scientificamerican--2020-11-26--Misinformation Has Created a New World Disorder

As someone who studies the impact of misinformation on society , I often wish the young entrepreneurs of Silicon Valley who enabled communication at speed had been forced to run a 9/11 scenario with their technologies before they deployed them commercially .
One of the most iconic images from that day shows a large clustering of New Yorkers staring upward .
The power of the photograph is that we know the horror they 're witnessing .
It is easy to imagine that , today , almost everyone in that scene would be holding a smartphone .
Some would be filming @ @ @ @ @ @ @ and Facebook .
Powered by social media , rumors and misinformation would be rampant .
Hate-filled posts aimed at the Muslim community would proliferate , the speculation and outrage boosted by algorithms responding to unprecedented levels of shares , comments and likes .
Foreign agents of disinformation would amplify the division , driving wedges between communities and sowing chaos .
Meanwhile those stranded on the tops of the towers would be livestreaming their final moments .
Stress testing technology in the context of the worst moments in history might have illuminated what social @ @ @ @ @ @ @ that humans are wired to respond to emotional triggers and share misinformation if it reinforces existing beliefs and prejudices .
Instead designers of the social platforms fervently believed that connection would drive tolerance and counteract hate .
They failed to see how technology would not change who we are fundamentally—it could only map onto existing human characteristics .
Online misinformation has been around since the mid-1990s .
But in 2016 several events made it broadly clear that darker forces had emerged : automation , microtargeting and coordination were fueling information campaigns designed to @ @ @ @ @ @ @ in the Philippines started raising flags as Rodrigo Duterte rose to power , buoyed by intensive Facebook activity .
This was followed by unexpected results in the Brexit referendum in June and then the U.S. presidential election in November—all of which sparked researchers to systematically investigate the ways in which information was being used as a weapon .
During the past four years the discussion around the causes of our polluted information ecosystem has focused almost entirely on actions taken ( or not taken ) by the technology companies .
But this fixation @ @ @ @ @ @ @ of societal shifts is making people more susceptible to misinformation and conspiracy .
Trust in institutions is falling because of political and economic upheaval , most notably through ever widening income inequality .
The effects of climate change are becoming more pronounced .
Global migration trends spark concern that communities will change irrevocably .
The rise of automation makes people fear for their jobs and their privacy .
Bad actors who want to deepen existing tensions understand these societal trends , designing content that they hope will so anger or excite targeted users @ @ @ @ @ @ @ .
The goal is that users will use their own social capital to reinforce and give credibility to that original message .
Most of this content is designed not to persuade people in any particular direction but to cause confusion , to overwhelm and to undermine trust in democratic institutions from the electoral system to journalism .
And although much is being made about preparing the U.S. electorate for the 2020 election , misleading and conspiratorial content did not begin with the 2016 presidential race , and it will not end after this @ @ @ @ @ @ @ and amplify content become cheaper and more accessible , it will be even easier to weaponize users as unwitting agents of disinformation .
Generally , the language used to discuss the misinformation problem is too simplistic .
Effective research and interventions require clear definitions , yet many people use the problematic phrase “ fake news.
” Used by politicians around the world to attack a free press , the term is dangerous .
Recent research shows that audiences increasingly connect it with the mainstream media .
It is often used as a catchall @ @ @ @ @ @ @ same , including lies , rumors , hoaxes , misinformation , conspiracies and propaganda , but it also papers over nuance and complexity .
Much of this content does not even masquerade as news—it appears as memes , videos and social posts on Facebook and Instagram .
In February 2017 I created seven types of “ information disorder ” in an attempt to emphasize the spectrum of content being used to pollute the information ecosystem .
They included , among others , satire , which is not intended to cause harm but still @ @ @ @ @ @ @ content , which is 100 percent false and designed to deceive and do harm ; and false context , which is when genuine content is shared with false contextual information .
Later that year technology journalist Hossein Derakhshan and I published a report that mapped out the differentiations among disinformation , misinformation and malinformation .
Purveyors of disinformation—content that is intentionally false and designed to cause harm—are motivated by three distinct goals : to make money ; to have political influence , either foreign or domestic ; and to cause trouble for the @ @ @ @ @ @ @ misinformation—false content shared by a person who does not realize it is false or misleading—are driven by sociopsychological factors .
People are performing their identities on social platforms to feel connected to others , whether the “ others ” are a political party , parents who do not vaccinate their children , activists who are concerned about climate change , or those who belong to a certain religion , race or ethnic group .
Crucially , disinformation can turn into misinformation when people share disinformation without realizing it is false .
We added @ @ @ @ @ @ @ genuine information that is shared with an intent to cause harm .
An example of this is when Russian agents hacked into e-mails from the Democratic National Committee and the Hillary Clinton campaign and leaked certain details to the public to damage reputations .
Having monitored misinformation in eight elections around the world since 2016 , I have observed a shift in tactics and techniques .
The most effective disinformation has always been that which has a kernel of truth to it , and indeed most of the content being disseminated now is @ @ @ @ @ @ @ wholly fabricated stories , influence agents are reframing genuine content and using hyperbolic headlines .
The strategy involves connecting genuine content with polarizing topics or people .
Because bad actors are always one step ( or many steps ) ahead of platform moderation , they are relabeling emotive disinformation as satire so that it will not get picked up by fact-checking processes .
In these efforts , context , rather than content , is being weaponized .
The result is intentional chaos .
Take , for example , the edited video of House @ @ @ @ @ @ @ 2019 .
It was a genuine video , but an agent of disinformation slowed down the video and then posted that clip to make it seem that Pelosi was slurring her words .
Just as intended , some viewers immediately began speculating that Pelosi was drunk , and the video spread on social media .
Then the mainstream media picked it up , which undoubtedly made many more people aware of the video than would have originally encountered it .
Research has found that traditionally reporting on misleading content can potentially cause more @ @ @ @ @ @ @ rely on heuristics , or mental shortcuts , to help us judge credibility .
As a result , repetition and familiarity are two of the most effective mechanisms for ingraining misleading narratives , even when viewers have received contextual information explaining why they should know a narrative is not true .
Bad actors know this : In 2018 media scholar Whitney Phillips published a report for the Data & Society Research Institute that explores how those attempting to push false and misleading narratives use techniques to encourage reporters to cover their narratives .
@ @ @ @ @ @ @ for the Future found that only 15 percent of U.S. journalists had been trained in how to report on misinformation more responsibly .
A central challenge now for reporters and fact checkers—and anyone with substantial reach , such as politicians and influencers—is how to untangle and debunk falsehoods such as the Pelosi video without giving the initial piece of content more oxygen .
In January 2017 the NPR radio show This American Life interviewed a handful of Trump supporters at one of his inaugural events called the DeploraBall .
These people had been @ @ @ @ @ @ @ advocate for the president .
Of Trump 's surprising ascendance , one of the interviewees explained : “ We memed him into power ... .
We directed the culture.
” The word “ meme ” was first used by theorist Richard Dawkins in his 1976 book , The Selfish Gene , to describe “ a unit of cultural transmission or a unit of imitation , ” an idea , behavior or style that spreads quickly throughout a culture .
During the past several decades the word has been appropriated to describe a type @ @ @ @ @ @ @ and takes on a particular aesthetic design , combining colorful , striking images with block text .
It often refers to other cultural and media events , sometimes explicitly but mostly implicitly .
This characteristic of implicit logic—a nod and wink to shared knowledge about an event or person—is what makes memes impactful .
Enthymemes are rhetorical devices where the argument is made through the absence of the premise or conclusion .
Often key references ( a recent news event , a statement by a political figure , an advertising campaign or a @ @ @ @ @ @ @ out , forcing the viewer to connect the dots .
This extra work required of the viewer is a persuasive technique because it pulls an individual into the feeling of being connected to others .
If the meme is poking fun or invoking outrage at the expense of another group , those associations are reinforced even further .
The seemingly playful nature of these visual formats means that memes have not been acknowledged by much of the research and policy community as influential vehicles for disinformation , conspiracy or hate .
Yet the @ @ @ @ @ @ @ be shared , and memes tend to be much more shareable than text .
The entire narrative is visible in your feed ; there is no need to click on a link .
A 2019 book by An Xiao Mina , Memes to Movements , outlines how memes are changing social protests and power dynamics , but this type of serious examination is relatively rare .
Indeed , of the Russian-created posts and ads on Facebook related to the 2016 election , many were memes .
They focused on polarizing candidates such as @ @ @ @ @ @ @ Trump and on polarizing policies such as gun rights and immigration .
Russian efforts often targeted groups based on race or religion , such as Black Lives Matter or Evangelical Christians .
When the Facebook archive of Russian-generated memes was released , some of the commentary at the time centered on the lack of sophistication of the memes and their impact .
But research has shown that when people are fearful , oversimplified narratives , conspiratorial explanation , and messages that demonize others become far more effective .
