Lizzy Bartelt (she/her): Well, and Tiffany Monique Quash, PhD - CTRL: oh. Tiffany Monique Quash, PhD - CTRL: hold on Tiffany Monique Quash, PhD - CTRL: and welcome back everyone to another episode of coloring outside the memos. I am Dr. Tiffany. I'm here with Dr. Lizzie. Tiffany Monique Quash, PhD - CTRL: And this week oh, this week is a very, very special week, because we are having a week of talking about a book, and we're going to get into that in a minute, but just a quick reminder to follow us on Twitter at 150 Tiffany Monique Quash, PhD - CTRL: at C. O. T. M. Underscore, pod or email us at C. O. Tm. Pod at gmail.com. Please, please. We love to get emails and responses from what's going on in our lover Lover. Oh. Tiffany Monique Quash, PhD - CTRL: Lindsay, edit that Tiffany Monique Quash, PhD - CTRL: we love to get. Tiffany Monique Quash, PhD - CTRL: Let's see. Edit edit. Tiffany Monique Quash, PhD - CTRL: We love to get responses for from you, our audience and our family members about what's going on in your world. So without further ado, I'm going to turn it over to Dr. Lizzie. So, Dr. Lizzie, tell me, what are we reading this week Lizzy Bartelt (she/her): this week? I'm so excited. Y'all. This is our very first book. Club Lizzy Bartelt (she/her): up. Lizzy Bartelt (she/her): dear listeners, you have no idea how excited I am. I love book clubs. I've been in a lot of them over the years. Dr. Tiffany and I were talking just before we got on about how much of a reader. I am even in grad school we would go out for drinks, and should come up, and i'd be like sitting in pawing through a book. Do you remember that Tiffany Monique Quash, PhD - CTRL: I do? I do. I do I remember that, or do I remember the alcohol which one Lizzy Bartelt (she/her): probably both. Anyway, we're so excited for a whole new thing for y'all. we are reading, and i'm holding up the book like you all can see me. You can't it's fine weapons of math destruction M. A. Th Lizzy Bartelt (she/her): weapons of M. A. Th destruction, and I am selling that out. Because. Lizzy Bartelt (she/her): dear listener, if you are old like me like Dr. Tiffany. we remember ma ss as a big thing weapons of M. A. Ss. Destruction, and weapons of M at H. Destruction are totally different. but also destructive. Lizzy Bartelt (she/her): So we'll talk about it. We'll get into it. It is written by Kathy O'neill. The subtitle of this book is how big data increases inequality and threatens democracy. Tiffany Monique Quash, PhD - CTRL: I am so excited about this. I'm. I'm beyond excited because Tiffany Monique Quash, PhD - CTRL: I am not Tiffany Monique Quash, PhD - CTRL: like looking at this. It's like wait. Is this a quant book Tiffany Monique Quash, PhD - CTRL: like I'm not gonna lie? I was like. Is this a quantum book? Are we? Are we talking about a quantum book on a call. Podcast! What is going on. So, Dr. Lizzie. Lizzy Bartelt (she/her): before we get into the backpack, let me tell you this quick story because you're going to get a hoot out of this. I didn't tell you this. Yeah, I've been saving it until we talked about this. Lizzy Bartelt (she/her): So a couple of weeks ago, I went on my trip to Napa, and I was sitting in the Detroit airport, having a glass of wine on a layover, and I'm. Reading this book in the airport bar, and i'm holding it up like this, and i'm drinking, and i'm like eating my dinner, and i'm reading the book. And all of a sudden the bartender comes up to me, and it's like, Are you one of those like people who love numbers? What is that book you are reading? Lizzy Bartelt (she/her): Are you one of those people she was like. I called you friend. When you came up here. I might have to revoke that, and I was like no hold on now. Lizzy Bartelt (she/her): and so then we had a back and forth about it for quite a long time, and she was like, okay, what are the good ones, and as I got up to leave for my Lizzy Bartelt (she/her): keep doing the good work, break down data, and I was like I got you. Tiffany Monique Quash, PhD - CTRL: Oh, I love it. I absolutely positively love it. Okay. So, readers, readers and listeners out there the next time you are at a bar, make sure you bring this book with you, because who knows what will happen to you? You may just get a free drink. Who knows? Tiffany Monique Quash, PhD - CTRL: And you'll make a new friend along the way. Lizzy Bartelt (she/her): Conversations with bartenders. It's just fine. Lizzy Bartelt (she/her): Everyone's going to think we're like huge drinkers. Now I know right right. Tiffany Monique Quash, PhD - CTRL: I mean, you know that's what we need to have is is a bottle of wine with our faces on it, talking about qualitative and like. Tiffany Monique Quash, PhD - CTRL: Maybe it's the the the logo for coloring outside the memos, and be like a wine of the day. I want a good day with the book. Oh, my goodness! I've got my backpack Lizzy Bartelt (she/her): right, and if you want to wine to read with this book. I'm. Going to recommend a temper neo, because that is a nice, strong, sassy wine, and it goes well with this book. Tiffany Monique Quash, PhD - CTRL: Oh, and and we have to remind tell listeners that you are a red wine person. Tiffany Monique Quash, PhD - CTRL: I really You are a red wine person, so I guess we're gonna have a new trend Tiffany Monique Quash, PhD - CTRL: book with wine. Tiffany Monique Quash, PhD - CTRL: There you go. Maybe that'll be the thing with the book Club books. Lizzy Bartelt (she/her): Let's move on before we've lost everyone in our divulsions. Lizzy Bartelt (she/her): So this book. Lizzy Bartelt (she/her): this book put on your backpacks. We're gonna embark on a journey about deconstructing big data. So this book. How did I find it. Lizzy Bartelt (she/her): cause I always like to tell people how I find books, because there's usually good story with really good reads, and this one I found on a Twitter list to call somebody posting what is the most influential book you've ever read in your life. And I was reading through them, and I was like. Yep. Yep. Yep. Wait. I haven't read that one. And then I kept scrolling, and I was like it came up again, and it kept scrolling came up again, and I was like Lizzy Bartelt (she/her): every other one that kept coming up was like kindred. Lizzy Bartelt (she/her): beloved blue, as I. You know, like all of these, that we were literally talking about before this that I've read over. You know. Lizzy Bartelt (she/her): multiple times when I was like, yeah, those are influential books. And then I was like, what is it not fiction book doing on this list? And why does everyone keep saying it? Twitter is not my go to for book recommendations, but sometimes it works out. So. Lizzy Bartelt (she/her): Hmm. Here we are. Lizzy Bartelt (she/her): Here we are Tiffany Monique Quash, PhD - CTRL: interesting. I love this. Okay, and continue so. This book is written by a former academic Lizzy Bartelt (she/her): who left higher LED because of the politics of higher LED. She really doesn't go into that Dr. O'neill does not. Lizzy Bartelt (she/her): Is it Dr. O'neill. Kathy O'neal does not go into that. but she does talk about Lizzy Bartelt (she/her): leaving higher LED leaving a tenure track position Lizzy Bartelt (she/her): in bio statistics and going into hedge fund management. Lizzy Bartelt (she/her): And then the housing crash happened. Lizzy Bartelt (she/her): What a time to leave higher! LED gave me the fear of death as I was reading. This is like, Don't leave higher LED. The housing crash will happen in your new industry. Lizzy Bartelt (she/her): You never know what the future will hold. Lizzy Bartelt (she/her): That's wow. Tiffany Monique Quash, PhD - CTRL: I mean right? Where's this? I'm. I'm sitting here thinking. This is the worst time to leave higher, LED. Lizzy Bartelt (she/her): I know. But who could have guessed right? She was there for 6 months, and then the housing crash happened, and like she's in the investment hedge fund stuff, and was like, Well. Lizzy Bartelt (she/her): I might not have a job. Lizzy Bartelt (she/her): What happened now like then? What happened? Yes, sir. Lizzy Bartelt (she/her): So there it's our dear Kathy. Lizzy Bartelt (she/her): dear