WEBVTT - End of Semester 5: What We Learned - Lab 129

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<v Speaker 1>You know what I've been thinking about lately. Oh my goodness.

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<v Speaker 1>Whenever he started sounds like that, I know some crazy

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<v Speaker 1>is about to come next. Yes, because that's usually how

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<v Speaker 1>it goes. History has told you what rabbit hole are

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<v Speaker 1>you going down? Now? Well, first of all, too many

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<v Speaker 1>rabbit holes. But I'm just thinking about one, and it's

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<v Speaker 1>that we're at our last lap of this semester. Huh.

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<v Speaker 1>It's been a year that we've been doing this. Yes, yes, yes,

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<v Speaker 1>but the science doesn't stop just because the semester is over.

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<v Speaker 1>So the lab lights are still on. That's what you're saying,

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<v Speaker 1>that's frighting overly on. I'm TT and I'm Zakiah and

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<v Speaker 1>this is Dope Labs. Welcome to Dope Labs, a weekly

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<v Speaker 1>podcast that mixes hardcore science with pop culture and a

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<v Speaker 1>healthy dose of friendship. Over the last year, we've covered

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<v Speaker 1>a lot of ground in the labs that we have done. Yeah.

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<v Speaker 1>Some of them have been heavy topics, yes, and others

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<v Speaker 1>have been really fun and some topics that had us

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<v Speaker 1>texting each other like wait, what is happening? Listen. It's

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<v Speaker 1>not just the topics but the news too. I'm still

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<v Speaker 1>wondering what is happening every day I wake up and

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<v Speaker 1>I say, are we still in twenty twenty six? A

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<v Speaker 1>lot has happened in just a few short months. But

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<v Speaker 1>today we're wrapping up semester five. But before we step

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<v Speaker 1>away for a little bit, we want to talk about

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<v Speaker 1>what we've been discussing and what we're keeping our eyes on. Okay,

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<v Speaker 1>so what do we know over the last year. We've

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<v Speaker 1>talked about a lot. But you know what stands out

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<v Speaker 1>to me the most. A lot of our labs that

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<v Speaker 1>we've done have been about systems. So, okay, what do

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<v Speaker 1>you mean by systems? I think, if I were to

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<v Speaker 1>like sum it up, it's like the invisible stuff, the

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<v Speaker 1>stuff we can't see that's shaping how we live our algorithms.

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<v Speaker 1>That's markets, labor markets, economic markets, environmental exposures, institutions. Right,

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<v Speaker 1>because we talked about everything this semester, AI relationships, sports

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<v Speaker 1>betting and prediction markets, the psychology of Black Friday shopping,

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<v Speaker 1>air pollution, and what's actually in the air we're breathing.

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<v Speaker 1>I know the air in my office right now is

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<v Speaker 1>mostly make up setting spray. We even talked about the

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<v Speaker 1>science behind the Grammys, which I still think people are underestimating. Yeah,

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<v Speaker 1>there's a lot of math in the Grammys, a lot

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<v Speaker 1>of psychology, and yeah it's heavy. It's heavy stuff. So

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<v Speaker 1>if you zoom out, what do you think the big

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<v Speaker 1>theme of our year was, Well, to piggyback off of

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<v Speaker 1>what you're saying, because you put that bug in my ear.

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<v Speaker 1>It's probably how science and systems are quietly shaping our lives.

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<v Speaker 1>And unfortunately, or fortunately I feel it was like the

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<v Speaker 1>quiet party is out loud now, oh my goodness, very loud.

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<v Speaker 1>All right, So we did a little look back at

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<v Speaker 1>what we've talked about. But we're going to be away

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<v Speaker 1>and I know we'll text about what we have our

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<v Speaker 1>eyes on. Yes, I want to know, so you can

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<v Speaker 1>tell everybody else what you have your eyes on for

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<v Speaker 1>twenty twenty six. Well, for twenty twenty six, I am

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<v Speaker 1>keeping my eyes open on the policy stuff. You know,

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<v Speaker 1>I'm into the policy arm now and so now all

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<v Speaker 1>of those things are just in the forefront of my mind.