These memes did just enough @ @ @ @ @ @ @ button .
Technology platforms such as Facebook , Instagram , Twitter and Pinterest play a significant role in encouraging this human behavior because they are designed to be performative in nature .
Slowing down to check whether content is true before sharing it is far less compelling than reinforcing to your “ audience ” on these platforms that you love or hate a certain policy .
The business model for so many of these platforms is attached to this identity performance because it encourages you to spend more time on their sites .
@ @ @ @ @ @ @ track memes across different social platforms .
But they can investigate only what they can access , and the data from visual posts on many social platforms are not made available to researchers .
Additionally , techniques for studying text such as natural-language processing are far more advanced than techniques for studying images or videos .
That means the research behind solutions being rolled out is disproportionately skewed toward text-based tweets , Web sites or articles published via URLs and fact-checking of claims by politicians in speeches .
Although plenty of blame has @ @ @ @ @ @ @ legitimate reasons— they are also products of the commercial context in which they operate .
No algorithmic tweak , update to the platforms ' content-moderation guidelines or regulatory fine will alone improve our information ecosystem at the level required .
In a healthy information commons , people would still be free to express what they want—but information that is designed to mislead , incite hatred , reinforce tribalism or cause physical harm would not be amplified by algorithms .
That means it would not be allowed to trend on Twitter or in the @ @ @ @ @ @ @ be chosen to appear in Facebook feeds , Reddit searches or top Google results .
Until this amplification problem is resolved , it is precisely our willingness to share without thinking that agents of disinformation will use as a weapon .
Hence , a disordered information environment requires that every person recognize how he or she , too , can become a vector in the information wars and develop a set of skills to navigate communication online as well as offline .
Currently conversations about public awareness are often focused on media literacy @ @ @ @ @ @ @ the public simply needs to be taught how to be smarter consumers of information .
Instead online users would be better taught to develop cognitive “ muscles ” in emotional skepticism and trained to withstand the onslaught of content designed to trigger base fears and prejudices .
Anyone who uses Web sites that facilitate social interaction would do well to learn how they work—and especially how algorithms determine what users see by “ prioritiz [ ing ] posts that spark conversations and meaningful interactions between people , ” in the case of a @ @ @ @ @ @ @ .
I would also recommend that everyone try to buy an advertisement on Facebook at least once .
The process of setting up a campaign helps to drive understanding of the granularity of information available .
You can choose to target a subcategory of people as specific as women , aged between 32 and 42 , who live in the Raleigh-Durham area of North Carolina , have preschoolers , have a graduate degree , are Jewish and like Kamala Harris .
The company even permits you to test these ads in environments that @ @ @ @ @ @ @ “ dark ads ” let organizations target posts at certain people , but they do not sit on that organization 's main page .
This makes it difficult for researchers or journalists to track what posts are being targeted at different groups of people , which is particularly concerning during elections .
Facebook events are another conduit for manipulation .
One of the most alarming examples of foreign interference in a U.S. election was a protest that took place in Houston , Tex.
, yet was entirely orchestrated by trolls based in Russia @ @ @ @ @ @ @ pages that looked authentically American .
One was named “ Heart of Texas ” and supported secession ; it created an “ event ” for May 21 , 2016 , labeled “ Stop Islamification of Texas.
” The other page , “ United Muslims of America , ” advertised its own protest , entitled “ Save Islamic Knowledge , ” for the exact same time and location .
The result was that two groups of people came out to protest each other , while the real creators of the protest celebrated the success @ @ @ @ @ @ @ Another popular tactic of disinformation agents is dubbed “ astroturfing.
” The term was initially connected to people who wrote fake reviews for products online or tried to make it appear that a fan community was larger than it really was .
Now automated campaigns use bots or the sophisticated coordination of passionate supporters and paid trolls , or a combination of both , to make it appear that a person or policy has considerable grassroots support .
By making certain hashtags trend on Twitter , they hope that particular messaging will get @ @ @ @ @ @ @ direct the amplification to bully specific people or organizations into silence .
Understanding how each one of us is subject to such campaigns—and might unwittingly participate in them—is a crucial first step to fighting back against those who seek to upend a sense of shared reality .
Perhaps most important , though , accepting how vulnerable our society is to manufactured amplification needs to be done sensibly and calmly .
Fearmongering will only fuel more conspiracy and continue to drive down trust in quality-information sources and institutions of democracy .
There are no @ @ @ @ @ @ @ we need to adapt to this new normal .
Just as putting on sunscreen was a habit that society developed over time and then adjusted as additional scientific research became available , building resiliency against a disordered information environment needs to be thought about in the same vein .

As someone who studies the impact of misinformation on society, I often wish the young entrepreneurs of Silicon Valley who enabled communication at speed had been forced to run a 9/11 scenario with their technologies before they deployed them commercially.
One of the most iconic images from that day shows a large clustering of New Yorkers staring upward. The power of the photograph is that we know the horror they’re witnessing. It is easy to imagine that, today, almost everyone in that scene would be holding a smartphone. Some would be filming their observations and posting them to Twitter and Facebook. Powered by social media, rumors and misinformation would be rampant. Hate-filled posts aimed at the Muslim community would proliferate, the speculation and outrage boosted by algorithms responding to unprecedented levels of shares, comments and likes. Foreign agents of disinformation would amplify the division, driving wedges between communities and sowing chaos. Meanwhile those stranded on the tops of the towers would be livestreaming their final moments.
Stress-testing technology in the context of the worst moments in history might have illuminated what social scientists and propagandists have long known: that humans are wired to respond to emotional triggers and share misinformation if it reinforces existing beliefs and prejudices. Instead designers of the social platforms fervently believed that connection would drive tolerance and counteract hate. They failed to see how technology would not change who we are fundamentally—it could only map onto existing human characteristics.
Online misinformation has been around since the mid-1990s. But in 2016 several events made it broadly clear that darker forces had emerged: automation, microtargeting and coordination were fueling information campaigns designed to manipulate public opinion at scale. Journalists in the Philippines started raising flags as Rodrigo Duterte rose to power, buoyed by intensive Facebook activity. This was followed by unexpected results in the Brexit referendum in June and then the U.S. presidential election in November—all of which sparked researchers to systematically investigate the ways in which information was being used as a weapon.
During the past six years the discussion around the causes of our polluted information ecosystem has focused almost entirely on actions taken (or not taken) by the technology companies. But this fixation is too simplistic. A complex web of societal shifts is making people more susceptible to misinformation and conspiracy. Trust in institutions is falling because of political and economic upheaval, most notably through ever widening income inequality. The effects of climate change are becoming more pronounced. Global migration trends spark concern that communities will change irrevocably. The rise of automation makes people fear for their jobs and their privacy.
Bad actors who want to deepen existing tensions understand these societal trends, designing content that they hope will so anger or excite targeted users that the audience will become the messenger. The goal is that users will use their own social capital to reinforce and give credibility to that original message.
Most of this content is designed not to persuade people in any particular direction but to cause confusion, to overwhelm and to undermine trust in democratic institutions from the electoral system to journalism. And although much has been made about preparing the U.S. electorate for election cycles since the 2016 presidential race, misleading and conspiratorial content did not begin with that election, and it will not end anytime soon. As tools designed to manipulate and amplify content become cheaper and more accessible, it will be even easier to weaponize users as unwitting agents of disinformation.
Credit: Jen Christiansen; Source: Information Disorder: Toward an Interdisciplinary Framework for Research and Policymaking, by Claire Wardle and Hossein Derakhshan. Council of Europe, October 2017
Weaponizing Context
Generally, the language used to discuss the misinformation problem is too simplistic. Effective research and interventions require clear definitions, yet many people use the problematic phrase “fake news.” Used by politicians around the world to attack a free press, the term is dangerous. Research has shown that audiences frequently connect it with the mainstream media. It is often used as a catchall to describe things that are not the same, including lies, rumors, hoaxes, misinformation, conspiracies and propaganda, but it also papers over nuance and complexity. Much of this content does not even masquerade as news—it appears as memes, videos and social posts on Facebook and Instagram.
In February 2017 I created seven types of “information disorder” in an attempt to emphasize the spectrum of content being used to pollute the information ecosystem. They included, among others, satire, which is not intended to cause harm but still has the potential to fool; fabricated content, which is 100 percent false and designed to deceive and do harm; and false context, which is when genuine content is shared with false contextual information. Later that year technology journalist Hossein Derakhshan and I published a report that mapped out the differentiations among disinformation, misinformation and malinformation.
Purveyors of disinformation—content that is intentionally false and designed to cause harm—are motivated by three distinct goals: to make money; to have political influence, either foreign or domestic; and to cause trouble for the sake of it.