Kathleen. Then it starts blogging Lizzy Bartelt (she/her): about how problematic Math formulas can be Lizzy Bartelt (she/her): joins occupy Wall Street. Lizzy Bartelt (she/her): and I know I know I know, and does some pretty high up work for them and talking about things that they're not talking about, and that they should be talking about, and then goes on to work at several other places and do some really cool stuff and write this book. So Lizzy Bartelt (she/her): turned out she did find for herself. Lizzy Bartelt (she/her): I don't know where she is now. Actually, I didn't look that up before this podcast probably should have. But we'll, we'll post an update on that. I don't know where she's been since 2,017, which was the last revision of this book. But Lizzy Bartelt (she/her): this is what she does. Lizzy Bartelt (she/her): So in this book she starts talking to us about Lizzy Bartelt (she/her): weapons of M. A. Th destruction, and i'm gonna keep spelling that out every time, just because I don't want you to hear Lizzy Bartelt (she/her): M. A. Ss. And I think it's really hard to enunciate that difference. So i'm going to keep spelling it out. I hope it's not too annoying. Tiffany Monique Quash, PhD - CTRL: I appreciate that Lizzy Bartelt (she/her): right right, because otherwise it's confusing. Lizzy Bartelt (she/her): So she starts by saying Lizzy Bartelt (she/her): walking us through this, what is going on Lizzy Bartelt (she/her): with data. Lizzy Bartelt (she/her): So if I just say to you, Dr. Tiffany, what is the biggest problem you see in our society Lizzy Bartelt (she/her): in the United States. What might you tell me Tiffany Monique Quash, PhD - CTRL: in the United States Tiffany Monique Quash, PhD - CTRL: other than the electoral college? Yeah, that's one of them. Tiffany Monique Quash, PhD - CTRL: Gosh! Tiffany Monique Quash, PhD - CTRL: Electoral college, I mean hate crime. Tiffany Monique Quash, PhD - CTRL: I mean the list goes on Tiffany Monique Quash, PhD - CTRL: right Tiffany Monique Quash, PhD - CTRL: rights for Tiffany Monique Quash, PhD - CTRL: marginalized people. Tiffany Monique Quash, PhD - CTRL: it's equal opportunity. Money! Tiffany Monique Quash, PhD - CTRL: Oh, my gosh! Money! The lack there of Tiffany Monique Quash, PhD - CTRL: little oh, food, insecurity! Lizzy Bartelt (she/her): There's just so many. And at the root of all of those, do you think there's one system driving it Tiffany Monique Quash, PhD - CTRL: capitalism. Lizzy Bartelt (she/her): right? Like? Lizzy Bartelt (she/her): Yeah, I might feel like our generation. That's our go to response right. It was capitalism all along. It's which is a phrase from the podcast You're wrong about. They use that all the time. credit where credit is due. I'm not stealing that phrase without a proper citation. Right? Lizzy Bartelt (she/her): Yes, thank you, Dr. Lizzie. it. So we we talk about that all the time. We all came about at a time of young adulthood when occupy Wall Street was a Lizzy Bartelt (she/her): really burgeoning thing right, and we all learned that less and hard and fast. Lizzy Bartelt (she/her): some of us will say racism is the biggest driver, and some people will say No, no, no, no! It's capitalism, and some people will say No, no, no, no, it's the combination of the 2. Lizzy Bartelt (she/her): and i'm not here to solve that debate for you. But Kathy will tell us throughout this book that it's not just capitalism. It's not just racism, but actually the root of all of this is big data and wait. What I know Tiffany Monique Quash, PhD - CTRL: Big data is the root of all of this. Tiffany Monique Quash, PhD - CTRL: I'm sorry I didn't mean to interrupt you. But continue Lizzy Bartelt (she/her): right, though, like it kind of reminds me of Lizzy Bartelt (she/her): No, go ahead. Go ahead. I I don't want to interrupt. Go ahead. Okay, save it, though. Make a note so that we can come. I'll save it. I'll save it all right. So Lizzy Bartelt (she/her): what the entire Lizzy Bartelt (she/her): synthesis? The entire conclusion of this book is is that these big data points Lizzy Bartelt (she/her): are run by computer based learning. You might have heard that phrase before, or machine learning it's another common phrase that gets tossed out. Sometimes when we're talking about I have a lot of friends who i'll talk about. Oh, well, the algorithm on the social media site or the dating site connected me with. So and so we all kind of sort of know that there are all of these data systems outside of our personal control that are influencing our lives right. Lizzy Bartelt (she/her): Oh, I was shopping and target the other day, and I stopped at the baby area because I was buying a present for a friend's baby shower, and then all of a sudden, I got baby ads flooding my, you know Lizzy Bartelt (she/her): whatever I was doing on my phone for the next 5 days, and we're I clicked on this link, and then I got emails about whatever. This one thing was that I did a Google search for. We all know that big data is influencing our lives. Lizzy Bartelt (she/her): But until I read this book I had no idea Lizzy Bartelt (she/her): how much of the systems that I hate and the things that I have complained about for years are actually due to problematic math formulas and problematic understanding of big data in machine learning. Lizzy Bartelt (she/her): So are you ready for this journey. I am ready. I'm ready. Lizzy Bartelt (she/her): I know right, because you're already like Lizzy Bartelt (she/her): It's happening. Lizzy Bartelt (she/her): Yeah, pretty much. Lizzy Bartelt (she/her): It is. Okay. So Lizzy Bartelt (she/her): we start on this journey with Lizzy Bartelt (she/her): understanding education. Lizzy Bartelt (she/her): So Lizzy Bartelt (she/her): if I were to say to you big problems in higher LED I've talked to you about this before i'm going to guess. Tiffany Monique Quash, PhD - CTRL: Take a hunch that you would say loans are one of the biggest problem with I. I would say loans are the biggest problems, and If there's anybody out there who is listening that wants to pay my student loans, you can definitely contact Tiffany Monique Quash, PhD - CTRL: me. and Tiffany Monique Quash, PhD - CTRL: I see not that I want to say that Dr. Lizzie Doesn't have student loans to pay for. But definitely, if you contact both of us direct them to Dr. Tiffany first. Tiffany Monique Quash, PhD - CTRL: I mean, I've got them. I'm not saying I don't have them, but I don't have as much as you do I. This is true. This is true. So yeah to loads through to loads. Yes, if we could get rid of student loans that would make my life a very. Tiffany Monique Quash, PhD - CTRL: I would just be a very happy camper. Lizzy Bartelt (she/her): It would be amazing right. and I, Lizzy Bartelt (she/her): This is a really important thing, and she talks about why we have student loan rates the way we do. Lizzy Bartelt (she/her): She breaks all of that down, based on the formulas. And so essentially the way that these loans work. Lizzy Bartelt (she/her): is that Lizzy Bartelt (she/her): you do a Google search for going back to school as an adult Lizzy Bartelt (she/her): in a Lizzy Bartelt (she/her): simple Google search right? Lizzy Bartelt (she/her): What happens on the back end of that Google Search is there are a bunch of people that are scooping up that data of what? Who's Google searching for what they're putting it into a formula and saying, If people search for going back to school as an adult Lizzy Bartelt (she/her): plus. Have search for coupons in the past, plus have searched for child care in the past. Then what we can do is we can send them a bunch of information on high interest Lizzy Bartelt (she/her): loans, and we'll tell them we'll say in the tunnel that they use. You can go back to college for free or low cost. Lizzy Bartelt (she/her): and both of us our faces are like horror because we know that's not true, and so they're getting Lizzy Bartelt (she/her): 1015% loans, right? They're getting these really predatory loans. Lizzy Bartelt (she/her): But they're being sold to them as colleges, free or almost free, based on these loans. Lizzy Bartelt (she/her): and they're They're starting