#MammothMonday: PUP’s pups sound off on How to Clone a Mammoth

The idea of cloning a mammoth, the science of which is explored in evolutionary biologist and “ancient DNA expert” Beth Shapiro’s new book, How to Clone a Mammoth, is the subject of considerable debate. One can only imagine what the animal kingdom would think of such an undertaking, but wonder no more. PUP staffers were feeling “punny” enough to ask their best friends:

 

Chester reads shapiro

Chester can’t get past “ice age bones”.

 

Buddy reads shapiro

Buddy thinks passenger pigeons would be so much more civilized… and fun to chase.

 

Tux reads shapiro

Tux always wanted to be an evolutionary biologist…

 

Stella reads Shapiro

Stella thinks 240 pages on a glorified elephant is a little excessive. Take her for a walk.

 

Murphy reads shapiro

A mammoth weighs how much?! Don’t worry, Murphy. The tundra is a long way from New Jersey.

 

Glad we got that out of our systems. Check out a series of original videos on cloning from How to Clone a Mammoth author Beth Shapiro here.

Yes, the Armenian genocide was just that, says Ronald Suny’s new book

Suny jacketApril 24th marks the 100th anniversary of the start of the Armenian genocide, the first genocide of the 20th century, though lesser-known, and more contested than other crimes against humanity that followed. Ronald Suny’s “They Can Live in the Desert but Nowhere Else”: A History of the Armenian Genocide claims that the massacres did indeed constitute genocide, and chronicles the human catastrophe through eyewitness accounts and archival documents. The end result is a deeply researched narrative history of how and why the atrocities were committed. The Sunday Times writes, “Suny is admirably dispassionate in explaining the particular circumstances that led the Ottoman government to embark on a policy of mass extermination…”

Check out this video where Suny, Charles Tilly Collegiate Professor of History at the University of Michigan, gives an overview of the genocide’s history, Turkey’s denial, and his own Armenian family’s experience:

Michael Chwe explains common knowledge, and why it matters to Mark Zuckerberg

Michael Chwe for UCOMM - 130321Michael Chwe, whose book, Rational Ritual: Culture, Coordination, and Common Knowledge has, in his words, “made its way out of the backwaters of course syllabi” to catch the attention of Mark Zuckerberg, had a terrific piece on the Monkey Cage blog of the Washington Post explaining exactly what common knowledge is, and why it’s so important. According to Chwe, common knowledge is generated by large scale social media platforms like Facebook, and this matters because of the many ways it can be leveraged, among them, stopping violence against women, and helping to foster collective political action.

From his piece on the Washington Post:

When Facebook’s Mark Zuckerberg chose my book “Rational Ritual” last week for his “A Year of Books” book club, I was surprised. “Rational Ritual” came out in 2001, and has somehow slowly made its way out of the backwaters of course syllabi into the elevated spheres of technology companies. This is gratifying to me, because even though it is a scholarly book published by a university press, “Rational Ritual” is essentially a popularization.

“Rational Ritual” tries to popularize the concept of “common knowledge” as defined by the philosopher David Lewis and the sociologist Morris Friedell in 1969. A fact or event is common knowledge among a group of people if everyone knows it, everyone knows that everyone knows it, everyone knows that everyone knows that everyone knows it, and so on.

When I was a graduate student in economics in the late 1980s, most people considered common knowledge as an idea of only theoretical interest. People who thought about collective action (and its flip side, political repression) were mostly interested in the problem of free riding, rather than how people communicate. But social change isn’t just about tackling incentives to free ride – it’s also a problem of coordination.

Read the rest here.

Recently, Michael Chwe, a master of interdisciplinary applications for otherwise “rarified mathematical theories” has been particularly active in exploring how game theory can help curb sexual violence. Check out his piece on the topic on the PBS Newshour blog here. His recent Q&A with Facebook Books is up here.

March Mathness 2015: The Wrap Up

balls

The champion has been crowned! After an eventful and surprising March Madness tournament, Duke has been named the new NCAA national champion.

A year of bragging rights goes to PUP paperbacks manager Larissa Skurka (98.6 percent) and PUP executive math and computer science editor Vickie Kearn (98.4 percent), who took first and second place in our ESPN bracket pool. Congrats to both! Check out all of the results here.

As we wrap up March Mathness, here are two final guest posts from basketball fans who used math and Tim Chartier‘s methods to create their brackets.

