Posts Tagged ‘measurement’
“You get what you measure”*…
Matt Stoller takes the occasion of Trump’s selection of Kevin Warsh to head the Fed (“an orthodox Wall Street GOP pick, though he is married to the billionaire heiress of the Estee Lauder fortune and was named in the Epstein files. He’s perceived not as a Trump loyalist but as an avatar of capital”) to ponder why public satisfaction with the economy is so low (“if you judge solely by consumer sentiment, Trump’s first term was the third best economy Americans experienced since 1960. Trump’s second term is not only worse than his first, it is the worst economic management ever recorded by this indicator”).
Stoller argues that we’re mesuring the wrong things (or, in some cases, the right things in the wrong ways)…
… the models underpinning how policymakers think about the economy just don’t reflect the realities of modern commerce. The fundamental dynamic is that those models were constructed in an era where America was one discrete economy, with Wall Street and the public tied together by the housing finance system. But today, Americans increasingly live in tiered bubbles that have less and less to do with one another. Warsh will essentially be looking at the wrong indicators, pushing buttons that are mislabeled.
While corporate America is experiencing good times, much of the country is experiencing recessionary conditions. Let’s contrast consumer sentiment indicators with statistics showing an economic boom. Last week, the government came out with stats on real gross domestic product increasing at a scorching 4.4% in the third quarter of last year. There’s higher consumer spending, corporate investment, government spending, and a better trade balance. Inflation, according to the Consumer Price Index, is low at 2.6.% over the past year. And while official numbers aren’t out for the final three months of the year, the Atlanta Fed’s GDPNow forecast shows that it estimates growth at 4.2%. And there are other indicators showing prosperity, from low unemployment to high business formation, which was up about 8% last year, as well as record corporate profits…
… Behavioral economists and psychologists have all sorts of reasons to explain that people don’t really understand the economy particularly well. But in general, when the stats and the public mood conflict, I believe the public is usually correct. Often, there are some weird anomalies with the data used by policymakers. In 2023, I noticed that the consumer price index, the typical measure of inflation, didn’t account for borrowing costs, so the Fed hike cycle, which caused increases in credit card, mortgage, auto loan, payday loans, et al, just wasn’t incorporated. The public wasn’t mad at phantom inflation, they were mad at real inflation that the “experts” didn’t see.
I don’t think that’s the only miscalculation…
[Stoller goes on to explain the ways in which “consumer spending” doesn’t tell us much about consumers anymore, about the painful reality of “spending inequality,” and about the obscure(d) problem of monopoly-driven inflation. He concludes…]
… Finally, there’s a more philosophical point, which I don’t think explains the short-term frustrations people feel, but is directionally correct. Do people actually want what the economy is producing? For most of the 20th century, the answer was yes. When Simon Kuznets invented these measurement statistics in 1934, financial value and the value that Americans placed on products and services were similar. A bigger economy meant things like toilets and electricity spreading across rural America, and cars and food and washing machines.
Today? Well, that’s less clear. According to the Bureau of Labor Statistics, the second fastest growing sector of the economy in terms of GDP growth from 2019-2024 was gambling. Philip Pilkington wrote a good essay last summer on the moral assumptions behind our growth statistics. There is no agreed upon notion of what makes up an economically valuable object or activity, so our stats are inherently subtle moral judgments. Classic moral philosophers like Adam Smith believed in the “use value” of an item, meaning how it could be used, whereas neoclassical economists believed in the “exchange value” of an item, making no judgments about use and are just counting up its market price.
Normal people subscribe on a moral level to use value. Most of us see someone spending money on a gambling addiction as doing something worse than providing Christmas presents for kids, but not because of price. However, our GDP models use the market value basis. Kuznets, presumably, was not amoral, he just thought that our laws would ban immoral activities like gambling, and so use value and market value wouldn’t diverge. But they have.
It’s not just things like gambling or pornography or speculation. A lot of previously unmeasured activity has been turned into data and monetized, which isn’t actually increasing real growth but measuring what already existed. Take the change from meeting someone at a party to using a dating app. One is part of GDP, the other isn’t. Both are real, but only one would show a bigger economy.
