In the winter of 1994, a young man in his early twenties named Tim was a patient in a London psychiatric hospital. Despite a happy and energetic demeanour, Tim had bipolar disorder and had recently attempted suicide. During his stay, he became close with a visiting US undergraduate psychology student called Matt. The two quickly bonded over their love of early-nineties hip-hop and, just before being discharged, Tim surprised his friend with a portrait that he had painted of him. Matt was deeply touched. But after returning to the United States with portrait in hand, he learned that Tim had ended his life by jumping off a bridge.

Matthew Nock now studies the psychology of self-harm at Harvard University in Cambridge, Massachusetts. Even though more than two decades have passed since his time with Tim, the portrait still hangs in his office as a constant reminder of the need to develop a way to predict when people are likely to try and kill themselves. There are plenty of known risk factors for suicide—heavy alcohol use, depression and being male among them—but none serve as tell-tale signs of imminent suicidal thoughts. Nock thinks that he is getting close to solving that.

Since January 2016, he has been using wristbands and a phone application to study the behaviour of consenting patients who are at risk of suicide, at Massachusetts General Hospital in Boston. And he has been running a similar trial at the nearby Franciscan Children’s Hospital this year. So far, he says, although his results have not yet been published, the technology seems able to predict a day in advance, and with reasonable accuracy, when participants will report thinking of killing themselves.

Nock’s trial is one effort to make use of the burgeoning science of mood forecasting: the idea that by continuously recording data from wearable sensors and mobile phones, it will be possible not only to track and perhaps identify signs of mental illness in a person, but even to predict when their well-being is about to dip. Nock collaborates with Rosalind Picard, an electrical engineer and computer scientist at the Massachusetts Institute of Technology (MIT) in Cambridge. Picard leads a team that has tracked hundreds of undergraduates in universities in New England with phones and wristbands, and reports being able to predict episodes of sadness in these students a day before symptoms arrive.

Hints that it might be possible to track impending emotional vulnerability have sparked strong commercial interest. Mindstrong Health, a company in Palo Alto, California, which has raised US$29 million in venture capital, tracks how people tap, type and scroll on their phones, to spot shifts in neurocognitive function. Paul Dagum, a physician and computer scientist who founded the firm, says that data from a person’s touchscreen interactions can identify oncoming episodes of depression, although that work has not yet been published. Other companies are also researching the use of such ‘digital phenotyping’ to recognize symptoms of mental illness. Among them is Verily, a life-sciences firm owned by Google’s parent company, Alphabet.

At this stage, the reliability of mood-prediction technology is unclear. Few results have been published, and groups that have released results say they have achieved only moderate rather than outstanding accuracy when it comes to forecasting moods. Picard, however, is confident that the concept will hold up. “I suffered from depression early in my career and I do not want to go back there,” she says. “I am certain that by tracking my behaviours with my phone I can make it far less likely I will return to that terrible place.”

But researchers including Picard have reservations about possible downsides of their creations. They worry that scientists and clinicians haven’t thought enough about how to inform users of an imminent emotional downturn. There are also questions about whether such warnings could cause harm. And some wonder whether corporations or insurance companies might use the technology to track the future mental health of their employees or customers. “The [potential for] misuse of this technology is what keeps me up at night,” Dagum says.

Predicting depression

Picard got into mood-prediction research indirectly. A decade ago, she showed that it was possible to use wristbands to detect seizures, sometimes minutes before spasms shook the body, by tracking the electrical conductance on a person’s skin. In 2013, she co-founded Empatica, a company in Cambridge that sells sensors, including a smartwatch approved by the US Food and Drug Administration to monitor signs of seizures and issue alerts to caregivers.

Working with her PhD student at the time Akane Sano, now at Rice University in Houston, Texas, Picard saw potential for wider applications. They hypothesized that it might be possible to combine data from wrist sensors and mobile phones to monitor stress, sleep, activity and social interactions to predict general mental health and well-being.

Sano and Picard collaborated with a team at Harvard Medical School to design a study that would track university students on a daily basis. Since 2013, the team has studied 300 students—50 each semester, for 30 days at a time—by giving them watch-like devices to wear. The instruments measure the students’ movements, note the amount of light they are exposed to, monitor their body temperature and record the electrical conductance of their skin. Sano and Picard also developed software, installed on participants’ phones, which records data about their calls, text messages, location, Internet use, ‘screen on’ timing and social interactions. The team also recorded much of their e-mail activity. Students filled out surveys twice a day about their academic, extracurricular and exercise activities. They described their sleep quality, their mood, health, stress levels, social interactions and how many caffeinated and alcoholic drinks they were consuming. The students also reported their exam scores and filled out extensive surveys at the beginning and end of the 30-day studies.

By 2017, the team had reported, training an algorithm to learn from these surveys and to weight the importance of hundreds of measurements. The system can accurately forecast, a day in advance, the students’ happiness, calmness and health, Picard’s team says. In the experiment, individuals had to be monitored for 7 days to reach forecast-accuracy levels of around 80%. Picard’s analysis suggests that wristbands and mobile phones are not able to predict slight changes in mood. But when changes in well-being are large, predictions are more reliable. Some of the signals make intuitive sense—moving around before bed might suggest agitation, for instance—but the details are not always understood. As an example, social interactions might modify stress levels, which can be reflected in skin electrical conductance, but it’s unclear whether many peaks of skin conductance in a day is good or bad, because it increases both when people are problem solving and when they are stressed.

