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Instead of trying to identify bits from space, he would instead teach himself to recognize the terrestrial source of all the samples he collected.

something that anybody can do. It could and should become part of teachings in schools, an aspect of citizen science.

The key is knowing what to look for.

the really painful message our daughter will receive is that we're embarrassing. For most people who aren't New Atheists, or old atheists, and have no passion invested in the subject, either negative or positive, believers aren't weird because we're wicked. We're weird because we're inexplicable; because, when there's no necessity for it that anyone sensible can see, we've committed ourselves to a set of awkward and absurd attitudes that obtrude, that stick out against the background of modern life, and not in some important or respectworthy or principled way, either.

Believers are people who try to insert Jee-zus into conversations at parties; who put themselves down, with writhings of unease, for perfectly normal human behaviour; who are constantly trying to create a solemn hush that invites a fart, a hiccup, a bit of subversion. Believers are people who, on the rare occasions when you have to listen to them, like at a funeral or a wedding, seize the opportunity to pour the liquidised content of a primary-school nativity play into your earhole, apparently not noticing that childhood is over.

What goes on inside believers is mysterious. So far as it can be guessed at it appears to be a kind of anxious pretending, a kind of continual, nervous resistance to reality.

to me, it's belief that involves the most uncompromising attention to the nature of things of which you are capable. Belief demands that you dispense with illusion after illusion, while contemporary common sense requires continual, fluffy pretending – pretending that might as well be systematic, it's so thoroughly incentivised by our culture.

The atheist bus says: "There's probably no God. So stop worrying and enjoy your life."

the word that offends against realism here is "enjoy". I'm sorry – enjoy your life?

If you based your knowledge of the human species exclusively on adverts, you'd think that the normal condition of humanity was to be a good-looking single person between 20 and 35, with excellent muscle-definition and/or an excellent figure, and a large disposable income. And you'd think the same thing if you got your information exclusively from the atheist bus

The implication of the bus slogan is that enjoyment would be your natural state if you weren't being "worried" by us believers and our hellfire preaching. Take away the malignant threat of God-talk, and you would revert to continuous pleasure

What's so wrong with this, apart from it being total bollocks? Well, in the first place, that it buys a bill of goods, sight unseen, from modern marketing. Given that human life isn't and can't be made up of enjoyment, it is in effect accepting a picture of human life in which those pieces of living where easy enjoyment is more likely become the only pieces that are visible.

But then, like every human being, I am not in the habit of entertaining only those emotions I can prove. I'd be an unrecognisable oddity if I did. Emotions can certainly be misleading: they can fool you into believing stuff that is definitely, demonstrably untrue. Yet emotions are also our indispensable tool for navigating, for feeling our way through, the much larger domain of stuff that isn't susceptible to proof or disproof, that isn't checkable against the physical universe. We dream, hope, wonder, sorrow, rage, grieve, delight, surmise, joke, detest; we form such unprovable conjectures as novels or clarinet concertos; we imagine. And religion is just a part of that, in one sense. It's just one form of imagining, absolutely functional, absolutely human-normal. It would seem perverse, on the face of it, to propose that this one particular manifestation of imagining should be treated as outrageous, should be excised if (which is doubtful) we can manage it.

suppose, as the atheist bus goes by, you are povertystricken, or desperate for a job, or a drug addict, or social services have just taken away your child. The bus tells you that there's probably no God so you should stop worrying and enjoy your life, and now the slogan is not just bitterly inappropriate in mood. What it means, if it's true, is that anyone who isn't enjoying themselves is entirely on their own. What the bus says is: there's no help coming.

Enjoyment is great. The more enjoyment the better. But enjoyment is one emotion. To say that life is to be enjoyed (just enjoyed) is like saying that mountains should only have summits, or that all colours should be purple, or that all plays should be by Shakespeare. This really is a bizarre category error.

A consolation you could believe in would be one that wasn't in danger of popping like a soap bubble on contact with the ordinary truths about us. A consolation you could trust would be one that acknowledged the difficult stuff rather than being in flight from it, and then found you grounds for hope in spite of it, or even because of it

The novelist Richard Powers has written that the Clarinet Concerto sounds the way mercy would sound, and that's exactly how I experienced it in 1997. Mercy, though, is one of those words that now requires definition. It does not only mean some tyrant's capacity to suspend a punishment he has himself inflicted. It can mean – and does mean in this case – getting something kind instead of the sensible consequences of an action, or as well as the sensible consequences of an action.

from outside, belief looks like a series of ideas about the nature of the universe for which a truth-claim is being made, a set of propositions that you sign up to; and when actual believers don't talk about their belief in this way, it looks like slipperiness, like a maddening evasion of the issue.

I am a fairly orthodox Christian. Every Sunday I say and do my best to mean the whole of the Creed, which is a series of propositions. But it is still a mistake to suppose that it is assent to the propositions that makes you a believer. It is the feelings that are primary. I assent to the ideas because I have the feelings; I don't have the feelings because I've assented to the ideas.

what I felt listening to Mozart in 1997 is not some wishy-washy metaphor for an idea I believe in, and it's not a front behind which the real business of belief is going on: it's the thing itself. My belief is made of, built up from, sustained by, emotions like that. That's what makes it real.

I think that Mozart, two centuries earlier, had succeeded in creating a beautiful and accurate report of an aspect of reality. I think that the reason reality is that way – that it is in some ultimate sense merciful as well as being a set of physical processes all running along on their own without hope of appeal, all the way up from quantum mechanics to the relative velocity of galaxies by way of "blundering, low and horridly cruel" biology (Darwin) – is that the universe is sustained by a continual and infinitely patient act of love. I think that love keeps it in being.

That's what I think. But it's all secondary. It all comes limping along behind my emotional assurance that there was mercy, and I felt it. And so the argument about whether the ideas are true or not, which is the argument that people mostly expect to have about religion, is also secondary for me.

No, I can't prove it. I don't know that any of it is true. I don't know if there's a God. (And neither do you, and neither does Professor Dawkins, and neither does anybody. It isn't the kind of thing you can know. It isn't a knowable item.)

let's be clear about the emotional logic of the bus's message. It amounts to a denial of hope or consolation on any but the most chirpy, squeaky, bubble-gummy reading of the human situation

It's got itself established in our culture, relatively recently, that the emotions involved in religious belief must be different from the ones involved in all the other kinds of continuous imagining, hoping, dreaming, and so on, that humans do. These emotions must be alien, freakish, sad, embarrassing, humiliating, immature, pathetic. These emotions must be quite separate from commonsensical us. But they aren't

The emotions that sustain religious belief are all, in fact, deeply ordinary and deeply recognisable to anybody who has ever made their way across the common ground of human experience as an adult.

