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This means that, even under the best circumstances, scientists can’t directly test what the results of a given gun policy are. The best you can do is to compare what was happening in a state before and after a policy was enacted, or to compare two different states, one that has the policy and one that doesn’t. And that’s a pretty inexact way of working.

Add in enough assumptions, and you can eventually come up with an estimate. But is the estimate correct? Is it even close to reality? That’s a hard question to answer, because the assumptions you made—the correlations you drew between cause and effect, what you know and what you assume to be true because of that—might be totally wrong.

It’s hard to tease apart the effect of one specific change, compared to the effects of other things that could be happening at the same time.

This process of taking the observational data we do have and then running it through a filter of assumptions plays out in the real world in the form of statistical modeling. When the NAS report says that nobody yet knows whether more guns lead to more crime, or less crime, what they mean is that the models and the assumptions built into those models are all still proving to be pretty weak.

From either side of the debate, he said, scientists continue to produce wildly different conclusions using the same data. On either side, small shifts in the assumptions lead the models to produce different results. Both factions continue to choose sets of assumptions that aren’t terribly logical. It’s as if you decided that anybody with blue shoes probably had a belly-button piercing. There’s not really a good reason for making that correlation. And if you change the assumption—actually, belly-button piercings are more common in people who wear green shoes—you end up with completely different results.

The Intergovernmental Panel on Climate Change (IPCC) produces these big reports periodically, which analyze lots of individual papers. In essence, they’re looking at lots of trees and trying to paint you a picture of the forest. IPCC reports are available for free online, you can go and read them yourself. When you do, you’ll notice something interesting about the way that the reports present results. The IPCC never says, “Because we burned fossil fuels and emitted carbon dioxide into the atmosphere then the Earth will warm by x degrees.” Instead, those reports present a range of possible outcomes … for everything. Depending on the different models used, different scenarios presented, and the different assumptions made, the temperature of the Earth might increase by anywhere between 1.5 and 4.5 degrees Celsius.

What you’re left with is an environment where it’s really easy to prove that your colleague’s results are probably wrong, and it’s easy for him to prove that yours are probably wrong. But it’s not easy for either of you to make a compelling case for why you’re right.

Statistical modeling isn’t unique to gun research. It just happens to be particularly messy in this field. Scientists who study other topics have done a better job of using stronger assumptions and of building models that can’t be upended by changing one small, seemingly randomly chosen detail. It’s not that, in these other fields, there’s only one model being used, or even that all the different models produce the exact same results. But the models are stronger and, more importantly, the scientists do a better job of presenting the differences between models and drawing meaning from them.

“Climate change is one of the rare scientific literatures that has actually faced up to this,” Charles Manski said. What he means is that, when scientists model climate change, they don’t expect to produce exact, to-the-decimal-point answers.

“It’s been a complete waste of time, because we can’t validate one model versus another,” Pepper said. Most likely, he thinks that all of them are wrong. For instance, all the models he’s seen assume that a law will affect every state in the same way, and every person within that state in the same way. “But if you think about it, that’s just nonsensical,” he said.

On the one hand, that leaves politicians in a bit of a lurch. The response you might mount to counteract a 1.5 degree increase in global average temperature is pretty different from the response you’d have to 4.5 degrees. On the other hand, the range does tell us something valuable: the temperature is increasing.

The problem with this is that it flies in the face of what most of us expect science to do for public policy. Politics is inherently biased, right? The solutions that people come up with are driven by their ideologies. Science is supposed to cut that Gordian Knot. It’s supposed to lay the evidence down on the table and impartially determine who is right and who is wrong.

Manski and Pepper say that this is where we need to rethink what we expect science to do. Science, they say, isn’t here to stop all political debate in its tracks. In a situation like this, it simply can’t provide a detailed enough answer to do that—not unless you’re comfortable with detailed answers that are easily called into question and disproven by somebody else with a detailed answer.

Instead, science can reliably produce a range of possible outcomes, but it’s still up to the politicians (and, by extension, up to us) to hash out compromises between wildly differing values on controversial subjects. When it comes to complex social issues like gun ownership and gun violence, science doesn’t mean you get to blow off your political opponents and stake a claim on truth. Chances are, the closest we can get to the truth is a range that encompasses the beliefs of many different groups.