Simply interpreting someone’s mood using such signals is a great achievement, says computer scientist Louis-Philippe Morency at Carnegie Mellon University in Pittsburgh, Pennsylvania, who thinks artificial-intelligence technology could help with mental-health assessments. But he is cautious about its ability to forecast moods. “Since tomorrow’s mood is often similar to today’s mood, we need more research to be able to clearly decouple these two phenomena. It is possible that current forecasting technologies are mostly predicting spillover emotion from one day to the next,” he says.

Picard thinks improvements will come: “We are the pioneers saying that this is truly possible and are showing data to back this claim up. Reliability will grow and grow with more data.” She has made her algorithms open-source, so that others with access to the technology can try to reproduce her work.

“Picard is on to something, and her track record of transparency with her algorithms, models and data sets makes me even more confident of that. People don’t make it so easy to recreate their work when they are unsure about their results,” says Jonathan Gratch, a psychologist at the Institute for Creative Technologies at the University of Southern California in Playa Vista.

Nock’s trial on suicidal thoughts grew out of a collaboration with Picard. So far, he has monitored 192 people, mainly using wristbands and by asking them how they are feeling, through a phone app or interview. For now, he has trained devices not on an individual’s data, but on those of the entire group of participants, and he says that he has identified a few measurable signs that can predict later suicidal thoughts with an accuracy of 75%. Some of the most important factors, he says, are considerable movement in the evening, perhaps denoting restlessness or agitation at night, mixed with spikes in skin electrical conductance and an elevated heart rate. But he declined to give more details because his paper is under review at a journal.

Moving to market

Commercial firms are less willing than are academics to discuss their results. But in March, Mindstrong, which is only 16 months old, reported finding digital biomarkers — patterns of swipes and taps on a phone—that correlate with scores on neuropsychological performance tests3. On its website, the firm says it has completed five clinical trials, the results of which have not been disclosed, and in February, it announced a partnership with Tokyo-based Takeda Pharmaceuticals to explore the development of digital biomarkers for conditions such as schizophrenia and treatment-resistant depression. It has competition: Verily says its digital phenotyping projects include one designed to detect post-traumatic stress disorder using smartphones and watches.

Mindstrong says it’s moving beyond measuring brain function with smartphones, to predicting it. “When we take in the trajectory of numerous biomarkers over the course of six or seven days, we can predict episodes of depression up to a week in the future,” says Dagum—although he declined to say which signals his firm is using, because the company was submitting papers on its work to journals.

The plan for Mindstrong’s phone-based app (the company is not using wristbands) is to embed its touchscreen-interaction measures into a digital mental-health-care system. It has been sharing results with the state of California, which sees enough clinical potential to have granted the firm $10 million over 3 years from a state-managed, $60-million mental-health innovation fund. “Will all of this data that we are collecting ultimately have clinical utility? We don’t know yet,” says psychiatrist Tom Insel, who co-founded Mindstrong and had previously started the mental-health unit at Verily after a 13-year stint as head of the US National Institute of Mental Health.

Picard questions Insel’s approach at Mindstrong. “I believe he has made a company with an idea that is not proven to work as well as other ideas,” she says. Neither she nor Nock yet have commercial plans for their mood-prediction technology. (Besides Empatica, however, Picard has co-founded Affectiva, a firm in Boston that sells technology to analyse facial and vocal expressions.)

Insel says the technology needs testing in real-world settings, with patients and health providers. “We are not running before walking. California is paying us to learn how to walk,” he says. He adds that he doesn’t view Picard as a rival. “This is a hard problem that no one has solved. My best guess is that it will take all of us using many approaches to prove the clinical value of this technology—and, frankly, I’d love to have at least ten other groups of Roz’s lab’s calibre working on digital phenotyping,” he says.

Changing behaviour

Picard is confident that mood forecasting—even if it requires individualized training from a consenting user—will become a perfected art. The real question, she says, is whether it can be used to help change a forecasted dark mood.

Nock and psychologist Evan Kleiman, also at Harvard University, are working with 150 patients to encourage them to reappraise things that they are viewing negatively by using cognitive reframing exercises. These exercises are activated on the patients’ phones when their wrist monitors detect signals that predict upcoming suicidal thoughts. Beyond this, Nock is unclear what to do with the data. “If we have someone who is predicted to be at high risk for suicidal thoughts, or who notes that they are 100% likely to kill themselves, what do we do? Do we send an ambulance? Contact their doctor? Do nothing?” he wonders. “The ethics of this are extremely challenging.” Nock says he knows that those in his trial want the technology. “Patients say all the time how useful they would find an alert or guidance system,” he says.

Morency thinks that it is too soon for computers to be giving mental-health advice on their own. His research involves teaching computers to study facial expressions and language so that they can work out what is on a person’s mind, and he is now collaborating with psychiatrists to install this technology in hospital mental-health wards. The goal is for machines to study people during their interactions with doctors, to discern whether psychiatric disorders are present. The physicians still do the diagnosis; the computer analysis provides a separate assessment that doctors can compare with their own. “The risks presented by a computer giving mental-health advice are significant. We need more research to understand the long-term impact of such technology,” Morency says.

Another issue, says Picard, is that actions to improve mood are different for different people. In one of her experiments, Picard found that one cluster of students who had conversations with friends before going to sleep enjoyed brighter moods the following day, whereas another cluster experienced the inverse effect.

