal with it. Again, Sanskrit cannot do anything to change that fact.

Extreme bullshitting

In 1985, NASA scientist Rick Briggs had invited 1,000 Sanskrit scholars from India for working at NASA. But scholars refused to allow the language to be put to foreign use.


THE FALSIFICATION

• There is absolutely no evidence to back the claim that Rick Briggs had consulted Sanskrit experts. It’s a fabrication. Widening the search parameters, none seem interested in the idea of Sanskrit for AI at all.
• Crazy arrogant Indians: It’s all fiction, but let’s reiterate the narrative. A thousand Indians would’ve got to work at NASA. All they had to do was explain Sanskrit grammar to those at NASA and thus contribute to the advancement of AI. They didn’t need to satisfy any other prerequisite as is necessary for anyone who aspires to work at NASA. Their only job was to explain their fantastic language. Every single one of them declines the offer because they did not want the language to be put to foreign use.
• You idiot! You got to work at NASA for an otherwise utterly useless skill and you declined. One bullet point isn’t enough to ridicule you. [!!!]


Americans know Sanskrit

After the refusal of the Indian Sanskrit scholars to help them acquire command over the language, US has urged its young generation to learn Sanskrit.


After the refusal of Indian experts to offer any help in understanding the scientific concept of the language, American kids were imparted Sanskrit lessons since their childhood.


THE FALSIFICATION

The funny thing is while the two sentences mean the exact same thing, you’ll find them both in some renditions of the hoax. That’s super redundant. Maybe they need Sanskrit after all. [!!!]
• Sanskrit isn’t scientific. It’s a convention. Calling it a scientific language, whatever that means, is akin to calling the SI system of measurement scientific.
Idiotic narrative: Sanskrit experts refuse to help the US. The US decides to teach Sanskrit to its children. Won’t they need Sanskrit experts for that too? The US ain’t India; they don’t just create experts out of thin air like they do in India. They need credibility. [!!!]
• American kids aren’t imparted the lessons. However, they are allowed to learn Sanskrit for credit by whatever means they can.

More lies

Very soon the traditional Indian language Sanskrit will be a part of the space, with the United States of America (USA) mulling to use it as computer language at NASA.


According to Rick Briggs, Sanskrit is such a language in which a message can be sent by the computer in the least number of words.


THE FALSIFICATION

• Not a computer language: There is no such thing happening at NASA.
• No such claim is made. It’s true, might I add in a very narrow range of circumstances, but nowhere in Briggs’ piece does he mention this property of the language.
Least word count? Yes, but Sanskrit words are often cascades of shorter words. It isn’t unique to Sanskrit. The German language can do that too. Extremely long words can be created in Sanskrit just by lining them up one after another and omitting the spaces in between. That doesn’t in and of itself provide any real benefit.
Computers don’t care about word count. A long word is going to take up more storage space or transmission time than a shorter word. Character count is the only thing that matters.

• Not really concise: Sanskrit nuts relish in its ability to create new words using Sanskrit’s own prescribed framework instead of borrowing words from other languages. However, since those new words are always going to be cascades of smaller words, I fail to see how any computer would benefit from using Sanskrit.
Actually, computers do not even need to communicate with each other in natural languages. They only need do so when interacting with people. They talk among themselves pretty well, transmitting predefined codes to one another. In fact, I can literally instruct a computer to note that a variable equals an entire Sanskrit sentence and make them transmit that back and forth instead of the Sanskrit directly. No AI scientist is stupid enough to suggest Sanskrit would reduce an already minimal transmission load.

Clear hogwash

The NASA website also confirms its Mission Sanskrit and describes it as the best language for computers. The website clearly mentions that NASA has spent a large sum of time and money on the project during the last two decades.