Those who spread misinformation—false content shared by a person who does not realize it is false or misleading—are driven by sociopsychological factors. People are performing their identities on social platforms to feel connected to others, whether the “others” are a political party, parents who do not vaccinate their children, activists who are concerned about climate change, or those who belong to a certain religion, race or ethnic group. Crucially, disinformation can turn into misinformation when people share disinformation without realizing it is false.
We added the term “malinformation” to describe genuine information that is shared with an intent to cause harm. An example of this is when Russian agents hacked into e-mails from the Democratic National Committee and the Hillary Clinton campaign and leaked certain details to the public to damage reputations.
While monitoring misinformation in eight elections around the world between 2016 and 2020, I observed a shift in tactics and techniques. The most effective disinformation has always been that which has a kernel of truth to it, and indeed most of the content disseminated recently is not fake—it is misleading. Instead of wholly fabricated stories, influence agents are reframing genuine content and using hyperbolic headlines. The strategy involves connecting genuine content with polarizing topics or people. Because bad actors are always one step (or many steps) ahead of platform moderation, they are relabeling emotive disinformation as satire so that it will not get picked up by fact-checking processes. In these efforts, context, rather than content, is being weaponized. The result is intentional chaos.
Take, for example, the edited video of House Speaker Nancy Pelosi that circulated in May 2019. It was a genuine video, but an agent of disinformation slowed down the video and then posted that clip to make it seem that Pelosi was slurring her words. Just as intended, some viewers immediately began speculating that Pelosi was drunk, and the video spread on social media. Then the mainstream media picked it up, which undoubtedly made many more people aware of the video than would have originally encountered it.
Research has found that traditionally reporting on misleading content can potentially cause more harm. Our brains are wired to rely on heuristics, or mental shortcuts, to help us judge credibility. As a result, repetition and familiarity are two of the most effective mechanisms for ingraining misleading narratives, even when viewers have received contextual information explaining why they should know a narrative is not true.
Bad actors know this: In 2018 media scholar Whitney Phillips published a report for the Data & Society Research Institute that explores how those attempting to push false and misleading narratives use techniques to encourage reporters to cover their narratives. Yet another report from the Institute for the Future found that only 15 percent of U.S. journalists had been trained in how to report on misinformation more responsibly. A central challenge now for reporters and fact-checkers—and anyone with substantial reach, such as politicians and influencers—is how to untangle and debunk falsehoods such as the Pelosi video without giving the initial piece of content more oxygen.
Memes: A Misinformation Powerhouse
In January 2017 the NPR radio show This American Life interviewed a handful of Trump supporters at one of his inaugural events called the DeploraBall. These people had been heavily involved in using social media to advocate for the president. Of Trump’s surprising ascendance, one of the interviewees explained: “We memed him into power…. We directed the culture.”
The word “meme” was first used by theorist Richard Dawkins in his 1976 book, The Selfish Gene, to describe “a unit of cultural transmission or a unit of imitation,” an idea, behavior or style that spreads quickly throughout a culture. During the past several decades the word has been appropriated to describe a type of online content that is usually visual and takes on a particular aesthetic design, combining colorful, striking images with block text. It often refers to other cultural and media events, sometimes explicitly but mostly implicitly.
This characteristic of implicit logic—a nod and wink to shared knowledge about an event or person—is what makes memes impactful. Enthymemes are rhetorical devices where the argument is made through the absence of the premise or conclusion. Often key references (a recent news event, a statement by a political figure, an advertising campaign or a wider cultural trend) are not spelled out, forcing the viewer to connect the dots. This extra work required of the viewer is a persuasive technique because it pulls an individual into the feeling of being connected to others. If the meme is poking fun or invoking outrage at the expense of another group, those associations are reinforced even further.
The seemingly playful nature of these visual formats means that memes have not been acknowledged by much of the research and policy community as influential vehicles for disinformation, conspiracy or hate. Yet the most effective misinformation is that which will be shared, and memes tend to be much more shareable than text. The entire narrative is visible in your feed; there is no need to click on a link. A 2019 book by An Xiao Mina, Memes to Movements, outlines how memes are changing social protests and power dynamics, but this type of serious examination is relatively rare.
Indeed, of the Russian-created posts and ads on Facebook related to the 2016 election, many were memes. They focused on polarizing candidates such as Bernie Sanders, Hillary Clinton or Donald Trump and on polarizing policies such as gun rights and immigration. Russian efforts often targeted groups based on race or religion, such as Black Lives Matter or Evangelical Christians. When the Facebook archive of Russian-generated memes was released, some of the commentary at the time centered on the lack of sophistication of the memes and their impact. But research has shown that when people are fearful, oversimplified narratives, conspiratorial explanation and messages that demonize others become far more effective. These memes did just enough to drive people to click the share button.
Technology platforms such as Facebook, Instagram, Twitter and Pinterest play a significant role in encouraging this human behavior because they are designed to be performative in nature. Slowing down to check whether content is true before sharing it is far less compelling than reinforcing to your “audience” on these platforms that you love or hate a certain policy. The business model for so many of these platforms is attached to this identity performance because it encourages you to spend more time on their sites.
Researchers have built monitoring technologies to track memes across different social platforms. But they can investigate only what they can access, and the data from visual posts on many social platforms are not made available to all researchers. Additionally, techniques for studying text such as natural-language processing are far more advanced than techniques for studying images or videos. That means the research behind solutions being rolled out is disproportionately skewed toward text-based tweets, websites or articles published via URLs, and fact-checking of claims made by politicians in speeches.
Although plenty of blame has been placed on the technology companies—and for legitimate reasons— they are also products of the commercial context in which they operate. No algorithmic tweak, update to the platforms’ content-moderation guidelines or regulatory fine will alone improve our information ecosystem at the level required.
Credit: Jen Christiansen; Source: Information Disorder: Toward an Interdisciplinary Framework for Research and Policymaking, by Claire Wardle and Hossein Derakhshan. Council of Europe, October 2017
Participating in the Solution
In a healthy information commons, people would still be free to express what they want—but information that is designed to mislead, incite hatred, reinforce polarization or cause physical harm would not be amplified by algorithms. That means it would not be allowed to trend on Twitter or in the YouTube content recommender. Nor would it be chosen to appear in Facebook feeds, Reddit searches or top Google results.
Until this amplification problem is resolved, it is precisely our willingness to share without thinking that agents of disinformation will use as a weapon. Hence, a disordered information environment requires that every person recognize how they, too, can become a vector in the information wars and develop a set of skills to navigate communication online as well as offline.
Currently conversations about public awareness tend to be focused on media literacy, often with a paternalistic framing that the public simply needs to be taught how to be smarter consumers of information. Instead online users would be better taught to develop cognitive “muscles” for emotional skepticism and trained to withstand the onslaught of content designed to trigger base fears and prejudices.
Anyone who uses websites that facilitate social interaction would do well to learn how they work—and especially how algorithms determine what users see by “prioritiz[ing] posts that spark conversations and meaningful interactions between people,” as Facebook once put it. I would also recommend that everyone try to buy an advertisement on Facebook at least once. The process of setting up a campaign helps to drive understanding of the granularity of information available. You can choose to target a subcategory of people as specific as women, aged between 32 and 42, who live in the Raleigh-Durham area of North Carolina, have preschoolers, have a graduate degree, are Jewish and like Kamala Harris. The company even permits you to test these ads in environments that allow you to fail privately. These “dark ads” let organizations target posts at certain people, but they do not sit on that organization’s main page. This makes it difficult for researchers or journalists to track what posts are being targeted at different groups of people, which is particularly concerning during elections.
Facebook events are another conduit for manipulation. One of the most alarming examples of foreign interference in a U.S. election was a protest that took place in Houston, Tex., yet was entirely orchestrated by trolls based in Russia. They had set up two Facebook pages that looked authentically American. One was named “Heart of Texas” and supported secession; it created an “event” for May 21, 2016, labeled “Stop Islamification of Texas.” The other page, “United Muslims of America,” advertised its own protest, entitled “Save Islamic Knowledge,” for the exact same time and location. The result was that two groups of people came out to protest each other, while the real creators of the protest celebrated the success at amplifying existing tensions in Houston.
Another popular tactic of disinformation agents is dubbed “astroturfing.” The term was initially connected to people who wrote fake reviews for products online or tried to make it appear that a fan community was larger than it really was. Now automated campaigns use bots or the sophisticated coordination of passionate supporters and paid trolls, or a combination of both, to make it appear that a person or policy has considerable grassroots support. They hope that if they make certain hashtags trend on Twitter, particular messaging will get picked up by the professional media, and they will be able to direct the amplification to bully specific people or organizations into silence.
Understanding how each one of us is subject to such campaigns—and might unwittingly participate in them—is a crucial first step to fighting back against those who seek to upend a sense of shared reality. Perhaps most important, though, accepting how vulnerable our society is to manufactured amplification needs to be done sensibly and calmly. Fearmongering will only fuel more conspiracy and continue to drive down trust in quality-information sources and institutions of democracy. There are no permanent solutions to weaponized narratives. Instead we need to adapt to this new normal. Just as putting on sunscreen was a habit that society developed over time and then adjusted as additional scientific research became available, building resiliency against a disordered information environment needs to be thought about in the same vein.