Barbara Fredrickson, a psychologist at the University of North Carolina at Chapel Hill, is concerned that the act of predicting a mood could affect how people feel. “It seems likely that people will give negative mood forecasts a great deal of attention, and for some, this could start an emotional negativity tailspin that could be truly damaging,” she says.

Justin Baker, a researcher in mental illnesses who is the scientific director of the McLean Institute for Technology in Psychiatry in Belmont, Massachusetts, says: “I think it will be just as difficult for us to determine what advice a person needs as it will be to determine how to present that advice to them in a manner that does not get ignored or make them worse.”

Picard has grand visions for digital mood forecasting. She thinks it could improve the health of the general public, and in particular that it might benefit corporations. “Why do so many amazing companies that give their employees every perk under the sun still lose so many staff to depression? Can we catch the coming transition before it takes place?” she says. But she also worries that the technology might be misused. Picard thinks that new regulations might be needed to prevent, say, corporations from targeting advertising at those whose bad or good moods can be seen coming, or to keep insurance companies from setting prices based on signs of their customers’ mental health.

“A few bad actors who misuse this technology could spoil the benefits for patients with serious mental-health issues,” says Insel. Mindstrong, he says, is working with a bioethics group at Stanford University, California and plans to publish a paper on these matters shortly.

Picard argues the research efforts are worthwhile. “Clinical depression is often emotional death by a thousand cuts,” she says. “If we can help to identify the many little things that weigh us down over time and drive us into a perpetual sorrowful state, we can make a big difference.”

This article is reproduced with permission and was first published on October 30, 2018.

A Two-Tier Economy

“Well-paying sectors that once employed lower-skilled workers have all but disappeared. In essence, there is a growing underclass that, while technically "employed" insofar as it has work, is not enjoying "employment" in the sense that it once was, i.e. permanent, full-time jobs, that provide benefits and pay a middle-class salary.” (Roger Salus)

Effective Trading

“As a trader, you shouldn't be stubbornly focused on being right all the time. It's okay to be wrong sometimes (as long as your losers are less than your winners), and remember to take what the market gives you instead of stubbornly focusing on what you are so certain is "right." Being right and being successful are not the same.” (Jeff Miller)

FIRE Movement

“The basic FIRE premise is that you need to save 50% of income until you have saved 25x your annual income. Then you live on a 4% withdrawal rate. Here is an example: Current annual income is $50,000 x 25 = $1,250,000 at 4% = $50,000. It's simple math. As I said, it's wrong because it is based on TODAY'S income level and not that of future income requirements.” (Lance Roberts)

The Annuity Puzzle

“A self-directed investor faced with uncertainty about how long she will live will want to keep some savings in reserve against long life. But, if she converts her savings into an annuity with reasonable terms she should get to spend substantially more because her longevity risk can be pooled with other people. The puzzle is: why don't more people convert their savings into a lifetime annuity as they get older, thus enjoying the benefits of being able to reserve less and spend more?” (Victor Haghani)

Thought For The Day

The above-linked article by Victor Haghani offers fresh ideas on the so-called “annuity puzzle,” which puzzles economists who expect that people would want to smooth out their income in retirement. There are numerous solutions to the annuity puzzle, which Haghani reviews in addition to his own thought that annuity avoiders are miscalculating the risks they are taking. As he puts it:

Bearing one's own longevity risk does not offer compensation in the form of a risk-premium. For many people, longevity risk can be more consequential than the risk they bear in their investment portfolio.”

This may well be the case for lots of investors, for which reason I highly commend this article. But for our purposes here, I’ll suggest my own solution to the annuity puzzle, as well as a critical takeaway that flows from it. The reason annuity sales are just 8% of retirement assets is that people don’t like to lose. As studies have shown, the pain of loss greatly exceeds the thrill of gain. The chance that the insurance company may “win,” and the investor ends up with less than he puts into his annuity is psychologically displeasing, a displeasure compounded by the fact that the investor cannot bequeath any remaining funds to his heirs, and that the sum in question is his life savings.

Put differently, an annuity investment is unlike an investment in real estate, in which an investor who partners with a financial institution sees his equity rise over time, while maintaining the hope that the underlying asset appreciates in value.

And yet while I can understand that an annuity contract and a home purchase are processed differently psychologically, I believe it would behoove investors to see a common advantage they have. There’s a reason we are prepared to take our hard earned savings – our cold hard cash sitting in the bank – and trade it in for a home. From a lifecycle point of view, people intuitively grasp an advantage in trading something impermanent for that which is enduring. We trade our labor – by selling goods or services – for income we use to pay rent, accumulating savings to purchase a home that we control. No less than the Monopoly player who owns properties on Boardwalk and Illinois Avenue, we make money by collecting income, not by paying rent.

And while annuity ownership is certainly not the same as property ownership – unless you outlive other annuitants and thus “profit” thereby – what the former has in common with the latter is the satisfaction of exchanging the impermanent (life savings that will wither from inflation) for the permanent (an income that you cannot outlive).

Not wanting to pay an insurance company is understandable, as is wanting to leave a bequest. By all means, become a real estate monopolist and retire rich, and you’ll never need an annuity. But however you do it, the life-cycle challenge of your post-working years is to replace your pre-retirement income. Whether through a bond ladder, dividend income, stock sales or rental income, some form of permanent income is the manifestation of post-work financial achievement.

