Humans are social and generally want to be part of the crowd. Studies of social conformity suggest that the group’s view may shape how we perceive a situation. Those individuals who remain independent show activity in a part of the brain associated with fear. ... We are natural pattern seekers and see them even where none exist. Our brains are keen to make causal inferences, which can lead to faulty conclusions. ... Standard economic theory assumes that one discount rate allows us to translate value in the future to value in the present, and vice versa. Yet humans often use a high discount rate in the short term and a low one in the long term. This may be because different parts of the brain mediate short- and long-term decisions. ... We suffer losses more than we enjoy gains of comparable size. But the magnitude of loss aversion varies across the population and even for each individual based on recent experience. As a result, we sometimes forgo attractive opportunities because the fear of loss looms too large.

This memo is my attempt to send the markets to the psychiatrist’s couch, and an exploration of what might be learned there. ... One of the most notable behavioral traits among investors is their tendency to overlook negatives or understate their significance for a while, and then eventually to capitulate and overreact to them on the downside. ... “Everyone knew” for years that the Chinese economy had been overstimulated with cheap financing, and that this had led to excessive investment in fixed assets. … One of the most significant factors keeping investors from reaching appropriate conclusions is their tendency to assess the world with emotionalism rather than objectivity. Their failings take two primary forms: selective perception and skewed interpretation. ... The bottom line is that investor psychology rarely gives equal weight to both favorable and unfavorable developments. Likewise, investors’ interpretation of events is usually biased by their emotional reaction to whatever is going on at the moment. ... in the real world, things generally fluctuate between “pretty good” and “not so hot.” But in the world of investing, perception often swings from “flawless” to “hopeless.” ... There is a general sense among my colleagues that investors have gone from evaluating securities based on the attractiveness of their yield (with company fundamentals viewed optimistically) to judging them on the basis of the likely recovery in a restructuring (with fundamentals viewed pessimistically).

All of her reactions, and her answers to the questions Motte asked as Megan used the site, went into a growing database. Expedia, the parent company of more than a dozen travel-oriented brands in addition to Expedia.com, is obsessed with figuring out how to make booking travel online more intuitive, more efficient, and more enjoyable. That means, among other things, understanding the psychodrama of trip planning: the shifting desires and paralyzing wealth of choices, the unsettling gyrations in room rates and ticket prices, the competing demands of family members and budgets and schedules, the need to balance the thirst for adventure against the fear of Zika virus in Latin America or Islamic State in Europe. ... The goal of Expedia’s usability researchers is not only to make Expedia’s various sites and mobile apps more efficient but also to make them an extension of the vacation fantasies that are always running in the back of our heads. ... What distinguishes Expedia is its dedication to understanding the psyche of the modern travel planner. That may be most apparent in the Usability Lab, but much of it happens on the sites themselves, as the company relentlessly tests new ideas about look and feel and function. ... each of Expedia’s brands has its own technology and marketing teams, and they’re encouraged to set their own course. They all benefit from the massive inventory of hotel rooms and plane tickets and the financial resources and technological firepower of the parent company. ... Two-thirds of the A/B tests Expedia runs show no effect or a negative effect, and most of the successful ones are only marginally so.

Defaults are the settings that come out of the box, the selections you make on your computer by hitting enter, the assumptions that people make unless you object, the options easily available to you because you haven’t changed them. ... They might not seem like much, but defaults (and their designers) hold immense power – they make decisions for us that we’re not even aware of making. Consider the fact that most people never change the factory settings on their computer, the default ringtone on their phones, or the default temperature in their fridge. Someone, somewhere, decided what those defaults should be – and it probably wasn’t you. ... What if I told you there was one simple change you could make in a school cafeteria to get children to eat more salad? It doesn’t cost anything, force anyone to eat anything they don’t want, and it takes only a few minutes to fix. And it happened in real life: a middle school in New York moved their salad bar away from its default location against a wall and put it smack in the middle of the room (and prominently in front of the two cash registers, as seen in the diagram below). Salad sales more than tripled.

Harris is the closest thing Silicon Valley has to a conscience. As the co‑founder of Time Well Spent, an advocacy group, he is trying to bring moral integrity to software design: essentially, to persuade the tech world to help us disengage more easily from its devices. ... While some blame our collective tech addiction on personal failings, like weak willpower, Harris points a finger at the software itself. That itch to glance at our phone is a natural reaction to apps and websites engineered to get us scrolling as frequently as possible. The attention economy, which showers profits on companies that seize our focus, has kicked off what Harris calls a “race to the bottom of the brain stem.” ... we’ve lost control of our relationship with technology because technology has become better at controlling us. ... He studied computer science at Stanford while interning at Apple, then embarked on a master’s degree at Stanford, where he joined the Persuasive Technology Lab. Run by the experimental psychologist B. J. Fogg, the lab has earned a cultlike following among entrepreneurs hoping to master Fogg’s principles of “behavior design”—a euphemism for what sometimes amounts to building software that nudges us toward the habits a company seeks to instill. ... Sites foster a sort of distracted lingering partly by lumping multiple services together.