THE FALSIFICATION

Search engines exist. Did they honestly think one wouldn’t do a simple search for ‘Mission Sanskrit’ in a new tab before sharing a nonsense piece of news like that? Oh, right, Indians! Spoke too soon!
• But seriously, here’s a list of all the things I did looking for this mysterious mission.
A general search. Yields thousands upon thousands of blog posts and Hindu propagandist website articles claiming that Mission Sanskrit is a real thing. Nothing at all from NASA.
• A site specific search on Google. (site:nasa.gov mission sanskrit) Returns results truly from NASA’s website. The results are either about their undertaken missions in general or missions with Sanskrit names. The first page is filled with results like ‘ABC means XYZ in [ancient] Sanskrit’.
• NASA’s own search, provided by Bing. There was no Mission Sanskrit. I learnt a lot though. Did you know there is a crater on the moon named after Kalidasa, a Sanskrit writer? There were 25 results to that search. I checked every single one of them and none point to a Mission Sanskrit.
I visited every single NASA mission page in search for Mission Sanskrit, just to be thorough. They have a handy index of all their missions.
• I made an enquiry via email to NASA about the whole thing. They sent me back a generic reply, but it said that the best source of information on anything that NASA was up to could be found on, well, NASA’s website. A more specific research could be done using their library site. So, I searched on their headquarters library and still nothing.
• I concluded that Mission Sanskrit is a hoax.
• NASA isn’t working on Sanskrit. Never has, never will.


Barking mad

The scientists believe that Sanskrit is also helpful in speech therapy besides helping in mathematics and science. It also improves concentration. The alphabets used in the language are scientific and their correct pronunciation improves the tone of speech. It encourages imagination and improves memory retention also.


THE FALSIFICATION

• Complementary bullshit: There’s not much bullshit that can be created out of thin air in this topic of discussion. Hence, they’ve brought forth a different but related bullshit to satisfy your bullshit needs of the day.
• The speech therapy part has some merit to it. There are papers in medical journals, of course by Indians, that suggest Sanskrit is useful for speech therapy. But that’s only limited to native speakers of languages that strictly follow the phonological structure of Sanskrit. It’s utterly useless to people speaking Latin derived languages or any other language for that matter. Sanskrit is limited to 8 vowels, 2 diphthongs and 33 consonant sounds. If you can do those well, you can do Sanskrit. You cannot master sounds outside its purview with Sanskrit speech therapy as they do not map on to every sound made in other languages.
Mathematics and science?! Nope. Absolutely false, yet presented as if it were an accepted fact. The only “evidence” provided for it, is a claim made by a Hindu propagandist Facebook page who add that Sanskrit was a compulsory language in a London based school -– untrue, they have a choice. They also claim that the school teaches Sanskrit to simplify mathematics and science while the school itself only ever acknowledges the speech therapy thing. A look at the videos from the school show they aren’t really even pronouncing the Sanskrit correctly as would be clear to any Indian the moment they watch it.
• Fabrications: The improvements in concentration, the tone of speech, imagination and memory retention are not supported by scientific studies. People will still believe it. That’s more to do with the stupidity of the average human than the efficacy of Sanskrit.


Tall claim

A report in Forbes magazine in 1987 said that Sanskrit is the most precise language and hence suitable language for computer software.


THE FALSIFICATION

There exists no such report. Forbes does not seem like a publication that sustain archives of its decades old releases. There is no way to verify it using the official source. No one has ever published a scan of the page that says anything like that. We have nothing but assertions. The simplest explanation: Forbes never claimed anything about Sanskrit as a language for computer software.
• Forbes is a business magazine. Even if they did publish a report like that, what makes it valid? Was it a science writer who wrote the piece? Regardless, it’s a Forbes article. Why does it even make it to the discussion?
A search for the article only reveals how powerful the internet is. Despite not having an original source and being likely false, searching for Forbes articles on Sanskrit returns over two hundred thousand results not one of which comes from Forbes’ website.

Generations of bullshit

A report by NASA scientists says the creation of 6th and 7th generation super computers is based on Sanskrit language. This will probably lead to revolutionize language all over the world for learning Sanskrit.


America is going to creating a 6th and 7th generation super computers based on the Sanskrit language for the use of super computers to their maximum extent. Project deadline is 2025 (6th generation) 2034 (7th generation) after this there will be a language revolution all over the world to learn Sanskrit.


