A wonderful conversation about how social media works, and the humanity of data. Check it out!
“Data is man made. This is something that we need to stress, especially in the age of generative AI. You know, even for a pedestrian who is listening in who may not be very well versed in social media, you probably have the experience of now opening a browser or a search engine, trying to look for information, but before you even get your search results, there is an automated AI version that claims to be a summary of everything you need, saving you time in scrolling and clicking. That is engineered by a person. The rankings where the information is scraped from, all of that is trained on engineers and what they perceive to be quality information versus what should be filtered out. And there are values involved in this. The ranking of search results is not always neutral, not always rarely neutral actually these days,”
“What was missing from this whole experience was learning how to be a good human citizen in society. I think one of the things that is the downside of a very competitive education system in Southeast Asia or East Asia is that it’s focused on rote learning, textbook learning, and worldly knowledge within the classroom confines. But if you were to take the average student, pop them in the park where they have to sit next to retired grandpa who may not be very interested in what they’re doing, put them in waiting rooms, boarding gates, long commutes on trains, buses and airplanes, the ability to have conversation with anyone and everyone without feeling like you’re exceptional, without assuming that the experience you’ve gone through is the benchmark for everyone. That is a skill that needs to be learned outside of the classroom, especially if you were schooled in a pretty much very safe, pretty secure, rich, first-world country like Singapore. And so my formal education continues, but my informal education really intensified with my work as an anthropologist, where I got to meet with people from literally all walks of life, literally.”
Linda (00:00)
Welcome back to another episode of Make Me Data Literate. We are venturing into a new topic this time that we haven’t covered before, which is anthropology, but specifically around the internet. I’m really excited about this one since I heard our guest speak at a conference some weeks ago now. So welcome, Professor Crystal Abidin.
Crystal (00:24)
Hi Linda.
Thank you for having me very, very enthused to be reunited with you after a very excellent time in Sydney just a few weeks ago.
Linda (00:33)
Yeah, it was great. It was such an interesting conference, and I learnt so much from just hearing you speak briefly. So I’m very excited to to be able to delve into it on the podcast.
Crystal (00:44)
Yeah, right.
Linda (00:45)
So can you tell us who are you and what do you do?
Crystal (00:47)
Hello world and listeners of Linda’s Podcast. My name is Crystal Abidin. I work as Professor of Internet Studies at Curtin University. I am an anthropologist by training and I study how digital culture shapes people’s practices and society. More specifically, what I do is conduct research in a university setting, do consulting work for government agencies and social media platforms to improve their policies and their features.
I teach students, undergraduates and postgraduates, and I also conduct field work spending time with the people I study, physically in the flesh, doing anthropological data collection, and also digitally online doing digital ethnography.
Linda (01:33)
That’s super interesting. Anthropology has so much to teach us. and I’m particularly fascinated to hear about the anthropology of the internet, you know, really delving into how l all of that works. I mean, until I heard you speak, I thought that memes and and going viral and things were all just kind of organic things that happened a bit randomly. And then there’s this whole industry around it that just fascinates me. How did you get into studying this stuff?
Crystal (02:03)
The version that is now on the record is that I was in the bathroom in university and always overhearing these other girls talk about other girls and what they were up to over the weekend, what they wore, what their partners gave them for gifts, where they ate. And I just assumed these must be the other girls from our cohort or in the university who were the popular girls in school.
But little did I know, not only did my friends not know who these girls were in the flesh, they had never even met. They were these online lifestyle bloggers who were writing about their lives as lived in open diaries, live journals, and blogs, but they had such a sway over thousands of young women in the country, eventually hundreds of thousands of young women across Southeast Asia, that people were tuning into them all the time.
And mind you, this was the early 2000s. We did not yet have social media in the way that feeds tell you what to look at and what to consume. It was the day where you had to go into your search bar, memorize URLs, manually type in https colon back slash the full address, just to find out what other people might be up to on their blogs. And so I was very intrigued by the sway of these young bloggers who would eventually become the first generation of influencers.
