How Many Slaves Work for You?

04/15/17 • 20 min

If someone came up to you and randomly asked you, "How many slaves work for you?" maybe you'd think, "Slavery ended a long time ago, Bro." Or maybe you would take the question seriously. With 20 million to 46 million people enslaved in the world, it is a serious question, and while we don't see it daily, some of these enslaved people make things for us. Even if we're judicious about what we buy, we would be surprised just how much global slavery goes into producing the goods we do buy. But how can we quantify it? How can we solve this? Justin Dillon, who has worked with the U.S. State Department and hundreds of businesses, thinks he has the answer.Transcript:Ginette: “Our world today is an extremely vast, complicated, and interconnected web of 7.5 billion people. We’re directly connected to some, and it’s really easy to see those connections on Facebook, Instagram, Twitter, LinkedIn. But there’s a whole other group of people we are much more subtly connected to—people who are basically (who are essentially working for us) invisible to us, 20 to 46 million of them.“Our guest today deals with this invisible web every day.”Ginette: “I’m Ginette.”Curtis: “And I’m Curtis.”Ginette: “And you are listening to Data Crunch.”Curtis: “A podcast about how data and prediction shape our world.”Ginette: “A Vault Analytics production . . .”Ginette: “Today’s episode is brought to you by data.world, the social network for data people. Discover and share cool data, connect with interesting people, and work together to solve problems faster at data.world. Quickly locating data, understanding it, and combining it with other sources can be difficult. The data.world Python library allows you to bring data.world datasets straight into your workflow. Easily work with data and metadata in your Python scripts and Jupyter notebooks. Ready to dive in? Learn how to use data.world’s Python library at meta.data.world. Curtis: “Before we get going, one other note about data.world—starting today until May 5th, we are hosting a data competition on their site, and we’d love your participation. Donald Trump’s tweets have been the source of a lot of media attention recently—many high profile news outlets have asserted his tweets show signs of authoritarianism, some say he’s using his twitter account to shape the new cycle, and some have even built algorithms to make stock market decisions based on his tweets. Whatever your stance is on the subject, we’ve uploaded a dataset of every single one of his Tweets up to data.world, and we want to see what you can make of the data. This is a create competition by nature—submissions can be of any format, but the point is we want to see what you can learn, assert, or create with this data set. It’s easy to participate—just go to data.world/datacrunch, and you’ll find the dataset and all of the details. Submit by May 5, and we’re going to take all the submissions that tell the most compelling stories, we want to feature them on a future podcast episode.”Ginette: “Now back to the story. A few months ago, I ran across a website. It sucked me in. It asked me a provocative question, which we’ll get to in just a second, but first, we’ll introduce you to the man who’ll situate the story for you—the main person behind the website.” Justin: “My name’s Justin Dillon. I’m the founder and CEO of Made in a Free World. We started off years ago. I would say probably the genesis for us was me getting a call from the State Department in about 2010. I’d already been doing some projects, a few websites and, films that I was producing, around human trafficking and modern-day slavery.”Curtis: “Justin directed a documentary he released in 2008 called ‘Call + Response,’ which ranked as one of the top documentaries in 2011.”Justin: “And the State Department called and said, we would like to do a project with you, we like the way that you use data and tell stories,

Previous Episode

Predicting the Unpredictable

We now know black swans exist, but Europeans once believed that spying one of their kind would be like stumbling across a unicorn in the woods—impossible. Then, Willem de Vlamingh spotted black swans in Australia, and this black bird, which once represented the impossible to Europeans, shifted to represent the unpredictable. One company now dons the name "Black Swan." Find out how it aims to predict what we currently consider to be unpredictable.TranscriptGinette: “Submerse yourself in early 1600s London culture for a minute. Shakespeare’s alive and in his late career. The first permanent English settlement in the Americas just happened. Oxygen hasn’t been discovered yet. But a lesser known cultural idiosyncrasy has to do with a large white bird, the swan. In Europe, the only swans anyone had seen or heard about were white, so of course, in their minds, a swan couldn’t be any other color. From this concept, a popular saying develops, originally stemming from a poem. You use it when you want to make a point that something either doesn't exist or couldn’t happen. You’d say something like this: ‘you’re not going to find out because it’s about as likely as seeing a black swan,’ meaning that, that thing or event was impossible.“But then a discovery blows everyone’s minds. Dutch explorer Willem de Vlamingh is sent on a highly important rescue mission. A lost ship with 325 people on it probably ran aground near Australia, and they needed him to go rescue these people and the goods on board. While Willem and the three ships under his command go and search Australia for this lost ship, they find lots of fish; unique trees; quokka, a cat-sized kangaroo-like creature; and . . . black swans. This last discovery inevitably permanently shifts the meaning of this saying. After this, people start using it more to say when something’s highly unlikely or an unpredictable moment. “Now this concept of an unpredictable moment is why Steve King named his company Black Swan, because they predict the seemingly unpredictable.”Ginette: “I’m Ginette.”Curtis: “And I’m Curtis.”Ginette: “And you are listening to Data Crunch.”Curtis: “A podcast about how data and prediction shape our world.”Ginette: “A Vault Analytics production.”Steve King: “I am Steve King; I’m the CEO of Black Swan. Black Swan is 250 people who focus on trying to predict consumer behavior using data science, artificial intelligence, and big data. We have lots of large clients. We mostly work with big companies that have big problems to solve. Our work sort of splits across the US and the UK. Black Swan is absolutely full of stories. A lot of the work we really do is finding a hard problem that no one’s really solved before and then using data science to crack it, but there always quite interesting stories because, you know, they’re stories of a little bit of adventure, luck, and skill.’”Ginette: “The UK’s Sunday Times has consistently placed Black Swan on its lists: in 2014, it was on the ‘Ones to Watch’ list in its Tech Track. In 2015, it was ranked number one on the Start-Up Track. And in 2016, it was ranked number one in the Export Track 100, because it had the fastest growing international sales for the UK’s small to medium enterprises. “So what’s the secret sauce to the rapid growth and success of Black Swan, a company that solves problems for large companies in many different industries? It turns out, they aim to be better than anyone else at accessing and crunching a specific datasource.”Steve: “The reason we’re quite broad is it actually sits on one simple idea, and the simple idea really is that the Internet is really the world’s biggest data source, and we call, we call the Internet the world’s biggest focus group. So pretty much every opinion of a consumer or the open data that governments are laying out is all there for you to consume, but the, the trick is can you consume it in a way to help you find patterns so you can ...

