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Scientific method

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Original author: 
Jeffrey Kluger

For Jeffrey Kluger’s feature on animal grieving in this week’s issue, TIME reached out to noted animal photographer Charlotte Dumas, who has been making deeply empathetic portraits of a variety of species for years.

If animals nurture their own (which they do) and care about their kin (they do that too) why would we not assume they mourn their dead? A growing group of researchers are coming to the conclusion that animals not only grieve, but in some cases grieve deeply. That’s an easy case to make by simple observation, but not in any other way. When you’re working with animals, there’s no possibility of the self-reporting that is so central a part of studies of human psychology. But when it comes to the beasts, those observations might be enough.

There are the elephants that hold what appear to be wakes for their dead — hovering over them as they die and coming back for a week or more to mind and tend the remains. There are the crows that similarly circle a fallen flock-mate and will bring twigs in seeming tribute and even cover the remains with grass. Dogs and cats will wander their homes looking for a lost littermate or playmate and often sink into what looks for all the world like the lethargy and lack of appetite that are the hallmarks of human depression. Bonobo and baboon mothers will carry their dead babies for weeks after they’ve died — and dolphin mothers will similarly push their lost young along through the water.

Studies of brain and blood chemistry — to they extent they exist for animals — confirm that something like a grief reaction is taking place. Baboons exhibit an uptick in hormones that lead to stress and later affiliation when a member of the troop is killed by a predator, and this is especially so among the friends or close social companions of the victim. Crows show stress reactions in the amygdala, just as humans do, and that response would likely be more acute if a mate died, particularly since crows may pair off for 20 years — longer than a lot of human marriages.

(Read more: The Mystery of Animal Grief )

In all animal research there is the ever-present risk of anthropomorphism. We refract their behavior through the prism of our own because that’s what we know best. But here it makes sense. All of the beasts — humans included — exist on a sort of continuum of intelligence, emotion and social complexity. Just because we’re at the top of that heap, doesn’t mean that the beasts below us don’t have experiences to ours — even if they’re briefer, blunter, simpler. Animals are social creatures and they’re also sentient creatures. The pain of death is likely not something they’re spared.

Charlotte Dumas is a photographer based in Amsterdam. Her latest book,
Anima, features the burial horses of Arlington Cemetery.

Jeffrey Kluger is an editor-at-large at TIME, oversees the magazine’s science, health and technology reporting.

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Jeff Leek, an Assistant Professor of Biostatistics at the Johns Hopkins Bloomberg School of Public Health, is teaching a course on data analysis on Coursera, appropriately named Data Analysis.

This course is an applied statistics course focusing on data analysis. The course will begin with an overview of how to organize, perform, and write-up data analyses. Then we will cover some of the most popular and widely used statistical methods like linear regression, principal components analysis, cross-validation, and p-values. Instead of focusing on mathematical details, the lectures will be designed to help you apply these techniques to real data using the R statistical programming language, interpret the results, and diagnose potential problems in your analysis.

The course starts on January 22, 2013.

You might also be interested in Computing for Data Analysis taught by Roger Peng, who is also a biostatistics professor at John Hopkins. Leek's course is focused on statistical methods, whereas Peng's course is focused on programming. Better take both. [via Revolutions]

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Editor’s note: This post is authored by guest contributor Thor Muller, a New York Times best selling author. His latest book, “Get Lucky: How to Put Planned Serendipity to Work for You and Your Business” is available now.

This is the story of how a young Irish fine artist accidentally became a materials scientist, founding a high-growth company that created a whole new product category. It’s also a parable for how great entrepreneurs systematically create their own luck.

Jane ni Dhulchaointigh is the founder and CEO of Sugru, a London-based startup that makes an amazing moldable adhesive for repairing any physical object. It’s a cross between silly putty and duct tape, a space age rubber that can be molded into any desired shape by hand, and that sticks to a vast array of surfaces. With customers in over 100 countries, and all seven continents, Sugru has taken the world by storm.

What we see in Jane’s journey, so far from California’s tech startup scene, is the same thing we see in virtually all startups that work: the ability to harness serendipity, the unplanned discoveries, large or small, that end up being the turning points in careers and businesses. Hard work, training and process may be the foundation of success, but serendipity is where the magic happens. And even though serendipity is by definition unpredictable, its appearance is anything but random.