THE FALSIFICATION

• You’re probably getting tired of reading that all of it is false over and over, but it’s true. I mean, the fact that it’s false is true. Just to be clear, Sanskrit will play no role in 6th and 7th generation supercomputers.
• 6th and 7th generation computing haven’t been defined. The 5th generation computers are those with artificial intelligence. We are currently using a combination of the 4th and 5th generation systems -– 4th for all your precise computations and 5th for the occasional AI application. Generations after that are not even in question as the problem of artificial intelligence hasn’t been adequately solved yet. In fact, there is no telling until perhaps the 2040s, which is when the technological singularity is predicted to occur.
• Computing generations know no deadlines. There are no strict descriptions of the generations either. It’s just made up on the fly. There is no consortium that decides the specifications of a computing generation before there is a need of one. That’s how computing has always been -– we see restructuring of clutter far more often than properly planned and executed conventions.

Ahh, the pain!

The idea of using a natural language for computer programming is to make it easier for people to talk to computers in their native tongue and spare them the pain of learning a computer friendly language like assembly/C/Java.


The level of competence of the hoax creators is baffling. If they could only understand how stupid they were, they’d be surprised how they managed to get patriots to share their piece far and wide.
• No, that’s not the idea of natural languages for computer programming. In fact, natural languages are out of the question altogether because a system like that will have to have prior encoded knowledge of the whole language rather than that assigned in compile time. A system without moving members would be dumbfounded trying to enact the statement, ‘Move 5 metres north’. There would be a lot of subroutines that the language would theoretically allow but be wasted for want of functionality.
• Learn Sanskrit to talk better with computers is essentially what they’re trying to say. Isn’t that a stupid proposition, especially since the whole premise of this discussion is flawed? I mean are they honestly expecting people to learn a new language just so they could communicate with their computers better?
Maybe they are. I can’t even tell the difference between the real and the ridiculous anymore.
• For the last time, there has been no research that suggests Sanskrit would do well as a programming language.

Conclusion

Let me make one thing absolutely clear. I do not hate Sanskrit. I am a descriptivist and I can vouch for those who say there exist features of Sanskrit that cannot be matched or have no parallels in other languages, including those derived from it. But, it’s not a perfect language. It’s not a complete language. It’s certainly not the mother of all languages. It’s not divine.

Sanskrit’s grammar comes close to certain knowledge representation schemes used in computers but it’s a language to learn from, not a language to use. It also has nothing to do with computer programming. NASA hasn’t had nor will have anything to do with the Sanskrit, except perhaps naming a few of their missions with words from the language.

In my somewhat arrogant but educated opinion, Sanskrit as a spoken language is worse than useless today. It’s extremely difficult to learn as is, and it’s not spoken widely. As I’ve said before, every attempt at enforcing Sanskrit education will fail for the same reason it has always failed -– it’s not a natural language.


And that’s it. Let me know if there’s anything I’ve missed in this article. Be sure to share it with your friends and your enemies (especially your enemies). If there are any factual errors in this piece, let me know that too. Are there articles popping up in your social feeds lately that are in need of some quality debunking? Throw them my way.

Think!

***************************

Clarify NASA's stance on Sanskrit.
by Denver Dias
change.org
https://www.change.org/p/nasa-nasa-clea ... n-sanskrit

"Sanskrit is a scientific language."

"Sanskrit is the best language for computer programming."

"NASA to use Sanskrit as a programming language."

"NASA to echo Sanskrit in space."

"The NASA website also confirms it's Mission Sanskrit..."

Those are article titles and snippets often listed when one looks up "Sanskrit" on their favourite search engine. They're flooded with websites that posit without any scope of plausible deniability that NASA is very involved in Sanskrit studies. They make claims that the US actively urges their young to learn Sanskrit and that American kids were imparted Sanskrit lessons after "Sanskrit experts refused to offer help in the scientific concept of the language" apparently.

Of all the claims, the most baffling one is that NASA had been working on a project called "Mission Sanskrit" because the people at NASA are supposedly of the opinion that Sanskrit is the best language for computer programming. This is something that could be fact checked in under a minute and found to be false but that doesn't seem to be happening.