Americans are used to thinking that their nation is special. In many ways, it is: the U.S. has by far the most Nobel Prize winners, the largest defense expenditures (almost equal to the next 10 or so countries put together) and the most billionaires (twice as many as China, the closest competitor). But some examples of American Exceptionalism should not make us proud. By most accounts, the U.S. has the highest level of economic inequality among developed countries. It has the world's greatest per capita health expenditures yet the lowest life expectancy among comparable countries. It is also one of a few developed countries jostling for the dubious distinction of having the lowest measures of equality of opportunity.

The notion of the American Dream—that, unlike old Europe, we are a land of opportunity—is part of our essence. Yet the numbers say otherwise. The life prospects of a young American depend more on the income and education of his or her parents than in almost any other advanced country. When poor-boy-makes-good anecdotes get passed around in the media, that is precisely because such stories are so rare.

Things appear to be getting worse, partly as a result of forces, such as technology and globalization, that seem beyond our control, but most disturbingly because of those within our command. It is not the laws of nature that have led to this dire situation: it is the laws of humankind. Markets do not exist in a vacuum: they are shaped by rules and regulations, which can be designed to favor one group over another. President Donald Trump was right in saying that the system is rigged—by those in the inherited plutocracy of which he himself is a member. And he is making it much, much worse.

America has long outdone others in its level of inequality, but in the past 40 years it has reached new heights. Whereas the income share of the top 0.1 percent has more than quadrupled and that of the top 1 percent has almost doubled, that of the bottom 90 percent has declined. Wages at the bottom, adjusted for inflation, are about the same as they were some 60 years ago! In fact, for those with a high school education or less, incomes have fallen over recent decades. Males have been particularly hard hit, as the U.S. has moved away from manufacturing industries into an economy based on services.

Deaths of Despair

Wealth is even less equally distributed, with just three Americans having as much as the bottom 50 percent—testimony to how much money there is at the top and how little there is at the bottom. Families in the bottom 50 percent hardly have the cash reserves to meet an emergency. Newspapers are replete with stories of those for whom the breakdown of a car or an illness starts a downward spiral from which they never recover.

In significant part because of high inequality [see “The Health-Wealth Gap,” by Robert M. Sapolsky], U.S. life expectancy, exceptionally low to begin with, is experiencing sustained declines. This in spite of the marvels of medical science, many advances of which occur right here in America and which are made readily available to the rich. Economist Ann Case and 2015 Nobel laureate in economics Angus Deaton describe one of the main causes of rising morbidity—the increase in alcoholism, drug overdoses and suicides—as “deaths of despair” by those who have given up hope.

Credit: Jen Christiansen; Sources: “The Fading American Dream: Trends in Absolute Income Mobility Since 1940,” by Raj Chetty et al., in Science, Vol. 356; April 28, 2017 (child-parent wealth comparison); World Inequality database (90% versus 1% wealth trend data)

Defenders of America's inequality have a pat explanation. They refer to the workings of a competitive market, where the laws of supply and demand determine wages, prices and even interest rates—a mechanical system, much like that describing the physical universe. Those with scarce assets or skills are amply rewarded, they argue, because of the larger contributions they make to the economy. What they get merely represents what they have contributed. Often they take out less than they contributed, so what is left over for the rest is that much more.

This fictional narrative may at one time have assuaged the guilt of those at the top and persuaded everyone else to accept this sorry state of affairs. Perhaps the defining moment exposing the lie was the 2008 financial crisis, when the bankers who brought the global economy to the brink of ruin with predatory lending, market manipulation and various other antisocial practices walked away with millions of dollars in bonuses just as millions of Americans lost their jobs and homes and tens of millions more worldwide suffered on their account. Virtually none of these bankers were ever held to account for their misdeeds.

I became aware of the fantastical nature of this narrative as a schoolboy, when I thought of the wealth of the plantation owners, built on the backs of slaves. At the time of the Civil War, the market value of the slaves in the South was approximately half of the region's total wealth, including the value of the land and the physical capital—the factories and equipment. The wealth of at least this part of this nation was not based on industry, innovation and commerce but rather on exploitation. Today we have replaced this open exploitation with more insidious forms, which have intensified since the Reagan-Thatcher revolution of the 1980s. This exploitation, I will argue, is largely to blame for the escalating inequality in the U.S.

After the New Deal of the 1930s, American inequality went into decline. By the 1950s inequality had receded to such an extent that another Nobel laureate in economics, Simon Kuznets, formulated what came to be called Kuznets's law. In the early stages of development, as some parts of a country seize new opportunities, inequalities grow, he postulated; in the later stages, they shrink. The theory long fit the data—but then, around the early 1980s, the trend abruptly reversed.

Explaining Inequality

Economists have put forward a range of explanations for why inequality has in fact been increasing in many developed countries. Some argue that advances in technology have spurred the demand for skilled labor relative to unskilled labor, thereby depressing the wages of the latter. Yet that alone cannot explain why even skilled labor has done so poorly over the past two decades, why average wages have done so badly and why matters are so much worse in the U.S. than in other developed nations. Changes in technology are global and should affect all advanced economies in the same way. Other economists blame globalization itself, which has weakened the power of workers. Firms can and do move abroad unless demands for higher wages are curtailed. But again, globalization has been integral to all advanced economies. Why is its impact so much worse in the U.S.?