That led me down a pathway of understanding why people gave attention to certain things online, from influencers to viral videos, to memes, to hashtag trends, and it led me to studying this whole ecology of what I like to call social media pop culture.
Linda (03:44)
It’s super interesting. And I’m fascinated to hear that the the people who went on to become influencers had such influence even before we had, you know, TikTok and Instagram pushing them at us into our feeds. That’s, I didn’t expect that. I thought it was, you know, very much algorithmic.
What did you have to learn to do your work? What was missing from your formal education?
Crystal (04:12)
Well, to work as a professor in the university to do what I do, the minimum qualification is a PhD. And so I would say I had many, many years of proper formal education. I was schooled in my early years in Singapore. I would consider that one of the more rigorous education systems in the Asia Pacific. And having moved through the Australian system, spending some years in the Nordic countries, working across East Asia and then coming back here to Australia, I think many different countries had pastiches of what I cobbled together as my informal education. But in my formal education, to be very cynical, a lot of it was about evidencing that you’ve got basic knowledge that was instilled in all the citizens by generation or by cohort.
Indicating that you’re passing benchmarks to qualify for the next batch of education, whether middle school, secondary school, junior college, pre-university, etc. but I felt that it was in university as an undergraduate that I was able to put together my own pathways for what I wanted to learn. For the first time in a long time, I was able to pick units, modules from across the faculties, in order to design what I felt was missing from my education. There was even the opportunity to overload, take more courses than we needed, and that was certainly something I did because I loved learning.
And alongside that, if you were lucky enough to have good supervisors, good lecturers, there was also the opportunity to take on additional learning through research assistant work, research paper writing that I felt was stuff I learned outside of the classroom.
What was missing from this whole experience was learning how to be a good human citizen in society. I think one of the things that is the downside of a very competitive education system in Southeast Asia or East Asia is that it’s focused on rote learning, textbook learning, and worldly knowledge within the classroom confines. But if you were to take the average student, pop them in the park where they have to sit next to retired grandpa who may not be very interested in what they’re doing, put them in waiting rooms, boarding gates, long commutes on trains, buses and airplanes, the ability to have conversation with anyone and everyone without feeling like you’re exceptional, without assuming that the experience you’ve gone through is the benchmark for everyone. That is a skill that needs to be learned outside of the classroom, especially if you were schooled in a pretty much very safe, pretty secure, rich, first-world country like Singapore. And so my formal education continues, but my informal education really intensified with my work as an anthropologist, where I got to meet with people from literally all walks of life, literally while walking on the street sometimes.
Linda (07:13)
Ha ha ha.
Crystal (07:14)
And to learn about what life was like for them. A lot of street knowledge, a lot of worldly cultures and a lot of skill sets that can really only be honed on the ground in the flesh.
Linda (07:26)
That’s super interesting. As a writer, I find it quite difficult sometimes to turn off the writing brain and not to store everything that happens away as a as, you know, potential things to write about. I imagine as an anthropologist that must be magnified dramatically. Like everything must be must sort of feed into your professional life to some extent.
Crystal (07:48)
Yeah, I often say that as an anthropologist, our the tools of the trade or the primary one is the ability to write very thick and very astute field notes.
You’re not just writing about what you observe and what you see, you’re also writing about the politics of knowledge projection. How is it that I see these peoples in these ways under these circumstances during this era of this backdrop of political crises, right? So we’re very, very conscious that all knowledge is socially constructed. But this is a gift and also a curse, because in encountering any type of grievous or difficult situation in life, my default mechanism is also to field note my way through. I have to feel everything, process everything, note everything, and then take time to calm down and calm down, go through my notes and then process things systematically.
