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Take an Equitable Approach to your Data work with the Do No Harm Guide
283 Plays4 years ago
In the 200th episode of the PolicyViz Podcast, we discuss the recent Do No Harm Guide about taking a racially equitable lens with your data.
The post Episode #200: Do No Harm Guide appeared first on PolicyViz.
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Transcript
Celebrating 200 Episodes of Policy Viz
00:00:14
Speaker
Welcome to the 200th episode of the Policy Viz podcast. That's right. This is episode number 200 of the podcast. I've been running this podcast now for six years. I've spoken to countless practitioners, researchers, experts in the fields of data visualization, open data and presentation skills. And I'm so happy to still be bringing you this podcast every other week.
00:00:38
Speaker
I really don't know how to put seven seasons of a podcast into perspective.
Podcast Evolution from 2015
00:00:43
Speaker
I started this podcast back in 2015. It was originally just a couple of audio shorts that I posted on my blog thinking, well, I'll just have some conversations with some folks in the field.
00:00:55
Speaker
and then turned it into a podcast. And since then, it's really just been continued in the various interviews that I've done with people from all across the field of data visualization and data communication and research, not just in the data visualization field, but also in public health and economics and artificial intelligence, machine learning. You count it. I have been talking about it on this show.
Shifting Focus from Metrics to Joy
00:01:20
Speaker
Early on, I was really concerned about trying to get the number of listeners and the number of downloads up on the show. I was trying to track the downloads, trying to check where people were listening to it, what platform they were listening to the show. And after a while, I just said, you know what? I'm just going to keep doing it. I enjoy doing it.
00:01:38
Speaker
I enjoy interviewing people, I enjoy talking to people about the work that they're doing, about the insights that they can provide to both myself and to you as a listener. And so, about two years ago, I stopped looking at the traffic. I don't even know how many people look and download the podcast at this point. I just do it because I enjoy doing it. And I enjoy the technical challenge of bringing you high quality audio and high quality interviews.
00:02:01
Speaker
I've enjoyed trying to get it over onto YouTube to see how I can improve that platform and getting the podcast over there. But I've also enjoyed just getting to know so many different data visualization experts and practitioners. And in many ways, the show just follows my interests in the data visualization field and related fields.
00:02:19
Speaker
I started this past season back in September really focusing on racial equity, especially as it applies to data and data visualization.
Racial Equity in Data Visualization
00:02:28
Speaker
Obviously something that I've been working on a lot on recently with two recent papers, one on racism in the field of economics and one on how we as data communicators can do a better job communicating our data through a lens of racial equity.
00:02:43
Speaker
So before we get to this week's episode, and it's sort of a special episode, I want to just thank everyone who's been listening to the show, downloading the show, reaching out to me with guests, both specific people and general ideas for topics. I want to thank all the folks who have helped me pull this podcast together, the sound editors, the folks who helped me with transcription, the folks who have made suggestions on different technical ideas of recording equipment and platforms, all the different support
00:03:11
Speaker
that I have required to make this show what it is each and every other week bring you to you for the last six years.
Interview with Host on 'Do No Harm Guide'
00:03:20
Speaker
So I'm very excited to bring you the 200th episode of the podcast. And for this 200th episode, I am going to switch things around a little bit. So instead of me interviewing someone on the show, I've actually invited two other folks to interview me on the podcast.
00:03:36
Speaker
So as you may know, a couple of weeks ago, my Urban Institute colleague Alice Feng and I released a report, the Do No Harm Guide, a view about racial equity in data visualization. We focus on many aspects of how we as data communicators can take a better perspective on racial equity as it applies to data and data visualization. For example, the words that we use in our graphs, the way in which we order racial and ethnic groups in our graphs.
Renee McLeod on Inclusive Marketing
00:04:04
Speaker
So for this week's episode of the show, I invited Renee McLeod, who is from Tableau, to help us talk about the Nuno Harm Guide and interview Alice and I about the report. So Renee works at Tableau. She has three daughters and she is on the board of directors at Families of Color Seattle. She has led inclusive marketing efforts at Tableau and she centers her work on the convergence of technology, data and community for driving advocacy, understanding and
Alice Feng Discusses Diversity in Data
00:04:34
Speaker
impact.
00:04:34
Speaker
Alice, my former colleague at the Urban Institute, she is now on a new adventure at Natira. She is passionate about using data and making data and information accessible to broader audiences, and she has been exploring ways to bring diversity equity inclusion into her daily data visualization work.