The shift from a manufacturing to a service-based economy is partly to blame. At its extreme—a firm of one person—the service economy is a winner-takes-all system. A movie star makes millions, for example, whereas most actors make a pittance. Overall, wages are likely to be far more widely dispersed in a service economy than in one based on manufacturing, so the transition contributes to greater inequality. This fact does not explain, however, why the average wage has not improved for decades. Moreover, the shift to the service sector is happening in most other advanced countries: Why are matters so much worse in the U.S.?

Again, because services are often provided locally, firms have more market power: the ability to raise prices above what would prevail in a competitive market. A small town in rural America may have only one authorized Toyota repair shop, which virtually every Toyota owner is forced to patronize. The providers of these local services can raise prices over costs, increasing their profits and the share of income going to owners and managers. This, too, increases inequality. But again, why is U.S. inequality practically unique?

In his celebrated 2013 treatise Capital in the Twenty-First Century, French economist Thomas Piketty shifts the gaze to capitalists. He suggests that the few who own much of a country's capital save so much that, given the stable and high return to capital (relative to the growth rate of the economy), their share of the national income has been increasing. His theory has, however, been questioned on many grounds. For instance, the savings rate of even the rich in the U.S. is so low, compared with the rich in other countries, that the increase in inequality should be lower here, not greater.

An alternative theory is far more consonant with the facts. Since the mid-1970s the rules of the economic game have been rewritten, both globally and nationally, in ways that advantage the rich and disadvantage the rest. And they have been rewritten further in this perverse direction in the U.S. than in other developed countries—even though the rules in the U.S. were already less favorable to workers. From this perspective, increasing inequality is a matter of choice: a consequence of our policies, laws and regulations.

In the U.S., the market power of large corporations, which was greater than in most other advanced countries to begin with, has increased even more than elsewhere. On the other hand, the market power of workers, which started out less than in most other advanced countries, has fallen further than elsewhere. This is not only because of the shift to a service-sector economy—it is because of the rigged rules of the game, rules set in a political system that is itself rigged through gerrymandering, voter suppression and the influence of money. A vicious spiral has formed: economic inequality translates into political inequality, which leads to rules that favor the wealthy, which in turn reinforces economic inequality.

Feedback Loop

Political scientists have documented the ways in which money influences politics in certain political systems, converting higher economic inequality into greater political inequality. Political inequality, in its turn, gives rise to more economic inequality as the rich use their political power to shape the rules of the game in ways that favor them—for instance, by softening antitrust laws and weakening unions. Using mathematical models, economists such as myself have shown that this two-way feedback loop between money and regulations leads to at least two stable points. If an economy starts out with lower inequality, the political system generates rules that sustain it, leading to one equilibrium situation. The American system is the other equilibrium—and will continue to be unless there is a democratic political awakening.

An account of how the rules have been shaped must begin with antitrust laws, first enacted 128 years ago in the U.S. to prevent the agglomeration of market power. Their enforcement has weakened—at a time when, if anything, the laws themselves should have been strengthened. Technological changes have concentrated market power in the hands of a few global players, in part because of so-called network effects: you are far more likely to join a particular social network or use a certain word processor if everyone you know is already using it. Once established, a firm such as Facebook or Microsoft is hard to dislodge. Moreover, fixed costs, such as that of developing a piece of software, have increased as compared with marginal costs—that of duplicating the software. A new entrant has to bear all these fixed costs up front, and if it does enter, the rich incumbent can respond by lowering prices drastically. The cost of making an additional e-book or photo-editing program is essentially zero.

In short, entry is hard and risky, which gives established firms with deep war chests enormous power to crush competitors and ultimately raise prices. Making matters worse, U.S. firms have been innovative not only in the products they make but in thinking of ways to extend and amplify their market power. The European Commission has imposed fines of billions of dollars on Microsoft and Google and ordered them to stop their anticompetitive practices (such as Google privileging its own comparison shopping service). In the U.S., we have done too little to control concentrations of market power, so it is not a surprise that it has increased in many sectors.

Credit: Jen Christiansen; Sources: Economic Report of the President. January 2017; World Inequality database

Rigged rules also explain why the impact of globalization may have been worse in the U.S. A concerted attack on unions has almost halved the fraction of unionized workers in the nation, to about 11 percent. (In Scandinavia, it is roughly 70 percent.) Weaker unions provide workers less protection against the efforts of firms to drive down wages or worsen working conditions. Moreover, U.S. investment treaties such as the North Atlantic Free Trade Agreement—treaties that were sold as a way of preventing foreign countries from discriminating against American firms—also protect investors against a tightening of environmental and health regulations abroad. For instance, they enable corporations to sue nations in private international arbitration panels for passing laws that protect citizens and the environment but threaten the multinational company's bottom line. Firms like these provisions, which enhance the credibility of a company's threat to move abroad if workers do not temper their demands. In short, these investment agreements weaken U.S. workers' bargaining power even further.

Liberated Finance

Many other changes to our norms, laws, rules and regulations have contributed to inequality. Weak corporate governance laws have allowed chief executives in the U.S. to compensate themselves 361 times more than the average worker, far more than in other developed countries. Financial liberalization—the stripping away of regulations designed to prevent the financial sector from imposing harms, such as the 2008 economic crisis, on the rest of society—has enabled the finance industry to grow in size and profitability and has increased its opportunities to exploit everyone else. Banks routinely indulge in practices that are legal but should not be, such as imposing usurious interest rates on borrowers or exorbitant fees on merchants for credit and debit cards and creating securities that are designed to fail. They also frequently do things that are illegal, including market manipulation and insider trading. In all of this, the financial sector has moved money away from ordinary Americans to rich bankers and the banks' shareholders. This redistribution of wealth is an important contributor to American inequality.