And I think that also is compounded by the fact that anthropologists are often empaths. It’s difficult to turn away when you see injustice, but it can also feel very frustrating when you know you cannot control or or cannot really have a say in the major power structures. And so a lot of what we do is working with weapons of the weak, people on the margins, coming out of circumventing strategies for people on the ground who are making do with their circumstance, or trying to make the best of the situation, cobbling together patchwork strategies, contingency plans to survive and then to thrive.
Linda (09:24)
I love the way you talked about your formal education not teaching you how to be a good human and then now you’re talking about your profession and how that sort of sometimes mitigates against you interacting with people and how you how you’ve used those two aspects, sort of pulled that pulled those aspects together, the being a good human and also being an anthropologist to try to, try to solve problems that aren’t always, you know, fully solvable. How do you build strategies to to cope with the small things? It is it’s actually one of the things I’m finding hardest at the moment is not immersing myself constantly in everything that’s going on in the world because if I think about it too much I, my mental health is shattered and so that ability to do what you can and then also still live and function as a human being is that’s a real challenge.
Crystal (10:30)
It’s important to care and I can see how caring too much about too much can often lead folks into a sense of paralysis or helplessness.
And I think that’s a rite of passage in processing just how much of the world is in crisis in all different vectors of life. And after sitting with that, I think it’s also important to start small, look small, but the small changes you can make at an individual level, with your social groups, with your community, and if you’ve got the bandwidth and network, how can you lobby? How can you work through the power structures and make your voice heard?
As an anthropologist, I often work with people who are very happy to share these tales and stories and in documenting their work and producing documentary about their work, I often wonder: is it enough to just do representation of what they say and do? Surely there must be more advocacy in the ways these are represented, in suppressing some bits of information but amplifying some bits, and using this comparative knowledge to inform changes or advisoring changes in policy, in platform features, in government regulations.
So it’s a very long haul game in starting small and then trying to accumulate enough knowledge, experience, but also gravitas, sometimes through qualifications, sometimes through achievement, sometimes through persona and persuasion, in order for people in power to be moved to mobilized or pressured or shamed to do something.
Linda (12:11)
I love that. I can see myself going back through this podcast and making notes. That’s they, they sound like really positive strategies. In the midst of all of this, you’ve written extensively about meme and influencer culture, including an astonishing number of books for someone who is a full time professor. I don’t know how you find the time. What is it that you think is really important to communicate about these phenomena? Why do you why are you putting those books out there? What’s, what’s the big message?
Crystal (12:45)
As an academic our jobs are primarily to educate and also to produce knowledge.
And oftentimes the knowledge that we produce comes in the form of paywalled scientific papers that are written in jargon, perhaps too long for grandpa in the park to go through, perhaps a bit too complex for maybe a student in high school who might be interested in the topic. So above and beyond that, something that some of us consider as free labor on top of our already overworked schedules, under paid in University, is good science communication.
It is trying to share the evidence, the frameworks and the knowledge that we have to people who can practice them, think about them more meaningfully, and hopefully enact some sort of foundational change in the way they see the world. In my research, I try to do that often by taking topics that may be commonly thought of as frivolous or vain. These are the likes of viral trends, selfies, influencers, and memes.
You know, on the one hand, it’s easy to just brush this off as entertainment. On the other hand, you have to realize that across the world, an increasing amount of our time is spent on platforms, not because we’re all addicted to social media and can’t look away, but because the way society has been structured, especially post pandemic, is leading us to forced digitalization. To do just about anything these days, you sort of need a stable email address, some sort of access to social media, internet connection, and an awareness of how the social media ecology works.
We only need to think about people who are job hunting, who need to know what a good LinkedIn profile looks like, how to do LinkedIn speak whenever you publish these inspirational posts. And all of these come to be recognized as important skill sets only when they have become invisible to society. By that I mean we used to be able to look at influencers and go, oh that’s clickbait, or look at memes and go, huh, that came across as humor, but actually there’s a deeper message. And we could signpost expertise to the producers of these contents. But now that these skill sets have become expected of just about any worker in society, we no longer privilege them as special skill sets originating from influencers or meme makers. We assume that everyone who’s a digital native or who spends time online can do so. But people in marketing will tell you otherwise. If you’ve ever spoken to someone who put a post up and sits with you and goes, Why didn’t that take off? Why didn’t it go viral? All that effort for this post and just 10 views, this is where you realize there’s actually an entire skill set behind what looks like seamless, fun, frivolous entertainment. And is it this kind of cultures of practice that I’m studying.