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<v Speaker 1>I feel like so much is going on behind the scenes,

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<v Speaker 1>like people are doing some very strange things that are

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<v Speaker 1>very anti what we're used to, Okay, and so I'm

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<v Speaker 1>just kind of like holding my breath. But also making

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<v Speaker 1>sure that I'm staying up to date with what's going

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<v Speaker 1>on in politics. It could be draining, but it's important.

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<v Speaker 1>It is so important to stay on top of it.

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<v Speaker 1>I'm also keeping my eye out on ways that I

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<v Speaker 1>can make sure that in the midst of all of

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<v Speaker 1>this turmoil and things that are stressing me out, ways

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<v Speaker 1>to incorporate self care because all of this can be

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<v Speaker 1>heavy on your psyche. All this can be heavy on

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<v Speaker 1>your emotions, and so making sure that I'm not suffering

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<v Speaker 1>from burnout with everything that's going on in the world,

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<v Speaker 1>and injecting more levity, injecting more art, injecting more music,

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<v Speaker 1>injecting all the things that make me smile, because I

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<v Speaker 1>think there has to be a balance there, you know. Yeah,

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<v Speaker 1>for sure, what are you keeping your eye on? I

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<v Speaker 1>think everything everything they're shifting around, looking right, looking weird

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<v Speaker 1>in the corner. Okay, I think there are a couple things.

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<v Speaker 1>So when you said self care, that really rang a

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<v Speaker 1>bell for me. You know, I think I've talked about

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<v Speaker 1>it on the show a lot, about getting my right

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<v Speaker 1>sleeping pattern. I'm back biking, hopefully in the next few

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<v Speaker 1>weeks because it's warming up here enough for that. Yeah,

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<v Speaker 1>and so getting outside, being in nature and also trying

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<v Speaker 1>to avoid all the pollen that will come along with that,

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<v Speaker 1>but also some community care and not just self care.

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<v Speaker 1>So one of the things recently I was like, oh,

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<v Speaker 1>I think I'll volunteer. And sometimes it feels like you

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<v Speaker 1>have to go to a church or a library to volunteer.

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<v Speaker 1>And I was like, let me start with the people

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<v Speaker 1>in my community. And so I just reached out to

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<v Speaker 1>some people I know here in Atlanta that are friends

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<v Speaker 1>and I was like, Hey, do you need any help

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<v Speaker 1>with anything today? I love that or tomorrow whatever. And

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<v Speaker 1>so I think, you know, people are aching for a community,

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<v Speaker 1>but a lot of the conversation I've seen is like, hey,

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<v Speaker 1>you got to be willing to contribute and create that

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<v Speaker 1>community that you want to be there for you. And

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<v Speaker 1>so that's one piece. The other thing is a little

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<v Speaker 1>bit more sociology and behavior. But it's Punched the monkey.

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<v Speaker 1>Okay have you seen them acaque over in Japan? Poor Punch.

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<v Speaker 1>I felt so bad for the baby. Let people know

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<v Speaker 1>who Punch is before you you talk about him. Punch

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<v Speaker 1>is a macaque in the I Chicago City Zoo in Japan,

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<v Speaker 1>and he was rejected at birth by his mother. This

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<v Speaker 1>is a very devastating thing to happen for someone like him.

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<v Speaker 1>I'm saying someone an animal. And he was bottle fed

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<v Speaker 1>by the zoo staff. He had to be reintegrated into

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<v Speaker 1>this new troop and they had to he had to

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<v Speaker 1>kind of fight for his own position. And one of

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<v Speaker 1>the monkeys was in there being a bully. Okay, a bully.

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<v Speaker 1>I said, get him out. Listen we he started throwing

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<v Speaker 1>Punch around. I said, get him out of there. Go

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<v Speaker 1>get our boy. The internet rally behind Punch. Yes, Punch

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<v Speaker 1>has pissed so many people on his side, and I

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<v Speaker 1>think that's interesting because it's animal behavior that we're seeing,

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<v Speaker 1>but we're able to resonate with it. And it made

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<v Speaker 1>me think about our first episode Cuffing Season, where we

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<v Speaker 1>talked about animal behavior around mating and how it looks

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<v Speaker 1>similar in some ways to human behavior. And then once

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<v Speaker 1>again we're seeing those same people are able to identify

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<v Speaker 1>and they're like, oh, this person is Punch his friend

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<v Speaker 1>or you know, we're looking at these social behaviors that

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<v Speaker 1>we also exhibit, and so I think it's really I'm like, hey,

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<v Speaker 1>we're all primeates. Baby, Yeah, these fingernails soft claws, soft clause.