But making decisions well is incredibly difficult, even for highly educated professional decision makers. As Chip Heath and Dan Heath point out in their book “Decisive,” 83 percent of corporate mergers and acquisitions do not increase shareholder value, 40 percent of senior hires do not last 18 months in their new position, 44 percent of lawyers would recommend that a young person not follow them into the law.

It’s becoming incredibly important to learn to decide well, to develop the techniques of self-distancing to counteract the flaws in our own mental machinery. The Heath book is a very good compilation of those techniques.

assume positive intent. When in the midst of some conflict, start with the belief that others are well intentioned. It makes it easier to absorb information from people you’d rather not listen to.

Suzy Welch’s 10-10-10 rule. When you’re about to make a decision, ask yourself how you will feel about it 10 minutes from now, 10 months from now and 10 years from now. People are overly biased by the immediate pain of some choice, but they can put the short-term pain in long-term perspective by asking these questions.

An "explosion" that may also be a "dissolution" or "disintegration," in my view. Unlimited choices. Conduct without boundaries. All of which may be viewed as either "great" or "terrible." The poor suffer when they have no means to pursue choices, which is terrible. The rich seem only to want more and more, wealth without boundaries, which is great for those so able to do. Yes, we need a new decision-making tool, but perhaps one that is also very old: simplify, simplify,simplify by setting moral boundaries that apply to all and which define concisely what our life together ought to be.

our tendency to narrow-frame, to see every decision as a binary “whether or not” alternative. Whenever you find yourself asking “whether or not,” it’s best to step back and ask, “How can I widen my options?”

deliberate mistakes. A survey of new brides found that 20 percent were not initially attracted to the man they ended up marrying. Sometimes it’s useful to make a deliberate “mistake” — agreeing to dinner with a guy who is not your normal type. Sometimes you don’t really know what you want and the filters you apply are hurting you.

It makes you think that we should have explicit decision-making curriculums in all schools. Maybe there should be a common course publicizing the work of Daniel Kahneman, Cass Sunstein, Dan Ariely and others who study the way we mess up and the techniques we can adopt to prevent error.

The explosion of choice places extra burdens on the individual. Poorer Americans have fewer resources to master decision-making techniques, less social support to guide their decision-making and less of a safety net to catch them when they err.

the stress of scarcity itself can distort decision-making. Those who experienced stress as children often perceive threat more acutely and live more defensively.

The explosion of choice means we all need more help understanding the anatomy of decision-making.

living in an area of concentrated poverty can close down your perceived options, and comfortably “relieve you of the burden of choosing life.” It’s hard to maintain a feeling of agency when you see no chance of opportunity.

In this way the choice explosion has contributed to widening inequality.

The relentless all-hour reruns of "Law and Order" in 100 channel cable markets provide direct rebuff to the touted but hollow promise/premise of wider "choice." The small group of personalities debating a pre-framed trivial point of view, over and over, nightly/daily (in video clips), without data, global comparison, historic reference, regional content, or a deep commitment to truth or knowledge of facts has resulted in many choosing narrower limits: streaming music, coffee shops, Facebook--now a "choice" of 1.65 billion users.

It’s important to offer opportunity and incentives. But we also need lessons in self-awareness — on exactly how our decision-making tool is fundamentally flawed, and on mental frameworks we can adopt to avoid messing up even more than we do.

A major part of managing Big Data projects, he says, is asking the right questions: How do you define the problem? What data do you need? Where does it come from? What are the assumptions behind the model that the data is fed into? How is the model different from reality?

Society might be well served if the model makers pondered the ethical dimensions of their work as well as studying the math, according to Rachel Schutt, a senior statistician at Google Research. “Models do not just predict, but they can make things happen,” says Ms. Schutt, who taught a data science course this year at Columbia. “That’s not discussed generally in our field.”

the increasing use of software that microscopically tracks and monitors online behavior has raised privacy worries. Will Big Data usher in a digital surveillance state, mainly serving corporate interests?

my bigger concern is that the algorithms that are shaping my digital world are too simple-minded, rather than too smart. That was a theme of a book by Eli Pariser, titled “The Filter Bubble: What the Internet Is Hiding From You.”