 Swearing by Bracketology

By Jeff Smith

My name is Jeff Smith, and I’ve been using Tim Chartier’s math algorithms to help with my March Madness brackets for several years now. I met Tim when we were traveling the ‘circuit’ together in creative ministries training. You may only know Tim for his math prowess, but I knew him for his creativity before I knew he was a brilliant mathematician. He and his wife, Tanya, are professional mimes, and his creativity is genius too.

Several years ago, he mentioned his method for picking brackets at a conference where we were doing some training together. He promised to send me the home page for his site and I could fill out my brackets using his parameters and formula. I was excited to give it a shot. Mainly, because I am part of a men’s group at our church that participates in March Madness brackets every year. Bragging rights are a big deal…for the whole year. You get the picture.

Also, I have two boys who did get one of my genes: the competitive edge. I sat down and explained the process. Because they did not know Tim, they were a little more skeptical, but I promised it wouldn’t hurt to try. That year, in a pool of 40+ guys, we all finished in the top ten. We were all hooked!

Since then, I have contacted Tim each year and reminded him to send me the link to his site where I could put in our numbers to fill out our brackets. Generally, the three of us each incorporate different parameters because we have different philosophies about the process. It has become a family event, where we sit around the dinner table; almost ceremonially, and we take our output and place them in the brackets. The submission is generally preceded by trash talking, prayer, and fasting. (Well, probably not the fasting, because we fill up with nachos and chips during the process.)

Jeff post

Men of March Mathness: Jeff, Samuel, Ben Smith.

This year, I was in South Africa on a mission trip during the annual ritual. Thank God for video chatting and internet access. Halfway across the world, we were still able to be together and place our brackets into the pool. It was such a wonderful experience. While my boys veered from the path, picking intuitively instead of statistically, I didn’t stray far. (I was strong!) If it wouldn’t have been for Villanova, whom I will never choose again in a bracket, I would be leading the pack. But, I’m still in the top ten of the men’s bracket at my church, with an outside shot of winning. In the Princeton bracket, I’m doing even better because I stayed away from the guessing game a little more.

I do not follow college basketball during the season. I’m from central Pennsylvania, and Penn State doesn’t have a good basketball team. So, I have no passion for the basketball season. Periodically, I’ll watch a game because my boys are watching, but generally, basketball season is the long wait until baseball season. (Go Pirates!) So, March Mathness has saved my reputation. It makes me look like a genius. Other guys in the group are looking at my bracket for answers. My boys and I are sworn to secrecy about the formula. The only reason I write this is because I’m sure none of them read this blog! But I’m thankful for Tim and the formula and the chance to look good in front of friends. I have never won the pool, however, if you factor my finishes over the course of the years I have been using Tim’s formula, I have the best average of all the guys.

 

 What Do Coaches Have to Do with It?

By Stephen Gorman, College of Charleston student

PUPSelfie2

It’s that time of year again. The time of year when everyone compares brackets to see who did the best. But if your bracket was busted early, don’t worry — you’re not the only one. In fact, nobody came out of the tournament with a perfect bracket.

The unpredictability of these games is an inescapable fact of March Madness. This tournament is so incredibly unpredictable that some people are willing to give out billions to anyone who can create a perfect bracket; Warren Buffett is one of these people. So is he crazy? Or does he realize your odds of creating a perfect bracket are 52 billion times worse than winning the Powerball. In layman’s terms – if you think playing the lottery is crazy, trying to create the perfect bracket is insane.

However, once you can accept the statistics, predicting March Madness becomes a game of bettering you’re odds – and there are many predictive models that can help you out along the way. Some of these models include rating methods, like the Massey method, which takes into account score differentials and strength of schedule. In addition to this, there are weighting methods that can be applied to rating methods; these take into account the significance of particular games and even individual player statistics. However, I noticed there is one thing missing from these predictive models: a method that quantifies the value of a good coach. In order to take into account the importance of a coach, a fellow researcher (John Sussingham) and I decided to create our own rating system for coaches.

Using data available from SportsReference.com, we made a system of rating that incorporated such factors as the coach’s career win percentage, March Madness appearances, and the record of success in March Madness. But before we implemented it, we wanted to justify that it was, indeed, a good way to quantify the strength of a coach. In order to do this, we tested the coach ratings in two ways. The first way being a comparison between how sports writers ranked the top 10 College Basketball coaches of all time and what our coach ratings said were the best coaches of all time. The second way was to test how the coach ratings did by themselves at predicting March Madness.