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<v Speaker 1>As my friend would say, Oh my goodness, I'm also

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<v Speaker 1>keeping my eye out on AI. And this kind of

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<v Speaker 1>goes to the policy honestly, because I mean AI is

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<v Speaker 1>changing every five minutes, literally, like every week. There's new

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<v Speaker 1>developments in the AI space, and the technology is advancing.

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<v Speaker 1>It is like when we say breakneck speed. It is

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<v Speaker 1>really really fast, and folks are just trying to keep up.

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<v Speaker 1>No one who works in the AI space anticipated that

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<v Speaker 1>it would be where it is right now in twenty

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<v Speaker 1>twenty six, and so one of the big questions that

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<v Speaker 1>scientists are asking right now is whether AI can actually

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<v Speaker 1>help discover new science. Let me tell you I was

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<v Speaker 1>asked from that question a while back, and I think

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<v Speaker 1>part of that is because people think about the large

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<v Speaker 1>language modelers and the interfaces that are like generic uses

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<v Speaker 1>like chat, GPT. But Anthropic has been growing on the scene.

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<v Speaker 1>You know, I've been following what they're doing with AI

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<v Speaker 1>for science, and I gotta tell you, I am I

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<v Speaker 1>am impressed. Okay, Now, I think they're showing us just

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<v Speaker 1>what's possible, even just for like one example I saw

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<v Speaker 1>was like this plug in and you can have all

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<v Speaker 1>your lab's data So think about a lab. Think about

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<v Speaker 1>the lab that I was in in grad school. You know,

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<v Speaker 1>my advisor ended up retiring, but there were samples in

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<v Speaker 1>those freezers from the eighties and nineties. Okay, so we're

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<v Speaker 1>talking in twenty fourteen. I'm trying to look back through

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<v Speaker 1>books and see writing in people's lab notebooks from the nineties. Now,

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<v Speaker 1>imagine all the results from our lab, negative results that

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<v Speaker 1>don't get published, all of that being catalog. Imagine those

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<v Speaker 1>things being scanned in and we have a database. So

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<v Speaker 1>when a new student comes along, they can say, hey,

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<v Speaker 1>actually it's not published, but I know this this and

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<v Speaker 1>this won't work, or here are the results of this

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<v Speaker 1>other experiment. So we don't waste time, we don't waste resources.

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<v Speaker 1>We could say, are there any patterns that I hadn't

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<v Speaker 1>see over the past twenty years but that AI can

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<v Speaker 1>detect and then I can test and verify, Like, baby,

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<v Speaker 1>what do you know what we could have done with

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<v Speaker 1>that type of technology? PhD in ten days they just

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<v Speaker 1>gonna be giving it out. But that's just one small

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<v Speaker 1>use case, and it's exciting. It is. And I think

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<v Speaker 1>that when people talk about AI, it's always just you know, chat, GPT,

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<v Speaker 1>and we got to expand our understanding of what AI

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<v Speaker 1>is and what it's possible with AI, because there's a

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<v Speaker 1>lot of really cool work being done. I know that

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<v Speaker 1>there are a lot of folks talking about its impact

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<v Speaker 1>on the environment and things like that, and we the

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<v Speaker 1>scientists understand and are working on those things too. As

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<v Speaker 1>AI advances, the the sustainability of it all will also advance,

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<v Speaker 1>so I think that that's something that we have to

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<v Speaker 1>keep in mind as well. Another thing that we talked

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<v Speaker 1>about this year was money, Where is it all going?

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<v Speaker 1>People are always want to know what's going on with

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<v Speaker 1>the economy, and I feel like the economy is such

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<v Speaker 1>a big word, like what does that even mean? And

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<v Speaker 1>everything it seems right? And we talked about the psychology

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<v Speaker 1>of spending, Black Friday, gambling, risk and all of those

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<v Speaker 1>things associated with it, because we really wanted to focus

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<v Speaker 1>on the individual because it feels like that's the only

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<v Speaker 1>thing we can control. All of this is behavioral science,

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<v Speaker 1>and I've been interested in this over the years. This

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<v Speaker 1>is not where my training is, okay, but I do

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<v Speaker 1>think I'm curious with the rise of AI and with

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<v Speaker 1>so much information, what about human processing of that information?