Beyond that much of our economy is now based on intangibles – the fastest growing sector was software publishing. Is Microsoft moving to a subscription fee model for Office truly some sort of groundbreaking new product? It’s hard to say, while corporate assets used to be hard things like factories, today much of it is intangibles like intellectual property.
A boomcession, where the rich and corporate America experience a boom while working people feel a recession, is a very unhealthy dynamic. It’s certainly possible to create metrics to measure it, and to help policymakers understand real income growth among different subgroups. You could start looking at real income after non-discretionary consumer spending, or find ways of adjusting for price discrimination.
But I think a better approach is to try to knit us into one society again. The kinds of policymakers who could try to create metrics to understand the different experiences of classes, and ameliorate them, don’t have power. Instead, the people in charge still use models which presume one economy and one relatively uniform set of prices, where “consumer spending” means stuff consumers want.
I once noted a speech in 2016 by then-Fed Chair Janet Yellen in which she expressed surprise that powerful rich firms and small weak ones had different borrowing rates, which affected the “monetary transmission channel” the Fed relied on. Sure it was obvious in the real world, but she preferred theory.
Or they don’t use models at all; Kevin Warsh is not an economist, he’s a lawyer and political operative, and is uninterested in academic theory. He cares about corporate profits and capital formation. That probably won’t work out well either.
At any rate, we have to start measuring what matters again. If we don’t, then we’ll continue to be baffled that normal people hate the economy that looks fine on our charts…
The models used by policymakers to understand wages, economic growth, and consumer spending are misleading. That’s why corporate America is having a party, and everyone else is mad. Eminently worth reading in full: “The Boomcession: Why Americans Hate What Looks Like an Economic Boom,” from @matthewstoller.bsky.social (or @mattstoller.skystack.xyz).
* Richard Hamming (and also to the article above, see “Goodhart’s law“)
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As we ponder the pecuniary, we might recall that it was on this date in 1958 that Benelux Economic Union was founded, creating the seed from the European Economic Community, then the European Union grew.
On that same day, Philadelphia doo wop group The Silhouettes started five weeks at the top of the Billboard R&B chart with their first single, “Get A Job.”
“February is the uncertain month, neither black nor white, but all shades between by turns. Nothing is sure.”*…
Yeah, but why is it shorter than all of the other months? Timothy Taylor has the story…
I understand why the calendar adds an extra day to February every four years. The revolution of the earth around the sun is approximately 365 and one-quarter days. Every four years, that adds up to one additional day, plus some extra minutes. The modest rounding error in this calculation is offset by steps like dropping the extra day of leap year for years ending in “00.”
But my question is why February has only 28 days in other years. After all, January has 31 days and March has 31 days. If those two months each donated a day to February, then all three months could be 30 days long, three years out of four, and February could be 31 days in leap years. Every other month is either 30 or 31 days. Why does February only get 28 days?…
… The answer to such questions leads to a digression back into the history of calendars. In this case, Jonathan Hogeback writing at the Britannica website tells me, it seems to settle on the Roman king Numa Pompilius back around 700 BCE, before the start of the Roman Empire. The ancient Roman calendar of that time had a flaw: it didn’t have nearly enough days. As Hogeback writes:
The Gregorian calendar’s oldest ancestor, the first Roman calendar, had a glaring difference in structure from its later variants: it consisted of 10 months rather than 12. In order to fully sync the calendar with the lunar year, the Roman king Numa Pompilius added January and February to the original 10 months. The previous calendar had had 6 months of 30 days and 4 months of 31, for a total of 304 days. However, Numa wanted to avoid having even numbers in his calendar, as Roman superstition at the time held that even numbers were unlucky. He subtracted a day from each of the 30-day months to make them 29. The lunar year consists of 355 days (354.367 to be exact, but calling it 354 would have made the whole year unlucky!), which meant that he now had 56 days left to work with. In the end, at least 1 month out of the 12 needed to contain an even number of days. This is because of simple mathematical fact: the sum of any even amount (12 months) of odd numbers will always equal an even number—and he wanted the total to be odd. So Numa chose February, a month that would be host to Roman rituals honoring the dead, as the unlucky month to consist of 28 days.
This discussion does explain why February would be singled out, since it was the month of rituals honoring the dead. In Numa’s calendar, the 355-day year would be made up of 11 months that had the lucky odd numbers of 29 or 31 days, plus unlucky February.