It's just that the emotions in question are rarely talked about apart from their rationalisation into ideas. This is what I have tried to do in my new book, Unapologetic.

You can easily look up what Christians believe in. You can read any number of defences of Christian ideas. This, however, is a defence of Christian emotions – of their intelligibility, of their grown-up dignity.

Code is too hard to think about. Before trying to understand the attempts themselves, then, it’s worth understanding why this might be: what it is about code that makes it so foreign to the mind, and so unlike anything that came before it.

Technological progress used to change the way the world looked—you could watch the roads getting paved; you could see the skylines rise. Today you can hardly tell when something is remade, because so often it is remade by code.

Software has enabled us to make the most intricate machines that have ever existed. And yet we have hardly noticed, because all of that complexity is packed into tiny silicon chips as millions and millions of lines of cod

The programmer, the renowned Dutch computer scientist Edsger Dijkstra wrote in 1988, “has to be able to think in terms of conceptual hierarchies that are much deeper than a single mind ever needed to face before.” Dijkstra meant this as a warning.

As programmers eagerly poured software into critical systems, they became, more and more, the linchpins of the built world—and Dijkstra thought they had perhaps overestimated themselves.

What made programming so difficult was that it required you to think like a computer.

“The problem is that software engineers don’t understand the problem they’re trying to solve, and don’t care to,” says Leveson, the MIT software-safety expert. The reason is that they’re too wrapped up in getting their code to work.

Though he runs a lab that studies the future of computing, he seems less interested in technology per se than in the minds of the people who use it. Like any good toolmaker, he has a way of looking at the world that is equal parts technical and humane. He graduated top of his class at the California Institute of Technology for electrical engineering,

“The serious problems that have happened with software have to do with requirements, not coding errors.” When you’re writing code that controls a car’s throttle, for instance, what’s important is the rules about when and how and by how much to open it. But these systems have become so complicated that hardly anyone can keep them straight in their head. “There’s 100 million lines of code in cars now,” Leveson says. “You just cannot anticipate all these things.”

a nearly decade-long investigation into claims of so-called unintended acceleration in Toyota cars. Toyota blamed the incidents on poorly designed floor mats, “sticky” pedals, and driver error, but outsiders suspected that faulty software might be responsible

software experts spend 18 months with the Toyota code, picking up where NASA left off. Barr described what they found as “spaghetti code,” programmer lingo for software that has become a tangled mess. Code turns to spaghetti when it accretes over many years, with feature after feature piling on top of, and being woven around

Using the same model as the Camry involved in the accident, Barr’s team demonstrated that there were actually more than 10 million ways for the onboard computer to cause unintended acceleration. They showed that as little as a single bit flip—a one in the computer’s memory becoming a zero or vice versa—could make a car run out of control. The fail-safe code that Toyota had put in place wasn’t enough to stop it

. In all, Toyota recalled more than 9 million cars, and paid nearly $3 billion in settlements and fines related to unintended acceleration.

The problem is that programmers are having a hard time keeping up with their own creations. Since the 1980s, the way programmers work and the tools they use have changed remarkably little.

“Visual Studio is one of the single largest pieces of software in the world,” he said. “It’s over 55 million lines of code. And one of the things that I found out in this study is more than 98 percent of it is completely irrelevant. All this work had been put into this thing, but it missed the fundamental problems that people faced. And the biggest one that I took away from it was that basically people are playing computer inside their head.” Programmers were like chess players trying to play with a blindfold on—so much of their mental energy is spent just trying to picture where the pieces are that there’s hardly any left over to think about the game itself.

The fact that the two of them were thinking about the same problem in the same terms, at the same time, was not a coincidence. They had both just seen the same remarkable talk, given to a group of software-engineering students in a Montreal hotel by a computer researcher named Bret Victor. The talk, which went viral when it was posted online in February 2012, seemed to be making two bold claims. The first was that the way we make software is fundamentally broken. The second was that Victor knew how to fix it.

This is the trouble with making things out of code, as opposed to something physical. “The complexity,” as Leveson puts it, “is invisible to the eye.”

in early 2012, Victor had finally landed upon the principle that seemed to thread through all of his work. (He actually called the talk “Inventing on Principle.”) The principle was this: “Creators need an immediate connection to what they’re creating.” The problem with programming was that it violated the principle. That’s why software systems were so hard to think about, and so rife with bugs: The programmer, staring at a page of text, was abstracted from whatever it was they were actually making.

“Our current conception of what a computer program is,” he said, is “derived straight from Fortran and ALGOL in the late ’50s. Those languages were designed for punch cards.”

WYSIWYG (pronounced “wizzywig”) came along. It stood for “What You See Is What You Get.”

Victor’s point was that programming itself should be like that. For him, the idea that people were doing important work, like designing adaptive cruise-control systems or trying to understand cancer, by staring at a text editor, was appalling.

With the right interface, it was almost as if you weren’t working with code at all; you were manipulating the game’s behavior directly.

When the audience first saw this in action, they literally gasped. They knew they weren’t looking at a kid’s game, but rather the future of their industry. Most software involved behavior that unfolded, in complex ways, over time, and Victor had shown that if you were imaginative enough, you could develop ways to see that behavior and change it, as if playing with it in your hands. One programmer who saw the talk wrote later: “Suddenly all of my tools feel obsolete.”

hen John Resig saw the “Inventing on Principle” talk, he scrapped his plans for the Khan Academy programming curriculum. He wanted the site’s programming exercises to work just like Victor’s demos. On the left-hand side you’d have the code, and on the right, the running program: a picture or game or simulation. If you changed the code, it’d instantly change the picture. “In an environment that is truly responsive,” Resig wrote about the approach, “you can completely change the model of how a student learns ... [They] can now immediately see the result and intuit how underlying systems inherently work without ever following an explicit explanation.” Khan Academy has become perhaps the largest computer-programming class in the world, with a million students, on average, actively using the program each month.