Sure, the internet is filled with hoaxes and I think most people will agree with me in that the best way to catch a hoax is to be tricked into believing in them once or twice and learning to see the pattern in what eventually becomes a series of obvious falsehoods. However, in this particular case, for most people who were conned into believing in the prowess of this ancient nigh dead language, this is not just a matter of discovering they were wrong about it. People have a strong sense of belongingness with Sanskrit and they will uncritically assimilate anything good that is said about the language. This is not helped by the fact that it appears to them that an organisation, known for its great strides in the fields of aeronautics and astronautics, seems to support those claims.

This would not have been a serious problem if the hoax remained confined in the minds of the believers, who would all individually, in their own private moments of curiosity, come to find out the truth about it sooner or later. But these lies have repeated so many times, that people can no longer realistically come to nip it in the bud. It has turned into a feedback loop with the source being a figurative echo chamber of websites that simply affirm without linking to their sources of that supposed information.

This has got so severe, we have politicians claiming that Sanskrit is necessary for computer literacy, NASA plans on using Sanskrit for their computers, and that the US and UK teach their children Sanskrit. We often hear about Sanskrit learning being made a mandatory subject for some bizarre reason.

A more recent bout of utter idiocy comes in the form of Smriti Irani requesting IITs - the most sought after institutes for engineering in India - to teach Sanskrit because of some misguided notion that it might help uncover scientific discoveries documented in Sanskrit literature.

There, of course, have been articles by rational thinkers, here and there, who have attempted to right this wrong by showing that the claims about Sanskrit just don't hold up to scrutiny. They often get dismissed by the believers with many of them accusing the writers of racism, anti-nationalism, jealousy and hatred of Sanskrit and India. They could repeatedly mention that there is no evidence NASA has ever pursued anything with regard to Sanskrit, with no tangible effect other than seeing their articles shared among the reasonable ones in the crowd. There is only one way I see out of this mess and that is for NASA to make a statement about this matter and put it to rest once and for all.

I know NASA has a lot on its plate and it isn't the best use of their time to take a break from innovating in order to clarify that the outrageous claims made about them are hoaxes. I, however, do not want people believing that this organisation is pursuing obvious dead ends. I believe it is the brightest of the bright that get to work there and at this point I cannot stand propaganda being pushed in their name. NASA has the final say in whether or not the claims about them are true and I think they should make the real truth about them known.

NASA, please make a statement about your stance on Sanskrit and whether or not it is or has been actively pursued by your organisation.

Petition closed.
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Re: Psychological Science Meets a Gullible Post-Truth World

Postby admin » Tue Jan 04, 2022 10:47 am

Excerpt from Albumazar
by John Tomkis


ALBUMAZAR.

ACT I, SCENE 1.


Enter Albumazar, Harpax, Ronca.

Alb. Come, brave mercurials, sublim'd in cheating;
My dear companions, fellow-soldiers
I' th' watchful exercise of thievery:
Shame not at your so large profession,
No more than I at deep astrology;

For in the days of old, Good morrow, thief,
As welcome was received, as now your worship.
The Spartans held it lawful, and the Arabians;
So grew Arabia felix, Sparta valiant.


Ron. Read on this lecture, wise Albumazar.

Alb. Your patron, Mercury, in his mysterious character
Holds all the marks of the other wanderers,
And with his subtle influence works in all,
Filling their stories full of robberies.
[b][size=105]Most trades and callings must participate
Of yours, though smoothly gilt with th' honest title
Of merchant, lawyer, or such like—the learned
Only excepted, and he's therefore poor.

Har. And yet he steals, one author from another.
This poet is that poet's plagiary.
And he a third's, till they end all in Homer.


