Chris Wiggins
Associate Professor, Columbia University. On 1 show, 3 appearances. The Shows tab opens the full record on each.
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Chris Wiggins is an Associate Professor of Applied Mathematics at Columbia University. He previously served as Chief Data Scientist at The New York Times, where he led machine learning and data science initiatives.
1shows
3appearances
20statements
6resolved
3supported
1contradicted
50%fully supported
1said about them ↓ Everything Chris Wiggins said on any show that made the record, most notable first. Each card names its show and opens the statement there.
Wiggins: Data science, not physics, won World War II
“I grew up as a physicist thinking that, you know, physics really won World War II, but now that I'm a data scientist, I realize that it was actually data science that won World War II, but that story was classified for about 75 years, which is the story of how…”
Every publishing company is now a startup searching for a business model
“I like to use Steve Blank's definition of a startup, that a startup is a temporary organization in search of a scalable and repeatable business model. And in that sense, every publisher is now a startup, because the business model of publishing just completely…”
The New Republic and First Look Media failures were total people failures
“Those are both, like, total people failures, right”
Wiggins: Data science hiring should prioritize listening skills over domain expertise
“So, I think what you're looking for is not a particularly somebody with a domain background, but somebody who's proven themselves to be a good listener.”
Wiggins: Students incorrectly assume that published academic papers are inherently true
“My biggest pain point is, is trying to re-educate students who have read a bad paper, and because it was published, they think it's true.”
Wiggins: 'Statistics' entered English to mean statecraft, not math or data
“Statistics entered the English language to mean statecraft. It had nothing to do with math, and it certainly had nothing to do with data.”
Wiggins: Early eugenicists believed data would improve society, not oppress it
“They weren't writing about themselves like we're the baddies and we really want to oppress the crap out of people. They wrote about themselves like we're going to do a solid for society and we're going to make society better with data.”
Wiggins: Early US computing was funded by intelligence for data processing
“That story had its own mirror on the other side of the Atlantic in Bell Labs, and how Bell Labs played a crucial role in scaling up code breaking as a computational problem that pairs Bell Labs with the nascent intelligence community, which goes on to fund IBM…”
Wiggins: The creator of 'artificial intelligence' coined the term for funding
“The guy who invented the term is on record as saying I made up the term to get money”
Wiggins: Early AI research rejected data in favor of logic
“It's really for the first half of the life of artificial intelligence, people thought it had nothing to do with data whatsoever.”
Data science differs from ML through interdisciplinary domain collaboration
“The thing that makes data science different from machine learning is not just getting epsilon better predictive accuracy on learning, you know, cat's faces from pictures. It's this thing where you interact with somebody from a different discipline, and then so…”
Tech companies and digital media now operate as church, state, and engineering
“I like to think about the New York Times or any technology company now as church, state, and engineering”
Wiggins: Supervised models beat clustering because errors are clear
“Working on, on supervised learning or predictive models to be reassuring because I know if I'm wrong. Whereas, you know, models where I'm clustering, I sort of never know at the end of the day, should I have clustered things a different way?”
Data literacy requires critical, rhetorical, and functional skills equally
“Critical literacy, rhetorical literacy, and functional literacy, I think, are all equally important parts of having a data literate society.”
Wiggins: Sir Francis Galton coined regression, correlation, and eugenics
“One of the founders of mathematical statistics we look at is Sir Francis Galton. Distant cousin of Charles Darwin, who gives us the word regression, give us the word correlation, and gives us the word eugenics.”
Wiggins: The New York Times data science team has about 22 people
“So the data science team is about a 22 person team that develops and deploys machine learning. For newsroom and business problems.”
US print advertising spend fell about 50% from 2008 to 2012
“Print advertising spend in the United States lost about 50% of its value in like four years, 2008 to 2012.”
NYT data science prefers buying or using open source over building custom
“In terms of build or buy, if we, if there's something out there we can buy, we'll buy it. And if there's an open source alternative, then we'll definitely use that because most of the group know open source.”
Wiggins: Guinness was the hottest IPO of the late 19th century
“The, that chapter opens up with the hottest IPO in the late 19th century, which was Guinness. So Guinness, the beer company, IPO'd in late 1800, and like literally people were breaking the doors down to try to get on that, get in on that IPO.”
The other half of the tape: Chris Wiggins's own voice is left out of every number here. Other people bring the name up 1 time in 1 episode across the shows. every mention, with the transcript →
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the MAD Podcast 1
One line per show, most statements first. The link opens Chris's full record on that show: the calibration, argument clarity, speaking style and every statement made there.
| Show | Role there | Eps | Statements | Record | |
|---|---|---|---|---|---|
| MADLEDGER | Associate Professor, Columbia University | 3 | 20 | 50% 3/6 | full record on the MAD Podcast → |