Linda (15:44)
That’s that’s just amazing to me that, this, what seems like just a sort of organic social phenomenon is actually this intense science. I’m I am hopeless at social media. It’s why the first thing I did when my charity had enough funding was hire a communications manager who’s really good at it. But it’s it’s there’s this all of this as you say, skills but also science behind it that that we’re just oblivious of, but it acts on us every day.
Now I didn’t put this question in the in the list of questions that I warned you about, but I have often thought that social media would be a lot less problematic if we simply regulated it so that the feed was chronological and not algorithmic, so that you get you know, you you follow the people you follow and you find out what they like and and you see what they post, but you don’t get drawn into these rabbit holes of rage and fear that are so lucrative for the social media platforms. That’s my uninformed perspective. I would love to hear your educated expertise perspective on that one.
Crystal (17:13)
Sure. Let’s think back let’s go back to the 2000s, pre-social media when we had blogs and online forums. Back in the day, if you spend time on an online forum or any online community, maybe even gaming communities, you sort of are able to identify that this is a loose network of people.
You might have shared interests or expertise in a topic or a skill, and therefore when you log on to that space, there is an expectation that you might share the same vocabulary, maybe the same benchmark for morality and values, and when you converse with each other, there is a very high likelihood that there is comprehension and there is agreement. If there is any disagreement, then maybe also an understanding that you can work this through because you are bounded by this network and you work as a community.
Then we moved on to the era of blogs where people were able to broadcast. And in broadcasting, you never really could tell who exactly was watching. In that era of network publics, you might imagine only the ten people who commented are watching your blog, but in reality there would be percentages more, a high proportion who are just lurking or watching. They might also be resharing the link. They might even be downloading or copying the content and then circulating it in other means.
But then people are here gathering on the blog in recognition that the person writing might have an interesting persona or good expertise on a topic, so you’re drawn to them again as if it’s a loosely bounded community. So in the first era of social media, at least here in Australia, think about MySpace, Friendster.
And then the early version of Facebook, where we would add people or connect with them directly in order to add them to our network. Think of these as egocentric networks, where it’s myself and all the people connected to me in some way. And so I’m able to derive value from the interests of all of these other folks.
The information may be given to me at that time in a chronological order, but in reality, in that time, the focus was on community and who I let into my network. So, what kind of ideas, principles, values, and this person I’m allowing into my networked space.
In later social media, as we move through its influencer and creator culture, there is now the ability for you to also receive content in your feed from people you do not follow, based on what the platforms might feel match your interests or your browsing patterns or even that of the people in your network.
So in this space now, we are focusing not so much on your personal networks, the egocentric part, but on the interests, the topics, the ways that your user behavior on social media might indicate that you’ve got latent or implicit interests, even if you’re not aware of it consciously. And so these were opportunities then for our platforms to help us stay on these platforms for much longer by diversifying our appetite and our palette, in order to keep us there.
What made this a lot more complicated was when metrics were involved. You know when these bits of information come through, we are on the baseline exposed to diversity. But it’s not always easy to glean whether or not a hot take is a good take or a bad take, or if information is good misinformation, bad misinformation, productive misinformation, in any valence. And as a shorthand, we are taking metrics as the indicator. Up votes or down votes on Reddit, the number of likes, shares, follows on the likes of TikTok, maybe even the valence of emotive emoji. Is it the like or the heart or the angry or the sad icon that you’re clicking on Facebook? These become shorthands for us to perceive the value of this piece of information. And it also becomes a space where we can be pulled very quickly into extreme rabbit holes of very different polarizing opinions.