to be some accountability for that right and the Biden administration. We know that some of that has started to be equaled out, but a lot of it, Hasn't Lizzy Bartelt (she/her): and Tiffany Monique Quash, PhD - CTRL: I want to quickly interject. That does not mean that we are here to promote one particular party over another for the record. We are not here to promote one particular party. We are just here to present facts. Lizzy Bartelt (she/her): Correct? Correct? Thank you for that. So, Kathy. It breaks this all down and traces it back to the Us. News report. Lizzy Bartelt (she/her): Do you remember when you were going to college and you got the bit. You went to the drugstore. You got the big magazine of the Us. And News World report, and you flipped through to the kind of college you wanted to go to. So women's, colleges for you, colleges for me, and you were like the number one school. Okay, I have to go and visit them. I have to like. Find out some information on them. Tiffany Monique Quash, PhD - CTRL: Those are your memories. I I so. And it was like my school was very. Tiffany Monique Quash, PhD - CTRL: It is highest, for for like beauty like it was like the best food and like the best dorm rooms. And I was like that's where i'm going. Yeah. Lizzy Bartelt (she/her): yeah, I mean, I mean, Yes, I was concerned about grades and like life after school, of course, but sure yeah. Who wasn't? But we all cared about what that ranking, and the Us. News and worlds report was right, and like Lizzy Bartelt (she/her): I mean my God, I like we could have a whole different conversation on going to college, and like that recruitment stuff, but turns out Lizzy Bartelt (she/her): Kathy traces back for us in chapter 3 here Lizzy Bartelt (she/her): about how Lizzy Bartelt (she/her): this all happened, and so she traces back Lizzy Bartelt (she/her): through this Us. News and rank cans, and how, when they first started to come out in the eighties. Lizzy Bartelt (she/her): no one really paid a whole lot of attention to them, but and they were just kind of getting reports from various college presidents and whatever not a big deal. But Lizzy Bartelt (she/her): as they started to do this. They wanted to get people complained at them, and they were like, Why weren't we the number one school? So what do they do? How do you make that fair right? How do you even out the rank hands? Lizzy Bartelt (she/her): Of course. Why do I have this image of somebody calling somebody up and be like. Tiffany Monique Quash, PhD - CTRL: Why, how did you get this ranking? when you know that my school is better than looking and better than your school, and my students are more knowledgeable than your students like. I. I just have this image of a bunch of Presidents Tiffany Monique Quash, PhD - CTRL: sitting at a table, and if it's the eighties, you know that there's like little to no women sitting at these tables so Lizzy Bartelt (she/her): right? And so it's like homecoming queen competition all over again. And then we're all trying out mean girls each other. And so what they do is they're like, hey, Us News and world report it's not cool that we're not number one on whatever category. Lizzy Bartelt (she/her): So us news and world report has to figure out some ways to systematize that and to try to make it more Lizzy Bartelt (she/her): understandable what they're doing right. So they create an algorithm they create some kind of formula to do this. Lizzy Bartelt (she/her): which seems fine right. But in theory that seems like a pretty horrible thing because Lizzy Bartelt (she/her): you want people to be able to go to the best schools. Great. Lizzy Bartelt (she/her): But it turns out Lizzy Bartelt (she/her): the way they did. That is, they said, okay, what are the best schools? So at that time what are the best schools that they're looking at? Lizzy Bartelt (she/her): Stanford, Yale, Harvard. Tiffany Monique Quash, PhD - CTRL: Now, the Ivs Lizzy Bartelt (she/her): right, and they say, what makes those better schools than other schools? Tiffany Monique Quash, PhD - CTRL: So if we white men I don't know I mean Yes, but it is people at this point to put race into their equation right? So they can't put race into the equation. So what did they do? Lizzy Bartelt (she/her): How much? What percentage of your alumni give money back to your school. What percentage of your alumni are employed 9 months after graduation, one percentage of Lizzy Bartelt (she/her): you know whatever. And so, looking at these various metrics that those schools did particularly well in this makes sense right like that kind of makes sense sort of yeah. But what the result of this is, is that the schools who aren't doing well? Say. Lizzy Bartelt (she/her): Aha! How do I get to this benchmark? Lizzy Bartelt (she/her): Wow! Lizzy Bartelt (she/her): Maybe if I put more money into creating a fancy dining room, or maybe if I put more money into landscaping, or maybe if we reject 50 of all applicants just off the cuff, maybe that'll get us. The better. Students quote unquote. Or maybe, if we accept this athlete, who maybe is really good at sports, but not so good at sports. Lizzy Bartelt (she/her): it'll even out, and so we'll have a really good student body, and we can get to that average we want at the end right? And so, as they start doing this, what happens is they're spending more money on aesthetics. The cost of tuition goes Lizzy Bartelt (she/her): right and sky rockets. We can draw this direct connection between the us news and World report and the changes in higher LED. And I know I know. And so, O'neill's conclusion is, this is all due to these Lizzy Bartelt (she/her): big data in the formulas that are being driven to do these rankings that Lizzy Bartelt (she/her): maybe are valuable, but maybe aren't so valuable. Right? Lizzy Bartelt (she/her): What they're pushing Lizzy Bartelt (she/her): the whole system of education. Lizzy Bartelt (she/her): And so we see this in the education system as a whole. But then she also breaks it down. How this happens with teacher evaluations, which is something I am acutely aware of. Lizzy Bartelt (she/her): and how people are getting fired because of teaching evaluations largely in K to 12 schools. But this happens in higher LED universities as well, and due to impart some reagan era Policy is some George W. Bush policies no child left behind. and how the Obama administration tried to regulate some of those, but kind of miss the mark, and how it's Still, Really, we're having this product of a lot of Presidencies passed, and again Lizzy Bartelt (she/her): i'm not trying to do anything. Say anything. Clinton also did some really terrible policies on this, frankly, and we'll come back to Clinton in a minute when we get to the criminal system, because she also does some really nice analysis of that. Lizzy Bartelt (she/her): And so she's taking us on this journey and saying, Look all of these evaluations, and these teachers who are getting fired. Lizzy Bartelt (she/her): All of these algorithms are literally nonsense. They mean absolutely nothing, because the data being fed into them is based on assumptions just like the Princeton Harvard Yale Assumptions of what makes a good school is what makes a good teacher Lizzy Bartelt (she/her): is based on the test scores of the students. But if you have really high performing students at the 90 ninth percentile. Lizzy Bartelt (she/her): one of the ways we test teachers is well did your students improve from the August exams or the October exams to the April exams Lizzy Bartelt (she/her): if they're in the 99 percentile they can't get any higher than that, because they don't do a 100% tile right. They only go up to 99. So if you have high performers, and they start at 99 in April. They're also going to be at 99. There's so improvement you might get a 3 for that. Year. but if you had students who are at the fiftieth percentile in October, and they're at the eightieth percentile in April you'll have a 90% rating. And so you'll be able to in that school district. Tiffany Monique Quash, PhD - CTRL: So Tiffany Monique Quash, PhD - CTRL: yeah, the words that I want to say are not appropriate for right now. But Tiffany Monique