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<v Speaker 1>That's gonna matter even more. And so like understanding the

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<v Speaker 1>drivers what makes you do the things you do. With

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<v Speaker 1>all this information, you now have access to what makes

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<v Speaker 1>you act on a thing or not all of that.

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<v Speaker 1>It feels like we're gonna need to understand that even better.

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<v Speaker 1>And I think in a world where capitalism is in

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<v Speaker 1>the driver's seat, it pays to know these things absolutely.

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<v Speaker 1>And the big question, one of the big questions right

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<v Speaker 1>now is what does AI mean for jobs? And I

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<v Speaker 1>think that folks are really nervous. People are nervous about

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<v Speaker 1>what that means for their jobs in the future. I know,

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<v Speaker 1>like in the law space, lawyers are actually really nervous

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<v Speaker 1>because you know all of that. I don't even know

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<v Speaker 1>what the right words are roxy if you're listening case law,

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<v Speaker 1>all those books and stuff. AI is able to do redlines.

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<v Speaker 1>AI is able to do all of these things. And

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<v Speaker 1>so I know it's not just the folks that are

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<v Speaker 1>doing jobs and a factory. It's like every industry is

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<v Speaker 1>feeling the impacts of AI. And so I think we're

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<v Speaker 1>going through one of those moments where technology changes the

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<v Speaker 1>kinds of work that humans do. I don't think that

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<v Speaker 1>it's going to just get rid of like whole sectors,

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<v Speaker 1>like we always going to need lawyers, you know what

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<v Speaker 1>I mean, And we're always going to need doctors, and

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<v Speaker 1>we're always going to need people that can help with

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<v Speaker 1>building people with trade skills. I think the jobs is

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<v Speaker 1>just gonna look a little different. I think they will

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<v Speaker 1>definitely look different, and how we prepare will look different. Listen,

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<v Speaker 1>these types of changes and shifts in the human workforce

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<v Speaker 1>have happened before the Industrial Revolution. Having computers, having the internet,

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<v Speaker 1>all those things have changed how we train, They've changed

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<v Speaker 1>what the education system looks like. And so I'm thinking

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<v Speaker 1>back to our episode where we talked about the economy

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<v Speaker 1>and the changes in the workforce, and I think what

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<v Speaker 1>we will see is a shift to more intermittent training.

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<v Speaker 1>So that means you don't just go to school one

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<v Speaker 1>time and you stay in that career for thirty years

0:13:03.360 --> 0:13:06.360
<v Speaker 1>and you rely on that knowledge from the institutional knowledge

0:13:06.400 --> 0:13:09.320
<v Speaker 1>from school and then the experiential knowledge from over time.

0:13:09.360 --> 0:13:10.880
<v Speaker 1>I don't think that's going to be the way it is.

0:13:11.120 --> 0:13:14.600
<v Speaker 1>I think you'll have three and four careers, and what

0:13:14.640 --> 0:13:17.079
<v Speaker 1>we need is infrastructure to support that to help people

0:13:17.160 --> 0:13:20.400
<v Speaker 1>shift as the workforce does. That's such a great point.

0:13:20.640 --> 0:13:24.120
<v Speaker 1>And that also makes me think about because we talked

0:13:24.120 --> 0:13:26.640
<v Speaker 1>about the politics more, and we talked about politics a

0:13:26.640 --> 0:13:29.600
<v Speaker 1>lot this season and found its way into almost every

0:13:29.600 --> 0:13:34.160
<v Speaker 1>single episode. And that's because science is never isolated from politics.