scientificamerican--2020-11-26--GDP Is the Wrong Tool for Measuring What Matters

Since World War II , most countries around the world have come to use gross domestic product , or GDP , as the core metric for prosperity .
The GDP measures market output : the monetary value of all the goods and services produced in an economy during a given period , usually a year .
Governments can fail if this number falls—and so , not surprisingly , governments strive to make it climb .
But striving to grow GDP is not the same as ensuring the well-being of a society .
In truth , “ GDP measures everything , @ @ @ @ @ @ @ , “ except that which makes life worthwhile.
” The number does not measure health , education , equality of opportunity , the state of the environment or many other indicators of the quality of life .
It does not even measure crucial aspects of the economy such as its sustainability : whether or not it is headed for a crash .
What we measure matters , though , because it guides what we do .
Americans got an inkling of this causal connection during the Vietnam War , with the military 's @ @ @ @ @ @ @ the weekly tabulation of the number of enemy soldiers killed .
Reliance on this morbid metric led U.S. forces to undertake operations that had no purpose except to raise the body count .
Like a drunk looking for his keys under the lamppost ( because that is where the light is ) , the emphasis on body counts kept us from understanding the bigger picture : the slaughter was inducing more Vietnamese people to join the Viet Cong than U.S. forces were killing .
Now a different body count—that from COVID-19—is proving to @ @ @ @ @ @ @ performance .
It has little correlation with GDP .
The U.S. is the richest country in the world , with a GDP of more than $ 20 trillion in 2019 , a figure that suggested we had a highly efficient economic engine , a racing car that could outperform any other .
But the U.S. recorded upward of 100,000 deaths by June , whereas Vietnam , with a GDP of $ 262 billion ( and a mere 4 percent of U.S. GDP per capita ) had zero .
In the race to save @ @ @ @ @ @ @ beaten us handily .
In fact , the American economy is more like an ordinary car whose owner saved on gas by removing the spare tire , which was fine until he got a flat .
And what I call “ GDP thinking ” —seeking to boost GDP in the misplaced expectation that that alone would enhance well-being—led us to this predicament .
An economy that uses its resources more efficiently in the short term has higher GDP in that quarter or year .
Seeking to maximize that macroeconomic measure translates , at @ @ @ @ @ @ @ cutting costs to achieve the highest possible short-term profits .
But such a myopic focus necessarily compromises the performance of the economy and society in the long term .
The U.S. health care sector , for example , took pride in using hospital beds efficiently : no bed was left unused .
In consequence , when SARS-CoV-2 reached America there were only 2.8 hospital beds per 1,000 people—far fewer than in other advanced countries—and the system could not absorb the sudden surge in patients .
Doing without paid sick leave in meat-packing plants @ @ @ @ @ @ @ which also increased GDP .
But workers could not afford to stay home when sick ; instead they came to work and spread the infection .
Similarly , China made protective masks cheaper than the U.S. could , so importing them increased economic efficiency and GDP .
That meant , however , that when the pandemic hit and China needed far more masks than usual , hospital staff in the U.S. could not get enough .
In sum , the relentless drive to maximize short-term GDP worsened health care , caused financial and @ @ @ @ @ @ @ and resilience , leaving Americans more vulnerable to shocks than the citizens of other countries .
The shallowness of GDP thinking had already become evident in the 2000s .
In preceding decades , European economists , seeing the success of the U.S. in increasing GDP , had encouraged their leaders to follow American-style economic policies .
But as signs of distress in the U.S. banking system mounted in 2007 , France 's President Nicolas Sarkozy realized that any politician who single-mindedly sought to push up GDP to the neglect of other indicators of @ @ @ @ @ @ @ confidence of the public .
In January 2008 he asked me to chair an international commission on the Measurement of Economic Performance and Social Progress .
A panel of experts was to answer the question : How can nations improve their metrics ?
Measuring that which makes life worthwhile , Sarkozy reasoned , was an essential first step toward enhancing it .
Coincidentally , our initial report in 2009 , provocatively entitled Mismeasuring Our Lives : Why GDP Does n't Add Up , was published right after the global financial crisis had demonstrated @ @ @ @ @ @ @ of economic orthodoxy .
It met with such positive resonance that the Organization for Economic Co-operation and Development ( OECD ) —a think tank that serves 37 advanced countries—decided to follow up with an expert group .
After six years of consultation and deliberation , we reinforced and amplified our earlier conclusion : GDP should be dethroned .
In its place , each nation should select a “ dashboard ” —a limited set of metrics that would help steer it toward the future its citizens desired .
In addition to GDP itself , @ @ @ @ @ @ @ and no more ) the dashboard would include metrics for health , sustainability and any other values that the people of a nation aspired to , as well as for inequality , insecurity and other harms that they sought to diminish .
These documents have helped crystallize a global movement toward improved measures of social and economic health .
The OECD has adopted the approach in its Better Life Initiative , which recommends 11 indicators—and provides citizens with a way to weigh these for their own country , relative to others , to @ @ @ @ @ @ @ on the things they care about .
The World Bank and the International Monetary Fund ( IMF ) , traditionally strong advocates of GDP thinking , are now also paying attention to environment , inequality and sustainability of the economy .
A few countries have even incorporated this approach into their policy-making frameworks .
New Zealand , for instance , embedded “ well-being ” indicators in the country 's budgetary process in 2019 .
As the country 's finance minister , Grant Robertson , put it : “ Success is about making New @ @ @ @ @ @ @ a living and a great place to make a life.
” This emphasis on well-being may partly explain the nation 's triumph over COVID-19 , which appears to have been eliminated after roughly 1,500 confirmed cases and 20 deaths in a total population of nearly five million .
Necessity is the mother of invention .
Just as the dashboard emerged from a dire need—the inadequacy of the GDP as an indicator of well-being , as revealed by the Great Recession of 2008—so did the GDP .
During the Great Depression , U.S. officials @ @ @ @ @ @ @ government did not collect statistics on either inflation or unemployment , which would have helped them steer the economy .
So the Department of Commerce charged economist Simon Kuznets of the National Bureau of Economic Research with creating a set of national statistics on income .
Kuznets went on to construct the GDP in the 1940s as a simple metric that could be calculated from the exceedingly limited market data then available .
An aggregate of ( the dollar value of ) the goods and services produced in the country , it was @ @ @ @ @ @ @ income—wages , profits , rents and taxes .
For this and other work , he received the Nobel Memorial Prize in Economic Sciences in 1971 .
( Economist Richard Stone , who created similar statistical systems for the U.K. , received the prize in 1984 . )
Kuznets repeatedly warned , however , that the GDP only measured market activity and should not be mistaken for a metric of social or even economic well-being .
The figure included many goods and services that were harmful ( including , he believed , armaments ) @ @ @ @ @ @ @ excluded many essential ones that were free ( such as caregiving by homemakers ) .
A core difficulty with constructing such an aggregate is that there is no natural unit for adding the value of even apples and oranges , let alone of such disparate things as armaments , financial speculation and caregiving .
Thus , economists use their prices as a proxy for value—in the belief that , in a competitive market , prices reflect how much people value apples , oranges , armaments , speculation or caregiving relative to one another @ @ @ @ @ @ @ relative value—made the GDP quite easy to calculate .
As the U.S. recovered from the Depression by ramping up the production and consumption of material goods ( in particular , armaments during World War II ) , GDP grew rapidly .
The World Bank and the IMF began to fund development programs in former colonies around the world , gauging their success almost exclusively in terms of GDP growth .
Over time , as economists focused on the intricacies of comparing GDP in different eras and across diverse countries and constructing complex economic @ @ @ @ @ @ @ GDP , they lost sight of the metric 's shaky foundations .
Students seldom studied the assumptions that went into constructing the measure—and what these assumptions meant for the reliability of any inferences they made .
Instead the objective of economic analysis became to explain the movements of this artificial entity .
GDP became hegemonic across the globe : good economic policy was taken to be whatever increased GDP the most .
In 1980 , following a period of seemingly poor economic performance—stagflation , marked by slow growth and rising prices—President Ronald Reagan @ @ @ @ @ @ @ up the economy .
He deregulated the financial sector and cut taxes for the better-off , arguing that the benefits would “ trickle down ” to those less fortunate .
Although GDP grew somewhat ( albeit at a rate markedly lower than in the decades after World War II ) , inequality rose precipitously .
Well aware that metrics matter , some members of the administration reportedly argued for stopping the collection of statistics on inequality .
If Americans did not know how bad inequality was , presumably we would not worry about @ @ @ @ @ @ @ unprecedented assaults on the environment , issuing leases for fossil-fuel extraction on millions of acres of public lands , for example .