So it’s in this space that we have to take all these cues and realize the bits of information coming to us come pre-filtered with an agenda, with a valence for a specific community, rather than thinking back on back in the day where we relied on the trust of people in our social network, where we vetted our friendship, the quality of our relationship, and took that as an indicator that what they shared might be believable or trustworthy.
So the whole game has changed from early to late stage social media. I wouldn’t say it’s so much an issue between a chronological feed versus an algorithmic feed, because as an anthropologist, for me, it’s about the boundedness of the people that we are interacting with online, the boundedness of what we may consider community, and therefore the boundedness of information that comes in and out of our social milieus.
Linda (22:42)
Hm. So it’s it’s the network and the community more than anything. More than the algorithm perhaps.
Crystal (22:52)
It’s all of it combined. But the algorithm would mainly represent the interests of the platforms and what they feel will help you stay longer.
Linda (23:03)
Yeah.
Crystal (23:04)
It is also a reflection of your latent or implicit interests. It can also indicate whatever’s trending at the moment in your social circle or in your geolocal region. And yeah, all of these are the entry points for diversifying the information you’re open to. Whereas with older social media, the entry points were literally just the people you let into your network.
Linda (23:30)
Yeah, that makes sense. So you you’ve talked about the the metrics and the data of the systems. Is there anything that you think if everybody understood this one thing about data it would it would make things a lot better or would make your work easier or is there one thing that you wish everyone understood about data?
Crystal (23:51)
Data is man made. This is something that we need to stress, especially in the age of generative AI.
You know, even for a pedestrian who is listening in who may not be very well versed in social media, you probably have the experience of now opening a browser or a search engine, trying to look for information, but before you even get your search results, there is an automated AI version that claims to be a summary of everything you need, saving you time in scrolling and clicking. That is engineered by a person.
The rankings where the information is scraped from, all of that is trained on engineers and what they perceive to be quality information versus what should be filtered out. And there are values involved in this. The ranking of search results is not always neutral, not always rarely neutral actually these days, and may not even be-
Linda (24:48)
I was gonna say, is it ever?
Crystal (24:50)
Yeah, may not even be based on like the compatibility or the overlapping in search. It’s sponsored. Who gets to be on the front page of Google? It can be hacked even if not sponsored. If you were clever in spamming SEO index key search words in your page. And so it feels like we are exploring information, weaving through data and gleaning for ourselves, when in reality there’s already predetermined information and search thrown into your lap. It makes it hard to look away when it feels that accessible.
If you are a user of chatbots or chat companions, know also that while it may feel very personable and personalized and intimate, these are trained on large-scale data from millions of people around the world. Know also that as you are engaging with them, you become part of the data set and whatever you share goes up in the cloud and helps also to train AI that comes after.
I would say one of the important decisions we have to work with and sit with at this juncture in society is how we feel about AI. We already know about the consequences to the climate. We already know about the uneven consequences, especially with water resourcing, experienced by third world countries or countries in the peripheries. We also know about the normalization and integration of AI into just about any aspect of life. I can turn it off in my email that I’ve used for years.
I can turn it off in a search engine that I’m trying to use for free. The workplace that I’m at, and many people right at are trying to integrate it as well. But when you make something so seamless over such a short time, it’ll be very difficult to disentangle from it if there is a need. It’s also going to be difficult if the ownership of these software becomes contentious and you need to opt out and switch over. It makes it difficult for people who do not want to participate in harm to Earth to continue engaging on a baseline basis because as with how social media became non-optional, as with how having a mobile phone or having email became a default way of functioning as a digital citizen, it seems like we’re going in that direction also with AI and Gen AI being so normalized so quickly.
Linda (27:18)
Cory Doctorow describes it as the asbestos that we’re building into the walls of our society and that it will take us generations to dig it out. That, that feels very relevant.