The comparison of the rankings are shown in the table below:

Rank Our Results CBS Sports Results Bleacher Report Results
1 John Wooden John Wooden John Wooden
2 Mike Krzyzewski Mike Krzyzewski Bobby Knight
3 Adolph Rupp Bob Knight Mike Krzyzewski
4 Jim Boeheim Dean Smith Adolph Rupp
5 Dean Smith Adolph Rupp Dean Smith
6 Roy Williams Henry Iba Jim Calhoun
7 Jerry Tarkanian Phog Allen Jim Boeheim
8 Al McGuire Jim Calhoun Lute Olson
9 Bill Self John Thompson Eddie Sutton
10 Jamie Dixon Jim Boeheim Jim Phelan

It is clear from the table above that there are striking similarities between all three rankings. This concluded our first test.

For the second test, we decided to use the coach ratings to predict the last fourteen years of March Madness. The results showed that over the last fourteen years, on average, coach ratings had 68.4 precent prediction accuracy and an ESPN bracket score of 946. As a comparison, the uniform (un-weighted) Massey method of rating (over the same timespan) had an average prediction accuracy of 65.2 precent and an average ESPN bracket score of 1006. Having a higher prediction accuracy, but lower ESPN bracket score essentially means that you have predicted more games correctly in the beginning of the tournament, but struggle in the later rounds. This comes to show that not only are these ratings good at predicting March Madness, but they stand their ground when compared to the effectiveness of very popular methods of rating.

To conclude this article, we decided that, this year, we would combine both the Massey ratings and our Coach ratings to make a bracket for March Madness. Over the last fourteen years, the combination-rating had an average prediction accuracy of 66.33 percent and an average ESPN bracket score of 1024. It’s interesting to note that while the prediction accuracy went down from just using the Coach ratings, the ESPN bracket score went up significantly. Even more interestingly, both the prediction accuracy and the ESPN Bracket score were better than uniform Massey.

This year, the combination-ratings had three out of the four Final Four teams correctly predicted with Kentucky beating Duke in the Championship. However, the undefeated Kentucky lost to Wisconsin in the Final Four. Despite this, the combination-ratings bracket still did well, finishing in the 87.6th percentile on ESPN.

Mathematics Awareness Month 2015: Math Drives Careers

Internet search, pharmaceuticals, insurance, finance, national security, medicine, ecology. What is the link between these diverse career fields? Students graduating with a mathematical sciences degree can find a professional future in all of these fields, and a wide range of others as well. This year’s Mathematics Awareness Month takes a step out of the classroom to show just where mathematics can lead after graduation.

Mathematics Awareness Month is an annual celebration dedicated to increasing public understanding of and appreciation for mathematics. The event, which started in 1986 as Mathematics Awareness Week, adopts a different theme each year. This year’s theme is “Math Drives Careers,” and PUP is excited to bring you a series of guest posts from our authors. Check back all this month for posts about using math to raise revenues, to understand sports and economics, and to solve complex problems.

The organizers of Mathematics Awareness Month explain the importance of mathematics in today’s workforce:

“Innovation is an increasingly important factor in the growth of world economies. It is especially important in key economic sectors like manufacturing, materials, energy, biotechnology, healthcare, networks, and professional and business services. The advances in and applications of the mathematical sciences have become drivers of innovation as new systems and methodologies have become more complex. As mathematics drives innovation, it also drives careers.”
Check out this official Mathematics Awareness Month poster, which includes career descriptions for 10 individuals who used their love for math to find rewarding careers:

 

MAM2015_8.5x11

Follow along with @MathAware and take a look at Math Awareness Month on Facebook.

Davidson student hangs onto 97 percent March Madness ranking

Are you still mourning the loss of your perfect bracket after the multiple upsets this March Madness season? Even before the Villanova and NC State match up on Saturday, 99.3 percent of brackets were busted. As experts deem a perfect March Madness bracket impossible, having a nearly perfect bracket is something to brag about. Today, we hear from David College student Nathan Argueta, who argues that knowing a thing or two about math can help with March Madness strategy.

balls

March Mathness: Calculating the Best Bracket

First and foremost… I am far from a Math Major and, prior to this class, the notion that math and sports going hand in hand seemed much more theoretical than based in reality. Now, 48 games later and a 97.2% ranking percentage on ESPN’s Bracket Contest has me thinking otherwise.