The discussion also explains why months that start with the prefix “Oct-” or eight, “Nov” or nine, and “Dec-” or ten, are actually months 10, 11, and 12 in the calendar. Those names were originally part of a 10-month calendar year.
But questions remains unanswered: Why did the Romans of that time view odd numbers as lucky, compared with unlucky even numbers? I suppose that explaining any superstition is hard, but I’ve never seen a great explanation. A Dartmouth course on “Geometry in Art and Architecture” describes Pythagorean feelings about odd and even numbers. For those of you keeping score at home, Pythagoras lived about two centuries after Numa Pompilius. The Dartmouth course material summarizes aspects of “Pythagorean Number Symbolism”:
Odd numbers were considered masculine; even numbers feminine because they are weaker than the odd. When divided they have, unlike the odd, nothing in the center. Further, the odds are the master, because odd + even always give odd. And two evens can never produce an odd, while two odds produce an even. Since the birth of a son was considered more fortunate than birth of a daughter, odd numbers became associated with good luck…
[Taylor recounts the recurrence of this theme, from Virgil to Shakespeare…]
… While I acknowledge this history of a belief in odd numbers, as a person born on an even day of an even month in an even year, I’m not predisposed to accept it. But it’s interesting that modern photographers have a guideline for composing photographs called the “rule of odds.” Rick Ohnsman at the Digital Photography School, for example, describes it this way:
This is where the rule of odds comes into play, a deceptively simple yet powerful tool in your photographic arsenal. It’s all about arranging your subjects in odd numbers to craft compositions that are naturally more pleasing to the eye. Unlike more static guidelines, the rule of odds offers a blend of structure and organic flow, making your images both aesthetically pleasing and impressively compelling.
The revised calendar of Numa Pompilius couldn’t last. With only 355 days, it didn’t reflect the actual period of the earth revolving around the sun, and thus led to further revisions which are a story in themselves.
But when you think about it, the question of February having 28 days all goes back to Numa Pompilius and the superstitions about odd numbers. The modern calendar has 365 days in a typical year. You might think that the obvious way to divide this up would be to start off with 12 months of 30 days, and then add five days. Indeed, the ancient Egyptians had a calendar of this type, with five “epagomenal” or “outside the calendar days added each year.
The preference over the last two millennia, at least since the time of Julius Caesar, is to have 12 months, with a few of them being a day longer. But even so, why not in a typical year have five months of 31 days, and the rest with 30? The “problem,” I think, is that most months would then have unlucky totals of an even number of days. By holding February to 28 days rather than 30, you can redistribute two days from February and have 31 days in January and March. Thus, you can have only four months with an even total of 30 days every year (“Thirty days hath September, April, June, and November …”), and seven months always with the luckier odd total of 31 days. In leap years, when February has 29 days, then eight months have an odd number of days. I think this makes February 29 a lucky day?…
“Why Does February (Usually) Have 28 Days?” from @TimothyTTaylor.
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As we muse on the marking of months, we might recall that it was on this date in 1692 that a doctor in Salem, Massachusetts (generally believed to have been William Griggs), was unable to find a physical explanation for the ailments (fits, pins-and-needles) of three young girls. As other young women in Salem began to evince the same symptoms, the local preacher declared them “bewitched”… and the stage was set for The Salem Witch Trials.
“Inflation hasn’t ruined everything. A dime can still be used as a screwdriver.”*…
As the recent election reminds us, inflation is a central issue to millions. How we calculate inflation has always been a subject of debate. And, as Carola Conches Binder explains, small changes that might seem trivial can lead to enormous changes in how well-off we think we are…
Every month, the US Bureau of Labor Statistics releases its newest data on the consumer price index (CPI). The CPI report is eagerly awaited by economists and policy wonks and investors. It garners heavy news coverage as a key piece of information in macroeconomic policymaking and analysis. The CPI and related measures affect monetary and fiscal policymaking and are often used to adjust Social Security payments, income tax brackets, and wages for millions of workers. Because of these far-reaching impacts, even relatively small changes in the measurement of the CPI can have major implications for households, firms, and the government’s budget. Thus, the technocratic task of measuring the price level is often at the center of political controversies. The evolution of inflation measurement in the United States has reflected both technical progress and these political forces.