The ideas spread. The notion of liveness, of being able to see data flowing through your program instantly, made its way into flagship programming tools offered by Google and Apple. The default language for making new iPhone and Mac apps, called Swift, was developed by Apple from the ground up to support an environment, called Playgrounds, that was directly inspired by Light Table.

“Typically the main problem with software coding—and I’m a coder myself,” Bantegnie says, “is not the skills of the coders. The people know how to code. The problem is what to code. Because most of the requirements are kind of natural language, ambiguous, and a requirement is never extremely precise, it’s often understood differently by the guy who’s supposed to code.”

In a pair of later talks, “Stop Drawing Dead Fish” and “Drawing Dynamic Visualizations,” Victor went one further. He demoed two programs he’d built—the first for animators, the second for scientists trying to visualize their data—each of which took a process that used to involve writing lots of custom code and reduced it to playing around in a WYSIWYG interface.

Victor suggested that the same trick could be pulled for nearly every problem where code was being written today. “I’m not sure that programming has to exist at all,” he told me. “Or at least software developers.” In his mind, a software developer’s proper role was to create tools that removed the need for software developers. Only then would people with the most urgent computational problems be able to grasp those problems directly, without the intermediate muck of code.

Victor implored professional software developers to stop pouring their talent into tools for building apps like Snapchat and Uber. “The inconveniences of daily life are not the significant problems,” he wrote. Instead, they should focus on scientists and engineers—as he put it to me, “these people that are doing work that actually matters, and critically matters, and using really, really bad tools.”

Bantegnie’s company is one of the pioneers in the industrial use of model-based design, in which you no longer write code directly. Instead, you create a kind of flowchart that describes the rules your program should follow (the “model”), and the computer generates code for you based on those rules

In a model-based design tool, you’d represent this rule with a small diagram, as though drawing the logic out on a whiteboard, made of boxes that represent different states—like “door open,” “moving,” and “door closed”—and lines that define how you can get from one state to the other. The diagrams make the system’s rules obvious: Just by looking, you can see that the only way to get the elevator moving is to close the door, or that the only way to get the door open is to stop.

. In traditional programming, your task is to take complex rules and translate them into code; most of your energy is spent doing the translating, rather than thinking about the rules themselves. In the model-based approach, all you have is the rules. So that’s what you spend your time thinking about. It’s a way of focusing less on the machine and more on the problem you’re trying to get it to solve.

“Everyone thought I was interested in programming environments,” he said. Really he was interested in how people see and understand systems—as he puts it, in the “visual representation of dynamic behavior.” Although code had increasingly become the tool of choice for creating dynamic behavior, it remained one of the worst tools for understanding it. The point of “Inventing on Principle” was to show that you could mitigate that problem by making the connection between a system’s behavior and its code immediate.

On this view, software becomes unruly because the media for describing what software should do—conversations, prose descriptions, drawings on a sheet of paper—are too different from the media describing what software does do, namely, code itself.

for this approach to succeed, much of the work has to be done well before the project even begins. Someone first has to build a tool for developing models that are natural for people—that feel just like the notes and drawings they’d make on their own—while still being unambiguous enough for a computer to understand. They have to make a program that turns these models into real code. And finally they have to prove that the generated code will always do what it’s supposed to.

tice brings order and accountability to large codebases. But, Shivappa says, “it’s a very labor-intensive process.” He estimates that before they used model-based design, on a two-year-long project only two to three months was spent writing code—the rest was spent working on the documentation.

uch of the benefit of the model-based approach comes from being able to add requirements on the fly while still ensuring that existing ones are met; with every change, the computer can verify that your program still works. You’re free to tweak your blueprint without fear of introducing new bugs. Your code is, in FAA parlance, “correct by construction.”

“people are not so easily transitioning to model-based software development: They perceive it as another opportunity to lose control, even more than they have already.”

The bias against model-based design, sometimes known as model-driven engineering, or MDE, is in fact so ingrained that according to a recent paper, “Some even argue that there is a stronger need to investigate people’s perception of MDE than to research new MDE technologies.”

“Human intuition is poor at estimating the true probability of supposedly ‘extremely rare’ combinations of events in systems operating at a scale of millions of requests per second,” he wrote in a paper. “That human fallibility means that some of the more subtle, dangerous bugs turn out to be errors in design; the code faithfully implements the intended design, but the design fails to correctly handle a particular ‘rare’ scenario.”

Newcombe was convinced that the algorithms behind truly critical systems—systems storing a significant portion of the web’s data, for instance—ought to be not just good, but perfect. A single subtle bug could be catastrophic. But he knew how hard bugs were to find, especially as an algorithm grew more complex. You could do all the testing you wanted and you’d never find them all.

An algorithm written in TLA+ could in principle be proven correct. In practice, it allowed you to create a realistic model of your problem and test it not just thoroughly, but exhaustively. This was exactly what he’d been looking for: a language for writing perfect algorithms.

TLA+, which stands for “Temporal Logic of Actions,” is similar in spirit to model-based design: It’s a language for writing down the requirements—TLA+ calls them “specifications”—of computer programs. These specifications can then be completely verified by a computer. That is, before you write any code, you write a concise outline of your program’s logic, along with the constraints you need it to satisfy

Programmers are drawn to the nitty-gritty of coding because code is what makes programs go; spending time on anything else can seem like a distraction. And there is a patient joy, a meditative kind of satisfaction, to be had from puzzling out the micro-mechanics of code. But code, Lamport argues, was never meant to be a medium for thought. “It really does constrain your ability to think when you’re thinking in terms of a programming language,”

Code makes you miss the forest for the trees: It draws your attention to the working of individual pieces, rather than to the bigger picture of how your program fits together, or what it’s supposed to do—and whether it actually does what you think. This is why Lamport created TLA+. As with model-based design, TLA+ draws your focus to the high-level structure of a system, its essential logic, rather than to the code that implements it.

But TLA+ occupies just a small, far corner of the mainstream, if it can be said to take up any space there at all. Even to a seasoned engineer like Newcombe, the language read at first as bizarre and esoteric—a zoo of symbols.

this is a failure of education. Though programming was born in mathematics, it has since largely been divorced from it. Most programmers aren’t very fluent in the kind of math—logic and set theory, mostly—that you need to work with TLA+. “Very few programmers—and including very few teachers of programming—understand the very basic concepts and how they’re applied in practice. And they seem to think that all they need is code,” Lamport says. “The idea that there’s some higher level than the code in which you need to be able to think precisely, and that mathematics actually allows you to think precisely about it, is just completely foreign. Because they never learned it.”