In 1995 I joined the Council of Economic Advisers for President Bill Clinton .
Worrying that our metrics paid too little attention to resource depletion and environmental degradation , we worked with the Department of Commerce to develop a measure of “ green ” GDP , which would take such losses into account .
When the congressional representatives from the coal states got wind of this , however , they threatened @ @ @ @ @ @ @ stopped our work , which we were obliged to .
The politicians knew that if Americans understood how bad coal was for our economy correctly measured , then they would seek the elimination of the hidden subsidies that the coal industry receives .
And they might even seek to move more quickly to renewables .
Although our efforts to broaden our metrics were stymied , the fact that these representatives were willing to spend so much political capital on stopping us convinced me that we were on to something really important .
( @ @ @ @ @ @ @ a decade later , Sarkozy approached me about heading an international panel to examine better ways of measuring “ economic performance and social progress , ” I leaped at the chance . )
I left the Council of Economic Advisers in 1997 , and in the ensuing years the deregulatory fervor of the Reagan era came to grip the Clinton administration .
The financial sector of the U.S. economy was ballooning , driving up GDP .
As it turned out , many of the profits that gave that sector such heft were , @ @ @ @ @ @ @ ' lending practices had generated a real-estate bubble that had artificially enhanced profits—and , with their pay being linked to profits , had increased their bonuses .
In the ideal free-market economy , an increase in profits is supposed to reflect an increase in societal well-being , but the bankers ' takings put the lie to that notion .
Much of their profits resulted from making others worse off , such as when they engaged in abusive credit-card practices or manipulated LIBOR ( for London Interbank Offered Rate of interest for international banks @ @ @ @ @ @ @ their earnings .
But GDP figures took these inflated figures at face value , convincing policy makers that the best way to grow the economy was to remove any remaining regulations that constrained the finance sector .
Long-standing prohibitions on usury—charging outrageous interest rates to take advantage of the unwary—were stripped away .
In 2000 the so-called Commodity Modernization Act was passed .
It was designed to ensure that derivatives ( risky financial products that played a big role in bringing down the financial system just eight years later ) would never be @ @ @ @ @ @ @ made it more difficult for those having trouble paying their bills to discharge their debts—making it almost impossible for those with student loans to do so .
By the early 2000s two fifths of corporate profits came from the financial sector .
That fraction should have signaled that something was wrong : an efficient financial sector should entail low costs for engaging in financial transactions and therefore should be small .
Ours was huge .
Untethering the market had inflated profits , driving up GDP—and , as it turned out , instability .
@ @ @ @ @ @ @ had been issuing mortgages indiscriminately , on the assumption that real-estate prices would continue to rise .
When the housing bubble broke , so did the economy , falling more than it had since the immediate aftermath of World War II .
After the U.S. government rescued the banks ( just one firm , AIG , received a government bailout of $ 130 billion ) , GDP improved , persuading President Barack Obama and the Federal Reserve to announce that we were well on the way to recovery .
But with 91 percent @ @ @ @ @ @ @ to 2012 going to the top 1 percent , the majority of Americans experienced none .
As the country slowly emerged from the financial crisis , others commanded attention : the inequality crisis , the climate crisis and an opioid crisis .
Even as GDP continued to rise , life expectancy and other broader measures of health worsened .
Food companies were developing and marketing , with great ingenuity , addictive sugar-rich foods , augmenting GDP but precipitating an epidemic of childhood diabetes .
Addictive opioids led to an epidemic of drug deaths @ @ @ @ @ @ @ and the other villains in that drama added to GDP .
Indeed , the medical expenditures resulting from these health crises also boosted GDP .
Americans were spending twice as much per person on health care than the French but had lower life expectancy .
So , too , coal mining seemingly boosted the economy , and although it helped to drive climate change , worsening the impact of hurricanes such as Harvey , the efforts to rebuild again added to GDP .
The GDP number provided an optimistic gloss to the worst @ @ @ @ @ @ @ disjuncture between GDP and societal well-being and the many ways that GDP fails to be a good measure of economic performance .
The growth in GDP before 2008 was not sustainable , and it was not sustained .
The increase in bank profits that seemed to fuel GDP in the years before the crisis were not only at the expense of the well-being of the many people whom the financial sector exploited but also at the expense of GDP in later years .
The increase in inequality was by any measure hurting our @ @ @ @ @ @ @ banks ' successes .
If there ever was an event that drove home the need for new ways of measuring economic performance and societal progress , the 2008 crisis was it .
The commission , led by three economists ( Amartya Sen of Harvard University , Jean-Paul Fitoussi of the Paris Institute of Political Studies and me ) , published its first report in 2009 , just after the U.S. financial system imploded .
We pointed out that measuring something as simple as the fraction of Americans who might have difficulty refinancing their @ @ @ @ @ @ @ mirrors underpinning the heady economic growth preceding the crisis and possibly enabled policy makers to fend it off .
More important , building and paying attention to a broad set of metrics for present-day well-being and its sustainability—whether good times are durable—would help buffer societies against future shocks .
We need to know whether , when GDP is going up , indebtedness is increasing or natural resources are being depleted ; these may indicate that the economic growth is not sustainable .
If pollution is rising along with GDP , growth is not @ @ @ @ @ @ @ the true health of an economy is the health of its citizens , and if , as in the U.S. , life expectancy has been going down—as it was even before the pandemic—that should be worrying , no matter what is happening to GDP .
If median income ( that of the families in the middle ) is stagnating even as GDP rises , that means the fruits of economic growth are not being shared .
It would have been nice , of course , if we could have come up with a @ @ @ @ @ @ @ a society or even an economy is doing—a GDP plus number , say .
But as with the GDP itself , too much valuable information is lost when we form an aggregate .
Say , you are driving your car .
You want to know how fast you are going and glance at the speedometer .
It reads 70 miles an hour .
And you want to know how far you can go without refilling your tank , which turns out to be 200 miles .
Both those numbers are valuable , conveying @ @ @ @ @ @ @ But now assume you form a simple aggregate by adding up the two numbers , with or without “ weights.
” What would a number like 270 tell you ?
Absolutely nothing .
It would not tell you whether you are driving recklessly or how worried you should be about running out of fuel .
That was why we concluded that each nation needs a dashboard—a set of numbers that would convey essential diagnostics of its society and economy and help steer them .
Policy makers and civil-society groups should pay attention not @ @ @ @ @ @ @ health , education , leisure , environment , equality , governance , political voice , social connectedness , physical and economic security , and other indicators of the quality of life .
Just as important , societies must ensure that these “ goods ” are not bought at the expense of the future .
To that end , they should focus on maintaining and augmenting , to the extent possible , their stocks of natural , human , social and physical capital .
We also laid out a research agenda for exploring links @ @ @ @ @ @ @ sustainability and developing good ways to measure them .
Concern about climate change and rising inequality had already been fueling a global demand for better measures , and our report crystallized that trend .
In 2015 a contentious political process culminated in the United Nations establishing a set of 17 Sustainable Development Goals .
Progress toward them is to be measured by 232 indicators , reflecting the manifold concerns of governments and civil societies from around the world .
So many numbers are unhelpful , in our view : one can lose sight @ @ @ @ @ @ @ Instead another group of experts , chaired by Fitoussi , Martine Durand ( chief statistician of the OECD ) and me , recommended that each country institute a robust democratic dialogue to discover what issues its citizens most care about .
Such a conversation would almost certainly show that most of us who live in highly developed economies care about our material well-being , our health , the environment around us and our relations with others .
We want to do well today but also in the future .
We care about how @ @ @ @ @ @ @ : we do not want a society in which a few at the top grab everything for themselves and the rest live in poverty .
A good indicator of the true health of an economy is the health of its citizens .
A decline in life expectancy , even for a part of the population , should be worrying , whatever is happening to GDP .
And it is important to know if , even as GDP is going up , so , too , is pollution—whether it is emissions of greenhouse gases @ @ @ @ @ @ @ means growth is not environmentally sustainable .
The choice of indicators may vary across time and among countries .
Countries with high unemployment will want to track what is happening to that variable ; those with high inequality will want to monitor that .
Still , because people generally want to know how they are doing in comparison with others , we recommended that the advanced countries , at least , share some five to 10 common indicators .
GDP would be among them .
So would a measure of inequality or some @ @ @ @ @ @ @ household is doing .
Over the years economists have formulated a rash of indicators of inequality , each reflecting a different dimension of the phenomenon .
It may well be that societies where inequality has become particularly problematic may need to have metrics reflecting the depth of the poverty at the bottom and the excesses of riches at the top .
To me , knowing what is happening to median income is of particular importance ; in the U.S. , median income has barely changed for decades , even as GDP has grown @ @ @ @ @ @ @ indicator of macroeconomic performance—an economy with a high unemployment rate clearly is not using all of its resources well .