Jane’s stunning rise is the result of her mastering what we call the skills of planned serendipity, a set of behaviors that have allowed her, over and over again, to generate the chance discoveries, recognize the good ones, and take action on those that matter most.

Here’s how it happened, and what we can learn from her breakout success.

Start With A “Geek Brain” 

Jane originally studied to be a sculptor, an interest that had possessed her for years. She returned to school in 2003 to study commercial product design at the Royal College of Art. It seemed a prudent career move given the high demand for designers (and the lack of jobs for sculptors), but it was a switch that proved difficult. Her impulse was to follow her own interests over solving the narrowly defined product problems discussed in class. Before long, her background in sculpture combined with her insatiable curiosity led her to begin experimenting with new materials.

Jane was equipped with one of the great advantages in cultivating serendipity, a geek brain–what we define as an obsessive curiosity in an area of interest and the ability to notice anomalies, overcoming the conventional wisdom that constrains others. The geek brain gave Jane distance from the rote conventions of design school, allowing her to connect ideas from across domains in unusual ways.

Find Space to Play 

Having a mindset geared for recognizing unexpected ideas is rarely enough on its own—Jane needed an environment that allowed her to explore and put this geek brain to good use. The workshop at her college served this purpose well:

I was destroying things and putting them back together: chipping blocks of wood apart and putting them back together with other materials…One experiment I did was combining silicone caulk with very fine wood dust from the workshop. From that combination I made these fancy wooden balls. I found it fascinating that you could make something that looked like wood but had other properties—if you threw them on the floor they’d bounce.

Jane’s early explorations with her strange rubbery material was driven by a fascination with the possibilities of what she could make, rather than any specific purpose to which it could be put. This is the hallmark of a true exploratory mode, as premature focus can kill good ideas before they ever emerge. Still, as her discovery started to take shape, she began to spend more and more time wondering what it might actually be good for.

Be Opinionated 

Jane’s boyfriend noticed that she had been using her funny rubber to repair or customize things around the house—enlarging a sink plug that was too small, or making a more ergonomic knife handle. It had been so natural for her to use the rubber in this way because she personally believed in the value of repairing her things rather than running out and buying a replacement. The instinct was so natural, in fact, that she hadn’t even consciously registered what she was doing. It was only when her boyfriend drew her attention to it that she saw the opportunity in a flash.

Jane had stumbled on a product idea that mapped perfectly to a deeply held conviction: she hated waste. She was fed up with it and knew she wasn’t alone. “In the past, some people would have thought that repairing something is a compromise because you couldn’t afford to buy it new again,” Jane says. “But now there are increasing numbers of people who would rather repair or reuse than throw something out and needlessly buy something new because of the waste involved.”

Her insight was that this space-age rubber she’d invented could be an essential innovation in this cause. She saw the potential in her chance discovery only because she had an overriding purpose that gave her a unique perspective. “Every granny who finds it hard to open a jam jar can manipulate this material,” she said. “Anyone who has a stiff part on their bike can adapt it to be whatever the bike needs.”

Project the Possibility

The only problem was that the material didn’t actually exist yet. The makeshift rubber Jane had been playing with had all kinds of problems: it didn’t adhere to enough surfaces, it had a terribly short shelf-life, and it was too high maintenance to make a successful commercial product.

This was the do-or-die moment. As an artist, there was every reason in the world to give up—she had no business thinking she could solve this incredibly technical problem. Instead, Jane pulled a Jujitsu serendipity move: employing only her faulty prototype and her storytelling skills, she projected her vision as broadly as she could, telling anyone who would listen about it. Early stage entrepreneurs like Jane don’t always know what exact outcomes to expect, but they are willing to publicly put their ideas into the world, allowing them to connect with the as yet unknown people and opportunities that make their products possible.

It worked. Attention followed from the strength of her vision, attracting local press mentions, a set of science advisors, and a grant from the National Endowment for Science, Technology, and Arts.

Follow Unplanned Paths

The grant wasn’t huge, a mere £35,000, but it was enough to start testing materials—as long as Jane did the testing herself. To do that, she realized, she would have to do something that was not only unexpected, but would have seemed absurd a few months before: she’d have to diverge from her career path and be trained as a lab technician and set up her own laboratory. She wasn’t waiting around to find a CTO who knew better. This former art student must learn to be a materials scientist.