In Finite Math, we have explored the realms of creating rankings for teams based on multiple factors (win percentage, quality wins, etc.). Personally, I also take into account teams’ prior experience in the NCAA Tournament. Coaches with experience in the Sweet 16, Final Four, and Championship Game (like Rick Pitino out of Louisville) also factored into my decisions when deciding close games. Rick Pitino has made the Sweet Sixteen for each of the past four years. With a roster whose minutes are primarily distributed amongst second and third year players (players who have had success in the NCAA tournament in the past couple of years) I found it difficult to picture Louisville losing to either UCI, UNI, or even the upcoming battle against upstart NC State (who have successfully busted the majority of brackets in our class’s circuit by topping off Villanova).

In theory, the quest to picking the best bracket on ESPN begins and ends with establishing rankings for each team in the contest. Sure there are four of each seeding (1’s, 2’s, etc.), yet these rankings are very discombobulating when attempting to decide which team will win between a 5th seed and a 12th seed or a 4th seed and a 13th seed. One particular matchup that I found extremely interesting was the one between 13th seeded Harvard and 4th seeded UNC. Gut reaction call—pick UNC. UNC boasts a higher ranking and has ritual success in the postseason. But hold on—Harvard had a terrific record this year (much better than UNC’s, albeit in an easier conference). The difficult thing about comparing Harvard and UNC, however, became this establishment of difficulty of schedule. I nearly chose Harvard, were it not for the fact that Harvard got beaten by about 40 points against UVA while UNC put up more of a fight and only lost by 10 points.

In order to pick the perfect bracket (which mind you, will never happen), categorizing and ranking teams based on their wins against common opponents with prior sports knowledge is imperative. My school pride got the better of me when I chose Davidson to advance out of the Round of 64 against Iowa simply because I disregarded factors like momentum, size, and location. Looking back, it is no wonder that Davidson lost by over 30 points in what many pundits were looking to be a potential upset match. While mathematically our team’s chances could have more than competed against Iowa, in reality our season was spiraling downwards out of control since the second round of the Atlantic 10 Tournament in which we hardly beat out a surprising La Salle team and got annihilated by an injury plagued VCU team that we shut-out just nine days before. Moral of the story… brackets will be brackets and while math can certainly guide you towards a higher ranking in your class pool, you can kiss perfection good-bye. This is March Madness.

Afghanistan President Ashraf Ghani mentions LOST ENLIGHTENMENT before Congress

Last night, Afghan President Ashraf Ghani and Afghan Chief Executive Abdullah were honored at a dinner held in the Ben Franklin Room. President Ashraf Ghani addressed the attendants of the dinner and stated, “[I]f there’s one book that you want to read please do read LOST ENLIGHTENMENT. [T]he story that Fred tells is not the story of the past. Its good news is that it’s the story of the future.” Read the transcript of the event, here.

LOST ENLIGHTENMENT is available in hardcover and will be released in paperback this June. Read the first chapter of this must-read for free, here.


 

bookjacket

Lost Enlightenment:
Central Asia’s Golden Age from the Arab Conquest to Tamerlane

S. Frederick Starr

Cinderella stories? A College of Charleston student examines March Madness upsets through math

Drew Passarello, a student at the College of Charleston, takes a closer look at how math relates to upsets and predictability in March Madness.

balls

The Madness is coming. In a way, it is here! With the first round of the March Madness tournament announced, the craziness of filling out the tournament brackets is upon us! Can math help us get a better handle on where we might see upsets in March Madness? In this post, I will detail how math helps us get a handle on what level of madness we expect in the tournament. Said another way, how many upsets do we expect? Will there be a lot? We call that a bad year as that leads to brackets having lower accuracy in their predictions. By the end of the article, you will see how math can earmark teams that might be on the cusp of upsets in the games that will capture national attention.

Where am I learning this math? I am taking a sports analytics class at the College of Charleston under the supervision of Dr. Tim Chartier and Dr. Amy Langville. Part of our work has been researching new results and insights in bracketology. My research uses the Massey and Colley ranking methods. Part of my research deals with the following question: What are good years and bad years in terms of March Madness? In other words, before the tournament begins, what can we infer about how predictable the tournament will be?

One way of answering this question is to see how accurate one is at predicting the winners of the tournaments coupled with how high one’s ESPN score is. However, I also wanted to account for the variability of the level of competition going into the tournament, which is why I also looked at the standard deviation of the ratings of those in March Madness. A higher standard deviation implies the more spread out the playing level is. Ultimately, a good year will have a high tournament accuracy, high ESPN score, and a high standard deviation of ratings for those competing in March Madness. Similarly, a bad year will have low tournament accuracy, low ESPN score, and a low standard deviation of the ratings. This assessment will be relative to the ranking method itself and only defines good years and bad years solely in terms of past March Madness data.