Technology has rewarded sprinters (people who can recognize and alertly post a message on Twitter about some interesting immediate event) and marathoners (people who can write large conceptual stories), but it has hurt middle-distance runners (people who write 800-word summaries of yesterday’s news conference).

Technology has rewarded graphic artists who can visualize data, but it has punished those who can’t turn written reporting into video presentations.

More generally, the age of brilliant machines seems to reward a few traits.

First, it rewards enthusiasm. The amount of information in front of us is practically infinite; so is that amount of data that can be collected with new tools. The people who seem to do best possess a voracious explanatory drive, an almost obsessive need to follow their curiosity.

Second, the era seems to reward people with extended time horizons and strategic discipline.

a human can provide an overall sense of direction and a conceptual frame. In a world of online distractions, the person who can maintain a long obedience toward a single goal, and who can filter out what is irrelevant to that goal, will obviously have enormous worth.

Third, the age seems to reward procedural architects. The giant Internet celebrities didn’t so much come up with ideas, they came up with systems in which other people could express ideas: Facebook, Twitter, Wikipedia, etc.

One of the oddities of collaboration is that tightly knit teams are not the most creative. Loosely bonded teams are, teams without a few domineering presences, teams that allow people to think alone before they share results with the group. So a manager who can organize a decentralized network around a clear question, without letting it dissipate or clump, will have enormous value.

Fifth, essentialists will probably be rewarded.

creativity can be described as the ability to grasp the essence of one thing, and then the essence of some very different thing, and smash them together to create some entirely new thing.

In the 1950s, the bureaucracy was the computer. People were organized into technocratic systems in order to perform routinized information processing.

now the computer is the computer. The role of the human is not to be dispassionate, depersonalized or neutral. It is precisely the emotive traits that are rewarded: the voracious lust for understanding, the enthusiasm for work, the ability to grasp the gist, the empathetic sensitivity to what will attract attention and linger in the mind.

Unable to compete when it comes to calculation, the best workers will come with heart in hand.

here is a truth with which I hope we can all agree. Our subjective system of cognition can be dangerous. It can produce perceptions that conflict with the evidence, what I call The Perception Gap, which can in turn produce profound harm.

The Perception Gap can lead to disagreements that create destructive and violent social conflict, to dangerous personal choices that feel safe but aren’t, and to policies more consistent with how we feel than what is in fact in our best interest. The Perception Gap may in fact be potentially more dangerous than any individual risk we face.

We need to recognize the greater threat that our subjective system of cognition can pose, and in the name of our own safety and the welfare of the society on which we depend, do our very best to rise above it or, when we can’t, account for this very real danger in the policies we adopt.

we have an obligation to confront our own ideological priors. We have an obligation to challenge ourselves, to push ourselves, to be suspicious of conclusions that are too convenient, to be sure that we're getting it right.

subjective cognition is built-in, subconscious, beyond free will, and unavoidably leads to different interpretations of the same facts.

Views that have more to do with competing tribal biases than objective interpretations of the evidence create destructive and violent conflict.

beauty is very much about familiarity and it’s reinforcing an idea we have already. It’s like when we go on holiday, all we really want to do is take the photograph that we’ve seen in the brochure. Because our idea of beauty is constructed, by family, friends, education, nationality, race, religion, politics, all these things

I have found the 21st-century version of the Venetian secret and it is a mathematical formula. What you do, you get a half-decent, non-offensive kind of idea, then you times it by the number of studio assistants, and then you divide it with an ambitious art dealer, and that equals number of oligarchs and hedge fund managers in the world.

the nearest we have to an empirical measure of art that actually does exist is the market. By that reckoning, Cézanne’s “Card Players” is the most beautiful lovely painting in the world. I find it a little bit clunky-kitsch but that’s me. It’s worth $260m.

The opposite arguments are that it’s art for art’s sake and that’s a very idealistic position to take. Clement Greenberg, a famous art critic in the 1950s, said that art will always be tied to money by an umbilical cord of gold, either state money or market money. I’m pragmatic about it: one of my favourite quotes is you’ll never have a good art career unless your work fits into the elevator of a New York apartment block.

there’s one thing about that red painting that ends up in Sotheby’s. It’s not just any old red painting. It is a painting that has been validated. This is an important word in the art world and the big question is: who validates? There is quite a cast of characters in this validation chorus that will kind of decide what is good art. They are a kind of panel, if you like, that decides on what is good quality, what are we going to end up looking at?