“In the 15th century,” he said, “people used to build cathedrals without knowing calculus, and nowadays I don’t think you’d allow anyone to build a cathedral without knowing calculus. And I would hope that after some suitably long period of time, people won’t be allowed to write programs if they don’t understand these simple things.”

Programmers, as a species, are relentlessly pragmatic. Tools like TLA+ reek of the ivory tower. When programmers encounter “formal methods” (so called because they involve mathematical, “formally” precise descriptions of programs), their deep-seated instinct is to recoil.

Formal methods had an image problem. And the way to fix it wasn’t to implore programmers to change—it was to change yourself. Newcombe realized that to bring tools like TLA+ to the programming mainstream, you had to start speaking their language.

he presented TLA+ as a new kind of “pseudocode,” a stepping-stone to real code that allowed you to exhaustively test your algorithms—and that got you thinking precisely early on in the design process. “Engineers think in terms of debugging rather than ‘verification,’” he wrote, so he titled his internal talk on the subject to fellow Amazon engineers “Debugging Designs.” Rather than bemoan the fact that programmers see the world in code, Newcombe embraced it. He knew he’d lose them otherwise. “I’ve had a bunch of people say, ‘Now I get it,’” Newcombe says.

In the world of the self-driving car, software can’t be an afterthought. It can’t be built like today’s airline-reservation systems or 911 systems or stock-trading systems. Code will be put in charge of hundreds of millions of lives on the road and it has to work. That is no small task.

they’re also used as talking points by politicians who are working to make it more difficult for the EPA and other federal agencies to use science in their regulatory decision-making, under the guise of basing policy on “sound science.” Science’s virtues are being wielded against it.

What distinguishes the two calls for transparency is intent: Whereas the “open science” movement aims to make science more reliable, reproducible and robust, proponents of “sound science” have historically worked to amplify uncertainty, create doubt and undermine scientific discoveries that threaten their interests.

“Our criticisms are founded in a confidence in science,” said Steven Goodman, co-director of the Meta-Research Innovation Center at Stanford and a proponent of open science. “That’s a fundamental difference — we’re critiquing science to make it better. Others are critiquing it to devalue the approach itself.”

alls to base public policy on “sound science” seem unassailable if you don’t know the term’s history. The phrase was adopted by the tobacco industry in the 1990s to counteract mounting evidence linking secondhand smoke to cancer.

The sound science tactic exploits a fundamental feature of the scientific process: Science does not produce absolute certainty. Contrary to how it’s sometimes represented to the public, science is not a magic wand that turns everything it touches to truth. Instead, it’s a process of uncertainty reduction, much like a game of 20 Questions.

Any given study can rarely answer more than one question at a time, and each study usually raises a bunch of new questions in the process of answering old ones. “Science is a process rather than an answer,” said psychologist Alison Ledgerwood of the University of California, Davis. Every answer is provisional and subject to change in the face of new evidence. It’s not entirely correct to say that “this study proves this fact,” Ledgerwood said. “We should be talking instead about how science increases or decreases our confidence in something.”

While insisting that they merely wanted to ensure that public policy was based on sound science, tobacco companies defined the term in a way that ensured that no science could ever be sound enough. The only sound science was certain science, which is an impossible standard to achieve.

“Doubt is our product,” wrote one employee of the Brown & Williamson tobacco company in a 1969 internal memo. The note went on to say that doubt “is the best means of competing with the ‘body of fact’” and “establishing a controversy.” These strategies for undermining inconvenient science were so effective that they’ve served as a sort of playbook for industry interests ever since

Doubt merchants aren’t pushing for knowledge, they’re practicing what Proctor has dubbed “agnogenesis” — the intentional manufacture of ignorance. This ignorance isn’t simply the absence of knowing something; it’s a lack of comprehension deliberately created by agents who don’t want you to know,

In the hands of doubt-makers, transparency becomes a rhetorical move. “It’s really difficult as a scientist or policy maker to make a stand against transparency and openness, because well, who would be against it?

But at the same time, “you can couch everything in the language of transparency and it becomes a powerful weapon.” For instance, when the EPA was preparing to set new limits on particulate pollution in the 1990s, industry groups pushed back against the research and demanded access to primary data (including records that researchers had promised participants would remain confidential) and a reanalysis of the evidence. Their calls succeeded and a new analysis was performed. The reanalysis essentially confirmed the original conclusions, but the process of conducting it delayed the implementation of regulations and cost researchers time and money.

Delay is a time-tested strategy. “Gridlock is the greatest friend a global warming skeptic has,” said Marc Morano, a prominent critic of global warming research

which has received funding from the oil and gas industry. “We’re the negative force. We’re just trying to stop stuff.”

these ploys are getting a fresh boost from Congress. The Data Quality Act (also known as the Information Quality Act) was reportedly written by an industry lobbyist and quietly passed as part of an appropriations bill in 2000. The rule mandates that federal agencies ensure the “quality, objectivity, utility, and integrity of information” that they disseminate, though it does little to define what these terms mean. The law also provides a mechanism for citizens and groups to challenge information that they deem inaccurate, including science that they disagree with. “It was passed in this very quiet way with no explicit debate about it — that should tell you a lot about the real goals,” Levy said.

in the 20 months following its implementation, the act was repeatedly used by industry groups to push back against proposed regulations and bog down the decision-making process. Instead of deploying transparency as a fundamental principle that applies to all science, these interests have used transparency as a weapon to attack very particular findings that they would like to eradicate.

Now Congress is considering another way to legislate how science is used. The Honest Act, a bill sponsored by Rep. Lamar Smith of Texas,3The bill has been passed by the House but still awaits a vote in the Senate. is another example of what Levy calls a “Trojan horse” law that uses the language of transparency as a cover to achieve other political goals. Smith’s legislation would severely limit the kind of evidence the EPA could use for decision-making. Only studies whose raw data and computer codes were publicly available would be allowed for consideration.

