The Ledger
Every statement that passed quotation and attribution checks. Mix any filter with any other: certainty 1/5, debate potential 5/5, or both at once.
why aren't all 8 resolved? a statement only gets an assessment when the public record can support or contradict it. opinions and what-ifs never can, and 0 checkable ones are still open, waiting for their date. predictions held up or didn't; assertions are supported or contradicted. on every card: ▮▮▮▮▮ certainty · ▮▮▮▮▮ debate potential. speakers are clickable
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…”
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: 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.”
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?”