00:04:53
Speaker
So I hope you will enjoy this turnaround on the policy of his podcast on this week's episode of the show, where we're going to talk about the do no harm
Origin of the 'Do No Harm Guide'
00:05:02
Speaker
guide. So we'll get right to it. Here is our discussion with Renee, Alice and myself. Hey there. Nice to meet everybody. I am Renee McLeod and I am a part of the marketing department over at Tableau and my role is around
00:05:21
Speaker
kind of building out our inclusive marketing office. And what that means is how do we make sure that folks are taking an inclusive lens against how they approach the work, right? So it's not just about DEI anchored topics or content or events. It's really about how do we make sure that end-to-end we as an organization are proactively thinking about inclusion in everything from
00:05:50
Speaker
how we think about who our customers are, how we think about our strategy, who we work with, all the way through to the content that we kind of put out there in the world. And that is one of the things that actually resonated so much with me about the Do No Harm Guide and your work, John and Alice, like to be able to, the way that you're thinking about how this lens can fold into research
00:06:19
Speaker
um, and the visualization of data and how you're working with communities that just resonated so much with what we're trying to accomplish, um, in our work. So I was really excited to get to be a part of this conversation and get to work with you. So.
00:06:37
Speaker
Yeah, thanks Renee. I guess I'll start. It was a long project and I think we learned a lot, not just about like the topic and the message of the report, but also how to do this kind of work. I mean, I don't want to speak for Alice, but like, I don't think either of us, I mean, I'm certainly a quantitative person. So like doing all of these interviews was definitely a new kind of experience. And then we talk a lot in the paper about like,
00:07:03
Speaker
quantitative people should be doing more qualitative work. And so we're trying to live by what we were, what we were talking about a little bit. Um, but it was a, it was a challenge in a lot of different ways. And it feels new, right? Like I feel like there are elements that have been touched on, right? From different perspectives, but this kind of cohesive guidance I think is really, really interesting and helpful. And it was one of, was there a particular catalyst or point in time
00:07:32
Speaker
where you realize that there was a need to address these topics or there was a need to kind of take this approach. Yeah, I mean, I think it's been on our back burner for a while. The original impetus for this work was from a plant update we wanted to do to the Urban Institute's data visualization style guide.
00:07:50
Speaker
And as part of that update, we wanted to expand beyond just giving design specifications or chart guidance.
Expansion with Tableau Support
00:07:56
Speaker
We wanted to make it a more complete and holistic document, and so we wanted to touch on other topics that go beyond just design of charts, but things like accessibility and this idea of how to integrate DEI into the way we visualize data was another topic that was brought up.
00:08:10
Speaker
But we embarked on this update a long, long time ago. I mean, when John said something could work on his fur for a very long time, he was not exaggerating. I mean, literally, before the pandemic, we started drafting this update. And so we had this idea that we were going to add DEI as a new section to this style guide. But I think our efforts were a bit slow in the beginning, just because this area was so new and undefined. We didn't see a lot of other people who had already been tackling these sorts of topics.
00:08:40
Speaker
So I think, yeah, we kind of let it slide dormant for a while until last summer, last May, when all the racial justice protests were happening, we realized that, oh, we can't just continue to sit on our hands here. We really have to do something. This is our opportunity to contribute to this broader dialogue this entire country has been having in a field that we are
00:09:04
Speaker
you know, both very comfortable with. And so we, I think that was kind of like the catalyst for us to really start moving on this. And there were already a lot of other people thinking about this, maybe we'll, we'll be the first ones to sort of start a, you know, plant flag in the ground and at least come out with our own thoughts.
00:09:20
Speaker
um, and ideas about this topic. Um, and from there, I think we just, it gets kind of snowballed. We got a great response to the original short paper that we published last year. And then, yeah, Tableau, I know John, you can probably talk more to exactly how we got connected with Tableau on this, but thanks to the support from Tableau, we were given an opportunity to really build on that initial short paper that we created and had a chance to really embark on this really great journey. Um, we got to talk to so many more people and just
00:09:49
Speaker
I definitely brought in my own horizons in terms of thinking about DEI and data bins. Yeah, it's also the case that there's so much research at Urban going on about different groups. We have a justice group that's working on criminal justice. We have a health group that was working on issues, especially during the pandemic, obviously, around COVID and how that was affecting different communities, especially communities of
Empathy in Data Visualization
00:10:12
Speaker
color. And I don't think we were really giving
00:10:16
Speaker
as an organization, giving a very strategic thought about how we were. Certainly we were trying to use people first language, but that's kind of as far as we went. And I think in the teams that were doing data visualization specifically, now I can say for myself, like it wasn't really something that I took a conscious thought to. And so could, you know, could we not so much set rules, but at least place a marker down that says at the end, like,
00:10:41
Speaker
Think about this, like just pause, take a breath and think about this. And then, you know, maybe the words that you're using are correct and maybe the order of the variables in the bar chart or table are correct. And that, you know, that can be fine, but there's probably a better way and we need to be thinking about that. And I don't think, I know I wasn't really taking a hard look at that before Alice and I really started diving into this, into this work.