Crystal (27:29)
And having worked on several Australian campuses where we have been told to vacate buildings in weeks because they’ve discovered asbestos that they need to take out. And we’re thinking, wow, so we’ve sat in this place for decades, and now you’re telling us the consequences don’t hit you in that time. They probably hit you years down the road when you realize cohorts of people with that shared experience have the same health issues. When people start thinking about holding construction companies accountable, holding universities accountable, when folks start thinking about the knowledge that we had then and whether it was concealed, whether we were blasé about our projections for health. Map that over into how we’re talking about AI, gen AI, or automated decision making, and there are questions that we can start grappling with now, even if it’s difficult to do so.
Linda (28:20)
Yeah, I think just having the conversation would be a really good start and it’s you’re having the conversation and you’re starting people thinking about it, but there’s not a lot in our decision making spaces, which is concerning.
Where am I up to in my questions? This is so interesting, I’m getting distracted.
Are there things that data shows that you wish more people knew about? Are there things that you see in data that you think people don’t understand?
Crystal (28:54)
Are there things that I see in data that I think people don’t understand?
I’m an anthropologist, so I deal a lot with ethnographic information, what we like to call ‘thick description’, or what anthropologist Trisha Wang has called thick data. You know, in the age of big data, when everybody was shifting towards quantification and looking for scale, looking for pattern recognition, but then also making these big, broad assumptions about society, anthropologists were here to remind us that this was how we ended up with hegemony, with a mainstream power, asserting their values, asserting their decision making over hordes of people. This is how people in the fringes, the marginalized, the subverted, the minorities become invisible, oppressed and suppressed.
And so in playing through this discourse, Trishan Wang was very clever and also really tricky in introducing thick description back to big data by calling it thick data. In that you do need qualitative insight and humanities scholars to help provide meaning behind the numbers. Humans are not all the same cookie-cutter model. You can’t come up with an amalgamation of selfies and say, this is what the average Australian looks like, this is what the as average American or Canadian looks like. It means nothing to us as humans, even if it feels as an easy shorthand to train robots.
And so I think it’s important for us to remember all data comes from somewhere it’s probably cleaned up to look neat because messy real life data is not easy to comprehend. And the term itself data in corporate language has also become this very crass shorthand for insights. When in reality oftentimes a lot of data is indecipherable. It’s just information. It might be results from a survey, it might be observations that don’t give us any meaningful outcome or implication. And there’s marketing speak involved whenever we just call something data as if it’s from the ground, as if it’s the same as analyzing the data, as if it’s the same with coming up with comprehensive ways to glean insights from the data.
Linda (31:16)
We talk about data as though it’s, it’s, it’s elements, it’s it’s you know, pure molecules of of stuff that are fundamental building blocks, but we forget what you’ve been talking about all along that, you know, the definitions of the data we collect are human, the data we collect is human, the collection process is human, the analysis process is human and we, we build ourselves into that all the way along. It’s not some kind of pure atomic level substance. It is a human artifact with all of the complexity and problems that that that involves.
I, I’m loving this perspective. It’s we we we like to think in science and especially in computer science that we have kind of washed away the, the humanity of things and that we’ve got down to pure objective facts. And and that we forget that there just isn’t any such thing, that the way we look at the world and the way we experiment on the world and the way we understand the world is all human and if you try to wash away the the human angle of it, what you do is just obscure it, not remove it.
I get very intense about these things.
I’ve been thinking a lot about it in medicine too, because literally no one has a textbook body because the textbook body is idealized and it’s a fantasy. Like the London tube map is a fantasy. You know, it doesn’t actually relate to the geo- the geography of London. It’s an idealized, stylized version. I had an angiogram last year and I got to watch it on the screen, which was fascinating for a a nerd like me. And the textbook diagrams of of blood vessels bear no relationship to the wiggly, squiggly, complex pattern of blood vessels in a real body. And that’s just one example of, you know, the many ways in which bodies are not the stylized representations we see in textbooks. It’s, it’s, it’s a nice analogy for data I think.