In 1997, during his final year as a doctoral student, Fogg spoke at a conference in Atlanta on the topic of how computers might be used to influence the behaviour of their users. He noted that “interactive technologies” were no longer just tools for work, but had become part of people’s everyday lives: used to manage finances, study and stay healthy. Yet technologists were still focused on the machines they were making rather than on the humans using those machines. ... Fogg called for a new field, sitting at the intersection of computer science and psychology, and proposed a name for it: “captology” (Computers as Persuasive Technologies). Captology later became behaviour design, which is now embedded into the invisible operating system of our everyday lives. The emails that induce you to buy right away, the apps and games that rivet your attention, the online forms that nudge you towards one decision over another: all are designed to hack the human brain and capitalise on its instincts, quirks and flaws. The techniques they use are often crude and blatantly manipulative, but they are getting steadily more refined, and, as they do so, less noticeable. ... The human brain releases pleasurable, habit-forming chemicals in response to social interactions, even to mere simulacra of them, and the hottest triggers are other people: you and your friends or followers are constantly prompting each other to use the service for longer. ... the internet’s potential to inform and enlighten was at loggerheads with the commercial imperative to seize and hold the attention of users by any means possible.

When I returned to addiction, it was as a scientist studying the addicted brain. The data were indisputable: brains change with addiction. I wanted to understand how – and why. I wanted to understand addiction with fastidious objectivity, but I didn’t want to lose touch with its subjectivity – how it feels, how hard it is – in the process. ... One explanation is that addiction is a brain disease. The United States National Institute on Drug Abuse, the American Society of Addiction Medicine, and the American Medical Association ubiquitously define addiction as a ‘chronic disease of brain reward, motivation, memory and related circuitry’ ... If only the disease model worked. Yet, more and more, we find that it doesn’t. First of all, brain change alone isn’t evidence for brain disease. Brains are designed to change. ... we now know that drugs don’t cause addiction. ... One idea is that addicts voluntarily choose to remain addicted: if they don’t quit, it’s because they don’t want to. ... The view that addiction arises through learning, in the context of environmental forces, appears to be gathering momentum.

Consider the number of networked cameras that capture data about you as you go about your day. Surveillance cameras are mounted in offices, stores, public transportation; on city streets, ATM machines, and car dashboards. You or your neighbors may have installed cameras to watch over your front door; you may have a webcam watching over your valuables—perhaps even your children. Security cameras are virtually everywhere, installed both to provide a record if a crime is committed and to deter people from committing a crime in the first place. Based on an exhaustive survey of the number of such cameras in one English county in 2011, it was estimated there were 2 million surveillance cameras in the United Kingdom alone—about one camera for every thirty people. ... Generalizing this to the rest of the world, there are about 100 million cameras watching public spaces, all day and all night. Yet, this is only one-tenth of the 1 billion cameras on smartphones. Within the next few years, there will be one networked camera for every single person on the planet. ... If technology continues to follow Moore’s Law, doubling the computing power available at the same price every 18 months, we will very likely be sharing the world with roughly 1 trillion sensors by 2020, in line with projections from Bosch, HP, IBM, and others. ... If everything is recorded, will it encourage "better" behavior? And how will the lack of any recording be interpreted?

Maps are for humans, but how do animals, which began navigating millions of years before parchment was invented, manage to find their way around? Do animal (and human) brains contain a map, and if so does it have islands and capes, North Poles and Equators, reference lines and so on? And if they do, where is it, and how does it work? How could a jelly-like blob of protoplasm contain anything as structured as a map? ... These questions have intrigued biologists for many decades, particularly because animals can perform astonishing feats such as navigating their way from the North Pole to the South and back again, like the Arctic tern; or returning home after being transported hundreds of miles away, like the homing pigeon. How animals (both human and non-human) work out their location is just beginning to be understood by brain scientists. There are maps in the brain, as it happens. The properties of these maps, which neuroscientists call ‘cognitive maps’, have turned out to be highly intriguing, and are helping us to understand not just how animals navigate, but also more general principles about how the brain forms, stores and retrieves knowledge.