They include artists, teachers, dealers, collectors, critics, curators, the media, even the public maybe. And they form this lovely consensus around what is good art.

there were four stages to the rise of an artist. Peers, serious critics and collectors, dealers, then the public.

Another member of that cast of validating characters is the collectors. In the 1990s, if Charles Saatchi just put his foot over the threshold of your exhibition, that was it. The media was agog and he would come in and Hoover it up. You do want the heavyweight collector to buy your work because that gives it kudos. You don’t want a tacky one who is just buying it to glitz up their hallway.

The next part of this chorus of validation are the dealers. A good dealer brand has a very powerful effect on the reputation of the artist; they form a part of placing the work. This is a slightly mysterious process that many people don’t quite understand but a dealer will choose where your work goes so it gains the brownie points, so the buzz around it goes up.

now, of course, galleries like the Tate Modern want a big name because visitor numbers, in a way, are another empirical measure of quality. So perhaps at the top of the tree of the validation cast are the curators, and in the past century they have probably become the most powerful giver-outers of brownie points in the art world.

ach of the encounters with these members of the cast of validation bestows upon the work, and on the artist, a patina, and what makes that patina is all these hundreds of little conversations and reviews and the good prices over time. These are the filters that pass a work of art through into the canon.

So what does this lovely consensus, that all these people are bestowing on this artwork, that anoints it with the quality that we all want, boil down to? I think in many ways what it boils down to is seriousness. That’s the most valued currency in the art world.

The whole idea of quality now seems to be contested, as if you’re buying into the language of the elite by saying, “Oh, that’s very good.” How you might judge this work is really problematic because to say it’s not beautiful is to put the wrong kind of criteria on it. You might say, “Oh, it’s dull!” [And people will say] “Oh, you’re just not understanding it with the right terms.” So I think, “Well, how do we judge these things?” Because a lot of them are quite politicised. There’s quite a right-on element to them, so do we judge them on how ethical they are, or how politically right-on they are?

What I am attempting to explain is how the art we see in museums and in galleries around the world, and in biennales – how it ends up there, how it gets chosen. In the end, if enough of the right people think it’s good, that’s all there is to it. But, as Alan Bennett said when he was a trustee of the National Gallery, they should put a big sign up outside saying: “You don’t have to like it all.”

Or then again I might say, “Well, what do I judge them against?” Do I judge them against government policy? Do I judge them against reality TV? Because that does participation very well. So, in the end, what do we do? What happens to this sort of art when it doesn’t have validation? What is it left with? It’s left with popularity.

Then, of course, the next group of people we might think about in deciding what is good art is the public. Since the mid-1990s, art has got a lot more media attention. But popularity has always been a quite dodgy quality [to have]. The highbrow critics will say, “Oh, he’s a bit of a celebrity,” and they turn their noses up about people who are well known to the public

“[Science] requires technical skill and it is a process of creating something new where you cannot always predict the outcome.”

Many scientists work under the principle that beauty and simplicity often underlie phenomena in nature,” says biophysicist Joshua Shaevitz. His work, “The history of gliding,”

is a dazzling array of colorful filaments made by tracking the paths of hundreds of thousands of the social bacterium Myxococcus xanthus. “The process of scientific research often seems dull from the outside, but on the inside there are stunningly beautiful elements to all aspects of nature,” says Shaevitz.

Another change that interested the panellists was the increased number of collaborative and multiple authored papers now submitted to journals, which led them to think about the ethics of acknowledgement. In Meurig Thomas’s view the author is, simply, “the person that primarily thinks about the experiment, plans it, and writes it. I can sleep more comfortably at night this way. If I claim to be a senior author, I have to write it and I have to concoct what the experiment was, and defend it.” Chaloner suggested that authorship has grown “because of the pressure for people to have publications in their names”, with an “agreement to let you come onto this paper and I’ll get on yours next time”. Frith referred to this as “gaming”.