00:11:08
Speaker
I think that's one of those things that stands out to me too, what you said just a moment ago about pausing, right? And I feel like sometimes, you know, sometimes we get caught in our brain tracks, right? And we keep doing the same thing and it is now best practice and we don't kind of reconsider, you know, how do we kind of influence a change to influence a change, right? Like, how do we take that moment? And I feel like,
00:11:35
Speaker
That's one of the really kind of lovely things about this as a tool, as a resource for folks to kind of help people bridge that gap. Um, you know, Alice, when you were talking a moment ago, you talked about kind of how initially this started as a style guide and then it kind of evolved into this do no harm guide. Did the process of creating it, did the process you were going through evolve with that or what did that process look like to where you were able to bring this into fruition?
00:12:04
Speaker
Yeah, I would say definitely process evolved a lot between the style guide and that initial short paper that John and I wrote last year. Our process was very, I guess.
00:12:17
Speaker
internal for lack of a better word.
Inclusive Practices in Data Development
00:12:19
Speaker
I mean, it's really just he and I kind of thinking, brainstorming, getting down our own thoughts. But we realized too, we really wanted to expand the scope of this work and bring in all the other issues surrounding DI and data biz that go beyond just, you know, what does your chart look like? We would have to talk to other people, you know, engage with other people working in this field. And I think that's one of the biggest changes in our approach between
00:12:46
Speaker
initial work and then this do no harm guide was, as John mentioned, going out there and conducting interviews, doing more qualitative type work, really reaching out to a variety of folks, people in academia, people in journalism, people in the private sector, really trying to get a variety of viewpoints and experiences as a guide about the I should.
00:13:10
Speaker
And yeah, just talking with them, learning from them, they connected us with more people, with more resources, and definitely, I think, made for a much stronger piece of work than it feels just what John and I could think of and were aware of. Right on. Right on. I'm just curious about the folks that you interviewed. As you were kind of going through this, it sounds almost like a snowball, right? Like has it evolved and grew?
00:13:38
Speaker
Did you find that you were connecting and having conversations with people from different fields? What did that look like? Was it researchers? Was it community members? What did that look like?
00:13:51
Speaker
Yeah, it was interesting. So I think we had like in the first, in the short paper that, you know, back to the style guide, like that paper starts with in redeveloping our Urban Institute style guide. I mean, it really starts with like, that's the anchor. Whereas the new piece is anchored on the issue of taking a more inclusive look to data and database. So it is just like a total sea change. I mean, we had a few people that we cited in the original paper that we reached out to.
00:14:21
Speaker
And then especially in late 2020, you know, we were connected with other people and then there were people just like doing more work. So I saw the director of the UCLA, I think their name is like center of public health communication. I can't exactly remember what, but Nina's Ponce runs that group and I saw Nina's talk at
00:14:43
Speaker
some event, you know, some virtual event and I was like, wow, like they are clearly doing work that is aligned with the work that Alice and I are doing. So, you know, you sort of take a shot and hope that they'll get back to you. You know, I sent Nina an email and she was like, yeah, we'll definitely talk. Like here's the six other people on our team that, you know, would also like to talk with you. And then we had talked with them for like 90 minutes and they said, you should talk to, you know, here's the seven other people you should talk to. And I'd say, you know, we
00:15:11
Speaker
You know, we had to at some point constrain ourselves because we could have spent, you know, hours upon hours talking to people and never getting to the point of like actually trying to circle around with what are we going to say? What is the point of this document? You know, you have to again, I come back to this like qualitative quantitative thing just because like for me personally, there's a lot of parts of this project that have been
00:15:32
Speaker
personal in a lot of ways in both like professionally and personally but on the professional side like the the concept of doing this qualitative work like when you do quantitative work for me at least you download some data you analyze the data you run your thing you write your paper and it kind of like wrapped up in the little bow
00:15:50
Speaker
And the qualitative work is like there's just all these threads that that just reach out and like I'm just fascinated by how qualitative folks end up like how do you cut the thread right and say okay I've like reached the point where like I can write this up and I think Allison I at some point just said we need to start writing and stop like talking to everybody.
00:16:11
Speaker
Because the other thing is to the other part of your questions, like all the different sectors that we talked to, I mean, it's so interesting to talk to a data journalist and then talk to someone in public health and then talk to a sociologist and then talk to someone, you know, building technical tools. I mean, you're learning all these different things and all these different perspectives. And that's terrific. It's like kind of like being a graduate student again, like you're getting paid to learn. Right. Like that's amazing.