0:13:34.240 --> 0:13:39.000
<v Speaker 1>You know, we've talked about immigration, surveillance, who knew Enemy

0:13:39.000 --> 0:13:45.520
<v Speaker 1>of the State was real? Nonfiction? All of these things

0:13:45.960 --> 0:13:48.920
<v Speaker 1>are shaped by what policy allows. Even when we look

0:13:48.960 --> 0:13:53.520
<v Speaker 1>at you know, what medicines are available, treatments are being approved,

0:13:53.600 --> 0:13:56.120
<v Speaker 1>what careers people are able to get loans for so

0:13:56.160 --> 0:13:58.600
<v Speaker 1>that they can continue to go to college. All of

0:13:58.600 --> 0:14:02.400
<v Speaker 1>these things are shaped by policy. And we know science

0:14:02.880 --> 0:14:05.000
<v Speaker 1>is also affected by those things because it depends on

0:14:05.080 --> 0:14:07.760
<v Speaker 1>ideas moving, even when they're not clear cut or they

0:14:07.760 --> 0:14:10.120
<v Speaker 1>feel messy at the beginning. So and it depends on

0:14:10.160 --> 0:14:15.200
<v Speaker 1>knowledge moving. Absolutely, those two things are intertwined, as are

0:14:15.320 --> 0:14:18.240
<v Speaker 1>all things. That's why we say science is in everything,

0:14:18.320 --> 0:14:20.480
<v Speaker 1>you know what I mean? Yeah, And that's like the

0:14:21.200 --> 0:14:24.520
<v Speaker 1>bedrock of Dope Labs is that science is in everything

0:14:24.600 --> 0:14:26.920
<v Speaker 1>and that we need to arm ourselves with resources that

0:14:26.960 --> 0:14:30.240
<v Speaker 1>will help us understand what is going on around us

0:14:30.280 --> 0:14:33.560
<v Speaker 1>in the world day to day. Yes, so we talked

0:14:33.560 --> 0:14:35.680
<v Speaker 1>about rabbit holes at the beginning. I didn't quite let

0:14:35.720 --> 0:14:38.080
<v Speaker 1>you get into it. But what rabbit hole are you

0:14:38.200 --> 0:14:43.760
<v Speaker 1>currently in? Thank you for opening the door. It's just

0:14:43.800 --> 0:14:47.560
<v Speaker 1>a little bit, don't get I put my foot in there. Okay,

0:14:47.640 --> 0:14:50.360
<v Speaker 1>you won't be able to close it back for me.

0:14:50.880 --> 0:14:53.800
<v Speaker 1>I think the there are a couple rabbit holes. So

0:14:53.800 --> 0:14:59.040
<v Speaker 1>I mentioned biking, but also birds. It's time the birds

0:14:59.080 --> 0:15:03.720
<v Speaker 1>are moving fir rating. Oh okay, you should have seen

0:15:03.720 --> 0:15:06.160
<v Speaker 1>the look she gave me. All she was not happy

0:15:06.240 --> 0:15:09.760
<v Speaker 1>with what do you mean time for what? Listen? These

0:15:09.760 --> 0:15:13.880
<v Speaker 1>are a pollinators. Sometimes these are our cues of seasons changing.

0:15:14.280 --> 0:15:18.360
<v Speaker 1>They're so exciting. There's so much to learn, and I

0:15:18.400 --> 0:15:19.840
<v Speaker 1>really would like to do a little bit. But what

0:15:19.840 --> 0:15:23.720
<v Speaker 1>do they call that container? Garden it? The earths are expensive, okay,

0:15:23.760 --> 0:15:26.840
<v Speaker 1>and they're going mushy in the refrigerator fab so I

0:15:26.880 --> 0:15:28.920
<v Speaker 1>need my own supply. I remember when we were in

0:15:28.960 --> 0:15:31.080
<v Speaker 1>grad school, you would open up their back door and

0:15:31.200 --> 0:15:34.120
<v Speaker 1>just cut out cut basal leaves and stuff like that,

0:15:34.160 --> 0:15:38.240
<v Speaker 1>and I was like, what is going on back there, honey?

0:15:38.360 --> 0:15:40.480
<v Speaker 1>Like I had never seen that before in my life.

0:15:40.480 --> 0:15:43.600
<v Speaker 1>Somebody opened their door and cut stuff and then put

0:15:43.640 --> 0:15:48.560
<v Speaker 1>it in the food Like is these lawn clippings no flavor.