I focused on ratings from uniformly weighted Massey and Colley ranking methods as the weighting might add some bias. However, my simple assessment can be applied for other variations of weighting Massey and Colley. I found the mean accuracy, mean ESPN score, and mean standard deviation of ratings of the teams in March Madness for years 2001 – 2014, and I then looked at the years which rested below or above these corresponding means. Years overlapping were those deemed to be good or bad, and the remaining years were labeled neutral. The good years for Massey were 2001, 2004, 2008, and 2009, and the bad years were 2006, 2010 – 2014. Neutral years were 2002, 2003, and 2007. Also, for Colley, the good years were 2005, 2007 – 2009; bad years were 2001, 2006, and 2010 – 2014; neutral years were 2002 – 2004. A very interesting trend I noticed from both Massey and Colley was that the standard deviation of the ratings of those in March Madness from 2010 to 2014 were significantly lower than the years before. This leads me to believe that basketball has recently become more competitive in terms of March Madness, which would also partially explain why 2010 – 2014 were bad years for both methods. However, this does not necessarily imply 2015 will be a bad year.

In order to get a feel for how accurate the ranking methods will be for this year, I created a regression line based on years 2001 – 2014 that had tournament accuracy as the dependent variable and standard deviation of the ratings of those in March Madness as the independent variable. Massey is predicted to have 65.81% accuracy for predicting winners this year whereas Colley is predicted to have 64.19%accuracy. The standard deviation of the ratings for those expected to be in the tournament was 8.0451 for Massey and 0.1528 for Colley, and these mostly resemble the standard deviation of the ratings of the March Madness teams in 2002 and 2007.

After this assessment, I wanted to figure out what defines an upset relative to the ratings. To answer this, I looked at season data and focused on uniform Massey. Specifically for this year, I used the first half of the season ratings to predict the first week of the second half of the season and then updated the ratings. After this, I would use these to predict the next week and update the ratings again and so on until now. For games incorrectly predicted, the median in the difference of ratings was 2.2727, and the mean was 3.0284. I defined an upset for this year to be those games in which the absolute difference in the ratings is greater than or equal to three. This definition of an upset is relative to this particular year. I then kept track of the upsets for those teams expected to be in the tournament. I looked at the number of upsets each team had and the number of times each team gets upset, along with the score differential and rating differences for these games. From comparing these trends, I determined the following teams to be upset teams to look for in the tournament: Indiana, NC State, Notre Dame, and Georgetown. These teams had a higher ratio of upsets over getting upset when compared to the other teams. Also, these teams had games in which the score differences and rating differences were larger than those from the other teams in March Madness.

I am still working on ways to weight these upset games from the second half of the season, and one of the approaches relies on the score differential of the game. Essentially, teams who upset teams by a lot of points should benefit more in the ratings. Similarly, teams who get upset by a lot of points should be penalized more in the ratings. For a fun and easy bracket, I am going to weight upset games heavily on the week before conference tournament play and a week into conference tournament play. These two weeks gave the best correlation coefficient in terms of accuracy from these weeks and the accuracy from March Madness for both uniform Massey and Colley. Let the madness begin!

 

Christopher Bail talks to Salon about “Terrified”

Christopher Bail, author of Terrified: How Anti-Muslim Fringe Organizations Became Mainstream, recently spoke with Paul Rosenberg for a feature in Salon on how anti-Muslim sentiment is fostered by the broader cultural landscape, and the innovative new methodology he has used to study that process. Paul Rosenberg at Salon writes:

It may be hard to fathom or remember, but in the immediate aftermath of 9/11 the American public responded with an increased level of acceptance and support for Muslims. President Bush—who had successfully courted the Muslim vote in 2000—went out of his way to praise American Muslims on numerous occasions in 2001 and 2002. However, the seeds were already being planted that would change that drastically over time.  Within a few short years, a small handful of fringe anti-Muslim organizations—almost entirely devoid of any real knowledge or expertise, some drawing on age-old ethno-religious conflicts—managed to hijack the public discourse about Islam, first by stoking fears, grabbing attention with their emotional messaging, then by consolidating their newfound social capital, forging ties with established elite organizations, and ultimately building their own organizational and media infrastructure.