Alb. And Homer filch'd all from an Egyptian priestess,
The world's a theatre of theft. Great rivers
Rob smaller brooks, and them the ocean;

And in this world of ours, this microcosm,
Guts from the stomach steal, and what they spare,
The meseraics filch, and lay't i' the liver:
Where, lest it should be found, turn'd to red nectar,
'Tis by a thousand thievish veins convey'd,
And hid in flesh, nerves, bones, muscles, and sinews:
In tendons, skin, and hair; so that, the property
Thus alter'd, the theft can never be discover'd.
Now all these pilf'ries, couch'd and compos'd in order,
Frame thee and me. Man's a quick mass of thievery.


Ron. Most philosophical Albumazar!


Har. I thought these parts had lent and borrowed mutual.

Alb. Say, they do so: 'tis done with full intention
Ne'er to restore, and that's flat robbery.
Therefore go on: follow your virtuous laws,
Your cardinal virtue, great necessity;
Wait on her close with all occasions;
Be watchful, have as many eyes as heaven,
And ears as harvest: be resolv'd and impudent:
Believe none, trust none; for in this city
(As in a fought field, crows and carcases)
No dwellers are but cheaters and cheatees.


Ron. If all the houses in the town were prisons,
The chambers cages, all the settles stocks,
The broad-gates, gallowses, and the whole people
Justices, juries, constables, keepers, and hangmen,
I'd practise, spite of all; and leave behind me
A fruitful seminary of our profession,
And call them by the name of Albumazarians.

Har. And I no less, were all the city thieves
As cunning as thyself.

Alb. Why, bravely spoken:
Fitting such generous spirits! I'll make way
To your great virtue with a deep resemblance
Of high astrology.
Harpax and Ronca,
List to our project: I have new-lodg'd a prey
Hard by, that (taken) is, so fat and rich,
'Twill make us leave off trading, and fall to purchase.


Har. Who is't? speak quickly.

Ron. Where, good Albumazar?

Alb. 'Tis a rich gentleman, as old as foolish;
The poor remnant of whose brain, that age had left him,

The doting love of a young girl hath dried:
And, which concerns us most, he gives firm credit
To necromancy and astrology.


Enter Furbo.

Sending to me, as one, that promise both.
Pandolfo is the man.

Har. What, old Pandolfo?

Alb. The same
: but stay, yon's Furbo, whose smooth brow
Shines with good news, and's visage promises
Triumphs and trophies to's.

[Furbo plays.

Ron. On my life
He has learnt out all; I know it by his music.
Then Furbo sings this song.
Bear up thy learned brow, Albumazar;
Live long, of all the world admir'd,
For art profound and skill retir'd,
To cheating by the height of star:
Hence, gipsies, hence; hence, rogues of baser strain,
That hazard life for little gain:
Stand off and, wonder, gape and gaze afar
At the rare skill of great Albumazar.


Fur. Albumazar,
Spread out thy nets at large, here's fowl abundance:
Pandolfo's ours; I understand his business,
Which I filch'd closely from him, while he reveal'd
T' his man his purposes and projects.

Alb. Excellent!

Fur. Thanks to this instrument: for, in pretence
Of teaching young Sulpitia, th' old man's daughter,
I got access to th' house, and while I waited
Till she was ready, overheard Pandolfo
Open his secrets to his servant. Thus 'tis:
Antonio, Pandolfo's friend and neighbour,
Before he went to Barbary, agreed
To give in marriage——

Alb. Furbo, this is no place
Fit to consider curious points of business:
Come, let's away, I'll hear't at large above.
Ronca, stay you below, and entertain him
With a loud noise, of my deep skill in art;
Thou know'st my rosy modesty cannot do it.
Harpax, up you, and from my bedchamber,
Where all things for our purposes are ready,
Second each beck and nod, and word of ours.
You know my meaning?

Har. Yes, yes.

Fur. Yes, sir.

[Furbo goes out singing, Fa la la, Pandolfo's ours.