But in societies where paid work is associated with dignity , employment is a value in its own right .
Other elements of the dashboard would include indicators for environmental degradation ( say , air or water quality ) , economic sustainability ( indebtedness ) , health ( life expectancy ) and insecurity .
Insecurity has both subjective and objective dimensions .
We can survey how insecure people feel : how worried they @ @ @ @ @ @ @ they feel to cope with a shock .
But we can also predict the likelihood that someone falls below the poverty line in any given year .
And some elements of the dashboard are “ intermediate ” variables—things that we may ( or may not ) value in themselves but that provide an inkling of how a society will function in the future .
One of these is trust .
Societies in which citizens trust their governments and one another to “ do the right thing ” tend to perform better .
In @ @ @ @ @ @ @ higher levels of trust , such as Vietnam and New Zealand , have dealt far more effectively with the pandemic than the U.S. , for instance , where trust levels have declined since the Reagan era .
Policy makers need to use such indicators much as physicians use their diagnostic tools .
When some indicator is flashing yellow or red , it is time to look deeper .
If inequality is high or increasing , it is important to know more : What aspects of inequality are getting worse ?
Since we began @ @ @ @ @ @ @ years ago , I have been amazed at the resonance that it has achieved .
A focus on many of the elements of the dashboard has permeated policy making everywhere .
Every three years the OECD hosts an international conference of nongovernmental organizations , national statisticians , government officials and academics furthering the “ well-being ” agenda , the most recent being in Korea in November 2018 , with thousands of participants .
Whenever the conference next convenes , the global crisis in human societies that a microscopic virus has precipitated will surely @ @ @ @ @ @ @ dimensions of it could take years or decades to become clear .
Recovering from this calamity and steering complex societies through the even more devastating crises that loom—catastrophic climate change and biodiversity collapse—will require , at the very least , an excellent navigational system .
To paraphrase the OECD : We have been developing the tools to help us drive better .
It is time to use them .

Since World War II, most countries around the world have come to use gross domestic product, or GDP, as the core metric for prosperity. The GDP measures market output: the monetary value of all the goods and services produced in an economy during a given period, usually a year. Governments can fail if this number falls—and so, not surprisingly, governments strive to make it climb. But striving to grow GDP is not the same as ensuring the well-being of a society.
In truth, “GDP measures everything,” as Senator Robert Kennedy famously said, “except that which makes life worthwhile.” The number does not measure health, education, equality of opportunity, the state of the environment or many other indicators of the quality of life. It does not even measure crucial aspects of the economy such as its sustainability: whether or not it is headed for a crash. What we measure matters, though, because it guides what we do. Americans got an inkling of this causal connection during the Vietnam War, with the military's emphasis on “body counts”: the weekly tabulation of the number of enemy soldiers killed. Reliance on this morbid metric led U.S. forces to undertake operations that had no purpose except to raise the body count. Like a drunk looking for his keys under the lamppost (because that is where the light is), the emphasis on body counts kept us from understanding the bigger picture: the slaughter was inducing more Vietnamese people to join the Viet Cong than U.S. forces were killing.
Now a different body count—that from COVID-19—is proving to be a horribly good measure of societal performance. It has little correlation with GDP. The U.S. is the richest country in the world, with a GDP of more than $20 trillion in 2019, a figure that suggested we had a highly efficient economic engine, a racing car that could outperform any other. But the U.S. has recorded more than 600,000 deaths, whereas Vietnam, with a GDP of $262 billion (and a mere 4 percent of U.S. GDP per capita), has had fewer than 500 to date. In the race to save lives, this less prosperous country has beaten us handily.
In fact, the American economy is more like an ordinary car whose owner saved on gas by removing the spare tire, which was fine until he got a flat. And what I call “GDP thinking”—seeking to boost GDP in the misplaced expectation that that alone would enhance well-being—led us to this predicament. An economy that uses its resources more efficiently in the short term has higher GDP in that quarter or year. Seeking to maximize that macroeconomic measure translates, at a microeconomic level, to each business cutting costs to achieve the highest possible short-term profits. But such a myopic focus necessarily compromises the performance of the economy and society in the long term.
The U.S. health care sector, for example, took pride in using hospital beds efficiently: no bed was left unused. In consequence, when SARS-CoV-2 reached America there were only 2.8 hospital beds per 1,000 people—far fewer than in other advanced countries—and the system could not absorb the sudden surge in patients. Doing without paid sick leave in meat-packing plants increased profits in the short run, which also increased GDP. But workers could not afford to stay home when sick; instead they came to work and spread the infection. Similarly, China made protective masks cheaper than the U.S. could, so importing them increased economic efficiency and GDP. That meant, however, that when the pandemic hit and China needed far more masks than usual, hospital staff in the U.S. could not get enough. In sum, the relentless drive to maximize short-term GDP worsened health care, caused financial and physical insecurity, and reduced economic sustainability and resilience, leaving Americans more vulnerable to shocks than the citizens of other countries.
The shallowness of GDP thinking had already become evident in the 2000s. In preceding decades, European economists, seeing the success of the U.S. in increasing GDP, had encouraged their leaders to follow American-style economic policies. But as signs of distress in the U.S. banking system mounted in 2007, France's President Nicolas Sarkozy realized that any politician who single-mindedly sought to push up GDP to the neglect of other indicators of the quality of life risked losing the confidence of the public. In January 2008 he asked me to chair an international commission on the Measurement of Economic Performance and Social Progress. A panel of experts was to answer the question: How can nations improve their metrics? Measuring that which makes life worthwhile, Sarkozy reasoned, was an essential first step toward enhancing it.
Coincidentally, our initial report in 2009, provocatively entitled Mismeasuring Our Lives: Why GDP Doesn't Add Up, was published right after the global financial crisis had demonstrated the necessity of revisiting the core tenets of economic orthodoxy. It met with such positive resonance that the Organization for Economic Co-operation and Development (OECD)—a think tank that serves 38 advanced countries—decided to follow up with an expert group. After six years of consultation and deliberation, we reinforced and amplified our earlier conclusion: GDP should be dethroned. In its place, each nation should select a “dashboard”—a limited set of metrics that would help steer it toward the future its citizens desired. In addition to GDP itself, as a measure for market activity (and no more) the dashboard would include metrics for health, sustainability and any other values that the people of a nation aspired to, as well as for inequality, insecurity and other harms that they sought to diminish.
These documents have helped crystallize a global movement toward improved measures of social and economic health. The OECD has adopted the approach in its Better Life Initiative, which recommends 11 indicators—and provides citizens with a way to weigh these for their own country, relative to others, to generate an index that measures their performance on the things they care about. The World Bank and the International Monetary Fund (IMF), traditionally strong advocates of GDP thinking, are now also paying attention to environment, inequality and sustainability of the economy.
A few countries have even incorporated this approach into their policy-making frameworks. New Zealand, for instance, embedded “well-being” indicators in the country's budgetary process in 2019. As the country's finance minister, Grant Robertson, put it: “Success is about making New Zealand both a great place to make a living and a great place to make a life.” This emphasis on well-being may partly explain the nation's triumph over COVID-19, which appears to have been limited to roughly 3,000 cases and 26 deaths in a total population of nearly five million.
Apples and Armaments
Necessity is the mother of invention. Just as the dashboard emerged from a dire need—the inadequacy of the GDP as an indicator of well-being, as revealed by the Great Recession of 2008—so did the GDP. During the Great Depression, U.S. officials could barely quantify the problem. The government did not collect statistics on either inflation or unemployment, which would have helped them steer the economy. So the Department of Commerce charged economist Simon Kuznets of the National Bureau of Economic Research with creating a set of national statistics on income. Kuznets went on to construct the GDP in the 1940s as a simple metric that could be calculated from the exceedingly limited market data then available. An aggregate of (the dollar value of) the goods and services produced in the country, it was equivalent to the sum of everyone's income—wages, profits, rents and taxes. For this and other work, he received the Nobel Memorial Prize in Economic Sciences in 1971. (Economist Richard Stone, who created similar statistical systems for the U.K., received the prize in 1984.)
Kuznets repeatedly warned, however, that the GDP only measured market activity and should not be mistaken for a metric of social or even economic well-being. The figure included many goods and services that were harmful (including, he believed, armaments) or useless (financial speculation) and excluded many essential ones that were free (such as caregiving by homemakers). A core difficulty with constructing such an aggregate is that there is no natural unit for adding the value of even apples and oranges, let alone of such disparate things as armaments, financial speculation and caregiving. Thus, economists use their prices as a proxy for value—in the belief that, in a competitive market, prices reflect how much people value apples, oranges, armaments, speculation or caregiving relative to one another.
This profoundly problematic assumption—that price measures relative value—made the GDP quite easy to calculate. As the U.S. recovered from the Depression by ramping up the production and consumption of material goods (in particular, armaments during World War II), GDP grew rapidly. The World Bank and the IMF began to fund development programs in former colonies around the world, gauging their success almost exclusively in terms of GDP growth.