Other means of so-called rent extraction—the withdrawal of income from the national pie that is incommensurate with societal contribution—abound. For example, a legal provision enacted in 2003 prohibited the government from negotiating drug prices for Medicare—a gift of some $50 billion a year or more to the pharmaceutical industry. Special favors, such as extractive industries' obtaining public resources such as oil at below fair-market value or banks' getting funds from the Federal Reserve at near-zero interest rates (which they relend at high interest rates), also amount to rent extraction. Further exacerbating inequality is favorable tax treatment for the rich. In the U.S., those at the top pay a smaller fraction of their income in taxes than those who are much poorer—a form of largesse that the Trump administration has just worsened with the 2017 tax bill.

Some economists have argued that we can lessen inequality only by giving up on growth and efficiency. But recent research, such as work done by Jonathan Ostry and others at the International Monetary Fund, suggests that economies with greater equality perform better, with higher growth, better average standards of living and greater stability. Inequality in the extremes observed in the U.S. and in the manner generated there actually damages the economy. The exploitation of market power and the variety of other distortions I have described, for instance, makes markets less efficient, leading to underproduction of valuable goods such as basic research and overproduction of others, such as exploitative financial products.

Credit: Jen Christiansen; Sources: World Inequality Report 2018. World Inequality Lab, 2017; Branko Milanovic

Moreover, because the rich typically spend a smaller fraction of their income on consumption than the poor, total or “aggregate” demand in countries with higher inequality is weaker. Societies could make up for this gap by increasing government spending—on infrastructure, education and health, for instance, all of which are investments necessary for long-term growth. But the politics of unequal societies typically puts the burden on monetary policy: interest rates are lowered to stimulate spending. Artificially low interest rates, especially if coupled with inadequate financial market regulation, often give rise to bubbles, which is what happened with the 2008 housing crisis.

It is no surprise that, on average, people living in unequal societies have less equality of opportunity: those at the bottom never get the education that would enable them to live up to their potential. This fact, in turn, exacerbates inequality while wasting the country's most valuable resource: Americans themselves.

Restoring Justice

Morale is lower in unequal societies, especially when inequality is seen as unjust, and the feeling of being used or cheated leads to lower productivity. When those who run gambling casinos or bankers suffering from moral turpitude make a zillion times more than the scientists and inventors who brought us lasers, transistors and an understanding of DNA, it is clear that something is wrong. Then again, the children of the rich come to think of themselves as a class apart, entitled to their good fortune, and accordingly more likely to break the rules necessary for making society function. All of this contributes to a breakdown of trust, with its attendant impact on social cohesion and economic performance.

There is no magic bullet to remedy a problem as deep-rooted as America's inequality. Its origins are largely political, so it is hard to imagine meaningful change without a concerted effort to take money out of politics—through, for instance, campaign finance reform. Blocking the revolving doors by which regulators and other government officials come from and return to the same industries they regulate and work with is also essential.

Credit: Jen Christiansen; Sources: Raising America’s Pay: Why It’s Our Central Economic Policy Challenge, by Josh Bivens et al. Economic Policy Institute, June 4, 2014; The State of Working America, by Lawrence Mishel, Josh Bivens, Elise Gould and Heidi Shierholz. 12th Edition. ILR Press, 2012

Beyond that, we need more progressive taxation and high-quality federally funded public education, including affordable access to universities for all, no ruinous loans required. We need modern competition laws to deal with the problems posed by 21st-century market power and stronger enforcement of the laws we do have. We need labor laws that protect workers and their rights to unionize. We need corporate governance laws that curb exorbitant salaries bestowed on chief executives, and we need stronger financial regulations that will prevent banks from engaging in the exploitative practices that have become their hallmark. We need better enforcement of antidiscrimination laws: it is unconscionable that women and minorities get paid a mere fraction of what their white male counterparts receive. We also need more sensible inheritance laws that will reduce the intergenerational transmission of advantage and disadvantage.

The basic perquisites of a middle-class life, including a secure old age, are no longer attainable for most Americans. We need to guarantee access to health care. We need to strengthen and reform retirement programs, which have put an increasing burden of risk management on workers (who are expected to manage their portfolios to guard simultaneously against the risks of inflation and market collapse) and opened them up to exploitation by our financial sector (which sells them products designed to maximize bank fees rather than retirement security). Our mortgage system was our Achilles' heel, and we have not really fixed it. With such a large fraction of Americans living in cities, we have to have urban housing policies that ensure affordable housing for all.

It is a long agenda—but a doable one. When skeptics say it is nice but not affordable, I reply: We cannot afford to not do these things. We are already paying a high price for inequality, but it is just a down payment on what we will have to pay if we do not do something—and quickly. It is not just our economy that is at stake; we are risking our democracy.

As more of our citizens come to understand why the fruits of economic progress have been so unequally shared, there is a real danger that they will become open to a demagogue blaming the country's problems on others and making false promises of rectifying “a rigged system.” We are already experiencing a foretaste of what might happen. It could get much worse.

The men and women who serve as financial aides de camp to Silicon Valley’s billionaires are brimming with phone calls from curious clients.

“Hey, I was talking to my buddy about this. It sounds too good to be true. Can you help me understand?”

That’s how tax accountant Mike Bernier describes his conversations this fall around “Opportunity Zones” — the hot new thing in the land of the mega wealthy.