How this all happened is the subject of a fascinating new book, “Terrified: How Anti-Muslim Fringe Organizations Became Mainstream,” by sociologist Christopher Bail, of the University of North Carolina.  The book not only lays bare the behind-the-scenes story of a momentous shift in public opinion, it employs cutting-edge computer analysis techniques applied to large archives of data to develop a new theoretical outlook, capable of making sense of the whole field of competing organizations struggling to shape public opinion, not just studying one or two the most successful ones. The result is not only a detailed account of a specific, significant, and also very pernicious example of cultural evolution, but also a case study in how to more rigorously study cultural evolution more generally in the future. In the process, it sheds considerable light on the struggles involved, and the difficulties faced by those trying to fight back against this rising tide of misdirected fear, anger and hatred.


Read the full interview with Christopher Bail that follows here.

Terrified, by Christopher Bail

May the odds be in your favor — March Mathness begins

Let the games begin! After the excitement of Selection Sunday, brackets are ready for “the picking.” Have you started making your picks?

Check out the full schedule of teams selected yesterday, and join the fun by submitting a bracket to the official Princeton University Press March Madness tournament pool.

Before you do, we recommend that you brush up on your bracketology by checking out PUP author Tim Chartier’s strategy:

 

 

For more on the math behind the madness, head over to Dr. Chartier’s March Mathness video page. Learn three popular sport ranking methods and how to create March Madness brackets with them. Let math make the picks!

Be sure to follow along with our March Mathness coverage on our blog, and comment below with your favorite strategy for making March Madness picks.

#TheDress: Consulting the experts on color

White and gold or blue and black are the questions that have been taking the world by storm. For those who managed to miss it, #TheDress is a picture that has been floating around the Internet. Some say it’s white and gold, while others swear by black and blue. Others have even switched their allegiances. Amazingly, one dress has sparked a huge debate over color and how humans perceive it.

Neuroscientists have started to chime in on the discussion with scientific evidence. If you are curious about neuroscience perhaps want to provide some concrete reasoning for your color choice, or would like to read more on the social history of color, check out these two books:


 

bookjacket Colour:
Why the World Isn’t Grey
Hazel Rossotti

 

bookjacket Black:
The History of a Color
Michel Pastoureau

 

CLIMATE SHOCK authors on TheAtlantic.com: Will camels roam Canada again?

Climate ShockThe last time concentrations of carbon dioxide were as high as they are today, write Marty Weitzman and Gernot Wagner, authors of Climate Shock: The Economic Consequences of a Hotter Planet, camels lived in Canada. That was a bit over 3 million years ago, of course. But how certain does science have to be for the world to act? Wagner and Weitzman had a terrific op-ed appear today on The Atlantic.com where they argue that climate is best thought of as a global-scale risk management problem. Check it out here:

Will Camels Roam Canada Again?

What we know about climate change is bad enough. What we don’t could make it even worse.

Gernot Wagner and Martin L. Weitzman

You are cruising down the highway at 65 miles per hour, reading a book in your self-driving car. Your life is in the hands of a machine—an eminently benevolent one. Meanwhile, in the lane next to you, an 18-wheeler using decidedly last-century technology—relying on a fallible human driver—appears to be swerving your way.

Your car’s computer is on the case. Equipped with orders of magnitude more computing power than the Apollo moon lander, it determines with all the confidence it can muster that there’s a greater-than-50-percent chance—it’s “more likely than not”—that the truck is about to hit you.

You may want to look up from your book. More importantly, you want to know with certainty that your onboard computer will hit the brakes, even if there’s a 49-percent chance that doing so will be a false alarm.

If, instead of “more likely than not,” the danger were “likely,” “very likely,” or even “extremely likely,” the answer would be clearer still. Even if there’s a 95-percent probability of a crash, there’s still a 1-in-20 chance that nothing will happen—but no one would gamble their life on those odds. Your car’s computer hopefully will have engaged the anti-lock braking systems already.

A perfect self-driving car doesn’t exist yet, nor has the world solved global warming. But it’s surprising that, by the standards that we’d expect in a car to keep its occupants safe, the governments of the world haven’t stepped on the brakes to avoid planetary-scale global warming disaster—a 100-year-storm hitting New York every other year, frequent and massive droughts, inundated coastal cities. In 1995, the Intergovernmental Panel on Climate Change declared that it was “more likely than not” the case that global warming was caused by human activity. By 2001, it had progressed to “likely.” By 2007, it was “very likely.” By 2013, it was “extremely likely.” There’s only one step left in official IPCC lingo: “virtually certain.”

Read the rest at The Atlantic.com here.