00:16:36
Speaker
But at some point you have to rein it in and say, okay, we're gonna start writing. And I think that was part of our challenge, was reining ourselves in to say, okay, we need to sit down and wrap this phase of the work up and start pulling it together.
00:16:53
Speaker
Yeah, I will say the other thing I was really blown away by was just the response we got when we reached out to people asking if they would be willing to take the time to talk to us.
Embedding Empathy in Research
00:17:00
Speaker
I think, you know, when John and I started drafting up a list, we, our expectations, like, maybe less than half of people would say yes, or even respond. And yet the vast, actually vast majority of people were very willing to talk to us. And they were many people we
00:17:12
Speaker
had no personal connection to, we had never really reached out to before, but they were just kind enough, generous enough to give us our time, give us their time. And I think that also just speaks to, yeah, just desire, enthusiasm to talk more about this really important topic. So that was, I think, also something that made it really exciting, but also, yeah, it would be hard to cut off because everyone just kept saying yes. Yes, and also you should talk. Yes, and also you should talk. Yeah. Well, and that's one of the things that has been
00:17:40
Speaker
you know in in my experience as well and another thing that resonates right is this there are these learnings and perspectives that when you kind of broaden the lens in the field of who you're speaking with that carry into what we're doing right like i feel like what you have created here is you know i you know i understand it's it's uh it's on a specific topic but the tenants that you speak of right and one of the things that has kind of
00:18:09
Speaker
really stood out to me was how you speak about empathy, right? And like these are the things that I think play into like different areas where folks are trying to apply a similar lens, right? Like I've learned so much from both of you that I can bring into my own work, right? Even outside of the piece where we're talking about visualization or some of the other elements. Could you talk to me a little bit about
00:18:37
Speaker
empathy and the role that that kind of played in this work for you. Yeah. That's a, that's a big, a big, if you want to start, I think there's in the database field specifically, there is this concept of how do we get our reader or our user
00:19:05
Speaker
to be empathetic with the content that we are presenting, right? I mean, it's just a constant challenge when you're communicating data. Like how do you get people to feel, you know, GDP and unemployment, but then like, you know, COVID mortality, infant mortality. Like how do you get people to put themselves in the perspective of the people that you're talking about or the data points, right? You make a bar chart and you're aggregating
00:19:35
Speaker
you know, deaths from COVID and it's just this abstract shape. And, you know, how do you get people to relate to that data? How do you get them to feel that so that they want to do something about it, right? And they want to, and policies can be changed and society can be improved. And so I think that's just an underlying challenge in the database field. And I think we wanted to see if we could take that
00:19:59
Speaker
another I don't know if it's a bigger step or just in a slightly different direction when it comes to it's not just about that abstract shape it's about you know who are you representing who are you talking about in in the in the visualization that you're that you're producing and
00:20:18
Speaker
I would say it was a common, it's certainly a common through line in the project, in the report. And I would say also that it was pretty common in all of our conversations that empathy or some variation on this idea of empathy would come up. And I'll just, I'll say one more thing and then let Alice fix everything. I said this wrong, but the conversation we had with the UCLA team,
00:20:41
Speaker
was really interesting. They do a lot of work in Southern California with Native Hawaiians and Asian Pacific Islanders. And one of the parts of that conversation was they bring a lot of their products about the AAPI community to the community groups that they're in touch with.
00:21:02
Speaker
And one of the members of that team told us, we've built these relationships over time. And one of the things that we have to do, especially for the Native Hawaiian community, is to go to them. We can't have them. Just the way that that culture and that society and that community works, we go to them. We don't have them. They don't come to us. And just that very,
00:21:26
Speaker
I don't want to say it's simple because it's not simple, but that insight was really striking to me because it is something that you have to do from the researcher or the data producer perspective position. And it's a physical thing you have to do, right? It's not sitting behind your computer, right? It's not picking the colors for your bar chart. It's something you physically have to do. And that to me was one of the bigger insights for me of this whole work that there's more to everything that we're doing that it's more than just
00:21:56
Speaker
using better words. It's more than just picking colors that make sense and not using icons that are racist or stereotypical. It's just, it's more than that. And that's, I think how the, the project went from what, as Alice mentioned earlier, that we thought we just talked to a few people and we write like a 15 page thing to, to, to growing to this 50 page report and talking to, or, you know, however many we, you know, a couple dozen people.