At private dinner parties and on the suddenly overflowing conference circuit, billionaires like Tom Steyer and the people who advise the rich are swapping notes, beating back viral rumors and trying to understand whether these tax write-offs are indeed too good to be true.

“It’s a lot of the high net worth individuals talking to each other,” said Bernier, who advises clients at Ernst and Young. “A lot of it comes from, ‘I heard this on the internet.’”

Behind it all is another Silicon Valley billionaire: Napster founder and early Facebook executive Sean Parker, who is using his celebrity and Rolodex to schmooze the wealthiest people in town. He’s been chatting up people like his longtime friend Peter Thiel, LinkedIn founder Reid Hoffman and venture capitalist John Doerr, pitching them on the idea in the way only a true peer can.

“I’ve had to do a lot of evangelism over the last couple of months,” Parker, who helped craft the new provision, told Recode in an interview. “It’s designed to have them do something with their capital that’s productive, rather than just sitting on a huge amount of Facebook stock or something.”

The ability to defer paying capital gains tax through 2026 after selling your company, for instance? Appetizing. The chance to not pay any capital gains tax on any money you make on top of that payday if it’s invested into an Opportunity Zone? The real cha-ching.

By spending the money in one of 8,700 Opportunity Zones — low-income census tracts ranging from nearby Oakland to the Aleutian Islands of Alaska and covering as much as 12 percent of the country — people can reap those extensive benefits thanks to the tax bill passed by Congress earlier this year.

And perhaps most alluring to image-conscious billionaires who want to be seen as modern-day Rockefellers or Carnegies: An anticipated gold mine of positive PR.

That’s much of what is driving America’s richest to invest, several wealth managers privately told Recode: Expect big boasts from Silicon Valley titans in 2019 about how their money is changing the world — and perhaps even some gumptious attempts to cast Opportunity Zone investments as “charity” — with little to no mention that this is simply money chasing more money.

“I hope there’s a lot of chest thumping,” said Michael Novogradac, a San Francisco accountant who hosted a conference on Opportunity Zones this month with more than 1,000 attendees. “If they thump their chest and get good PR, they will probably get others to look in the area. If it’s ‘marketing,’ that’s great.”

There is not much of a scandal here — the whole point of tax breaks is that it incentivizes selfish behavior that the government thinks is good for society.

Silicon Valley’s one-percenters have long flocked to tax loopholes to try and keep the IRS out of their lives. When you’re as rich as Mark Zuckerberg or Jeff Bezos, you have legions of highly paid lawyers and advisers who specialize in taking advantage of every subsection of the tax code to keep your billions your billions.

The rage in recent years has been the rise of Donor Advised Funds, limitless pools of cash that earn a tax break since they are earmarked for philanthropy but have drawn criticism because there is little accountability to ensure the money is actually spent.

That’s old news. This is the new toy — “impact investing on steroids.”

“I would say it’s very clearly not technically charity. But the charitable impulse is something we hear about a lot,” said John Lettieri, who is now flooded with calls from Silicon Valley’s wealthiest as the chief lobbyist who pushed for the inclusion of Opportunity Zones in the tax bill. “They view this as an alternative to traditional forms of philanthropy.”

Silicon Valley’s billionaires also all talk with one another, and Parker today remains their main point of contact. He said he’s been bringing Opportunity Zones up in virtually every meeting, feeling out people like Ben Horowitz of Andreessen Horowitz, who Parker described as “very much up to speed” and studying ways to invest in them.

One other billionaire described as interested: Tom Steyer, the San Francisco-based Democratic mega donor and climate change activist, is said to be very curious about how he can invest in the zones, according to one person in touch with his camp.

Wealth managers in Silicon Valley say what had once been a trickle of calls about Opportunity Zones from billionaires has turned into a stream of several a week. Yet there are early rumbles of a backlash to the new investing gambit, with multiple wealth managers telling Recode they worry that their clients are being overly influenced by aggressive accountants and billionaire friends to invest in communities where they might not actually make any money.

For instance, if a startup CEO sells her company and puts her new $100 million fortune — a capital gain — into an Opportunity Zone fund that invests in real estate in Oakland, she would be able to defer the capital gains tax, yes. But what if that real estate bet goes belly-up and she loses all of her money? Then it wasn’t smart to invest the $100 million into an Opportunity Zone, even if the math was slightly more friendly with the tax break.

Plus, a more important question: Is it even good for Oakland?

Steve Rosenthal, an expert at the Tax Policy Center, doesn’t think so. He imagines that some investors will make small tweaks to already-in-progress development plans and not actually revitalize any communities.

“I expect that billionaires will do very well for themselves,” he said. But he’d rather see the government just spend money to alleviate poverty rather than “take a wild gamble on the public’s money.”

That’s the worst-case scenario — a rich person getting richer thanks to American taxpayers, but without changing his behavior. Here’s the best-case scenario: A client of Bernier is in the grocery store business and has looked in the past at investing in one particular part of the country that has very few supermarkets. But the numbers never made sense from the grocer’s point of view, and he instead prioritized stores in more posh areas.

Now that there’s a tax break on the table? The numbers work. He’s planning on doing it.

The federal government as soon as this month is expected to clarify some more specifics that observers predict will truly trigger a commotion in the world of high finance. That’s when to expect a new round of phone calls (and probably a first round of press releases).

But in a sign of how much energy there is behind these, some investors aren’t even waiting for all the rules to be nailed down before hatching plans — including venture capitalists.