0:15:49.240 --> 0:15:55.160
<v Speaker 1>Ho really should have excited me for that. Oh my gosh,

0:15:55.400 --> 0:15:58.080
<v Speaker 1>Now what about you, I'm not letting you get away?

0:15:58.280 --> 0:16:00.960
<v Speaker 1>Uh huh Okay. So for me, the rabbit hole that

0:16:01.000 --> 0:16:04.560
<v Speaker 1>I'm going down is mainly focused on human behavior. I

0:16:04.560 --> 0:16:07.720
<v Speaker 1>think the rise of parasocial relationships, like people feeling like

0:16:07.920 --> 0:16:11.800
<v Speaker 1>they know someone because they follow them on Instagram or

0:16:11.840 --> 0:16:15.800
<v Speaker 1>TikTok or watch their YouTube videos. Yes, that is just

0:16:15.840 --> 0:16:18.360
<v Speaker 1>so interesting to me because and it's not even coming

0:16:18.360 --> 0:16:20.480
<v Speaker 1>from a place of judgment. I be feeling like I

0:16:20.560 --> 0:16:23.320
<v Speaker 1>know these people. I've been following some people for over

0:16:23.360 --> 0:16:26.120
<v Speaker 1>a decade, and when they get married, I'm like, wow,

0:16:26.160 --> 0:16:30.400
<v Speaker 1>I didn't even get invited. It's interesting though, because we

0:16:31.160 --> 0:16:35.120
<v Speaker 1>talk about this t t and I feel like there

0:16:35.120 --> 0:16:39.960
<v Speaker 1>are some og Dope Labs listeners that I'm like, hey,

0:16:40.600 --> 0:16:44.360
<v Speaker 1>I can't believe how much your baby has grown, and

0:16:44.360 --> 0:16:46.040
<v Speaker 1>I'm like telling them I said, hello, look at our

0:16:46.040 --> 0:16:49.320
<v Speaker 1>little tiny shift. Right, That's how I feel. And then

0:16:49.440 --> 0:16:51.960
<v Speaker 1>some people I'm like, who is this? You know? Right,

0:16:52.160 --> 0:16:56.520
<v Speaker 1>there's this woman on TikTok who had a very public

0:16:56.960 --> 0:16:59.400
<v Speaker 1>dating relationship. When she went on a first date with

0:16:59.440 --> 0:17:01.840
<v Speaker 1>this man, knew about it. She talked about him. She

0:17:02.120 --> 0:17:08.159
<v Speaker 1>eventually married this man and UH had like a what

0:17:08.280 --> 0:17:10.560
<v Speaker 1>felt like a TikTok wedding where it was like all

0:17:10.560 --> 0:17:14.119
<v Speaker 1>these brands, like brands bought her dress, brands did the

0:17:14.160 --> 0:17:16.720
<v Speaker 1>makeup brands, like it was just very TikTok because she's

0:17:16.760 --> 0:17:20.080
<v Speaker 1>like one of the most popular TikTokers or whatever. She

0:17:20.320 --> 0:17:22.520
<v Speaker 1>also let us like a little bit too much into

0:17:22.600 --> 0:17:25.800
<v Speaker 1>her life and so we were we observed like her

0:17:25.880 --> 0:17:31.360
<v Speaker 1>husband's drug addiction and like now they're getting a divorce,

0:17:31.440 --> 0:17:34.119
<v Speaker 1>and so people are just like in the comments talking

0:17:34.160 --> 0:17:37.680
<v Speaker 1>crazy and I'm just like, we don't know her, we

0:17:37.800 --> 0:17:40.600
<v Speaker 1>don't know her. I'm like, I have the biggest we

0:17:40.920 --> 0:17:45.000
<v Speaker 1>don't know her. We don't know her. Like she's volunteered

0:17:45.000 --> 0:17:47.080
<v Speaker 1>a lot of information, and so people are like, well,

0:17:47.119 --> 0:17:48.879
<v Speaker 1>if you put that out there, we're allowed to comment,

0:17:48.920 --> 0:17:51.520
<v Speaker 1>and I'm like, but you don't have to. But you

0:17:51.520 --> 0:17:53.440
<v Speaker 1>don't have to. You don't have to, and so it's