Quash, PhD - CTRL: wow. Tiffany Monique Quash, PhD - CTRL: you're just you're you. There's a no win situation here Lizzy Bartelt (she/her): right right? And so what O'neal does is she compares this to the algorithms of like Google or Amazon or apple, right? They all depend on the algorithms and big data, too, and they want to know. Lizzy Bartelt (she/her): like I was giving you the example of Where were you shopping in target and then giving you online apps for that, because that'll mean revenue for them, right If they're giving you ads that you're likely to click on. That increases their revenue. Lizzy Bartelt (she/her): This makes sense right? And so they optimize this all the time. But if you go once to the baby, Ariel, and you never go again, they're not going to give you baby ads Lizzy Bartelt (she/her): because Lizzy Bartelt (she/her): you're not gonna buy baby stuff, right? And so they're constantly putting in new data and saying, okay, we want to optimize this so that these ads are actually getting clicks, so that we're getting more money back. Lizzy Bartelt (she/her): This makes enough sense, right. But if we go back to the evaluation criteria teachers. Lizzy Bartelt (she/her): This formula doesn't have any error basis. So if it doesn't have, if it can't put in like, this is the reason these students didn't improve. So the teacher evaluations couldn't go up if it's never getting that data back in it's going to keep using the same formula to the end of time, because it thinks it's the right formula, and it can't put in any more data because it's not following students long term. It only has 2 data points. Lizzy Bartelt (she/her): So if you only have 2 data points and you have like 30 students, there's no way you can ever change that formula right because it's relying on the philosophy of big data in large numbers. Lizzy Bartelt (she/her): but it can't actually play those out, because there isn't enough data to play that out, and there's not the same kind of thing. So it's using the same formulas that Google and Amazon are using. But it's applying them in a way that is not the same. Does that make sense? It makes a lot of sense, and it and it's really it's it's Tiffany Monique Quash, PhD - CTRL: frustrating. Lizzy Bartelt (she/her): It's so frustrating and just thinking that Tiffany Monique Quash, PhD - CTRL: here are Tiffany Monique Quash, PhD - CTRL: and again going back to what you're talking about with teachers Tiffany Monique Quash, PhD - CTRL: who are out there, and again shout out to Teachers K. Through 12 and above Tiffany Monique Quash, PhD - CTRL: and above. Lizzy Bartelt (she/her): you know, unlimited K. 12, and above Tiffany Monique Quash, PhD - CTRL: you're out there, and Tiffany Monique Quash, PhD - CTRL: I mean Tiffany Monique Quash, PhD - CTRL: course evaluations at the collegiate level Tiffany Monique Quash, PhD - CTRL: is one thing. Tiffany Monique Quash, PhD - CTRL: and then Tiffany Monique Quash, PhD - CTRL: trying to get students in Kv. 12 Tiffany Monique Quash, PhD - CTRL: at a point where they need to be like. Tiffany Monique Quash, PhD - CTRL: they should be able to articulate and and understand Tiffany Monique Quash, PhD - CTRL: certain Tiffany Monique Quash, PhD - CTRL: certain things literally be math, or let it be grammar. What have you? I mean it just. Tiffany Monique Quash, PhD - CTRL: and if the sorry i'm i'm lost for words right now, because if the student misses, I don't want to see the student misses the mark, because that's not what i'm saying. But Tiffany Monique Quash, PhD - CTRL: if the algorithm doesn't work, it doesn't work, and then it penalizes Tiffany Monique Quash, PhD - CTRL: it, penalizes Tiffany Monique Quash, PhD - CTRL: the teacher for no reason. Lizzy Bartelt (she/her): Yeah, and that's that's exactly what this is showing right, and Lizzy Bartelt (she/her): this is perhaps not new information to some of you. I've known this more or less since. Tiffany Monique Quash, PhD - CTRL: probably. Oh, 6, I think I wrote a paper in undergrad on this very phenomenon. Of course you did, Dr. Living? Lizzy Bartelt (she/her): Oh, I was real salty about standardized tests. I did not like them at that age, and I was real mad about the no child left behind thing. at that point in my life. Lizzy Bartelt (she/her): either. Which way, though, it tells us that this is a formula, right? And it is a flawed formula. Lizzy Bartelt (she/her): Hmm. So okay, that might be just enough to say, like Lizzy Bartelt (she/her): education has a flawed formula. Tiffany Monique Quash, PhD - CTRL: It doesn't: Stop at education, does it? No, no. So what it what else? What else does Kathy? Lizzy Bartelt (she/her): So many things? So i'm not going to go through all of for examples. But i'm going to go through at least 2 more, and then we'll jump to some conclusions. Sound good. Lizzy Bartelt (she/her): It sounds good. Okay. So the next one she really does in. That is the criminal justice, system Lizzy Bartelt (she/her): and Yup! I'm already taking my head before actually we leave education. Let me do one last point, because I this is an important one, that the standards for these evaluation of K. To 12 teachers and even higher LED teachers are Lizzy Bartelt (she/her): use these flawed formulas in big schools, but in smaller schools, in private schools and non-public schools. Lizzy Bartelt (she/her): They don't use these formulas. They go based on recommendation Lizzy Bartelt (she/her): and so caregivers, our students, and they do other evaluative things because they principal has just maybe 20 teachers to watch over instead of 200 teachers to watch over, and if you have 20 you can know them, one on one, and if you have 200 you can't. And so you have to rely on the formula. Tiffany Monique Quash, PhD - CTRL: Wow! Lizzy Bartelt (she/her): So who is getting most affected by these flawed formulas. Lizzy Bartelt (she/her): the already marginalized. Lizzy Bartelt (she/her): Okay. So this is a system. So the ones that are in the the schools with 200 teachers Tiffany Monique Quash, PhD - CTRL: and Don't have access to a private education Tiffany Monique Quash, PhD - CTRL: chart. I I I i'm not trying to throw it hard to schools under the bus for the record, but Tiffany Monique Quash, PhD - CTRL: charter school up education, all those types of education, you know, versus like a public school education. Tiffany Monique Quash, PhD - CTRL: Yeah. Lizzy Bartelt (she/her): than that. Tiffany Monique Quash, PhD - CTRL: That that really hurt my soul. Yup. Yep. Lizzy Bartelt (she/her): I know. Lizzy Bartelt (she/her): I know. Lizzy Bartelt (she/her): and I will say, as a product of a rural school. Rural schools also. Lizzy Bartelt (she/her): Well, they are smaller. Rely on that public funding. just as much as the really urban schools do that have the 200 plus teachers per district, and even though they're smaller, they still have to use the same formulas as the really big schools do, because they don't have that private funding. And so Lizzy Bartelt (she/her): it it's a similar scenario. So it's Lizzy Bartelt (she/her): a really really flawed formula. Okay, let's move on to the justice system. Lizzy Bartelt (she/her): Yes. Lizzy Bartelt (she/her): so in the justice system. Lizzy Bartelt (she/her): one of the things she breaks down is how we decide whether or not people can be released early from jails and prisons. and one of the formulas they use to determine. That is Lizzy Bartelt (she/her): how likely they are to have recidivism. Lizzy Bartelt (she/her): They to end up, back in jail or prison. How do we determine that? Tiffany Monique Quash, PhD - CTRL: By a formula? Because, of course, we do, of course, by a formula. Right, thanks, Kathy thing up, Kathy. Lizzy Bartelt (she/her): Yeah, sure is. And the Formula One of the questions is. Lizzy Bartelt (she/her): Have you had prior Lizzy Bartelt (she/her): dealings with law enforcement? Who has likely now that isn't a question about race, but it's absolutely a question about race, because Lizzy Bartelt (she/her): who is had? What more likely to have had dealings past dealings with law enforcement? Tiffany Monique Quash, PhD - CTRL: Are you asking me or you telling me? I mean, I was gonna leave it like hanging there. But I mean go for it. Tiffany Monique Quash, PhD - CTRL: I mean, if we're going to go statistically. I mean, we're probably going to say like a black male. Lizzy Bartelt (she/her): That's what. Tiffany Monique Quash, PhD - CTRL: Wow! Lizzy Bartelt (she/her): black and indigenous men and Latin X men, or let you know men. Lizzy Bartelt (she/her): So men of color, men of color. Lizzy Bartelt (she/her): Yeah. Lizzy Bartelt (she/her): But also women of color. That's also an increasing Lizzy Bartelt (she/her): demographic for incarceration. Lizzy Bartelt (she/her): right? So that's point. 