00:22:20
Speaker
Yeah, I think I think Johnny captured it perfectly. It's just empathy I think needs to be baked into the entire project and process. It can't just be retrofitted onto the database portion. You can't just make your charts with people first language and the right colors. If your entire research process of the data you're using is, you know, flawed, biased, racist, what have you, right? Following the principles in our guide won't fix those sorts of issues. So you really need to have empathy in the way that you engage,
00:22:50
Speaker
your communities, the way you approach your research, the way you're understanding of your data, and also just who it is that's doing the research. Who are you? Who's your team? Who's your organization? Do you all also reflect and embrace that spirit of DEI? I think all these pieces are really important to have final communication products that are empathetic. I guess the other thing I would also add is that, as John mentioned, in the database field, there's definitely some debate over whether or not
00:23:18
Speaker
DataViz can even...
00:23:21
Speaker
really achieve any empathy, right? There's some people who I think feel strongly that charts and graphs just, they just can't inherently they can. But I would argue even if you have that perspective, database can definitely be still used in wrong and harmful and harmful sorts of ways. We have that example of the red lining map from the homeowners loan corporation, right? And that's definitely a very explicitly racist data visualization that has had harmful impacts that's been perpetuated across generations. So even if you don't necessarily believe that database can achieve empathy,
00:23:51
Speaker
If you aren't still thoughtful about how you make your charts and how you communicate your data, you can still end up with harmful impacts, right? I think that's obviously how I would add. I'm so glad that you are speaking to this. As you're speaking to this idea of, there are the end game things that you can do that will visually do A, B, and C and help you do these things.
00:24:19
Speaker
But if from the beginning, from the development of your strategy, how you're choosing to engage, like if you're not bringing that lens in early, it can influence all throughout. And I feel like that's one of the things that has stood out for me when I was reading through the guide is that it takes
00:24:42
Speaker
things that may initially feel abstract and provides practical guidance. And I think that that is one of the big missing pieces and from the beginning, right? Like it has you think foundationally. And so I think that's one of the things that stands out to me and that I am incorporating.
00:25:03
Speaker
into my own work. That's awesome. That's what we want to hear. I mean, it is. I think we definitely struggled with some of the sections like we write about, you know, having a diverse workforce and a diverse teams and how that impacts the analysis. And, you know, there are whole
00:25:23
Speaker
libraries, right? Whole, you know, sets of literature on that particular topic. And, but we felt it was important, especially when it comes to the data part. Like it's not just about having diverse teams because having diverse teams is, you know, good in some sort of.
00:25:40
Speaker
you know, I don't even know what the woke, right? Like in the derogatory use of the word woke, right? But that having those diverse teams makes the final products better, right? And thinking about these different groups makes the work ultimately better. I'll tell one story. So this is sort of a little off topic, but you know, one of the things that we considered early on is should we write about accessibility,
Practical DEI Alternatives in Visualization
00:26:07
Speaker
right? So should we write about
00:26:09
Speaker
you know, people who have challenges with, you know, because of vision impairments or physical impairments. And we said, you know, again, we need to like, we need to cut this off at some point. Otherwise we're, you know, we'll never get it done. But we, we're doing similar work along those lines. And we ended up talking to our blog team.
00:26:27
Speaker
head urban about, you know, we should have our researchers write alt text for the images that appear in their blog posts. And we sort of have this back and forth. Well, should the researcher do it? You know, they don't really know how to write alt text. You know, it is a skill, even though they're content producers. Well, maybe the blog team should write it because, you know, they're the writers and, you know, they know how to write it. And Alice made this really fantastic point in this meeting that
00:26:49
Speaker
The researchers really should write the alt text because it forces them to recognize that there are these other needs and these groups of people that maybe the researcher doesn't necessarily think about immediately. And I think that that insight was one of those other things that sort of came out of this report.
00:27:08
Speaker
And again, sort of right goes back to empathy. I mean, at its core, right, that's that's about empathy. But it's about getting everybody in this case, everybody in the organization to think about and think about these other groups and to have empathy as opposed to saying,
00:27:23
Speaker
there's this group of people in the communications department or in the dataviz department and that's their job to think about that and the researchers or the marketing folks or the PR or whoever it is will just do their work and these other people will think about it and that's where we tried to I think kind of tried to bridge the gap a little bit. Yeah and that that seems like another example of that pause right and and when you're talking about
00:27:49
Speaker
I feel like there's this third piece when we're talking about the process being more inclusive, leading to a better outcome too. I feel, as someone who gets to experience being an only in different rooms, it also, I feel, makes spaces more inclusive for the people doing the work. If you're not always the one that has to raise your hand to flag the thing,
00:28:19
Speaker
because it's attached to your identity or somehow connected or whatever the reason is. And so that's the other thing that I think is really great. And because the way that you have painted this picture with this guide, I feel like it helps kind of bring in that context there. We were talking about the practical application a little bit and we're talking about having a moment to pause
00:28:47
Speaker
And so I was wondering, can we talk a little bit about why it's important to, like, it's important to have best practices, even while we're kind of breaking old practices. Can you talk a little bit more about that? I feel like you're, you're, you're example a moment ago, kind of, kind of touches on this, but if we could go down that road further, I'd be into it. You ought to start. Want me to start? You start. Hey, you can go for a shot. I mean, I think.