Despite all of the technological developments in the last fifty years, there has been no quick or easy response to questions over refereeing, and the event ended with the feeling that although there is no doubt technology has transformed the way science is communicated, its effect has not invariably simplified the process.

audited existing maps for 174 infectious diseases of clinical importance. Following a huge systematic review, they scored the maps for each disease according to how much of the known global range is covered and the quality of the data—whether they were up-to-date and whether they relied on accurate measures like molecular diagnostics or GPS coordinates, rather than unverified expert opinion.

even the highest-scoring diseases have room for improvement.

. They argue that technology can help to plug the gaps in our maps in the future, and they point to several untapped sources of data. For example, both PubMed and GenBank, which collect biomedical literature and gene sequences respectively, contain geospatial information for the majority of diseases that the team reviewed. And social networks like Twitter can provide invaluable real-time clues about spreading symptoms and illnesses, often tagged with geographical information. During the 2009 outbreak of H1N1 swine flu, for example, Twitter predicted outbreaks 1 or 2 weeks ahead of traditional surveillance measures.

I struggled because governments or researchers wouldn’t share their information,” he said. “But there was all this incredible knowledge on the web being discussed through professional networks or news media.”

believes that the problem now is not a lack of data but a deluge of it. Sites like HealthMap and BioCaster are already using learning algorithms to filter online sources for information relevant to infections. They are also using crowdsourcing tools that ask online volunteers to check if flagged social media chatter actually relates to the disease of interest.

But perhaps the paper by Liao, Sandberg and Roache will turn out to be a prank played on the journal, like the Sokal hoax, named after the physicist whose paper deploying post-modern gobbledegook to show that “quantum gravity is a social and linguistic construct” was published in a cultural studies journal.

It’s easy to imagine academics sitting around swapping the most outrageous solutions to climate change and then daring one another to have them published. I hope this will turn out to be the case. In the meantime I cringe at the thought of what the long-dead giants of Western philosophy would make of their discipline’s response to the climate crisis.

“We’re at the beginning of a 10-year period where we’re going to transition from computers that can’t understand language to a point where computers can understand quite a bit about language.”

E-discovery technologies generally fall into two broad categories that can be described as “linguistic” and “sociological.”

The most basic linguistic approach uses specific search words to find and sort relevant documents. More advanced programs filter documents through a large web of word and phrase definitions.

The sociological approach adds an inferential layer of analysis, mimicking the deductive powers of a human Sherlock Holmes

When you consider the alternative — an anesthetized dream of self-sufficiency, abetted by technology — pain emerges as the natural product and natural indicator of being alive in a resistant world. To go through a life painlessly is to have not lived.

Yahoo! News — the biggest news site on the Web — is personalized, and even mainstream sites like those of the New York Times and the Washington Post are giving more space to personalized recommendations. As Google executive chairman Eric Schmidt has said, "It will be very hard for people to watch or consume something that is not tailored for them."

when technology changes the travel experience itself — from immersion and surprise to documentary one-upmanship — it defeats the point of the journey. We travel to freshen senses dulled by routine. We travel for discovery and reinvention.

a park ranger in Washington State told me about a group of kids trying to get a fix on 500-year-old trees at the lower elevation of Mount Rainier. They could not fully fathom what they were experiencing, he said, until they could filter it through their phones — as pictures or Wikipedia definitions. Nature deficit disorder, so called, is a symptom of being connected to everything, while being unable to connect to anything.

. Parents have more to spend if they only have to fork out for one wedding (they usually share costs with the spouse-to-be’s family).

The result is evident in weddings, which now focus on the couple. Both sets of parents are represented, but their position is peripheral. Weddings often feature a day of wedding photos, shot before the event, with the couple in a range of outfits against romantic backgrounds, but with no family members.

Scientists have done studies where they give people different colored candies and ask if they taste differently

Your brain is constantly filtering it through your sense of taste, touch, smell, and – most importantly – your memories.

The human eye is actually really bad at perceiving color.

Your brain has to fill in the gaps.

"When color is processed by the brain, a lot of information has to be extracted from not very much incoming information," said Mathan. "The color that we perceive doesn't correspond - at all - with the colors that are in the world."