1.2 is, how many people do you know who have had dealings with the one like Lizzy Bartelt (she/her): with the legal system? Lizzy Bartelt (she/her): Again, lower in community, lower income communities and communities of color, much more likely to know other people who are in the system. Lizzy Bartelt (she/her): Then white commute law enforcement, and then the legal Tiffany Monique Quash, PhD - CTRL: Okay. Lizzy Bartelt (she/her): and if both of those things are true, then you're unlikely to be released early. Lizzy Bartelt (she/her): So, and like. There's other things that go into this. But those are 2 of the biggest drivers. For how those formulas are done. Lizzy Bartelt (she/her): do people on the inside know that? Lizzy Bartelt (she/her): Right it? Lizzy Bartelt (she/her): No one. The legal systems will not release, or the justice is the incarceration. Communities will not release the formulas they use For this. The companies who give the recidivism formulas will not release the formulas they use. Lizzy Bartelt (she/her): But you can kind of do some backwards design and like, figure out who's been released and who has it? And people who have been released will tell you what those questions were that they answered. And so you can kind of do some figuring out. And so that's how some of this data has come to us of why this is such a problem, but it's also a problem not only for that, but also in how policing happens Lizzy Bartelt (she/her): right? So she breaks down for us how Lizzy Bartelt (she/her): they are. Lizzy Bartelt (she/her): how we use. There's some a system called pred poll, and it is essentially Lizzy Bartelt (she/her): a crime reporting Lizzy Bartelt (she/her): system that will analyze how likely crime is to be in a certain area. Lizzy Bartelt (she/her): No, you might think to yourself Lizzy Bartelt (she/her): that seems really useful, right? I want to know if i'm going out in a neighborhood, if i'm likely to have my Lizzy Bartelt (she/her): car robbed if i'm likely to have my purse matched, if i'm likely to experience whatever whatever. Whatever Lizzy Bartelt (she/her): the problem here is, it is not just analyzing violent crime. Lizzy Bartelt (she/her): It is not just analyzing major more major crimes like car theft. It is also analyzing things like loitering things like drug use not like selling, but just use Lizzy Bartelt (she/her): it's also analyzing things like sex work data and other data that is really really flawed right not only flawed and like who gets it, but also in terms of like, how often those things are being reported and prosecuted, and whatever Lizzy Bartelt (she/her): So it's analyzing all of that. So what does that mean? It's actually just further targeting low-income communities. Lizzy Bartelt (she/her): Yeah. Lizzy Bartelt (she/her): Yeah. And so, then, if there are more police in those areas what's going to happen. But there is going to be Lizzy Bartelt (she/her): more crime quote, unquote in those areas, because, of course, there is because anytime police are around. They're going to see more crime right? Not necessarily because more crime is happening. But because if you're watching an area really closely, you're gonna see people doing things that everyone does right. I like to give my students the example of Lizzy Bartelt (she/her): how bad of a system Lizzy Bartelt (she/her): having speeding. Lizzy Bartelt (she/her): how we understand speeding in our society. Right? It's always one of my go-to examples for how behavior, how not to do behavior change because when do people slow down on the highway when they see a they don't ever do what outside of that? Right at the beginning of the month, and at the end of the month. Lizzy Bartelt (she/her): you know. You know I've slowed down my driving a lot over the years, and I rarely sweet anymore. But I used to all the time when I was in my early twenties, because Tiffany Monique Quash, PhD - CTRL: that was the culture I grew up in right and well, I mean it Also in Indiana is also speed a speedy place. I'm just saying, I mean the Indy 500. Tiffany Monique Quash, PhD - CTRL: My My period is that everybody thinks they're in the Indy 500 in Indiana. I'm just saying, yeah, especially on a couple of different highways. Yeah, yeah, One of my coworkers used to always say, oh, you're out on the racetrack today, and I was like first time, she said that I was like, No, it's just on the highway, and she was like, yeah, the racetrack. Tiffany Monique Quash, PhD - CTRL: No, but I mean, this is just so. Not only are you penalized Tiffany Monique Quash, PhD - CTRL: as a Tiffany Monique Quash, PhD - CTRL: and and this is what i'm taking away in this moment. Tiffany Monique Quash, PhD - CTRL: as a child of color. Tiffany Monique Quash, PhD - CTRL: in your education. Tiffany Monique Quash, PhD - CTRL: Then Tiffany Monique Quash, PhD - CTRL: you've got a government system or a not government system. But you've got the penal system that's pretty much coming after you Tiffany Monique Quash, PhD - CTRL: at a very early age. Yup. Tiffany Monique Quash, PhD - CTRL: if you don't hit certain criteria. Yep. Lizzy Bartelt (she/her): Yep. Lizzy Bartelt (she/her): Correct. Lizzy Bartelt (she/her): She says Lizzy Bartelt (she/her): it on page 87 Lizzy Bartelt (she/her): in our largely segregated cities. Lizzy Bartelt (she/her): Geography is a highly effective proxy for race. Hmm. Lizzy Bartelt (she/her): That feels really, really and for me to read that one more time. I'm sorry I need you to one more time. I sure can. Lizzy Bartelt (she/her): In our largely segregated cities geography is a highly effective proxy for race. Lizzy Bartelt (she/her): Now let me just read you one more. Quote. Lizzy Bartelt (she/her): This is on page 90. Lizzy Bartelt (she/her): This is a little bit longer. So stay with me for a second. Tiffany Monique Quash, PhD - CTRL: Okay. Lizzy Bartelt (she/her): Just imagine if police enforced their 0 tolerance strategy in finance Lizzy Bartelt (she/her): they would arrest people for even the slightest infraction. Whether it was chiseling investors on case providing misleading guidance or committee and petty frauds, perhaps swat teams would descend on Greenwich, Connecticut. They'd go under cover in taverns in Chicago's mercantile exchange. Lizzy Bartelt (she/her): Likely, of course, the Cops don't have the expertise for that kind of work Lizzy Bartelt (she/her): everything about their jobs, from their training to their bulletproof fest is adapted to the mean streets. She goes on for a little bit, and i'm going to pick it back up on page 91. Lizzy Bartelt (she/her): The result is that we criminalize poverty, believing all the while that our tools Lizzy Bartelt (she/her): are not only scientific, but fair. Lizzy Bartelt (she/her): Yeah. Lizzy Bartelt (she/her): i'm sorry I didn't realize you heard my sigh. I did. Lizzy Bartelt (she/her): I did. Lizzy Bartelt (she/her): The result is that we criminalize poverty. Let me say that one more time, because I think that's a really important point, and I think Lizzy Bartelt (she/her): this picture she paints of how we differentiate, what kind of crimes we care about, what kind of crimes. We police what it would look like if some people were pleased in a way that others were in. Our society is a really really important point, and it reinforces this whole outline of all of these formulas that we use to determine how policing happens. Lizzy Bartelt (she/her): what we consider dangerous, and what we don't, and how we reinforce this, not only in our judicial systems and in our prison systems, in