It might seem like an easy task to sort good science from bad, but in reality it’s not so simple. “There’s a misplaced idea that we can definitively distinguish the good from the not-good science, but it’s all a matter of degree,” said Brian Nosek, executive director of the Center for Open Science. “There is no perfect study.” Requiring regulators to wait until they have (nonexistent) perfect evidence is essentially “a way of saying, ‘We don’t want to use evidence for our decision-making,’

ost scientific controversies aren’t about science at all, and once the sides are drawn, more data is unlikely to bring opponents into agreement.

objective knowledge is not enough to resolve environmental controversies. “While these controversies may appear on the surface to rest on disputed questions of fact, beneath often reside differing positions of value; values that can give shape to differing understandings of what ‘the facts’ are.” What’s needed in these cases isn’t more or better science, but mechanisms to bring those hidden values to the forefront of the discussion so that they can be debated transparently. “As long as we continue down this unabashedly naive road about what science is, and what it is capable of doing, we will continue to fail to reach any sort of meaningful consensus on these matters,”

The dispute over tobacco was never about the science of cigarettes’ link to cancer. It was about whether companies have the right to sell dangerous products and, if so, what obligations they have to the consumers who purchased them.

Similarly, the debate over climate change isn’t about whether our planet is heating, but about how much responsibility each country and person bears for stopping it

While researching her book “Merchants of Doubt,” science historian Naomi Oreskes found that some of the same people who were defending the tobacco industry as scientific experts were also receiving industry money to deny the role of human activity in global warming. What these issues had in common, she realized, was that they all involved the need for government action. “None of this is about the science. All of this is a political debate about the role of government,”

These controversies are really about values, not scientific facts, and acknowledging that would allow us to have more truthful and productive debates. What would that look like in practice? Instead of cherry-picking evidence to support a particular view (and insisting that the science points to a desired action), the various sides could lay out the values they are using to assess the evidence.

For instance, in Europe, many decisions are guided by the precautionary principle — a system that values caution in the face of uncertainty and says that when the risks are unclear, it should be up to industries to show that their products and processes are not harmful, rather than requiring the government to prove that they are harmful before they can be regulated. By contrast, U.S. agencies tend to wait for strong evidence of harm before issuing regulations

the difference between them comes down to priorities: Is it better to exercise caution at the risk of burdening companies and perhaps the economy, or is it more important to avoid potential economic downsides even if it means that sometimes a harmful product or industrial process goes unregulated?

But science can’t tell us how risky is too risky to allow products like cigarettes or potentially harmful pesticides to be sold — those are value judgements that only humans can make.

We were led to wonder whether a broken robot can break a child.

Kids are central to the sociable-robot project, because its agenda is to make people more comfortable with robots in roles normally reserved for humans, and robotics companies know that children are vulnerable consumers who can bring the whole family along.

In October, Mattel scrapped plans for Aristotle — a kind of Alexa for the nursery, designed to accompany children as they progress from lullabies and bedtime stories through high school homework — after lawmakers and child advocacy groups argued that the data the device collected about children could be misused by Mattel, marketers, hackers and other third parties. I was part of that campaign: There is something deeply unsettling about encouraging children to confide in machines that are in turn sharing their conversations with countless others.

Recently, I opened my MIT mail and found a “call for subjects” for a study involving sociable robots that will engage children in conversation to “elicit empathy.” What will these children be empathizing with, exactly? Empathy is a capacity that allows us to put ourselves in the place of others, to know what they are feeling. Robots, however, have no emotions to share

What they can do is push our buttons. When they make eye contact and gesture toward us, they predispose us to view them as thinking and caring. They are designed to be cute, to provoke a nurturing response. And when it comes to sociable AI, nurturance is the killer app: We nurture what we love, and we love what we nurture. If a computational object or robot asks for our help, asks us to teach it or tend to it, we attach. That is our human vulnerability.

digital companions don’t understand our emotional lives. They present themselves as empathy machines, but they are missing the essential equipment: They have not known the arc of a life. They have not been born; they don’t know pain, or mortality, or fear. Simulated thinking may be thinking, but simulated feeling is never feeling, and simulated love is never love.

Breazeal’s position is this: People have relationships with many classes of things. They have relationships with children and with adults, with animals and with machines. People, even very little people, are good at this. Now, we are going to add robots to the list of things with which we can have relationships. More powerful than with pets. Less powerful than with people. We’ll figure it out.

The nature of the attachments to dolls and sociable machines is different. When children play with dolls, they project thoughts and emotions onto them. A girl who has broken her mother’s crystal will put her Barbies into detention and use them to work on her feelings of guilt. The dolls take the role she needs them to take.

Sociable machines, by contrast, have their own agenda. Playing with robots is not about the psychology of projection but the psychology of engagement. Children try to meet the robot’s needs, to understand the robot’s unique nature and wants. There is an attempt to build a mutual relationship.

Some people might consider that a good thing: encouraging children to think beyond their own needs and goals. Except the whole commercial program is an exercise in emotional deception.

when we offer these robots as pretend friends to our children, it’s not so clear they can wink with us. We embark on an experiment in which our children are the human subjects.

it is hard to imagine what those “right types” of ties might be. These robots can’t be in a two-way relationship with a child. They are machines whose art is to put children in a position of pretend empathy. And if we put our children in that position, we shouldn’t expect them to understand what empathy is. If we give them pretend relationships, we shouldn’t expect them to learn how real relationships — messy relationships — work. On the contrary. They will learn something superficial and inauthentic, but mistake it for real connection.

In the process, we can forget what is most central to our humanity: truly understanding each other.

For so long, we dreamed of artificial intelligence offering us not only instrumental help but the simple salvations of conversation and care. But now that our fantasy is becoming reality, it is time to confront the emotional downside of living with the robots of our dreams.

Her reason for coming was obvious. She was around 40 weeks pregnant

She was an office worker in Ohio when she became pregnant by a man who wasn’t going to marry her. The most remarkable part of her story was this: When she knew she was about to give birth, she drove westward out of Ohio, stopping at Indianapolis only because it was the first big city she encountered

She arranged to place the baby for adoption and gave birth the next day.

The baby was me. If she’d driven farther, I’d be a native of Chicago or St. Louis, but Indianapolis it was

Life is a journey, and I was born on a road trip.

Secrecy was considered best for all concerned. In recent decades, open adoption has been replacing this practice, but rules governing past adoptions change slowly, and I was barred from seeing my birth records.