0:17:53.480 --> 0:17:57.040
<v Speaker 1>just really interesting how people make those decisions. I'm like,

0:17:57.119 --> 0:17:59.240
<v Speaker 1>is it a generational thing? I don't think so, because

0:17:59.240 --> 0:18:01.879
<v Speaker 1>I see some folks my age and older who are

0:18:01.920 --> 0:18:05.200
<v Speaker 1>in the comments section doing stuff behaving terribly. Yeah, because

0:18:05.200 --> 0:18:09.320
<v Speaker 1>I'm and I'm just like me. I'm not like the

0:18:09.359 --> 0:18:11.159
<v Speaker 1>way that I interacted with the Internet. I feel like

0:18:11.200 --> 0:18:13.399
<v Speaker 1>you're the same way too, Like we remember what it

0:18:13.480 --> 0:18:17.360
<v Speaker 1>was like before there was social media. We know, in

0:18:17.440 --> 0:18:21.080
<v Speaker 1>person beef, you know, yes, all this it don't mean

0:18:21.119 --> 0:18:25.560
<v Speaker 1>nothing to me. All that typing, all that typing, right, oh,

0:18:25.800 --> 0:18:28.200
<v Speaker 1>in person beef and internet beef is making me think

0:18:28.200 --> 0:18:31.159
<v Speaker 1>about fifty cent and TI the South got something to

0:18:31.160 --> 0:18:36.399
<v Speaker 1>say now. I haven't even been able to keep up

0:18:36.520 --> 0:18:38.919
<v Speaker 1>what's going on? Can you please bring me up to

0:18:38.920 --> 0:18:42.560
<v Speaker 1>speed really quick. It's not even important. It's grown people

0:18:43.680 --> 0:18:48.200
<v Speaker 1>being ridiculous. Okay, that's all it is. I don't think

0:18:48.200 --> 0:18:49.840
<v Speaker 1>that beef is worth any of our time. There's so

0:18:50.000 --> 0:18:53.000
<v Speaker 1>much on our plate. Take that little piece of beef off. Okakay,

0:18:53.359 --> 0:18:55.800
<v Speaker 1>don't don't even worry about it. That's the gristle. Throw

0:18:55.800 --> 0:19:00.800
<v Speaker 1>it in the track, yes, the gristle. So well, that's

0:19:00.920 --> 0:19:03.320
<v Speaker 1>mainly what my rabbit hole has been. And just like

0:19:03.359 --> 0:19:06.800
<v Speaker 1>why we make the decisions that we make, and trusting

0:19:06.840 --> 0:19:10.240
<v Speaker 1>some technologies over others, and you know, how we interact

0:19:10.240 --> 0:19:13.320
<v Speaker 1>with technology. Those are the things that I've been kind

0:19:13.320 --> 0:19:24.840
<v Speaker 1>of like deep diving into and trying to understand more.

0:19:30.520 --> 0:19:33.480
<v Speaker 1>If there's something I can say, I want everybody to

0:19:33.560 --> 0:19:35.840
<v Speaker 1>keep their eye on and to keep the pressure on,

0:19:36.960 --> 0:19:42.199
<v Speaker 1>is scientific discovery. Don't stop asking for more things, you know.

0:19:42.280 --> 0:19:44.240
<v Speaker 1>I feel like we're seeing funding cuts. I was on

0:19:44.280 --> 0:19:46.480
<v Speaker 1>the GAO website which I said, I don't think I'm

0:19:46.520 --> 0:19:49.560
<v Speaker 1>even supposed to be over here, okay, and that's the

0:19:49.640 --> 0:19:53.600
<v Speaker 1>Government Accountability Office. I've been looking at research infrastructure, how

0:19:53.640 --> 0:19:57.320
<v Speaker 1>it's slowed since twenty twenty four. What was expected. Projects

0:19:57.359 --> 0:20:02.280
<v Speaker 1>are being scrapped, so scope has decreased, delivery is delayed,

0:20:02.720 --> 0:20:05.480
<v Speaker 1>and so I'm just like I recently went to a

0:20:05.520 --> 0:20:07.679
<v Speaker 1>Rare disease conference put on by the Boston Globe, and