our education systems, but also in our employment systems, which is where we're going to go to next. Lizzy Bartelt (she/her): You are taking us there today. Tiffany Monique Quash, PhD - CTRL: right? Thank you, Dr. Lizzie, and and wait and thank you. Kathy: O'neal. Lizzy Bartelt (she/her): Yeah. Lizzy Bartelt (she/her): Yeah, seriously, seriously. Lizzy Bartelt (she/her): So. Lizzy Bartelt (she/her): I Lizzy Bartelt (she/her): before before I leave this, I'm going to give you one last little Lizzy Bartelt (she/her): little quote from her, because I think Lizzy Bartelt (she/her): this is really important. she says on page 103 and 104 innocent people, surrounded by criminals, get treated badly, and criminals surrounded by law abiding people get a pass. Lizzy Bartelt (she/her): The rest of us barely have to think about them. Lizzy Bartelt (she/her): and I think this is one of the biggest conclusions from this text is that these formulas Lizzy Bartelt (she/her): are designed, so that the people who experience the disproportionate and the disadvantageous effects of these feel it all the time, and the people who don't Lizzy Bartelt (she/her): Don't even have to notice it at all. And I think this is part of her conclusion that these weapons of Mit H destruction are destroying society. They are so opaque that people can't really see them. Lizzy Bartelt (she/her): and that they are causing problems in a way, and which is further dividing in society, and Lizzy Bartelt (she/her): is doing so in a way that we can proclaim is good, and is saving money, and is leading to the benefit of society, when, in fact, it is doing the exact opposite. Lizzy Bartelt (she/her): so the employment one. Partly she goes through implicit bias with names and such, and resumes, which i'm pretty sure most people know at this point that Lizzy Bartelt (she/her): a Shannon is more likely to get a job than a shante. Lizzy Bartelt (she/her): but she also talks about how that is not only true for a specific hiring manager, but it is also inputted into certain formulas that screen resumes before they even get to the hiring managers tasks. So Lizzy Bartelt (she/her): If there are like a 100 applicants for one position, you're not reviewing 100 applications. And so now there are these Lizzy Bartelt (she/her): formulas, these computers that will set up to give you the like 10 best ones. Lizzy Bartelt (she/her): But it's not actually a human. On the other end of that, that is reviewing all of those with whatever kind of salary that they have. It's a $1,000 computer program that refuse them quickly Lizzy Bartelt (she/her): and then gives you the top candidates. But the ways that that happens Lizzy Bartelt (she/her): is bad inputs right. And it is the assumptions that whoever was designing that code Lizzy Bartelt (she/her): had that are Lizzy Bartelt (she/her): typically implicitly racist and classes. Lizzy Bartelt (she/her): This isn't Tiffany Monique Quash, PhD - CTRL: go ahead. No, it it just it just reminds me of a time where I wanted Tiffany Monique Quash, PhD - CTRL: to Tiffany Monique Quash, PhD - CTRL: instead of going by my full name, which I do professionally. Tiffany Monique Quash, PhD - CTRL: was go. I was going. I was going to go by Tm Quash Tiffany Monique Quash, PhD - CTRL: to like level the P. Playing field for myself. Tiffany Monique Quash, PhD - CTRL: because I was like, you know. Tiffany Monique Quash, PhD - CTRL: Tiffany. Tiffany Monique Quash, PhD - CTRL: it could go either way, you know. Gosh. Tiffany Monique Quash, PhD - CTRL: it probably leans more white. Excuse me, more black than white, but it could, you know you never know. So I was gonna go like let me go by Team Quash. Tiffany Monique Quash, PhD - CTRL: because then you don't really know, and you don't know gender. You don't know Tiffany Monique Quash, PhD - CTRL: you. You just don't know Tiffany Monique Quash, PhD - CTRL: But yeah, you're just saying so much Tiffany Monique Quash, PhD - CTRL: right now that resonates with me. Lizzy Bartelt (she/her): yeah. Tiffany Monique Quash, PhD - CTRL: I never. I never actually applied for a job Tiffany Monique Quash, PhD - CTRL: like that. But I definitely thought about it several times, and I had Tiffany Monique Quash, PhD - CTRL: friends that talked me out of it Tiffany Monique Quash, PhD - CTRL: because they're like. Why, why are you doing this to yourself? And i'm like. Tiffany Monique Quash, PhD - CTRL: I want to give myself the best chance. you know. So Lizzy Bartelt (she/her): yeah. Lizzy Bartelt (she/her): yeah, Well, and that's just it right. And it's how how do you know how to navigate that as an individual, but also how do we Lizzy Bartelt (she/her): change that As a system? Right? And I think both need to be addressed simultaneously, and it makes it so so challenging for the people Lizzy Bartelt (she/her): who know they're disproportionately impacted by that. Lizzy Bartelt (she/her): So true. Lizzy Bartelt (she/her): she breaks down that it's not just getting a job, but it's also how you maintain it. And hours are set by algorithms as well for a lot of big Lizzy Bartelt (she/her): box stores right now in big companies. Lizzy Bartelt (she/her): So Starbucks has this big mantra. Lizzy Bartelt (she/her): and i'm going to pick on them specifically because i'm in Buffalo, and there's been a lot of kernel with Starbucks lately last year. Lizzy Bartelt (she/her): Anyway, if you know what. If you don't that's fine. Lizzy Bartelt (she/her): So Lizzy Bartelt (she/her): Starbucks has this big company policy that says we'll give employees at least a week's notice of what their schedule will be like for the next week. Lizzy Bartelt (she/her): However. Lizzy Bartelt (she/her): the algorithms will decide 72 h in advance. Oh, there's a storm coming in, so people are likely to do a bunch of shopping from this window to this window. So then they'll schedule people in 72 h before Lizzy Bartelt (she/her): then that might be fine. But if you are somebody who has to arrange child care Lizzy Bartelt (she/her): 72 h is not a Lizzy Bartelt (she/her): no, and for most people who are working in those jobs. Lizzy Bartelt (she/her): Maybe they have low income or low education. Maybe that's the only job they can get. Maybe they don't have a partner. Maybe they do, but it's maybe they don't have somebody they can put the child on, and Tiffany Monique Quash, PhD - CTRL: they don't have that type of community Lizzy Bartelt (she/her): period exactly, and if you can't do that, then you're not working. And if you're not working, then that cycle is even worse for you, right because you're trying to figure out how else to get a job. But if that's the only kind of job you can get. Lizzy Bartelt (she/her): then what are you doing right? You have to figure it out, and so it becomes increasingly stressful and hard to manage and navigate. As you try to balance child care with work, and particularly given the high cost of child care right? You might have to be working all of those hours to be able to pay for childcare. Lizzy Bartelt (she/her): These systems also ensure that you're not working more than 35 h. So you're not ever getting Lizzy Bartelt (she/her): qualified for health insurance. Lizzy Bartelt (she/her): which is a really big problem as well. Lizzy Bartelt (she/her): So this becomes really tricky. a lot of these companies also use a big 5 personality test, and Tiffany Monique Quash, PhD - CTRL: with employment, which means they're violating them. Oh, okay, can I just say for the record. I did not get a job at Starbucks because I had to take that personality test. Tiffany Monique Quash, PhD - CTRL: I will let that go eventually. Lizzy Bartelt (she/her): eventually, Eventually. Tiffany Monique Quash, PhD - CTRL: at some point. Tiffany Monique Quash, PhD - CTRL: You know what i'm talking about, Dr. Lizzie. Do you know what i'm talking about it's like. Okay. Tiffany Monique Quash, PhD - CTRL: You okay. I'm: sorry. I don't mean to take the J out of the joy. See? Ca: Thank you, Kathy. Tiffany Monique Quash, PhD - CTRL: Explain it to me, Kathy, because I am very bitter. Tiffany Monique Quash, PhD - CTRL: I am very bitter. Tiffany Monique Quash, PhD - CTRL: Why can't I be