Credit: Amanda Montañez; Sources: World Bank (GDP data); U.S. Census Bureau (inequality data); Organization for Economic Co-operation and Development (Better Life Index data)
Over time, as economists focused on the intricacies of comparing GDP in different eras and across diverse countries and constructing complex economic models that predicted and explained changes in GDP, they lost sight of the metric's shaky foundations. Students seldom studied the assumptions that went into constructing the measure—and what these assumptions meant for the reliability of any inferences they made. Instead the objective of economic analysis became to explain the movements of this artificial entity. GDP became hegemonic across the globe: good economic policy was taken to be whatever increased GDP the most.
In 1980, following a period of seemingly poor economic performance—stagflation, marked by slow growth and rising prices—President Ronald Reagan assumed office on the promise of ramping up the economy. He deregulated the financial sector and cut taxes for the better-off, arguing that the benefits would “trickle down” to those less fortunate. Although GDP grew somewhat (albeit at a rate markedly lower than in the decades after World War II), inequality rose precipitously. Well aware that metrics matter, some members of the administration reportedly argued for stopping the collection of statistics on inequality. If Americans did not know how bad inequality was, presumably we would not worry about it.
The Reagan administration also unleashed unprecedented assaults on the environment, issuing leases for fossil-fuel extraction on millions of acres of public lands, for example. In 1995 I joined the Council of Economic Advisers for President Bill Clinton. Worrying that our metrics paid too little attention to resource depletion and environmental degradation, we worked with the Department of Commerce to develop a measure of “green” GDP, which would take such losses into account. When the congressional representatives from the coal states got wind of this, however, they threatened to cut off our funding unless we stopped our work, which we were obliged to.
The politicians knew that if Americans understood how bad coal was for our economy correctly measured, then they would seek the elimination of the hidden subsidies that the coal industry receives. They might even seek to move more quickly to renewables. Although our efforts to broaden our metrics were stymied, the fact that these representatives were willing to spend so much political capital on stopping us convinced me we were on to something important. (It also meant that when, a decade later, Sarkozy approached me about heading an international panel to examine better ways of measuring “economic performance and social progress,” I leaped at the chance.)
I left the Council of Economic Advisers in 1997, and in the ensuing years the deregulatory fervor of the Reagan era came to grip the Clinton administration. The financial sector of the U.S. economy was ballooning, driving up GDP. As it turned out, many of the profits that gave that sector such heft were, in a sense, phony. Bankers' lending practices had generated a real-estate bubble that had artificially enhanced profits—and, with their pay being linked to profits, had increased their bonuses. In the ideal free-market economy, an increase in profits is supposed to reflect an increase in societal well-being, but the bankers' takings put the lie to that notion. Much of their profits resulted from making others worse off, such as when they engaged in abusive credit-card practices or manipulated LIBOR (for London Interbank Offered Rate of interest for international banks lending to one another) to enhance their earnings.
But GDP figures took these inflated figures at face value, convincing policy makers that the best way to grow the economy was to remove any remaining regulations that constrained the finance sector. Long-standing prohibitions on usury—charging outrageous interest rates to take advantage of the unwary—were stripped away. In 2000 the so-called Commodity Modernization Act was passed. It was designed to ensure that derivatives (risky financial products that played a big role in bringing down the financial system just eight years later) would never be regulated. In 2005 a bankruptcy law made it more difficult for those having trouble paying their bills to discharge their debts—making it almost impossible for those with student loans to do so.
By the early 2000s two fifths of corporate profits came from the financial sector. That fraction should have signaled that something was wrong: an efficient financial sector should entail low costs for engaging in financial transactions and therefore should be small. Ours was huge. Untethering the market had inflated profits, driving up GDP—and, as it turned out, instability.
Opioids, Hurricanes
The bubble burst in 2008. Banks had been issuing mortgages indiscriminately, on the assumption that real-estate prices would continue to rise. When the housing bubble broke, so did the economy, falling more than it had since the immediate aftermath of World War II. After the U.S. government rescued the banks (just one firm, AIG, received a government bailout of $130 billion), GDP improved, persuading President Barack Obama and the Federal Reserve to announce that we were well on the way to recovery. But with 91 percent of the gains in income in 2009 to 2012 going to the top 1 percent, the majority of Americans experienced none.
As the country slowly emerged from the financial crisis, others commanded attention: the inequality crisis, the climate crisis and an opioid crisis. Even as GDP continued to rise, life expectancy and other broader measures of health worsened. Food companies were developing and marketing, with great ingenuity, addictive sugar-rich foods, augmenting GDP but precipitating an epidemic of childhood diabetes. Addictive opioids led to an epidemic of drug deaths, but the profits of Purdue Pharma and the other villains in that drama added to GDP. Indeed, the medical expenditures resulting from these health crises also boosted GDP. Americans were spending twice as much per person on health care than the French but had lower life expectancy. So, too, coal mining seemingly boosted the economy, and although it helped to drive climate change, worsening the impact of hurricanes such as Harvey, the efforts to rebuild again added to GDP. The GDP number provided an optimistic gloss to the worst of events.
These examples illustrate the disjuncture between GDP and societal well-being and the many ways that GDP fails to be a good measure of economic performance. The growth in GDP before 2008 was not sustainable, and it was not sustained. The increase in bank profits that seemed to fuel GDP in the years before the crisis were not only at the expense of the well-being of the many people whom the financial sector exploited but also at the expense of GDP in later years. The increase in inequality was by any measure hurting our society, but GDP was celebrating the banks' successes. If there ever was an event that drove home the need for new ways of measuring economic performance and societal progress, the 2008 crisis was it.
Credit: Samantha Mash
The Dashboard
The commission, led by three economists (Amartya Sen of Harvard University, Jean-Paul Fitoussi of the Paris Institute of Political Studies and me), published its first report in 2009, just after the U.S. financial system imploded. We pointed out that measuring something as simple as the fraction of Americans who might have difficulty refinancing their mortgages would have illuminated the smoke and mirrors underpinning the heady economic growth preceding the crisis and possibly enabled policy makers to fend it off. More important, building and paying attention to a broad set of metrics for present-day well-being and its sustainability—whether good times are durable—would help buffer societies against future shocks.
We need to know whether, when GDP is going up, indebtedness is increasing or natural resources are being depleted; these may indicate that the economic growth is not sustainable. If pollution is rising along with GDP, growth is not environmentally sustainable. A good indicator of the true health of an economy is the health of its citizens, and if, as in the U.S., life expectancy has been going down—as it was even before the pandemic—that should be worrying, no matter what is happening to GDP. If median income (that of the families in the middle) is stagnating even as GDP rises, that means the fruits of economic growth are not being shared.
It would have been nice, of course, if we could have come up with a single measure that would summarize how well a society or even an economy is doing—a GDP plus number, say. But as with the GDP itself, too much valuable information is lost when we form an aggregate. Say, you are driving your car. You want to know how fast you are going and glance at the speedometer. It reads 70 miles an hour. And you want to know how far you can go without refilling your tank, which turns out to be 200 miles. Both those numbers are valuable, conveying information that could affect your behavior. But now assume you form a simple aggregate by adding up the two numbers, with or without “weights.” What would a number like 270 tell you? Absolutely nothing. It would not tell you whether you are driving recklessly or how worried you should be about running out of fuel.
That was why we concluded that each nation needs a dashboard—a set of numbers that would convey essential diagnostics of its society and economy and help steer them. Policy makers and civil-society groups should pay attention not only to material wealth but also to health, education, leisure, environment, equality, governance, political voice, social connectedness, physical and economic security, and other indicators of the quality of life. Just as important, societies must ensure that these “goods” are not bought at the expense of the future. To that end, they should focus on maintaining and augmenting, to the extent possible, their stocks of natural, human, social and physical capital. We also laid out a research agenda for exploring links between the different components of well-being and sustainability and developing good ways to measure them.
Concern about climate change and rising inequality had already been fueling a global demand for better measures, and our report crystallized that trend. In 2015 a contentious political process culminated in the United Nations establishing a set of 17 Sustainable Development Goals. Progress toward them is to be measured by 232 indicators, reflecting the manifold concerns of governments and civil societies from around the world. So many numbers are unhelpful, in our view: one can lose sight of the forest for the trees. Instead another group of experts, chaired by Fitoussi, Martine Durand (chief statistician of the OECD) and me, recommended that each country institute a robust democratic dialogue to discover what issues its citizens most care about.
Such a conversation would almost certainly show that most of us who live in highly developed economies care about our material well-being, our health, the environment around us and our relations with others. We want to do well today but also in the future. We care about how the fruits of our economy are shared: we do not want a society in which a few at the top grab everything for themselves and the rest live in poverty. A good indicator of the true health of an economy is the health of its citizens. A decline in life expectancy, even for a part of the population, should be worrying, whatever is happening to GDP. And it is important to know if, even as GDP is going up, so, too, is pollution—whether it is emissions of greenhouse gases or particulates in the air. That means growth is not environmentally sustainable.