0:20:07.680 --> 0:20:11.200
<v Speaker 1>I was looking at what's happening next, what's in the pipeline,

0:20:11.520 --> 0:20:13.520
<v Speaker 1>and how these companies are pushing for these things, and

0:20:13.560 --> 0:20:15.680
<v Speaker 1>I was like, we need our government to push as well,

0:20:15.720 --> 0:20:19.800
<v Speaker 1>and so like, I am keeping my eyes on scientific discovery,

0:20:19.920 --> 0:20:24.399
<v Speaker 1>innovation and application for people to have better lives across

0:20:24.400 --> 0:20:27.760
<v Speaker 1>the board. Absolutely, I think I'm right there with you

0:20:28.040 --> 0:20:32.600
<v Speaker 1>because it is so so important to stay on top

0:20:32.640 --> 0:20:34.439
<v Speaker 1>of these things. What they're hoping is is that we

0:20:34.480 --> 0:20:36.959
<v Speaker 1>won't and that all these things will be going on

0:20:37.000 --> 0:20:40.080
<v Speaker 1>in the background and we are being distracted by a

0:20:40.119 --> 0:20:43.040
<v Speaker 1>bunch of other stuff. The midterm elections are coming up,

0:20:43.080 --> 0:20:45.159
<v Speaker 1>and we have got to get to the polls because

0:20:45.200 --> 0:20:48.600
<v Speaker 1>when we vote, we win. Okay, that's the theme for

0:20:48.640 --> 0:20:50.879
<v Speaker 1>this next midterm is like, you got to get to

0:20:50.920 --> 0:20:53.919
<v Speaker 1>the polls because if we all show up and vote,

0:20:54.359 --> 0:20:59.160
<v Speaker 1>we will win. Period. I like that. And don't be distracted.

0:20:59.200 --> 0:21:01.920
<v Speaker 1>Like you said, you can always click another link, add

0:21:01.960 --> 0:21:04.320
<v Speaker 1>another tab, come back to it later and read it,

0:21:04.440 --> 0:21:09.080
<v Speaker 1>learn about it, be informed exactly. Science doesn't stop, Curiosity

0:21:09.160 --> 0:21:13.680
<v Speaker 1>doesn't stop, that's right, just curiouser and curiouser. So that's

0:21:13.720 --> 0:21:17.320
<v Speaker 1>a wrap on semester five. This has been so much

0:21:17.359 --> 0:21:22.000
<v Speaker 1>fun bringing you labs every single week for the past year,

0:21:22.440 --> 0:21:26.720
<v Speaker 1>hit after hit after hit after here and I guess

0:21:26.760 --> 0:21:28.679
<v Speaker 1>we'll just see you next time. You know where to

0:21:28.720 --> 0:21:36.320
<v Speaker 1>find us, by y'all. You can find us on X

0:21:36.400 --> 0:21:39.919
<v Speaker 1>and Instagram at Dope Labs podcast. You can find me

0:21:40.320 --> 0:21:46.840
<v Speaker 1>ct on X, threads and Instagram at dr Underscore t Sho,

0:21:47.320 --> 0:21:51.160
<v Speaker 1>and you can find Zakiya at z said So. Dope

0:21:51.240 --> 0:21:55.320
<v Speaker 1>Labs is a production of Lemonada Media. Our supervising producer

0:21:55.560 --> 0:21:59.320
<v Speaker 1>is Keegan Zemma. Dope Labs is sound designed, edited, and

0:21:59.440 --> 0:22:04.200
<v Speaker 1>mixed by James sparber Lemonada's Senior Vice President of Content

0:22:04.320 --> 0:22:09.280
<v Speaker 1>and Production is Jackie Danziger. Executive producer from iHeart Podcast

0:22:09.400 --> 0:22:13.680
<v Speaker 1>is Katrina Norvil. Marketing lead is Alison Kanter. Original music

0:22:13.800 --> 0:22:18.280
<v Speaker 1>composed and produced by Takayatsuzawa and Alex suki Ura, with

0:22:18.440 --> 0:22:23.400
<v Speaker 1>additional music by Elijah Harvey. Dope Labs is executive produced

0:22:23.440 --> 0:22:26.560
<v Speaker 1>by us T T Show Dia and Zakiah Wattley.