00:29:13
Speaker
The whole guide is intended to be practical, right? It's intended to, and it's not intended to be a set of rules. I think we, we were pretty conscious about that upfront. I mean, I will say from my perspective is like.
00:29:28
Speaker
I have to say middle-aged at this point. It feels very middle-aged. Middle-aged white guy. Like, perhaps I'm not the right person to be writing about this. And so we definitely didn't want to set rules. We definitely didn't want to say this is the right way or the wrong way because
00:29:45
Speaker
like you said earlier, Renee, like there's not a lot out there on these particular topics. So how can we just, I don't want to even say like kick off a discussion because these discussions are being had, but like, how can we sort of have this maybe cornerstone document that can really start, you know, have more of the literature written around this and maybe we can find best practices. I mean, I think for me, one of the,
00:30:10
Speaker
Most tangible things that we talked about was like finding a phrase to replace the word other or a word or phrase replace the word other in our work like again you know i download any data set that i use in my in my research there's gonna be a category for other and there are lots of.
00:30:29
Speaker
technical reasons that that happens. There's like survey reasons, there's practical reasons why, you know, survey instruments don't just list 500 categories in every survey. I mean, there are reasons for it, but as the communicator, are there better ways? And can we provide in this particular guide, can we provide the reader with some practical alternatives? And I think we, I mean, just interestingly, like stumbling upon
00:30:56
Speaker
you know, people trying different things. We have a list, I think of like seven or eight alternatives. And one of those options was like, someone sent it to me in like the chat window of a talk I was giving like, Hey, what about, you know, this idea and like, okay, yeah, that, that works. Like.
00:31:11
Speaker
Sure. Like whoever has a good idea, let's put it in the hopper and let's see what works. And, um, I think there's in DataViz, one of the things that I like about the DataViz community is that for the most part, people are kind of like, there's not really rules. We're just kind of trying to figure out what are the best ways forward. And there is research obviously, but a lot of it is on, on the practice, like let's try some things and let's see what works and let's see what doesn't work. And, um,
00:31:41
Speaker
And, and we'll see what, you know, what we think kind of works the best. Yeah. And I think the other thing is that I hope that our guide also offers, uh, sort of a variety of effort for some of these, uh, changes might be like, like, I think there's some steps that are. Pretty manageable, right? Like in terms of how much change we're asking you to make, like things like choosing a better color palette or like alternatives to the word. Oh, they're using people first language. Like those are changes, I think.
00:32:10
Speaker
are within a scope that most people I think would feel comfortable embracing. Or some other changes we asked were, like, how do you go about doing organizational change? Or how do you go about, you know, doing qualitative research, if that's not at all your background? Or how do you, you know, address data that might be biased? Or like, those things might feel like really big, kind of daunting topics, you know, things to try to embrace in your own practice. So I hope the guy kind of offers like a spectrum of things that are easily achievable, and things that are maybe a bit more ambitious. So people
00:32:38
Speaker
are overwhelmed, but can definitely read the guide and come away with some concrete actions that they can hopefully themselves and their teams actually implement in their work. In this piece, it's a little bit attached to what we were just talking about and the idea of there being, we got to focus in on scope. Where do we hold the line? Sorry, stick with me. There's a couple of ideas in my head right now. There's that piece.
00:33:08
Speaker
But then there's also this idea or this piece of some of the idea of evolving understanding, right? Like even I'm hearing conversations about evolving from the word inclusion because it implies being someone brought in versus belonging, which is like you are already here and you are supposed to be here. And when you think about the way forward, right?
00:33:36
Speaker
Can you talk a little bit about how you see this guide potentially evolving or other kind of conversations that you hope grow from this point?
Guide as a Starting Point for Evolution
00:33:47
Speaker
Yeah. I mean, I would say that this guide is definitely very much a living, breathing document. It is very much a first iteration or first volume. It's something, you know, we don't, we certainly don't claim to be experts that, you know, this, this is it. This is how you do DEI database, right? This is just, this is the list.