Venture capitalists are studying these investment zones carefully and considering raising funds to invest directly into these areas, but there’s a holdup: Getting the full tax benefit requires holding onto an investment for 10 years, which doesn’t always happen. What if their portfolio company is sold, for instance?

That’s expected to be answered in the next few weeks.

It hasn’t stopped Peter Brack, who is one of the few venture capitalists who is actively planning an Opportunity Zone fund already through his new organization, Hypothesis Ventures.

Brack, like other venture capitalists, is in this to make money. His reasoning syncs with a growing desire in investing to find cheaper deals outside of Silicon Valley. It’s a business decision.

But there’s something of a bargain that seems to have been struck among investors, philanthropists and governments: Yeah, maybe some of the deals will go awry. And maybe this is a tax loophole that is being exploited. And maybe some of the new cash is, in effect, buying a press release.

“If I were a community organizer or a city manager or a mayor or even a governor,” he said, “I’m not going to really worry about the intent behind those dollars — as long as they’re pointed at my community.”

For the 50 million individuals worldwide ailing from Alzheimer’s disease, the announcements by pharmaceutical giants earlier this year that they will end research on therapeutics were devastating. The news is even more devastating considering projections that 100 million more people will be diagnosed with Alzheimer’s disease across the globe by 2050, all potentially without a medical means to better their quality of life.

As it happens, though, the pursuit of a therapeutic has been given a lifeline. New research shows that physical exercise can “clean up” the hostile environments in the brains of Alzheimer’s mice, allowing new nerve cells in the hippocampus, the brain structure involved in memory and learning, to enable cognitive improvements, such as learning and memory. These findings imply that pharmacological agents that enrich the hippocampal environment to boost cell growth and survival might be effective to recuperate brain health and function in human Alzheimer’s disease patients.

The brain of an individual with Alzheimer’s disease is a harsh place filled with buildups of harmful nerve cell junk—amyloid plaques and neurofibrillary tangles—and dramatic loss of nerve cells and connections that occur with severe cognitive decline, such as memory loss. Targeting and disrupting this harmful junk, specifically amyloid plaques, to restore brain function has been the basis of many failed clinical trials. This futility has led to a re-evaluation of the amyloid hypothesis—the central dogma for Alzheimer’s disease pathology based on the toxic accumulation of amyloid plaques.

At the same time, there have been traces of evidence for exercise playing a preventative role in Alzheimer’s disease, but exactly how this occurs and how to take advantage of it therapeutically has remained elusive. Exercise has been shown to create biochemical changes that fertilize the brain’s environment to mend nerve cell health. Additionally, exercise induces restorative changes relevant to Alzheimer’s disease pathology with improved nerve cell growth and connectivity in the hippocampus, a process called adult hippocampal neurogenesis. For these reasons, the authors Choi et al. explored whether exercise-induced effects and hippocampal nerve cell growth could be utilized for therapeutic purposes in Alzheimer’s disease to restore brain function.

                                                                                                                                 

The researchers found that exercised animals from a mouse model of Alzheimer’s had greatly enhanced memory compared to sedentary ones due to improved adult hippocampal neurogenesis and a rise in amounts of a specific molecule that promotes brain cell growth called BDNF.  Importantly, they could recover brain function, specifically memory, in mice with Alzheimer’s disease but without exercise by increasing hippocampal cell growth and BDNF levels using a combination of genetic—injecting a virus—and pharmacological means. On the other hand, blocking hippocampal neurogenesis early in Alzheimer’s worsened nerve cell health later in stages, leading to degeneration of the hippocampus and, subsequently, memory function. This provides preclinical proof of concept that a combination of drugs that increase adult hippocampal neurogenesis and BDNF levels could be disease-modifying or prevent Alzheimer’s disease altogether.

With this work, things don’t look promising for the amyloid hypothesis—that Alzheimer’s disease is caused by the deposition of amyloid plaques. In this study, it was shown that eliminating amyloid plaques were not to necessary to ameliorate memory defects, which is consistent with evidence that plaques can also be found in the brains of healthy individuals. On the contrary, we may be looking at a new and improved fundamental theory for Alzheimer’s disease based on promoting a healthier brain environment and adult hippocampal neurogenesis.

However, this inspiring news should be taken with an important caution—mouse models of Alzheimer’s are notorious for failing to translate into humans such that treatments that have worked to remedy mice have failed for humans. Besides, even if these findings translate into humans, it may apply to a fraction of Alzheimer’s individuals with relevant genetic components to the mouse model utilized. Future studies will need to replicate these results in mouse models emulating the range of known Alzheimer’s disease genetic milieus and, more importantly, prove its medical relevance to human disease.

Before translating these findings into human patients, there remains significant research to establish that a medication or drug could mimic the effects of exercise—exercise mimetics—by “cleaning up” the brain with BDNF and stimulating neurogenesis to combat Alzheimer’s disease. Currently, the method for administering BDNF to animals in the lab—by direct injection into the brain—is not ideal for use in people, and a hippocampal neurogenesis stimulating compound remains elusive.

Future attempts to generate pharmacological means to imitate and heighten the benefits of exercise—exercise mimetics—to increase adult hippocampal neurogenesis in addition to BDNF may someday provide an effective means of improving cognition in people with Alzheimer’s disease. Moreover, increasing neurogenesis in the earliest stages of the disease may protect against neuronal cell death later in the disease, providing a potentially powerful disease-modifying treatment strategy.

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