It took her two years of painstaking trial-and-error, but eventually she created a brand new, patented class of silicone that worked for her aims. Only Jane’s immovable sense of purpose kept her going through month after month of laborious formulation and failure, long before her work would bear fruit. This is a recurring paradox of serendipity: stick-to-itness—the ability to stay committed to a purpose—is often the very thing that allows new paths to be recognized and taken.

Design Openness into the Product and Company

Initially there was tremendous pressure to fit the new product into a well-worn category that the traditional business world would understand. Then it struck Jane that she could create a brand designed to activate the creative spark in people. She could leave the product’s purpose intentionally open—the tagline would become “Hack Things Better”—so that customers could use their own imagination. One of the first things she did after launching the product was create an online community for customers to share their ideas. Creating permeability at the edge of her company allowed new directions and opportunities to serendipitously emerge.

As a result the company and its customers have developed a truly symbiotic relationship. That “perfect fit” Jane had been seeking for her unusual rubber years ago? Her customers are telling her what it is—or rather, all of the perfect fits they’ve found. Repairing computers, cables for laptop chargers, phones, and outdoor equipment have emerged as the leading uses for her one-of-a-kind product. Jane is finding the company being pulled by customers in directions she could never have imagined during those years of painstaking materials research, but in each case the path is perfectly aligned with the company’s purpose.

The Kind of Luck That Matters

Entrepreneurs often cite “luck” as a key ingredient of success, yet this means far more than just being in the right time, right place. The luck that builds careers and companies is the kind that unfolds gradually, choice by choice, as people recognize and seize surprise opportunities, attracting others to them long before it’s obvious that their business is the next big thing. These skills of planned serendipity are not vague, metaphysical concepts; they can be mastered by any of us, and can shape how we run our startups as they grow.

We can learn how to make our businesses luckier.

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I don’t know if Highlight, Glancee, Banjo, or any one of those other startups you’re now officially sick to death of hearing about are going to make it, but I know that for the first time in a long time, we’re starting to move in the right direction in terms of mobile innovation. And no, I don’t mean we need more people-stalking apps, I mean we need more passive use of our mobile phones.

Less life lived looking down means more life actually lived.

The trend that strikes me here as being important is not necessarily “ambient location” or even “people finders” – that’s just all we’re capable of today. The real end game is engineering serendipity.

Each of the new contenders, oddly, has decided to go after the same vertical: people tracking. Perhaps this is the more easy and obvious market to first attack, given the apps’ abilities to run on top of existing social structures like Facebook or Foursquare. But arranging serendipitous encounters isn’t always a function of who you know, it should also be a function of who you want to know. Or who you should want to know, even if you don’t realize you should want to know them. That’s a bigger challenge than any of the new socializing apps can address.

Consider this, instead, a giant alpha test in preparation of taking that next step.

To move forward, the metrics these startups should be obsessed with should not just be how many users signed up, how many downloads they have, or how many pings they sent out, but how many real connections between people are actually being made. This is the Holy Grail for engineering serendipitous people discovery: alerting users immediately that somebody is nearby, but also making sure that’s a connection the person actually wanted to make. (It’s too bad all smartphones don’t have a nifty proximity sensor in them that can detect when you’re rapidly closing the distance between you and a fellow app user, for example. That would indicate a real connection! There are ways around this, but they’re far more complex than tapping into a provided sensor like the GPS).

Case in point of what a poor serendipitous experience feels like: one of the top apps alerts me that Steve Wozniak is at the airport, and he’s even in my terminal! He’s having a bite at a nearby restaurant. I rush to the other side of the terminal (which was a hell of a lot bigger than I thought), and scope out the restaurant, but no Woz. I scope out the nearby gates, still no Woz. What happened? A little manual people-stalking of my own and I find his flight took off over an hour ago. Fail, fail, fail, fail. (True story, sadly.)

A good app wouldn’t have even mentioned he was there. A good app would wait until it could say, Steve Wozniak is at the airport…and HE’S RIGHT BEHIND YOU!

So yes, all these apps still have a way to go before they even work correctly at their primary function.

While I know that it’s one step at a time, I worry that the market will see these apps as tools that do only one thing – merely alerting us to nearby people of interest – and will later give up on them when the trendiness wears off. That concerns me because we’ll then lose sight of other, bigger challenges companies operating in this space could one day solve. Challenges that take time. Not months, but years: engineering serendipity is not just about the who, but also the what, where, how and why.