The government’s role in the collection and publication of price indexes has been politically controversial from its origins, which were surprisingly late. Wesley Clair Mitchell, the former president of the American Economic Association, in 1921 called it:
a curious fact that men did not attempt to measure changes in the level of prices until after they had learned to measure such subtle things as the weight of the atmosphere, the velocity of sound, fluctuations of temperature, and the precession of the equinoxes . . . Perhaps disinclination on the part of ‘natural philosophers’ to soil their hands with such vulgar subjects as the prices of provisions was partly responsible for the delay…
[Binder recounts the history of price measurement, starting in Italy in the 18th century, explaining that economic and political pressures first resisted having indices at all, then struggled to shape them. She then compares the current approaches in use and unpacks the recent [and current] debate over whether we have inflation and if so, how much…]
… At the time of writing in 2024, inflation is falling by nearly any measure. But as Krugman’s super core episode [see here, here, and here] illustrates, the past few years have intensified public scrutiny of official price indexes and led to debates about their interpretations. In light of this scrutiny, it is important for national statistics agencies to maintain their credibility by adopting methodological improvements, learning from both the private sector and academic researchers, and communicating clearly with the public.
Just as the Bureau of Labor Statistics responded to the Stigler and Boskin Commissions by revising its methods, it has also responded to the Covid-19 pandemic and post-pandemic inflation. For example, the pandemic demonstrated that biennial (every other year) updates to the CPI expenditure weights are too infrequent in times of rapid economic changes. The pandemic very quickly shifted the types of goods and services that people were buying, so expenditure weights based on survey data from 2018 became out of date. People were spending more on food and other items facing large price increases, and less in categories experiencing falling prices, like transportation, implying that the official CPI measure was underestimating inflation.
The Bureau of Labor Statistics could not move quickly enough to change its estimates of expenditure weights, but private researchers could. The economist Alberto Cavallo used data collected from credit and debit card transactions to build his own set of weights that he used to construct a new Covid CPI measure, which indeed rose more quickly than the official CPI in the first months of the pandemic…
Cavallo’s experience constructing alternatives to official inflation statistics began when his home country, Argentina, began doctoring its inflation statistics in 2007 to hide inflation that rose above 12 percent in 2006 and likely averaged above 20 percent from 2007 to 2011. Cavallo and a group called the Billion Prices Project at MIT used web-scraping techniques to collect the prices of goods sold online in Argentina and four other Latin American countries. For all but Argentina, the price indexes based on online prices closely tracked official price indexes, but for Argentina, Cavallo’s estimates of inflation were three times higher than official estimates, and Cavallo’s estimates soon became more trusted than the official statistics.
Cavallo and the other researchers behind the Billion Prices Project have since extended their methodology to other countries, including the United States. In 2011, they started a private company called PriceStats that produces daily-frequency inflation measures for central banks and financial-sector customers in 25 countries, including the United States, using data on millions of product prices from hundreds of retailers.
In the United States, private inflation estimates may supplement the official estimates, but are unlikely to replace them. In part, this reflects the statistical agencies’ willingness to refine their methods, learn from private researchers, and maintain methodological transparency. For example, having learned that biennial expenditure weight updates are too infrequent, the BLS will update its expenditure weights every year beginning in 2023. The BLS also recently sponsored a study, Modernizing the Consumer Price Index for the 21st Century, to investigate additional improvements to the CPI that could be adopted in years to come. The study’s panelists considered a variety of innovations by Cavallo and other researchers, and recommended that the BLS experiment with using a wider variety of data sources, including online transactional data, to improve the timeliness and accuracy of its estimates.
The development of price and inflation measures has often been driven by political controversies, especially during times of war or during labor disputes. The development of the consumer price index arose from a need to ensure that wages and benefits would keep up with the cost of living. The recommendations of several different commissions have led to changes in how the index is computed – changes that have major impacts on the federal budget and on the distribution of resources. Especially in recent years, alternative inflation measures have proliferated. Overall, the official price indexes represent a tremendous intellectual and public achievement, despite the debates that continue to surround their use and interpretation…
Measuring price changes: “Where inflation comes from,” by @cconces in @WorksInProgMag.
(Image above: source)
* H. Jackson Brown Jr.