Everything I just told you about my biological parents was unknown to me growing up; they were such a blank that I could not even imagine what they might be like.

I accepted this until I became an adoptive parent in 2012 and a social worker suggested that my adopted daughter might want to know my story someday

She’s from China, and like many international adoptees, she also had no story of her biological family.

I requested my records from the State of Indiana and was denied.

Next I called the Children’s Bureau, where a kind woman on the phone had my records in her hands, but was not allowed to share them.

Typed notes from the Children’s Bureau recorded a visit with my biological mother in the hospital. Asked how she felt, she cried

It’s been nearly two years since I first read those documents, and I’m still not over it. Knowing that story has altered how I think about myself, and the seemingly simple question of where I’m from

It’s brought on a feeling of revelation, and also of anger. I’m not upset with my biological mother; it was moving to learn how she managed her predicament alone.

Her decisions left me with the family that I needed — that I love. Nor am I unhappy with the Children’s Bureau, which did its duty by preserving my records.

I am angry that for 50 years, my state denied me the story of how I came to live on this earth. Strangers hid part of me from myself.

While I now have the privilege of knowing my information, many people’s stories are still hidden.

About 2 percent of U.S. residents — roughly six million people — are adoptees

A majority were adopted domestically, with records frequently sealed, especially for older adoptees

I was never able to tell a doctor my family medical history when asked. It’s one of those little things that never bother you until it does.

The people who blocked me from learning my past must have thought their motives were pure.

Closed adoption began as “confidential” adoption in the early 20th century, enabling parents and children to avoid the stigma of illegitimacy.

Records were sealed to all but people directly involved

But nobody asked if I wanted my identity hidden from me.

Should adoptees and biological families contact each other, after the law forbade it for so long?

Not without mutual consent:

information alone is powerful.

As records are opened, people’s privacy should be respected; that’s why I’m withholding my biological mother’s name and any details that might identify her. But my story is mine, and other adoptees have a right to recover theirs.

You must immediately know to cross a road quickly – even run – when you hear a car rapidly approaching.

These limitations represent a thinking problem: Our brains simply do not have enough resources to understand the world without taking some mental shortcuts.

Our brains find shortcuts to overcome the thinking problem by relying on thoughts already stored in our minds, called schemas. Schemas do the processing for the brain, like auto-fill, but for thinking.

Schemas are the building blocks of our knowledge about the world. Our brains rely on different types of schemas to understand different types of situations.

When our brains try to understand unfamiliar objects, they must rely on a schema for a different but similar object because the correct schema is unavailable. If the object and chosen schema closely match, our brains effortlessly – but inaccurately – assume the two objects are the same.

A person who has never seen a bat might assume a bat is a bird because the features of the bat and their schema for a bird are similar: Both are small animals with wings and can fly. Our brains accept occasional inaccuracies.

“When people hear ‘clown,’ the first associations that pop into their head are the killer clowns in the movies — It, the Joker— and then John Wayne Gacy, the real-life mass murderer,” McAndrew says of the 1970s serial killer who became known as the “Killer Clown” for his volunteer clown work. “It’s kind of hard to get past all of that.”

“[Some of the] very first clowns were the court jesters who poked fun at kings and made people in high places uncomfortable. That’s why they exist,” he tells TIME of the history of clowns in medieval Europe. “They’re designed to make people afraid. If you go all the way back to the beginning of clownhood, they’ve always been bad. They’re pranksters, they play tricks.”

However, while many people are apprehensive or fearful of clowns, both Nader and McAndrew agree that someone having an actual phobia of clowns, a.k.a. coulrophobia, is rare.

“Fortunately, we live in a society where clowns aren’t just wandering around, so it’s pretty easy to avoid them or at least not come into contact with them very regularly. Rarely does this fear ever cause a person to experience a disruption in their lifestyle or ability to do things.”

“We like to learn about dangers in a safe way so that we’re prepared in some unknown future time to deal with them if they ever come our way. So by going to see IT and watching this evil clown lure children in and kill them, we learn strategies for avoiding that kind of fate ourselves,” he says. “We’re not consciously sitting there, watching the movie and thinking these things, but that impulse to like to scare ourselves is there.”

According to the police procedures, if people are protesting, there is a way you handle it — but if now they overrun — overrun, for instance, a police station — you will have to stop it by using lethal fire. Rioting and attacking civilians and attacking property, it is something that we cannot accept.

[Ugandans] don't have to work hard. Now, that's a big struggle, which these know-it-all from [the] outside don't know, because in other parts of the world, people are pressured to work either by the environment, which is hostile, or by competition between man and man. But here, fools can survive.

It actually showed the lack of seriousness of those who [say] that you just go, just [leave power].

Yes, we are committed to the freedom of the press, but see, the press, especially the Western press, is arrogant. You don't want to learn; you know it all. Then you come on and impose your ignorance on our society.

How can we continue dealing with these arrogant ignoramuses? So if they change their attitude from arrogance to inquisitiveness and investigation, I'm very happy.

when we extend our knowledge by deducing logical consequences of what we already know. If you know that either Mary or Mark did the murder (only they had access to the crime scene at the right time), and then Mary produces a rock-solid alibi, so you know she didn’t do it, you can deduce that Mark did it

Logic also helps us recognize our mistakes, when our beliefs turn out to contain inconsistencies. If I believe that no politicians are honest, and that John is a politician, and that he is honest, at least one of those three beliefs must be false, although logic doesn’t tell me which one.

The power of logic becomes increasingly clear when we chain together such elementary steps into longer and longer chains of reasoning, and the idea of logic as uninformative becomes correspondingly less and less plausible. Mathematics provides the most striking examples, since all its theorems are ultimately derived from a few simple axioms by chains of logical reasoning

The conception of logic as a neutral umpire of debate also fails to withstand scrutiny, for similar reasons. Principles of logic can themselves be debated,

one principle of standard logic is the law of excluded middle, which says that something either is the case, or it isn’t. Either it’s raining, or it’s not.

Whichever side is right, logical theories are players in these debates, not neutral umpires.

That her medium was poetry is no mere detail. It is almost the whole story. Poetry not only allows her to express herself – her desire for consolation, her anxiety about what’s disappearing. It is also the form of writing par excellence that can keep an eye open for what is peripheral. It can discern truths that words otherwise struggle to articulate. It glimpses, and hopes.

to know Socrates was to know someone who sought all the truth, and in so doing, realised it mostly lies out of sight.