Decision fatigue helps explain why ordinarily sensible people get angry at colleagues and families, splurge on clothes, buy junk food at the supermarket and can’t resist the dealer’s offer to rustproof their new car. No matter how rational and high-minded you try to be, you can’t make decision after decision without paying a biological price. It’s different from ordinary physical fatigue — you’re not consciously aware of being tired — but you’re low on mental energy. The more choices you make throughout the day, the harder each one becomes for your brain, and eventually it looks for shortcuts, usually in either of two very different ways. One shortcut is to become reckless: to act impulsively instead of expending the energy to first think through the consequences. (Sure, tweet that photo! What could go wrong?) The other shortcut is the ultimate energy saver: do nothing. Instead of agonizing over decisions, avoid any choice. Ducking a decision often creates bigger problems in the long run, but for the moment, it eases the mental strain. You start to resist any change, any potentially risky move ... experiments confirmed the 19th-century notion of willpower being like a muscle that was fatigued with use, a force that could be conserved by avoiding temptation. ... Any decision, whether it’s what pants to buy or whether to start a war, can be broken down into what psychologists call the Rubicon model of action phases, in honor of the river that separated Italy from the Roman province of Gaul.

In his new book, Adaptive Markets: Financial Evolution at the Speed of Thought, M.I.T. finance professor Andrew Lo attempts to account for the messier, more feeling realities of human behavior. A key premise is that markets evolve, like species, but much faster: “evolution at the speed of thought.” And that this evolution happens in fits and starts, in response to changes in the environment—hence, what he calls the “adaptive” markets hypothesis. It’s during these times of change that human emotions play their biggest role. Lo believes we are in one of those times now and, in his book, he applies biology, psychology, neuroscience, and history toward the goal of improving on the efficient markets hypothesis—which, Lo says, is not only flawed but is becoming increasingly so as the financial environment continues to change. ... The efficient markets hypothesis is a special case of adaptive markets. Markets are efficient if the environment is stable and investors interact with each other and natural selection operates over a long period of time.

Whatever the truth of actual brainwashing incidents, the battle for people’s minds loomed large in the late 1950s, and was the subject of serious Pentagon discussions. The US and the Soviet Union were engaged in an ideological – and psychological – battle. Eager to exploit the science of human behaviour as it had physics and chemistry, the Pentagon commissioned a high-level panel at the Smithsonian Institution to recommend the best course of action. ... Psychology during the Cold War had fast become a darling of the military. ... That recommendation was translated by Pentagon officials into two separate assignments handed down to ARPA: one in the behavioural sciences, which would include everything from the psychology of brainwashing to quantitative modelling of society, and a second in command-and-control, to focus on computers. ... Licklider envisioned the modern conception of interactive computing: a future where people worked on personal consoles at their desks, rather than having to walk into a large room and feed punch cards into machines to crunch numbers. ... Licklider wanted people to understand that, more than any specific application, what he was describing was an entire metamorphosis of man and machine interaction. Personal consoles, time-sharing, and networking – the article essentially spelled out all the underpinnings of the modern internet.

Legions of robots now carry out our instructions unreflectively. How do we ensure that these creatures, regardless of whether they’re built from clay or silicon, always work in our best interests? Should we teach them to think for themselves? And if so, how are we to teach them right from wrong? ... In 2017, this is an urgent question. Self-driving cars have clocked up millions of miles on our roads while making autonomous decisions that might affect the safety of other human road-users. Roboticists in Japan, Europe and the United States are developing service robots to provide care for the elderly and disabled. One such robot carer, which was launched in 2015 and dubbed Robear (it sports the face of a polar-bear cub), is strong enough to lift frail patients from their beds; if it can do that, it can also, conceivably, crush them. Since 2000 the US Army has deployed thousands of robots equipped with machineguns, each one able to locate targets and aim at them without the need for human involvement (they are not, however, permitted to pull the trigger unsupervised).

Lying, it turns out, is something that most of us are very adept at. We lie with ease, in ways big and small, to strangers, co-workers, friends, and loved ones. Our capacity for dishonesty is as fundamental to us as our need to trust others, which ironically makes us terrible at detecting lies. Being deceitful is woven into our very fabric, so much so that it would be truthful to say that to lie is human. ... The ubiquity of lying was first documented systematically by Bella DePaulo, a social psychologist at the University of California, Santa Barbara. Two decades ago DePaulo and her colleagues asked 147 adults to jot down for a week every instance they tried to mislead someone. The researchers found that the subjects lied on average one or two times a day. Most of these untruths were innocuous, intended to hide one’s inadequacies or to protect the feelings of others. Some lies were excuses—one subject blamed the failure to take out the garbage on not knowing where it needed to go. Yet other lies—such as a claim of being a diplomat’s son—were aimed at presenting a false image. ... That human beings should universally possess a talent for deceiving one another shouldn’t surprise us. Researchers speculate that lying as a behavior arose not long after the emergence of language. The ability to manipulate others without using physical force likely conferred an advantage in the competition for resources and mates, akin to the evolution of deceptive strategies in the animal kingdom, such as camouflage.