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As we muse on measurement, we might note that today marks the anniversary of another measurement regime that supplanted what had been a largely an informal (and often intuitive) understanding of a basic fact of life: on this date in 1883, precisely at noon, North American railroads switched to a new standard time system for rail operations, which they called Standard Railway Time (SRT). Almost immediately after being implemented, many American cities enacted ordinances adopting the standard, thus resulting in the creation of time “zones” in the U.S.– Eastern, Central, Mountain, and Pacific. Though tailored to the railroad companies’ train schedules, the new system was quickly adopted nationwide, forestalling federal intervention in civil time for more than thirty years, until 1918, when daylight saving time was introduced.
“Be careful what you wish for”*…
… And how you wish for it. Eric Athas, with an all-too-timely reminder…
Whenever I’m thinking about ideas to send to you all, I’m reminded of a principle called Goodhart’s Law, which says: “When a measure becomes a target, it ceases to be a good measure.”
In other words, when you tell people they’re being evaluated by a target they must hit, you risk pushing them to produce the wrong results in the name of reaching the target. The incentives can drive them to fixate on achieving the target, not achieving the overall goal.
The concept is named after the economist Charles Goodhart, who introduced it in a 1975 paper about monetary management. But the theory has been connected to a range of situations.
One of the most famous examples is a story about colonial India, when the British government sought to subdue an overpopulation of cobras in Delhi by placing a bounty on the snakes. Turn in a snakeskin, get some money.
But the plan backfired. People started farming cobras to cash in on the bounties, only exacerbating the population problem. This tale, which you can hear more about in a 2012 Freakonomics episode, spawned a shorthand for this phenomenon—the cobra effect…
… Goodhart’s Law, or the cobra effect, isn’t limited to economic policy or invasive species. You can apply it to everyday situations:
- A fitness tracker rewards you for clocking 10,000 steps a day, so you spend your evenings pacing around your living room. [see here]
- A calorie-counting app pushes you to form an unhealthy diet to stay under the limit.
- You set a resolution to read book a week but soon begin selecting books purely based on length—not interest or relevance—to hit the target.
- A construction firm is given unrealistic milestones and must cut corners to fulfill a contract.
- A school becomes hyper-focused on its test scores and offers incentives for grades instead of providing a well-rounded educational experience.
That last one happened in a years-long cheating scandal in Atlanta that unraveled in the 2010s.
Workplace quotas can have this effect, too. When you’re evaluated based on a quota, you may do anything to meet that quota, even if the quality of the work diminishes.
On the flip side, a quota policy may demotivate workers. Here’s what Adam Cobb, a professor of management at Wharton, said in a Wharton write-up about quotas: “People might start withholding effort … If you can easily meet your monthly quota, why should you try as hard once the goal is reached? Doing so may encourage the company to raise the quota, making your life harder.”
You can find the cobra effect in academic research, too, with the push for publication fueling an increase in fake papers.
Today, we’re surrounded by measurements that can be tempting to use as targets in our behavior. What is inbox zero but a target that may distract us from completing more fulfilling work?
I think a lot about the cobra effect with social media, where your success is tied to your ability to accrue views, likes, comments, and shares. Those targets can create an expectation that you must always be creating something new. Social media managers, influencers, and YouTubers have talked about the pressure to churn out new content to please algorithms and feed their audiences…
… Which brings me back to the point I started with a few hundred words ago, and the title of this post. I send this newsletter every Sunday. The routine is helpful because it provides me with a structure to work within. Absent that framework, I could end up spending too little or too much time on it.
But I must remind myself that the weekly tempo isn’t the target. If it were, I’d be critiquing myself based on arbitrary timing, not on the quality of the information I’m sharing with you. I’d be more prone to “spin up” content, as opposed to finding interesting ideas to share with you. I try to keep Goodhart’s Law in mind each week.
As you go about your day, consider your own goals, personally and professionally. When you take an action, like posting a photo on social media or completing a work task, are you doing it to please a measurement? To hit a target?…
The cobra effect and the dangers of turning measures into targets: “I’m not writing this to hit a weekly target,” from @ericathas.