Moses too does not see anything directly. He apparently doesn’t see anything at all. Instead, an oblique experience is granted to him. It is better described as a kind of unknowing, rather than knowing. He must leave behind what he has previously observed because this seeing consists in not seeing. That which is sought transcends all knowledge.

What she realises is that the truth which is beyond us, which is discerned only indirectly, is the only truth that is truly worth seeking. That which we can readily grasp and manipulate is too easy for us. It’s humdrum. It leaves life too small for us, the creature with an eye for the transcendent. But look further, and what you are offered is what she calls truth’s ‘superb surprise’. That’s why success lies in circuit. Our humanity is spoken to, from a direction – a source – that we had not expected. And our humanity expands as a result.

Fourth, there is humility, which is not letting your own desire for status get in the way of accuracy.

Fifth, there is autonomy

Autonomy is the median of knowing when to bow to authority and when not to

Such a person is open to learning from anyone at any stage in life.

The median point between flaccidity and rigidity is the virtue of firmness. The firm believer can build a steady worldview on solid timbers but still delight in new information

Finally, there is generosity

the mind is embedded in human nature, and very often thinking well means pushing against the grain of our nature — against vanity, against laziness, against the desire for certainty, against the desire to avoid painful truths.

Good thinking isn’t just adopting the right technique. It’s a moral enterprise and requires good character, the ability to go against our lesser impulses for the sake of our higher ones.

wisdom isn’t a body of information. It’s the moral quality of knowing how to handle your own limitations

Montaigne once wrote that “We can be knowledgeable with other men’s knowledge, but we can’t be wise with other men’s wisdom.”

Is it possible to display and cultivate character if you are just an information age office jockey, alone with a memo or your computer?

Some people are just more ardently curious than others, either by cultivation or by nature.

Most investors regard Warren Buffett as someone who has parlayed brilliant analysis, hard work and extensive connections into one of the best track records in financial history. Mr. Housel, however, notices that Mr. Buffett accrued at least 95% of his wealth after age 65.

Had Mr. Buffett earned his world-beating returns for only 30 years rather than much longer, he would be worth 99.9% less, notes Mr. Housel. “The real key to his success is that he’s been a phenomenal investor for three quarters of a century,” he writes of Mr. Buffett. “His skill is investing, but his secret is time.”

So Mr. Buffett—traditionally viewed as the greatest living example of investing skill—is also proof of the power of luck and longevity.

In a similar vein, “The Psychology of Money” argues the biggest determinant of long-term returns often happens to be when you were born. Adjusted for inflation, people born in 1950 earned essentially nothing in the stock market between the ages of 13 and 30, Mr. Housel shows. Those born in 1970 earned roughly nine times as much on stocks in their formative years. Those born in 2000? They may have to save a lot more than their parents did.

Bubbles form when catchy stories and the human need for imitation and conformity turn investing into a social imperative.

Mr. Housel urges investors to think about what money and wealth are for. He draws a critical distinction between being rich (having a high current income) and being wealthy (having the freedom to choose not to spend money).

Many rich people aren’t wealthy, Mr. Housel argues, because they feel the need to spend a lot of money to show others how rich they are

He defines the optimal savings level as “the gap between your ego and your income.” Wealth consists in caring less about what others think about you and more about using your money to control how you spend your time.

He writes: “The ability to do what you want, when you want, with who[m] you want, for as long as you want to, pays the highest dividend that exists in finance.”

In each case, there was a failure of imagination, as Tom Friedman has noted. Warnings found little receptiveness among the public or government officials. We didn’t think what happened could happen. The presumption of progress bred complacency.

We fooled ourselves into thinking we had engineered permanent improvements in our social and economic systems.

To be fair, progress as it’s commonly understood — higher living standards — has not been at a standstill. Many advances have made life better

Similar inconsistencies and ambiguities attach to economic growth. It raises some up and pushes others down.

What we should have learned by now is that progress is often grudging, incomplete or contradictory.

Still, the setbacks loom ever larger. Our governmental debt is high, and economic stability is low. Many of the claims of progress turn out to be exaggerated, superficial, delusional or unattainable,

Sure, the Internet enables marvelous things. But it also imposes huge costs on society

Global warming is another example. It is largely a result of the burning of fossil fuels, which has been the engine of our progress. Now, it is anti-progress.

the lesson of both economic growth and technologies is that they are double-edged swords and must be judged as such.

What connects these various problems is the belief that the future can be orchestrated.

The reality is that our control over the future is modest at best, nonexistent at worst. We react more to events than lead them.

We worship at the altar of progress without adequately acknowledging its limits.

it does mean that we should be more candid about what is possible. If not, we might yet again wander over the “border between reality and impossibility.”

It’s hard to break free from anxious thoughts when you’re consumed with the world falling apart with no end in sight.”

my anxiety always gave me this sinking feeling that something bad was going to happen.

But when the isolating isn’t by choice, and it’s to avoid a deadly disease, it can be the cause of panic-inducing thoughts that you can’t escape from.

“Racial injustice doesn’t mix well with trauma, so I’ve had to do my mental illness a favor and log off of social media.

It’s as if the worry and anxiety is always at the back of my mind even when I sleep and as soon as I wake up, it overwhelms me immediately.

“As someone with anxiety, I already feel an unrealistic and heavy responsibility on how my actions and words affect others.

At first I was filled with panic, but now I’ve adjusted to this new normal.

my anxiety started to stem from not knowing when this will end or when things can go back to feeling normal.

Now, I realize that the world can change in a second and that I have to learn to let certain things go. Who knows what is going to happen next.

“My mind immediately goes to the worst-case scenario and that’s when things start spiraling for me.

Today, after a few months, the COVID anxiety isn’t as strong as it was ― when, strangely, COVID is stronger than ever in my city

I’m unable to save money for retirement and I get very anxious when I think about the future.

Worse, I’ve lost my sense of meaning to myself. I feel like the culture has moved on without me, and I don’t know what to do.

I feel alone in many ways and unsuccessful by most measures. I don’t own a home and no one needs me; I am nobody’s mother and now I am nobody’s child, as my parents are no longer living.

on bad ones, I feel such futility, like I’ve squandered my own youth and beauty in the hall of mirrors that is our consumerist society.