At root, this national obsession was mostly the work of a very eccentric politician: John Vasconcellos. Vasconcellos, who died in 2014, was a California state legislator for 38 years. In his obituary, the San Jose Mercury News described him as a “famously rumpled bear-of-a-man” who was “colorful, witty, brilliant, angry, intellectual and elegantly foul of mouth.” Most of all, though, he was a nonconformist — during one three-year stretch, he decided to just let his hair grow and grow and grow — and his nonconformity frequently took on a decidedly Californian hue. Vasconcellos was an idealist who was convinced that humans had untold, untapped greatness, but it was an idealism driven in part by a bevy of personal demons and a long-running battle to control his anger problems. He was quite public about his varied attempts at self-improvement, which ranged from obscure forms of therapy to the teachings of the New Age Esalen Institute in Big Sur. ... Somewhere along the way, Vasconcellos discovered what was by then a good-size body of psychological research on self-esteem. It showed that people with high versus low self-esteem reacted in different ways to various challenges and instances of adversity ... This was a career-defining find for Vasconcellos. The logic was simple: If low self-esteem is tied to so many maladaptive responses, to so many forms of underachievement and bad behavior, then surely raising kids’ (and other’s) self-esteem could bring with it untold benefits. Soon, Vasconcellos was lobbying Sacramento to launch a statewide self-esteem commission to study the public-policy implications of self-esteem. ... little published evidence supporting Vasconcellos’s ideas. In some areas, high self-esteem actually correlated with worse behavior — some criminals, it turns out, actually view themselves quite favorably.

Suppose you wanted to build the perfect dog from scratch. What would be the key ingredients in the recipe? Loyalty and smarts would be musts. Cuteness would be as well, perhaps with gentle eyes, and a curly, bushy tail that wags in joy in anticipation of your appearance. ... You needn’t bother trying. Lyudmila Trut and Dmitri Belyaev have already built it for you. The perfect dog. Except it’s not a dog, it’s a fox. A domesticated one. They built it quickly—mind-bogglingly fast for constructing a brand new biological creature. It took them less than 60 years, a blink of an eye compared to the time it took for wolves to become dogs. They built it in the often unbearable negative 40 degrees Fahrenheit cold of Siberia, where Lyudmila and, before her, Dmitri, have been running one of the longest, most incredible experiments on behavior and evolution ever devised. ... Except for house pets, most domesticated animals do not form close relationships with humans, and by far the most intense affection and loyalty forms between owners and dogs. What made the difference? Had that deep human-animal bond developed over a long time? Or might this affinity for people be a change that could emerge quickly, as with so many other changes Lyudmila and Belyaev had seen in the foxes already? Would living with a human come naturally to a fox that had been bred for tameness?

In an investing and economic world in which almost everything seems to have changed in the last 20 years, one thing has remained constant: human nature. And, we can more or less prove it. At least in the case of the stock market. ... Our model does not attempt to justify the P/E levels as logical or deserved, nor does it attempt to predict future prices. It just shows what has tended to be the market’s typical response over the years to major market factors. By far, the two most important of these are pro t margins, the higher the better, and inflation, where stable and lower is better, except not too low. ... A third behavioral factor, which we first modeled 16 years ago and still has explanatory power, although much less than the first two, is the volatility of GDP growth. Notice that this is absolutely not the growth rate of GDP. ... we added two new factors, which we believe provide a little further value. The first addition was an on-off switch, which causes P/Es to be a bit lower after a down quarter. Again, not a very scientific reflex in a mean-reverting world, but understandable. The second was to add the US 10-year bond rate, where higher rates are negative, modestly improving the model even after the inflation component had done the heavy lifting for nominal interest rates. ... The market, however, appears not to care at all about the past or to learn much from it. This model for sure seems to say that for 92 years, at least, the market has with remarkable consistency been a coincident indicator of superficially appealing variables that in a strict economic sense have been inappropriate, and that have caused spectacular and unnecessary market volatility. The model is apparently a reflection of human nature and, of all factors influencing the market, human nature, as economically inefficient and unsophisticated it may be, seems the least likely to change.