Apposite: “When workplace bonuses backfire” (Economist gift link)
(Image above: source)
* Aesop’s Fables
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As we interrogate our intentions, we might recall that it was on this date in 1793 that the Queen of France, Marie Antoinette, was beheaded. The French Revolution had begun in 1789…
… The Storming of the Bastille on 14 July led to a series of radical measures by the Assembly, among them the abolition of feudalism, state control over the Catholic Church in France, and a declaration of rights.
The next three years were dominated by the struggle for political control, exacerbated by economic depression. Military defeats following the outbreak of the French Revolutionary Wars in April 1792 resulted in the insurrection of 10 August 1792. The monarchy was replaced by the French First Republic in September, while Louis XVI was executed in January 1793.
After another revolt in June 1793, the constitution was suspended, and adequate political power passed from the National Convention to the Committee of Public Safety [which decreed Marie Antoinette’s fate]. About 16,000 people were executed in a Reign of Terror, which ended in July 1794. Weakened by external threats and internal opposition, the Republic was replaced in 1795 by the Directory. Four years later, in 1799, the Consulate seized power in a military coup led by Napoleon Bonaparte. This is generally seen as marking the end of the Revolutionary period…
“Those who are not shocked when they first come across quantum theory cannot possibly have understood it”*…
A scheduling note: your correspondent is headed onto the road for a couple of weeks, so (Roughly) Daily will be a lot more roughly than daily until September 20th or so.
100 years ago, a circle of physicists shook the foundation of science. As Philip Ball explains, it’s still trembling…
In 1926, tensions were running high at the Institute for Theoretical Physics in Copenhagen. The institute was established 10 years earlier by the Danish physicist Niels Bohr, who had shaped it into a hothouse for young collaborators to thrash out a new theory of atoms. In 1925, one of Bohr’s protégés, the brilliant and ambitious German physicist Werner Heisenberg, had produced such a theory. But now everyone was arguing with each other about what it implied for the nature of physical reality itself.
To the Copenhagen group, it appeared reality had come undone…
[Ball tells the story of Niels Bohr’s building on Max Planck, of Werner Heisenberg’s wrangling of Bohr’s thought into theory, of Einstein’s objections and Erwin Schrödinger’s competing theory; then he homes in on the ontological issue at stake…]
Quantum mechanics, they said, demanded we throw away the old reality and replace it with something fuzzier, indistinct, and disturbingly subjective. No longer could scientists suppose that they were objectively probing a pre-existing world. Instead, it seemed that the experimenter’s choices determined what was seen—what, in fact, could be considered real at all.
In other words, the world is not simply sitting there, waiting for us to discover all the facts about it. Heisenberg’s uncertainty principle implied that those facts are determined only once we measure them. If we choose to measure an electron’s speed (more strictly, its momentum) precisely, then this becomes a fact about the world—but at the expense of accepting that there are simply no facts about its position. Or vice versa…
…A century later, scientists are still arguing about this issue of what quantum mechanics means for the nature of reality…
[Ball recounts subsequent attempts to reconcile quantum theory to “reality,” including Schrödinger’s wave mechanics…]
… Schrödinger’s wave mechanics didn’t restore the kind of reality he and Einstein wanted. His theory represented all that could be said about a quantum object in the form of a mathematical expression called the wave function, from which one can predict the outcomes of making measurements on the object. The wave function looks much like a regular wave, like sound waves in air or water waves on the sea. But a wave of what?
At first, Schrödinger supposed that the amplitude of the wave—think of it like the height of a water wave—at a given point in space was a measure of the density of the smeared-out quantum particle there. But Born argued that in fact this amplitude (more precisely, the square of the amplitude) is a measure of the probability that we will find the particle there, if we make a measurement of its position.
This so-called Born rule goes to the heart of what makes quantum mechanics so odd. Classical Newtonian mechanics allows us to calculate the trajectory of an object like a baseball or the moon, so that we can say where it will be at some given time. But Schrödinger’s quantum mechanics doesn’t give us anything equivalent to a trajectory for a quantum particle. Rather, it tells us the chance of getting a particular measurement outcome. It seems to point in the opposite direction of other scientific theories: not toward the entity it describes, but toward our observation of it. What if we don’t make a measurement of the particle at all? Does the wave function still tell us the probability of its being at a given point at a given time? No, it says nothing about that—or more properly, it permits us to say nothing about it. It speaks only to the probabilities of measurement outcomes.