The choice of indicators may vary across time and among countries. Countries with high unemployment will want to track what is happening to that variable; those with high inequality will want to monitor that. Still, because people generally want to know how they are doing in comparison with others, we recommended that the advanced countries, at least, share some five to 10 common indicators.
GDP would be among them. So would a measure of inequality or some pointer toward how the typical individual or household is doing. Over the years economists have formulated a rash of indicators of inequality, each reflecting a different dimension of the phenomenon. It may well be that societies where inequality has become particularly problematic may need to have metrics reflecting the depth of the poverty at the bottom and the excesses of riches at the top. To me, knowing what is happening to median income is of particular importance; in the U.S., median income has barely changed for decades, even as GDP has grown.
Employment is often used as an indicator of macroeconomic performance—an economy with a high unemployment rate clearly is not using all of its resources well. But in societies where paid work is associated with dignity, employment is a value in its own right. Other elements of the dashboard would include indicators for environmental degradation (say, air or water quality), economic sustainability (indebtedness), health (life expectancy) and insecurity.
Insecurity has both subjective and objective dimensions. We can survey how insecure people feel: how worried they are about adverse effects or how prepared they feel to cope with a shock. But we can also predict the likelihood that someone falls below the poverty line in any given year. And some elements of the dashboard are “intermediate” variables—things that we may (or may not) value in themselves but that provide an inkling of how a society will function in the future. One of these is trust. Societies in which citizens trust their governments and one another to “do the right thing” tend to perform better. In fact, societies in which people have higher levels of trust, such as Vietnam and New Zealand, have dealt far more effectively with the pandemic than the U.S., for instance, where trust levels have declined since the Reagan era. Policy makers need to use such indicators much as physicians use their diagnostic tools. When some indicator is flashing yellow or red, it is time to look deeper. If inequality is high or increasing, it is important to know more: What aspects of inequality are getting worse?
Steering through Storms
Since we began our work on well-being indicators some dozen years ago, I have been amazed at the resonance that it has achieved. A focus on many of the elements of the dashboard has permeated policy making everywhere. Every three years the OECD hosts an international conference of nongovernmental organizations, national statisticians, government officials and academics furthering the “well-being” agenda, the most recent being in Korea in November 2018, with thousands of participants.
Whenever the conference next convenes, the global crisis in human societies that a microscopic virus has precipitated will surely be on the agenda. The full dimensions of it could take years or decades to become clear. Recovering from this calamity and steering complex societies through the even more devastating crises that loom—catastrophic climate change and biodiversity collapse—will require, at the very least, an excellent navigational system. To paraphrase the OECD: We have been developing the tools to help us drive better. It is time to use them.


scientificamerican--2020-11-26--Eating Turkey Does Not Really Make You Sleepy

'T is the season for giving thanks and sharing blame .
The supercomittee , the White House , `` the One Percent , '' Greece , Italy—the accusations seem to be swirling everywhere this fall .
So in the spirit of sharing guilt , we thought it might be fun to ask a physician , Dr. Howard Markel of the University of Michigan , to help us re-examine a more classic case of finger-pointing : Is turkey the sole culprit behind our drowsy spells after Thanksgiving dinner ?
Or are other side dishes in on the act , too ?
@ @ @ @ @ @ @ the bird ?
Dr. Markel : Most people blame it on simply stuffing one 's stomach with too much food .
More medically-minded folks cite the myth that a huge meal causes a diversion of the blood supply to the gastrointestinal system as it digests all that turkey , dressing , potatoes , and pumpkin pie .
But in reality , the blood that is diverted tends to come from skeletal muscle tissue and is helped along by the heart 's ability to increase the volume of blood pumped forward with each beat @ @ @ @ @ @ @ blood and oxygen to the brain is rigidly controlled by the cardiovascular system and does not drop after any meal .
More recently , chemists have suggested that the post-feast drowsiness was caused by the high levels of an amino acid called L-tryptophan contained in turkey meat .
( There was even a `` Seinfeld '' episode about trying to get someone to sleep by feeding them turkey . )
But even though the turkey does contain high levels of L-tryptophan , it is comparable to that contained in many other meats that @ @ @ @ @ @ @ for L-tryptophan to really make you sleepy , you need to take it on an empty stomach and without ingesting any other types of amino acids or protein .
But there is a lot of protein in the average slice of turkey , and it 's usually not the only dish being served .
So what is the real medical answer ?
It may well have to do with the other foods that are served at the Thanksgiving table , particularly those dishes rich in carbohydrates .
Laboratory studies in both animals and @ @ @ @ @ @ @ triggers the pancreas to release of insulin , the hormone that helps us breakdown and utilize sugar .
But insulin also stimulates the muscles to take in large neutral branched-chain amino acids but not tryptophan , which is an aromatic amino acid .
This results in a far greater ratio of L-tryptophan to branch-chained amino acids in the blood , and eventually , in the cerebral spinal fluid , the body fluid that bathes and cushions the spinal cord and brain .
And now here 's the climax of all this organic chemistry @ @ @ @ @ @ @ the L-tryptophan into serotonin that is eventually metabolized by the pineal gland into melatonin , a substance many travelers know as nature 's sleeping pill .
By the way , another sleep inducer that accompanies many Thanksgiving meals is alcohol .
Too much of any spirit , wine or beer is bound to make you sleepy , at best , and grouchy or a dangerous driver at worst .
So enjoy the meal , watch the carbohydrates and limit your alcohol intake for a safe Thanksgiving .
This article is reprinted with permission @ @ @ @ @ @ @ published on November 23 , 2011 .

'Tis the season for giving thanks and sharing blame. The supercomittee, the White House, "the One Percent," Greece, Italy—the accusations seem to be swirling everywhere this fall. So in the spirit of sharing guilt, we thought it might be fun to ask a physician, Dr. Howard Markel of the University of Michigan, to help us re-examine a more classic case of finger-pointing: Is turkey the sole culprit behind our drowsy spells after Thanksgiving dinner? Or are other side dishes in on the act, too?
NewsHour: Can we blame it on the bird?
Dr. Markel: Most people blame it on simply stuffing one's stomach with too much food. More medically-minded folks cite the myth that a huge meal causes a diversion of the blood supply to the gastrointestinal system as it digests all that turkey, dressing, potatoes, and pumpkin pie. But in reality, the blood that is diverted tends to come from skeletal muscle tissue and is helped along by the heart's ability to increase the volume of blood pumped forward with each beat. In fact, the flow of blood and oxygen to the brain is rigidly controlled by the cardiovascular system and does not drop after any meal.
More recently, chemists have suggested that the post-feast drowsiness was caused by the high levels of an amino acid called L-tryptophan contained in turkey meat. (There was even a "Seinfeld" episode about trying to get someone to sleep by feeding them turkey.) But even though the turkey does contain high levels of L-tryptophan, it is comparable to that contained in many other meats that we consume. Moreover, in order for L-tryptophan to really make you sleepy, you need to take it on an empty stomach and without ingesting any other types of amino acids or protein. But there is a lot of protein in the average slice of turkey, and it's usually not the only dish being served.
So what is the real medical answer? It may well have to do with the other foods that are served at the Thanksgiving table, particularly those dishes rich in carbohydrates. Laboratory studies in both animals and human beings have demonstrated that carbohydrate-rich meals triggers the pancreas to release of insulin, the hormone that helps us breakdown and utilize sugar. But insulin also stimulates the muscles to take in large neutral branched-chain amino acids but not tryptophan, which is an aromatic amino acid. This results in a far greater ratio of L-tryptophan to branch-chained amino acids in the blood, and eventually, in the cerebral spinal fluid, the body fluid that bathes and cushions the spinal cord and brain. And now here's the climax of all this organic chemistry and human physiology: the brain converts the L-tryptophan into serotonin that is eventually metabolized by the pineal gland into melatonin, a substance many travelers know as nature's sleeping pill.
By the way, another sleep inducer that accompanies many Thanksgiving meals is alcohol. Too much of any spirit, wine or beer is bound to make you sleepy, at best, and grouchy or a dangerous driver at worst. So enjoy the meal, watch the carbohydrates and limit your alcohol intake for a safe Thanksgiving.
This article is reprinted with permission from PBS NewsHour. It was first published on November 23, 2011.


scientificamerican--2020-11-26--Snap, Crackle, Whop--How to Win the Wishbone

Don ’ t crack under pressure !
Explore the scientific—and sometimes sleazy—secrets to win a wish at this year ’ @ @ @ @ @

Don’t crack under pressure! Explore the scientific—and sometimes sleazy—secrets to win a wish at this year’s Thanksgiving wishbone pull.