00:34:06
Speaker
We've dropped all the knowledge that we can walk away. We are absolutely open to receiving feedback. We hope we'll receive feedback and we want to hear from other people what other things that we miss, what other things that other people are doing. And so we definitely anticipate that this is a
00:34:26
Speaker
document that will continue to be hopefully updated and maintained over time. And we are definitely other topics that we know we haven't touched on accessibility, as, as I mentioned before, this conversation definitely is a big another really big gap that currently exists in the field of data is that's something that absolutely needs to be addressed as well. And just yes, you know, society technology continues to change and evolve, we expect
00:34:50
Speaker
our thinking will evolve, best practices will evolve, new issues will also come up that will need to be addressed. So yeah, I think that this is very much just the start of a conversation, certainly not the end of one.
00:35:04
Speaker
We were in the last week or two as we're wrapping up all of the work on this. We're in the stage of getting all the final touches on the report, doing the copy editing, getting all the blogs written, all the things that you have to do now. It used to just be you would write the report and you would be done. Now there's this whole ecosystem around it.
00:35:21
Speaker
I'm listening to an episode of code switch and they're talking about, do we need to retire the phrase people of color? And, you know, we've kind of had this phrase people of color and now we have, um, you know, we have BIPOC and there's a whole part of the podcast is like, what, how do we pronounce BIPOC? You know, and, and so I'm, I'm, I'm listening to this podcast. I'm like, Oh my God, we should have included that in the report. Like we should be talking about, I'm like, okay, this is, this thing is going to keep evolving and it's going to keep changing and we're going to need to
00:35:51
Speaker
you know, kind of constantly update it and revisit it. And, you know, I think that's the challenge both as data communicators and also just society, right? That we need to keep revisiting. And if we can keep that empathetic approach to all of this, I think we can, you know, we can keep doing that and that's okay.
00:36:14
Speaker
And, and be willing to make those changes and to say, yeah, the language that we used last year is not the language that we're going to use this year because reasons X, Y, and Z. I think that's a, I love that you use that example. I was, um, I was actually just this weekend having a conversation about this with some close friends of mine. And we were talking about how we identify.
00:36:43
Speaker
just a low-key lady's day. We're talking about how we identify and how that evolves. We got into this conversation, and one of the things that stood out to me is just what you called out. One, the evolution of language, but also from the code switch perspective, the different ways that I may describe how I identify based on the context and based on where things are out.
00:37:06
Speaker
That's one of the things that I think is really that I'm so glad that we're having these conversations so that there can be an understanding of that. Like even being aware that that is a consideration when we're doing this type of work is a, is a win, right? Because if you know it, you might see it. You might kind of have a moment to understand it. Um, I have another question I want to ask and I were almost out of time, but one of the,
00:37:32
Speaker
You know, one of the other elements of that, those evolutions and of, to Alice, to your point, like these big rocks, right? When I'm approaching my work and trying to bring folks along and provide resources and as folks grow their own lens, that's one of the challenges, right? Is that it's kind of a moving piece. I was wondering if one, if you have any thoughts on
00:37:59
Speaker
Do you see that as one of the biggest challenges or do you have ways that you would suggest that people think about this work to better equip the folks around them with it? Is there any standouts for you? Change is the hardest part of this. I think we know that everything changes, right? That language and when it comes to data and data viz, like the technology and the tools, all of that's changing.
00:38:28
Speaker
I think a couple things we need to do is one, we need to be able to have these conversations.
Importance of Open DEI Discussions
00:38:34
Speaker
We need to be able to talk about race and we need to talk about ethnicity and gender and the intersections of all those different groups. And we need to be able to have those conversations openly, especially with the people that we work with. I mean, at least we start there, right? And we can say,
00:38:50
Speaker
What is the better path forward for us as a team or an organization? And then it builds up to society as a whole. But if we can have those conversations openly and honestly, which is very hard to do. And I will say, something that I reference a lot, Robin DiAngelo and her White Fragility book,
00:39:12
Speaker
makes, I think, the accurate point that talking about race is not easy for white people. Because as a white person, we take for granted. We don't have a lot of the, Renee, as you just mentioned, I don't have a code switching perspective. I don't have to think about that. And that perspective is something that we, I think, can change, obviously, again, back to the empathy, but also having people around us where we can have these conversations. And especially within a group or a team,
00:39:41
Speaker
where someone can say to me, John, you said this thing wrong, or you wrote down this thing that it doesn't have to be a personal thing. You use this term that I think would be better off if we use this other term. It's not aggressive. It's not personal. I think we could be improved. That, I think, only makes us all better. And that, again, is, I think, in a lot of ways, easier when it's within our own teams and groups and organizations when we are working with the people that we
00:40:10
Speaker
trust and are friendly with and interact with all the time, you know, before you worry about saying something wrong on Twitter, you know, Facebook, you know, the social media machines. So I think that's where I tend to think about starting is that honest discussion. Yeah, I think definitely honest discussions are critical. I think I think I would hope that our guide is one of those tools that for people who are trying to
00:40:38
Speaker
bring about change in their organization. There's always going to be spectrum of people who are very eager and embracing of these sorts of efforts. And then there's always going to be people who are just incredibly reluctant, no matter how many brown bags, no matter how many resources you throw at them. They just aren't going to attend. They're not going to read it. They just don't want to be involved or think about these issues at all, right?