Crucially, this means that what we see depends on what and how we measure. There are situations for which quantum mechanics predicts that we will see one outcome if we measure one way, and a different outcome if we measure the same system in a different way. And this is not, as is sometimes implied (this was the cause of Heisenberg’s row with Bohr), because making a measurement disturbs the object in some physical manner, much as we might very slightly disturb the temperature of a solution in a test-tube by sticking a thermometer into it. Rather, it seems to be a fundamental property of nature that the very fact of acquiring information about it induces a change.
If, then, by reality we mean what we can observe of the world (for how can we meaningfully call something real if it can’t be seen, detected, or even inferred in any way?), it is hard to avoid the conclusion that we play an active role in determining what is real—a situation the American physicist John Archibald Wheeler called the “participatory universe.”..
… Heisenberg’s “uncertainty” captured that sense of the ground shifting. It was not the ideal word—Heisenberg himself originally used the German Ungenauigkeit, meaning something closer to “inexactness,” as well as Unbestimmtheit, which might be translated as “undeterminedness.” It was not that one was uncertain about the situation of a quantum object, but that there was nothing to be certain about.
There was an even more disconcerting implication behind the uncertainty principle. The vagueness of quantum phenomena, when an electron in an atom might seem to jump from one energy state to another at a time of its own choosing, seemed to indicate the demise of causality itself. Things happened in the quantum world, but one could not necessarily adduce a reason why. In his 1927 paper on the uncertainty principle, Heisenberg challenged the idea that causes in nature lead to predictable effects. That seemed to undermine the very foundation of science, and it made the world seem like a lawless, somewhat arbitrary place….
… One of Bohr’s most provocative views was that there is a fundamental distinction between the fuzzy, probabilistic quantum world and the classical world of real objects in real places, where measurements of, say, an electron with a macroscopic instrument tell us that it is here and not there.
What Bohr meant is shocking. Reality, he implied, doesn’t consist of objects located in time and space. It consists of “quantum events,” which are obliged to be self-consistent (in the sense that quantum mechanics can describe them accurately) but not classically consistent with one another. One implication of this, as far as we can currently tell, is that two observers can see different and conflicting outcomes from an event—yet both can be right.
But this rigid distinction between the quantum and classical worlds can’t be sustained today. Scientists can now conduct experiments that probe size scales in between those where quantum and classical rules are thought to apply—neither microscopic (the atomic scale) nor macroscopic (the human scale), but mesoscopic (an intermediate size). We can look, for example, at the behavior of nanoparticles that can be seen and manipulated yet are small enough to be governed by quantum rules. Such experiments confirm the view that there is no abrupt boundary of quantum and classical. Quantum effects can still be observed at these intermediate scales if our devices are sensitive enough, but those effects can be harder to discern as the number of particles in the system increases.
To understand such experiments, it’s not necessary to adopt any particular interpretation of quantum mechanics, but merely to apply the standard theory—encompassed within Schrödinger’s wave mechanics, say—more expansively than Bohr and colleagues did, using it to explore what happens to a quantum object as it interacts with its surrounding environment. In this way, physicists are starting to understand how information gets out of a quantum system and into its environment, and how, as it does so, the fuzziness of quantum probabilities morphs into the sharpness of classical measurement. Thanks to such work, it is beginning to seem that our familiar world is just what quantum mechanics looks like when you are 6 feet tall.
But even if we manage to complete that project of uniting the quantum with the classical, we might end up none the wiser about what manner of stuff—what kind of reality—it all arises from. Perhaps one day another deeper theory will tell us. Or maybe the Copenhagen group was right a hundred years ago that we just have to accept a contingent, provisional reality: a world only half-formed until we decide how it will be…
Eminently worth reading in full: “When Reality Came Undone,” from @philipcball in @NautilusMag.
See also: When We Cease to Understand the World, by Benjamin Labatut.
* Niels Bohr
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As we wrestle with reality, we might spare a thought for Ludwig Boltzmann; he died on this date in 1906. A physicist and philosopher, he is best remembered for the development of statistical mechanics, and the statistical explanation of the second law of thermodynamics (which connected entropy and probability).
Boltzmann helped paved the way for quantum theory both with his development of statistical mechanics (which is a pillar of modern physics) and with his 1877 suggestion that the energy levels of a physical system could be discrete.
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