on my lone island? What is so wrong? Lizzy Bartelt (she/her): So nothing is wrong. The problem is, even the people who have designed this will not be able to fully answer how they designed it, or why the test will reject. Some people, or will say, other people are good to hire. They don't fully understand it. Lizzy Bartelt (she/her): It is not 100% clear Lizzy Bartelt (she/her): there. The Lizzy Bartelt (she/her): companies will all say. No one question will bar you from employment. However, some questions, the way you answer them will give a red flag, and if you have a red flag you're unlikely to be called for an interview. Lizzy Bartelt (she/her): or you're unlikely to be hired. Tiffany Monique Quash, PhD - CTRL: Well, I guess I was just a cute red flag. At least Lizzy Bartelt (she/her): I mean to me it would show like, okay. Tiffany Monique Quash, PhD - CTRL: dependability. Tiffany Monique Quash, PhD - CTRL: you know, i'm, i'm dependable. I am somebody who, if you put me on that island by myself. Tiffany Monique Quash, PhD - CTRL: that I can survive. Lizzy Bartelt (she/her): correct. Lizzy Bartelt (she/her): correct. Lizzy Bartelt (she/her): but the same here, I can send this book to all everybody that I apply to other place. Lizzy Bartelt (she/her): Well, right, and the problem is, as she says, is like Lizzy Bartelt (she/her): you're stuck. If no matter what you answer, because you don't know what they're looking for. There's no rhyme or reason for why they're screening you the way that you are. And so you don't know how to answer most of the questions, because most of the questions are not like. Are you a hard work or yes or no? They're like. Lizzy Bartelt (she/her): Would you get angry if people were complaining at you in line, and it's like, and the options are either yes, all the time or yes, some of the time, and it's like Well, I don't know what to put there like. I would get very angry if somebody was yelling at me Lizzy Bartelt (she/her): right right. Who wouldn't but like Also, what does that even mean? And what does angry mean? Because what I think angry means might be very different than what you think. And. Lizzy Bartelt (she/her): huh? Tiffany Monique Quash, PhD - CTRL: Oh, as a chair. We are both on it today. We are both like a chair is not a chair, or maybe a Tiffany Monique Quash, PhD - CTRL: Yes, we are bringing it away. We're going back to our roots, our qualitative roots. Tiffany Monique Quash, PhD - CTRL: our chair may not be a chair. Yes, yes. Lizzy Bartelt (she/her): yes, all the way back to episode one. Yeah, if you haven't listened to that episode. Listeners. Lizzy Bartelt (she/her): please do it. It's a gem. Lizzy Bartelt (she/her): As I recall, I haven't really listened to it, but i'm sure it's a gym. I remember it being a chat. It's a gym. It's a gym because we were there. Lizzy Bartelt (she/her): That's right. That's right. Lizzy Bartelt (she/her): So Lizzy Bartelt (she/her): she also goes through some examples, and i'm not going to get go into all of these, but of credit, and how credit is used, how credit formulas are used, how health insurance is used how voting and campaign advertisements are used. Lizzy Bartelt (she/her): All of these are big data formulas and all of that is driven by these big data formulas. And so At this point she jumps into conclusion Lizzy Bartelt (she/her): and Lizzy Bartelt (she/her): talks about the Lizzy Bartelt (she/her): It would be great if we could get rid of these big data formulas right? That sounds lovely. Lizzy Bartelt (she/her): However. Lizzy Bartelt (she/her): even if we could get rid of them in education, the problem is that the formulas that they use in education have already fed into the formulas used for voting have already fed into the formulas used for the judicial system. They've already fed in to the ways the formulas that are used for how we're being advertised to Lizzy Bartelt (she/her): almost impossible at this point in our society to just pull out these formulas and the big data, and all of the flaws in them. Lizzy Bartelt (she/her): which, you know, is truly a depressing thought. Honestly, Tiffany Monique Quash, PhD - CTRL: just a little. Lizzy Bartelt (she/her): just to Smithy. Lizzy Bartelt (she/her): Okay, so Lizzy Bartelt (she/her): I want to read this because I think it's it's a lovely, lovely quote. but i'm actually going to give it to you to read. Lizzy Bartelt (she/her): So page 200 Lizzy Bartelt (she/her): start us off on the Are you at page 200 Lizzy Bartelt (she/her): the second paragraph, our national model. Tiffany Monique Quash, PhD - CTRL: our national motto Hmm. Tiffany Monique Quash, PhD - CTRL: I guess we're reading Latin now. Huh? Yup, Tiffany Monique Quash, PhD - CTRL: Thank you. E pluribus unum means out of many Tiffany Monique Quash, PhD - CTRL: one. Tiffany Monique Quash, PhD - CTRL: but wmd so weapons of Mass, M. A. S. Math. Tiffany Monique Quash, PhD - CTRL: M. 8, C. I did it. M. A. T. H. Tiffany Monique Quash, PhD - CTRL: Destruction Tiffany Monique Quash, PhD - CTRL: reverses the equation. Tiffany Monique Quash, PhD - CTRL: reverse the equation working in darkness. They crave or excuse me. They carve one into many while hiding us from the harms they inflict upon our neighbors near and far. Tiffany Monique Quash, PhD - CTRL: and those charms are legion Lizzy Bartelt (she/her): perfect. Lizzy Bartelt (she/her): Do you want to Lizzy Bartelt (she/her): do that one more time? Lizzy Bartelt (she/her): I am okay. Now, Lindsay, we're doing this again, because I can't read. Okay, Near and far is where I want you to. Lizzy Bartelt (she/her): Oh, near and far, i'm stopping. Yep. Tiffany Monique Quash, PhD - CTRL: Okay. Tiffany Monique Quash, PhD - CTRL: Our national motto E Pluribus on Unum means out of many one. But Wmds or weapons of mass destruction reverse the equation. Working in darkness. They carve one into many Tiffany Monique Quash, PhD - CTRL: while hiding us from the harms they inflict upon our neighbors near and far. Lizzy Bartelt (she/her): Thank you. Lizzy Bartelt (she/her): So Lizzy Bartelt (she/her): I love this I love. I think this is just a nice example of how brilliantly O'neal right, and like how lovely this ties together for us of Lizzy Bartelt (she/her): this reversal of this tenant of American Lizzy Bartelt (she/her): ideology! We were probably all taught this out of many one idea at some point in our childhood, or in my case many. I cannot tell you how many times we were shouted that at it like as children like Remember, get along with each other. That'll be my next step, too. Lizzy Bartelt (she/her): One right. Lizzy Bartelt (she/her): And yet this ideal of these M. At H. weapons of M at H. Destruction are that it's the reverse. It's Lizzy Bartelt (she/her): out of one many, and it's this: we're going to collapse. All of this data use all of this giant data to change, to say, like. Lizzy Bartelt (she/her): here's how we can understand people. And we can understand people in this problematic way or this problematic way, right? And I think Lizzy Bartelt (she/her): this is where I really wanted to spend some time actually chatting back up and forth, and like as we're wrapping up our discussion of this book, she says: One of the ways we can solve. This is through research. So we can use research to kind of poke calls in this and to say, okay, if we can't get rid of these Lizzy Bartelt (she/her): math formulas all together in this big data altogether, we can at least use research to pull calls in it. And to say, this is the problem with these formulas, and it's causing all of these problems. Lizzy Bartelt (she/her): We can also have conversations about it and educate people about it. We can also try to think about other ways of having data, hey? Lizzy Bartelt (she/her): Maybe this podcast will help you understand how to have other ways of having data. Lizzy Bartelt (she/her): but I think Lizzy Bartelt (she/her): there is no type of research that is without flaw. There is no type of research or information that cannot be used by somebody from a different ideology as yourself. Lizzy Bartelt (she/her): But if we don't talk about those problems, we allow them to perpetuate and to be reinforced. And