A: What you wrote is in no way frivolous; it concerns the entire value, direction and purpose of your life.

You’ve realized that, in curating what we call taste, you’ve unwittingly become part of the system, the media-driven consumerist machine that creates the desire to possess things you’ll likely never be able to afford.

Beauty — distracting, exclusionary, often more talismanic and notional than “real” — has never been a steady organizing principle for life

your sense of what is beautiful has become more complicated, as you have. Your work is no longer satisfying to you because it is no longer relevant to the person you are.

your way of seeing things, including yourself, seems not wholly true or right or your own, and is in dire need of a refresh. It feels reductive and merciless, informed too much by the very aspects of our culture that have become deadening to you.

You’re seeking new paths to the shore, new things that sustain you, and this requires doing the work to find out what that looks like. It requires acknowledging the value shift that probably began happening inside you long ago.

Imbued with their own neurons, octopus arms can act semi-autonomously, gathering and exchanging information without routing it through the main brain.

It’s long been unclear, for instance, how the animals, just by probing their surroundings with their limbs, can distinguish something like a crab from a less edible object.

exposed to octopus ink, which is sometimes released as a “warning signal,” Dr. van Giesen said. “Maybe there is some kind of filtering of information that is important for the animal in specific situations,” like when danger is afoot, she said.

But they found that some of the cells in the animal’s suckers would shut down when

Humans, who tend to be very visual creatures, probably can’t fully appreciate the sensory nuances of a taste-sensitive arm

“Sometimes we assume in neuroscience or animal behavior, there’s only one way of doing it

But then again, most people could probably do without the metallic tang of keys every time they rummage in their pockets — or the funk that would inevitably dissuade every new parent from changing a diaper.

(Even after amputation, these adept appendages can still snatch hungrily at morsels of food.)

The cells of octopus suckers are decorated with a mixture of tiny detector proteins. Each type of sensor responds to a distinct chemical cue, giving the animals an extraordinarily refined palate that can inform how their agile arms react, jettisoning an object as useless or dangerous, or nabbing it for a snack.

That arm has all the cellular machinery to taste your tongue right back.

Each type of sensor responds to a distinct chemical cue, giving the animals an extraordinarily refined palate that can inform how their agile arms react, jettisoning an object as useless or dangerous, or nabbing it for a snack.

Octopuses certainly know how to put that processing power to good use.

By mixing and matching these proteins, cells could develop their own unique tasting profiles, allowing the octopus’s suckers to discern flavors in fine gradations, then shoot the sensation to other parts of the nervous system.

Underwater, some chemicals can travel far from their source, making it possible for some creatures to catch a whiff of their prey from afar. But for chemicals that don’t move through the ocean easily, a touch-taste strategy is handy, Dr. Bellono said.

One message they all had: You are stronger than you think you are, and everyone is able to adapt in ways they didn’t think possible.

there are a few techniques to help you along — 100-mile race not required.

There’s a pacing in living day to day, just as there’s pacing in climbing.

Training to become an elite endurance athlete means learning to embrace discomfort. Instead of hiding from pain, athletes must learn to work with it. A lot of that comes down to pacing

Similarly, as you muscle through an ongoing pandemic, you must look for ways to make peace with unknowns and new, uncomfortable realities. “When we think about the coronavirus, we are in it for the long run; so how do you pace yourself?”

She recommends thinking about your routines, practicing positive self-talk and focusing on processes instead of outcomes

You don’t know when the pandemic will end, but you can take control of your daily habits

“always have a little in reserve.”

Deplete your resources early and you’ll be in trouble. Focusing on day-to-day activities will pay off in the long run.

If you burn out all your mental energy in one day or week, you may find it more difficult to adapt when things don’t return to normal as quickly as you would hope.

Pace Yourself

“Don’t play all your cards at once and keep a little something in reserve.”

Create Mini-Goals

Sports psychologists frequently recommend creating mini milestones en route to a big goal. There are many steps on the path from base camp to a mountain’s summit. Likewise, there are smaller, more achievable milestones to reach and celebrate as you venture ahead into the unknown.

Focus on Something New

“I’m really good at breaking things down into small increments and setting micro-goals,” he said. How micro?

“I break things down to 10 seconds at a time,” Mr. Woltering continued. “You just have to be present in what you are doing and you have to know that it may not be the most fun — or super painful — now, but that could change in 10 seconds down the road.”

And it may not change quickly. Mr. Woltering said he has spent six-hour stretches counting to 10 over and over again. “You just keep moving and keep counting,” he said. “And you have to have faith that it will change at some point.”

Create Structure

“Part of expedition life is having a routine that you’re comfortable with. When I’m on expedition, I always start the day with a basin of warm water and soap. I wash my hands, face, neck and ears and get the sand out of my eyes,” he said. “It’s something that’s repeated that gets you a sense of comfort and normalcy.”

During the pandemic, he has found comfort and normalcy by getting outdoors, and climbing whenever possible to “run the engine.”

Dee Caffari, a British sailor and the first woman to sail solo, nonstop, around the world in both directions, said structure is imperative to fight back loneliness and monotony.

“In your day you need structure,” Ms. Caffari said. “You need to get up in the morning knowing you’re going to make something happen.”

“Setting goals that are controllable makes it easier to adapt,” Dr. Meijen said. “If you set goals that are controlled by other people, goals that aren’t realistic or are tough or boring, those are much harder to adapt to.”

When all else fails, look to something new: a new hobby, a new goal, a new experience

During a particularly hard patch of a competition, some athletes say they focus on a different sense, one that perhaps is not at the forefront of their mind when the pain sets in. A runner could note the smells around her and a climber could note the way his hair is blowing in the wind.

When athletes are injured, sports psychologists and coaches frequently encourage them to find a new activity to engage their mind and body. The key is to adapt, adapt and then adapt again.

“We all want mental toughness, it’s an important part of dealing with difficult things,”

“The current definition of mental toughness is the ability to pivot and to be nimble and flexible.”

“The next moment is always completely uncertain, and it’s always been that way,” Dr. Gervais said. But adapting, adjusting expectations and discovering new goals or hobbies can allow you to continue to build the muscle that is mental toughness.

Bottom line? “Optimism is an antidote to anxiety,”