A little history: a couple of years ago, Google’s then CEO, now Executive Chairman, Eric Schmidt spoke of a world where our phones alerted us to nearby shops and deals and discounts as we walked down the street, all personalized to our own interests. Serendipitous discovery of the world around us.

Now forgive me for saying so, but a world where Google knows what I want to do before I do it, gives me a chill. Can’t someone else build this first, please? And build it on top of data that comes from everywhere, not just one big Google-owned database?

Apps could start by telling you who’s nearby, then slowly grow, until they could alert you about all sorts of things, and do so just as spontaneously.

One company already doing this, to some extent, is Foursquare. With its Radar feature, Foursquare is branching out from check-ins to become a tool for exploring by suggesting nearby places and alerting you to nearby friends. In terms of engineering discovery of the world, not just people, it’s already ahead of the trendy background location apps. As CEO Dennis Crowley explained, “what we have been doing with Radar is finding a way for people to use the app really without having to actually use it.” BINGO. But this is all such a new game; anyone can still win.

Engineering discovery is a complicated one to solve. For example, it’s a combination of knowing not just where you say you like to shop, but where you’ve actually shopped; not just where you say you like to dine, but where you actually dine. It also needs to know what sort of activities you would want to attend (Concerts? Games? Family friendly outdoor festivals? Dog shows? Plays?), then ping you accordingly. It needs to tell you of a concert only when there are still tickets left. It needs to know personal details like your shoe size, shirt size, dress size, and then check the in-store inventory levels before it ever bothers you about a nearby sale. And so on. It needs intelligence. Otherwise, the damn thing will be way too annoying.

And yes, some of this may not even be possible yet. But it will be, so plan ahead.

Oh, and here’s another tricky part: for any app to be able to truly be capable of serendipitous discovery, it would also have to surprise you from time to time with something that’s just outside your typical interests, but where historical, aggregate data from a wide user base indicates that hey, you just might like this, too.

So how would any app be able to know all these things? Well, APIs, for starters. Many web companies provide them, but apps tend to build on top of only the social three (Facebook, Twitter, Foursquare).

How interesting would it be for apps to build on top of your preferred food-sharing and wine-tasting apps, your travel logs, your Amazon purchases, your credit card statements, your daily deal buys, your past check-ins, your Eventbrite ticket purchases, your Meetup groups, your Kindle e-book collection, your favorite shops at Fab and Etsy, etc., etc.? Oh, and all those your friends like too, of course?

Scenario: That guy browsing cookbooks at the bookstore knows your friend Julie and is currently reading the Steve Jobs bio (he’s got it on his Kindle, actually). PING!

Scenario: When you were in N.Y., you went to a restaurant your friend Joe recommended and loved it. This local restaurant is owned by the same folks and your friend Jim ate the ribs here two weeks ago and thought they were crazy good. PING!

Scenario: That little black dress that’s been sitting in your Amazon cart for 2 days looks a lot like the one this store is selling. And it’s half off. And they have your size in stock. PING!

Does any of that sound crazy? Then you’re not dreaming hard enough yet.

Or maybe it just sounds terrifying. Well, sorry (old fart?), but the machines are coming and they want to get to know you better.

Unfortunately, not all the data to build a (creepy) understanding of you and your behavior is available via API just yet, but by the time anyone could get around to expanding into all these verticals, that may change.

To be clear, the end result is not a scenario where every store you walk by blasts you with a geo-targeted deal, just one store does, and the result is incredibly, almost disturbingly, relevant. The apps don’t tell you about every possible dinner recommendation, only if the restaurant you’re considering now is any good. They don’t tell you about every person you’re somehow connected to nearby, only the ones you really want to know.

Or in other words: serendipity means you don’t have to manually launch apps all the time to know what’s going on. The apps launch you.

They don’t constantly ping you, and bother you with every little thing. Every time the phone buzzes, it would feel random, but would be meaningful and important to address.

Looking at what we have now, well, let’s just say we’re far, far away from that vision. But in the people trackers, we see the first baby steps.

That’s why they’re interesting.

And, who knows, at the end of the day, maybe such a thing won’t even be an app, but an extension of the handset itself. Maybe that’s what Siri and its VPA brethren will become. A smarter Siri who doesn’t just wake when you need something, but who, like a real-life assistant, would tap you on your shoulder and whisper, Pssst….Did you know?

Image credit: Flickr user ktoine

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