so, as I was kind of thinking about the biggest pieces of this, these formulas are going to hurt. Our most marginalized community is more Lizzy Bartelt (she/her): these formulas. Lizzy Bartelt (she/her): We like to say that they are free of bias, because remember, back to our last episode listeners of positionality. And we talked about the fact that a lot of people think want is free of bias. Lizzy Bartelt (she/her): and what O'neill does so brilliantly in this book is, say, actually, these formulas are reinforcing bias. But we're pretending that they remove bias because we're saying, Look, none of these things within the judicial system. Ask about race because it's illegal to do so. Lizzy Bartelt (she/her): But they're asking about race because they're using other things as a proxy for it. The job employment applications with personality isn't asking about intelligence which is illegal. Lizzy Bartelt (she/her): But it's absolutely violating the Ada. But people who are most hurt by this who are most vulnerable to this are not being able to push back, because the employers are saying, Well, we're not asking about intelligence, so it can't be wrong, and it's like Lizzy Bartelt (she/her): this is a way to reinforce the human stereotypes and the human problems and imply them to the most vulnerable in our society. Tiffany Monique Quash, PhD - CTRL: You took us there. Lizzy Bartelt (she/her): Kathy took us there. Kathy took us there. Tiffany Monique Quash, PhD - CTRL: Wow. Tiffany Monique Quash, PhD - CTRL: Wow! Tiffany Monique Quash, PhD - CTRL: I'm sitting with everything that you just said. Tiffany Monique Quash, PhD - CTRL: because it makes me. It reminds me Tiffany Monique Quash, PhD - CTRL: again. I probably was one of those red flags. Tiffany Monique Quash, PhD - CTRL: because it was like, you know like. Oh, well, she can't be a team player. I'm like, Listen. I can be a team player. I just happen to to play sports where it's individual sports all my life, you know, like swimming tennis like those are Tiffany Monique Quash, PhD - CTRL: individual sports, you know. you depend upon yourself. Tiffany Monique Quash, PhD - CTRL: I feel like i'm defending myself in this moment. But Tiffany Monique Quash, PhD - CTRL: but I mean it's it's kind of like. Tiffany Monique Quash, PhD - CTRL: If somebody were to ask me that question. Tiffany Monique Quash, PhD - CTRL: Hey, are you going to get mad? If somebody is yelling at you Tiffany Monique Quash, PhD - CTRL: while you're standing in the Starbucks line. Tiffany Monique Quash, PhD - CTRL: you know, and you're behind the counter. I'm like, Yes, yeah, yes, I will get mad. I will do my best to push Tiffany Monique Quash, PhD - CTRL: whatever down, but I just i'm Tiffany Monique Quash, PhD - CTRL: could very well Tiffany Monique Quash, PhD - CTRL: get upset Tiffany Monique Quash, PhD - CTRL: because my feelings are hurt. I'm a human. Tiffany Monique Quash, PhD - CTRL: I'm a human Tiffany Monique Quash, PhD - CTRL: and isn't that a beautiful thing, and it is a beautiful thing I mean. Not all of us can be emotionless. Lizzy Bartelt (she/her): you know. I just. Tiffany Monique Quash, PhD - CTRL: We just can't be emotionless. I don't get it. I don't get it. Tiffany Monique Quash, PhD - CTRL: But it I I Tiffany Monique Quash, PhD - CTRL: It's really interesting. How how you took us through Tiffany Monique Quash, PhD - CTRL: like Tiffany Monique Quash, PhD - CTRL: how Kathy Tiffany Monique Quash, PhD - CTRL: takes us through Tiffany Monique Quash, PhD - CTRL: education. Tiffany Monique Quash, PhD - CTRL: and then the judicial system. And then. Tiffany Monique Quash, PhD - CTRL: you know, just employment. These are things that you need in life. Tiffany Monique Quash, PhD - CTRL: In order to succeed. Tiffany Monique Quash, PhD - CTRL: They and go go ahead. Sorry. Sorry. No, no, no! Go ahead. Go ahead. Lizzy Bartelt (she/her): They are, and I think Lizzy Bartelt (she/her): that's part of why I wanted to ask you at the beginning. What is the biggest problem in American society, right? Because I've spent the entire last semester. I was teaching social determinants of health, and every week I would ask my students. Lizzy Bartelt (she/her): Okay, let's talk. We would talk about race, and then we would talk about gender, and then we would talk about sexual identity, and then we would talk about class, and then we would talk about Lizzy Bartelt (she/her): geography and right, and we would go on this journey every week of talking about these different problems in our society, and how they impact our health? Lizzy Bartelt (she/her): and every week I would say to them. Lizzy Bartelt (she/her): how much is it life worth. Lizzy Bartelt (she/her): and whose life is worth more. Tiffany Monique Quash, PhD - CTRL: Hmm. Tiffany Monique Quash, PhD - CTRL: Become a simple life worth, and how and whose life is worth more. Wow! Tiffany Monique Quash, PhD - CTRL: And what were your students responses? Lizzy Bartelt (she/her): Well, mostly I would leave them that with that every week. But I would say right like it was kind of my ending question, because Lizzy Bartelt (she/her): is we're going on this journey, and then they would write me reflections, and they would be like oh, i'm thinking about this thing in a whole different way because of what we talked about in class or oh, i'm understanding how race is connected to classes connected to gender is called it Connected to a environmental toxins is connected to right, and so like they're making this web in their mind of how all of these are connected, and they'd say at the end of the day, public health is all about out Lizzy Bartelt (she/her): protecting the health of the most vulnerable. Lizzy Bartelt (she/her): But we have to understand who that is, and how that is. These systems are reinforcing themselves right. Lizzy Bartelt (she/her): and I think the conclusion for me is always been well. We don't care about certain people in our society, and we have set up our society to tell people that Lizzy Bartelt (she/her): Kathy's conclusion is, it's due to the math formulas and the big data, and that is reinforcing those Lizzy Bartelt (she/her): human stereotypes that we have had for years. And I think that's such an important conclusion to draw on. And I think how it connects us back to this is Lizzy Bartelt (she/her): we're Lizzy Bartelt (she/her): Where do we sit with research, and how do we conceptualize research? And how do we do the most good? How do we Tiffany Monique Quash, PhD - CTRL: change society from what it is to what we want it to be Sorry I don't want to say No, it's okay. I almost wouldn't say like, how can we be the better researchers? How can we Tiffany Monique Quash, PhD - CTRL: almost Tiffany Monique Quash, PhD - CTRL: like when we go into the field? How can we leave the field Tiffany Monique Quash, PhD - CTRL: as good, if not better, than when we left it? Lizzy Bartelt (she/her): The movie came. Tiffany Monique Quash, PhD - CTRL: Yeah. Lizzy Bartelt (she/her): yeah. Tiffany Monique Quash, PhD - CTRL: yeah, and and and it just, you know, as as researchers, I feel like sometimes we go in and we destroy it. You know, we don't. We don't really care. Tiffany Monique Quash, PhD - CTRL: and I think we need to change that. Tiffany Monique Quash, PhD - CTRL: You know we need. There needs to be a Tiffany Monique Quash, PhD - CTRL: a sense of caring Tiffany Monique Quash, PhD - CTRL: going on. Love Tiffany Monique Quash, PhD - CTRL: like being genuine when you go in. And when you leave, you know Lizzy Bartelt (she/her): that's right. Tiffany Monique Quash, PhD - CTRL: So yeah. Tiffany Monique Quash, PhD - CTRL: wow. Tiffany Monique Quash, PhD - CTRL: Dr. Lizzie. Thank you. Lizzy Bartelt (she/her): Yeah, yeah, you're welcome. Lizzy Bartelt (she/her): Thank you, Kathy O'neill. Yes, thank you, Kathy O'neal. Lizzy Bartelt (she/her): It was a great book. It was a great Think her Lizzy Bartelt (she/her): Wow! Lizzy Bartelt (she/her): Well, listeners, we appreciate you joining us on this amazing journey with myself, Dr. Tiffany and Dr. Lizzie. Tiffany Monique Quash, PhD - CTRL: We can't wait to have you back, and until next time Lizzy Bartelt (she/her): tears, tears.