00:40:56
Speaker
So I think for the people who are like the change makers within their organizations, I hope that our resource can be one of those tools that helps them bring about that change and that they can point to as they try to convince the less change friendly people in the group that, you know, this is something we should all be thinking about. This is either the practices that we should be adopting. This is a better way for us to be doing our work. So I hope we can also help people in that sense as well. Awesome. So
00:41:24
Speaker
Uh, I think y'all know, I have a favorite last question. So after our chat today and, and though the work that's underway, if there's one thing you want to make sure folks walk away with that really sticks with them, what would that be?
00:41:53
Speaker
I mean...
00:41:57
Speaker
Gosh, there's so many things I hope people take away from our report. But I would just, yeah, I think I would just continue to reiterate the thoughtfulness, right? The fact is that the world is really, really complex. Issues like racism or discrimination, those are very, very complex topics. And I think that's part of the reason why we shied away from trying to claim we had any rules about what to do or what not to do. The fact is, it's going to really depend on your situation.
00:42:25
Speaker
topic you're studying, on who you're communicating to. So just be thoughtful when you make decisions and don't be afraid I think as well to try things. This is a really difficult topic, it's hard for people. I think a lot of people I think have good intentions and don't always know how to go about doing things in the best way and so they become afraid of even trying but we're all going to
00:42:53
Speaker
mess up, and that's okay. Just keep trying, keep learning, keep being open to hearing feedback from others. And ultimately, I think if we keep doing that, we can hopefully really bring about a better society for all of us. So I think my answer, you'll see why Alice and I work so well together. So Alice has the aspirational thoughts, and I am going to give you like the more practical thing that I hope people do.
00:43:21
Speaker
There are a lot of practical things, I think, in the guide. And for me, I've already talked about the word other, and we have some suggestions for that. But the other one is, when you are making your bar chart or your table or your graph, the order of the groups, just think about what is that order. And that's a practical thing that everybody can do. And if you take your racial groups and you order them by sample size or you order them by population,
00:43:50
Speaker
Those are reasonable ways to order your data. If you order them alphabetically, but maybe ordering them by the purpose of the study or the magnitude of the effect. Like there's a lot of ways that we can present our data. And, and I just hope that in, as just as that is an example, that people will think purposely about how they're presenting their results to their reader, their user, their audience member, whatever it is. And keeping in mind that, you know, how would you feel
00:44:19
Speaker
If you were one of those data points and how would you feel being presented always in the last column or the last row or the last bar, even if the effect was large or whatever. So, um, so this is why Alice and I like make the perfect team because we get both the macro and I'll do both more of the micro stuff. They're hand in hand, right? Hand in hand. Yeah, that's right.
00:44:43
Speaker
That's awesome. Well, thank you. And thank you both for letting me come and be a part of this conversation with you. I really, really dig this work and talking with you. So just congratulations. I know this was a long road. Thanks Renee. Appreciate it. Thank you for doing this Renee.
00:45:03
Speaker
And thanks to everyone for tuning in to this week's episode of the Policy Viz Podcast. I hope you enjoyed it. I hope you have taken time to listen to maybe some of the 200 previous episodes of the show. So this is the last episode of the show for the summer. I'll be taking a break, but back to you again in September with more episodes. If you would like to support the show financially, head over to my Patreon page.
00:45:27
Speaker
where you as a patron not only can receive some good PolicyBiz swag, but also can ask questions to future guests on the show. So that'll be something new that you'll be hearing in the new season of the show. I'll be asking some questions that are provided by my patrons. So have a great summer. Thanks again for listening to the show. This has been the PolicyBiz podcast. Thanks so much for listening.
00:45:50
Speaker
A number of people help bring you the Policy Vis podcast. Music is provided by the NRIs, audio editing is provided by Ken Skaggs, and each episode is transcribed by Jenny Transcription Services. If you would like to help support the podcast, please share it and review it on iTunes, Stitcher, Spotify, or wherever you get your podcasts. The Policy Vis podcast is ad-free and supported by listeners. If you'd like to help support the show financially, please visit our Patreon page at patreon.com slash policyvis.