***********************************

[L]ong before the ninth century the chronological system of the Hindus was as complete, or rather, perfectly the same as it is now; for Albumazar, who was contemporary with the famous Almamun, and lived at his court at Balac or Balkh, had made the Hindu antiquities his particular study. He was also a famous astronomer and astrologer, and had made enquiries respecting the conjunctions of the planets, the time of the creation of the world, and its duration, for astrological purposes; and he says, that the Hindus reckoned from the Flood to the Hejira 720,634,442,715 days, or 3725 years.* [See Bailly's Astron. Anc. p. 30. and Mr. Davis's Essay in the second volume of the Asiatick Researches, p. 274.]

Here is a mistake, which probably originates with the transcriber or translator, but it may be easily rectified. The first number, though somewhat corrupted, is obviously meant for the number of days from the creation to the Hejira; and the 3725 years are reckoned from the beginning of the Cali-yug to the Hejira. It was then the opinion of Albumazar, about the middle of the ninth century, that the aera of the Cali-yug coincided with that of the Flood. He had, perhaps, data which no longer exist, as well as Abul-Fazil in the time of Akbar. Indeed, I am sometimes tempted to believe, from some particular passages in the Puranas, which are related in the true historical style, that the Hindus have destroyed, or at least designedly consigned to oblivion, all genuine records, as militating against their favourite system. In this manner the Romans destroyed the books of Numa, and consigned to oblivion the historical books of the Etrurians, and I suspect also those of the Turdktani in Spain....

Megasthenes was a native of Persia, and enjoyed the confidence of Sibyrtius* [Arrian, B. 5., p. 203.], governor of Arachosia, (now the country of Candahar and Gazni,) on the part of Seleucus. Sibyrtius sent him frequently on the embassies to Sandrocuptos. When Seleucus nvaded India, Megasthenes enjoyed also the confidence of that monarch, who sent him, in the character of ambassador, to the court of the king of Prachi. We may safely conclude, that Megasthenes was a man of no ordinary abilities, and as he spent the greatest part of his life in India, either at Candahar or in the more interior parts of it; and, as from his public character, he must have been daily conversing with the most distinguished persons in India, I conceive, that if the Hindus, of that day, had laid claim to so high an antiquity, as those of the present, he certainly would have been acquainted with their pretensions, as well as with those of the Egyptians and Chaldaeans; but, on the contrary, he was astonished to find a singular conformity between the Hebrews and them in the notions about the beginning of things, that is to say, of ancient history. At the same time, I believe, that the Hindus, at that early period, and, perhaps, long before, had contrived various astronomical periods and cycles, though they had not then thought of framing a civil history, adapted to them. Astrology may have led them to suppose so important and momentous an event as the creation must have been connected with particular conjunctions of the heavenly bodies; nor have the learned in Europe been entirely free from such notions. Having once laid down this position, they did not know where to stop; but the whole was conducted in a most clumsy manner, and their new chronology abounds with the most gross absurdities; of this, they themselves are conscious, for, though willing to give me general ideas of their chronology, they absolutely forsook me, when they perceived my drift in a stricter investigation of the subject.

The loss of Megathenes' works is much to be lamented. From the few scattered fragments, preserved by the ancients, we learn that the history of the Hindus did not go back above 5042 years. The MSS. differ; in some we read 6042 years; in others 5042 and three months, to the invasion of India by Alexander. Megasthenes certainly made very particular enquiries, since he noticed even the months. Which is the true reading, I cannot pretend to determine; however, I inclined believe, it is 5042, because it agrees best with the number of years assigned by Albumazar, as cited by Mr. Bailly, from the creation to the flood. This famous astronomer, whom I mentioned before, had derived his ideas about the time of the creation and of the flood, from the learned Hindus he had consulted; and He assigns 2226 years, between what the Hindus call the last renovation of the world, and the flood. This account from Megasthenes and Albumazar, agrees remarkably well with the computation of the Septuagint. I have adopted that of the Samaritan Pentateuch, as more conformable to such particulars as I have found in the puranas; I must confess, however, that some particular circumstances, if admitted, seem to agree best with the computations of the Septuagint: besides, it is very probable, that the Hindus, as well as ourselves, had various computations of the times we are speaking of.

-- On the Chronology of the Hindus, by Captain Francis Wilford, Asiatic Researches, Vol. V, P. 241, 1799
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