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When a Picture Is Worth a Life

What if you found out your infant had eye cancer? That news would rock anyone’s world. But what if you had a tool that helped you catch it early enough that your baby didn’t have to lose his or her eye and didn’t have to go through chemo? You’d probably do almost anything to get it. Bryan Shaw has dedicated his time to helping parents detect this cancer sooner so their children don't have to go through what his son went through—and he’s doing it for free. With computer scientists from Baylor University, he's harnessed the power of a machine learning algorithm to detect cancer that no human eye can detect.Below is a partial transcript. For the full interview, listen to the podcast episode by selecting the Play button above or by selecting this link or you can also listen to the podcast through iTunes, Google Play, Stitcher, and Overcast. Bryan Shaw: “The very first person who ever contacted me because our app helped them was a gentleman in Washington State, and his little girl had myelin retinal nerve fiber layer, which is an abnormal myelination of the retina, and it can cause blindness, but it presents with white eye. And his little girl was five years old, and he kept seeing white-eye pics. He heard our story. He downloaded our app. Our app detected the white-eye pics. That emboldened him enough to grill the child's doctor. You know, 'My camera's telling me this. Look, this app. I heard this story . . .’ The doctor takes a close look. The girl had been 75 percent blind in one of her eyes for years, and nobody had ever caught it.”Ginette: “I’m Ginette.”Curtis: “And I’m Curtis.”Ginette: “And you are listening to Data Crunch.”Curtis: “A podcast about how data and prediction shape our world.”Ginette: “A Vault Analytics production.”Curtis: “Data Crunch is again brought to you by data.world, the social network for data people. Discover and share cool data, connect with interesting people, and work together to solve problems faster at data.world. Did you know that you can add files via URL to your data sets on data.world? Data.world APIs allow you to pull live survey data into your data set, enable automatic file updates, and more. Get the full details on data.world APIs at docs.data.world, or search ‘Austin Cycling Survey’ on data.world to see live survey sync in action in Rafael Pereira's data set!”Ginette: “One quick reminder that our data competition is currently up on data.world. Be sure to post your submissions by May 5.“Okay, now back to the story. If you know someone who’s about to have a child, has a child five or under, or plans to have children, you need to send them this episode, and you’re about to find out why from this man, Bryan Shaw.”Bryan: “When Noah was three-months-old, we started noticing that a lot of his pictures had white pupillary reflections, what doctors call leukocoria, white core, white pupil, and that can be a symptom of a lot of different eye diseases.”Ginette: “You probably put this together, but Noah is Bryan’s son. And to add in Noah’s mom’s perspective here, when she started noticing this strange white reflection in Noah’s eyes, like most moms today, she aggressively searched the Internet for answers. Like Bryan said, leukocoria could indicate a disease, or it could indicate nothing, but the Shaws decided they needed to tell their pediatrician about what they’d found.”Bryan: “Noah passed all his red reflex tests, until we told his pediatrician that we noticed leukocoria, and he had a very good pediatrician—Pearl Riney, Cambridge, Massachusetts. And then she really looked really, really closely. And on that test, she noticed a white pupillary reflection and immediately sent us that afternoon to an opthamologist.”Ginette: “At this point, Bryan’s wife, Elizabeth, was freaking out because she’d done all the research about leukocoria, or white eye, and she knew what white eye might mean for their four-month-old son.”Bryan: “In Noah's case,