Big data

And I had gotten really interested in a set of developments in the early 2010s that were happening.

around the kind of academia, but also in public policy and governance around what was then called big data.

And so there is this, especially this kind of this moment where NYU opened up a center called the Center for Urban science and politics or something like that.

It's the CUSP, the CUSP Center, Center for Urban Science and I think it's not politics.

But anyway, the CUSP Center and it was the center that the whole premise was that it was going to leverage these new informatics systems that were capable of getting enormously granular data on everything about the kind of fluxes and flows of urban life in order to you know, in the kind of language of the big data revolution at the time to, like, completely revolutionize the way we understand how cities work so that we can, you know, improve governance and et cetera, et cetera.

And it was very much a part of the kind of smart city bubbling happening.

And And I was really interested because when they opened it, none of the people who were involved in the center at the leadership level were social scientists or humanities scholars of any kind.

So you have the Center for Urban Science and Progress that is supposed to be about understanding New York City that is being staffed by physicists, astrophysicists, and computer scientists.

And I think that mistake is, however, being made again and again and again, and you can really see that in the data space.

You know, there were, I don't know if some listeners still remember that, everybody got excited about big data about 10 or 12 years ago, right?

[laughs]

And, and suddenly everyone is, "Oh, and we need to do big data." But that's not a strategy.

That's an enabler.

That's something that you can use to, you know, have a better customer experience, to get that new business model going, to be faster, to be more efficient.

yeah But, you know, so, like, why...

And, you know, like, the new album is out on Big Data.

Like, I know you put out a lot of...

Wait, but do you

That's two years.

I don't know what happened, but that's two years.

Like I was saying, the other cool thing about Leap Life is that it's being released on Big Data.

I know they put out a lot of your early singles from the stuff that you were releasing.

Oh, God, when that thing came in a while ago, something...

What was it? Big, big- Big Data and panel ...

and panel.

Nobody watches [laughs] What? What? What? Everything's a web of lies.

[laughs]

It's the magic of, of Big Data.

We're watching you express so well on the screen, John.

You look skeptical.

So I want to step back because, you know, you were doing this way before ChatGPT came in and I want to make sure we look at some of the things you're doing.

One of your approaches involves lots of data, you know, big data approaches.

And so could you tell us about some of the resources that you've set up and how you use them to learn about language acquisition? Absolutely.

So

despite the fact that language learning we're talking about is a big data problem, a lot of the earlier approaches to studying language were very bespoke.

It was studying one child, maybe somebody keeping a diary, or doing an experimental study of 15 kids at the nursery school.

And one of the things we've learned is that that kind of small data approach doesn't really work because of the diversity of outcomes for kids, even in one culture, and then the vast diversity of the languages and cultures that kids are learning in around the world.

Enjoy time together.