Crystal (33:45)
Yeah.
Linda (33:46)
No one’s as you say, no one’s the average on any thing.
Crystal (33:48)
Do something similar in one of my newest books titled Child Influencers, How Children Become Entangled with Social Media Fame, like your description. I was offering, you know, what even is a child influencer, when the media talks about it, when parents moral panic over it, when politicians raise it, even in the examples we see in the news spreadsheets, in the broadsheets and documentaries.
We are really talking past each other whenever we refer to a child influencer. It is simultaneously the child who is a YouTuber, the child who is ward to a famous parent blogger, the children who happen to feature in the background of contents of family influencers, children who accidentally go viral and then become instantaneously famous just by their video overnight.
People who are maybe known as the face of a meme or a gif, a reaction gif, but we know nothing much about them. And we called all of these children child influencers. It feels like an easy shorthand, it’s just famous children on social media. But the reality is when we start to talk about safeguards, regulation, and law, we need precision. Because the law is all about definition.
And so if you’re talking about, say, protecting the income of child influencers. Not all of these children I mentioned actually earn an income. They are surely income generating sometimes for other people, not themselves. If we talk about child labor, not all of these children will be recognized as committing to labor by the contracts that clients make the bloggers or influencers sign because they’re contracting the parent, not the child, who happens to be in content.
We think about the space of the workplace. in Australia, the New South Wales Children of the Guidance Office has guidelines about the environment in which children film. If this is a workplace on set in a studio at a client space, but if you’re filming at home with a parent for a TikTok, that’s not a workspace. And so despite our best intentions with guidelines, precision means that a whole lot of children in this space are excluded from protection, by virtue of definition, and there’s a lot of fine hair splitting there. And so my book does what I feel anthropologists do best, which is to reflect on the diversity in the space.
And across 10 different chapters, I look at ten different angles of what might constitute a child influencer or under this umbrella and how they need to be viewed from their locale, origin story, history, in order for us to understand that these ten children are really experiencing ten different realities despite being loosely referred to as child influencers.
Linda (36:49)
Have you sent a copy of that book to the members of the federal government? ‘Cause I feel like that could be helpful for them to understand.
Crystal (36:58)
If anyone is tuning in, this research was funded by the Australian Research Council, which is the research arm of the government. And with thanks to that funding, it’s also open access, free to read for anybody forever, via my publisher’s website, Polity Books. So do your homework, thank you, friends.
Linda (37:18)
Fantastic. I will be sending it far and wide.
What are the worst data mistakes that you’ve seen in your professional life?
Crystal (37:31)
Hmm. Primarily as an anthropologist, my biggest challenges come with working with industry. They are often looking for generalizability. And so in my early days working with industry and platforms, when they ask for evidence, I give them vignettes, I give them personal accounts, personal interview snippets, for instance. And the first thing they often ask is, ‘What is the occurrence?’ ‘What is the frequency?’ ‘How many people are involved?’ ‘What percentage of the population is impacted by it?’ And I think this is the wrong way about it, because these are questions that assume only if it’s applicable to the mainstream and majority, should it be something that you take action on.
I like to describe the work that I do and that anthropologists do as being a Mars rover. You’re slowly crawling through a globe, and you’re picking up very small bits of information that people might miss. I’m not going for scale. I’m looking for the minutiae and comparatively collecting many bits of minutiae that can give me the thick detail of this planet. Maybe before someone else who’s got different skill sets is able to look for frequency, quantification, and the like.
Linda (38:52)
That’s really cool. I like that. I when I first set up this podcast I, I started with my list of questions and I thought I will have to change those sooner or later. They will get boring. But honestly, I, I never get the same answer twice and I have never, I must be up to close to fifty episodes now and I have never had someone say, Do I need this graph? I love that. That’s it’s a it’s there’s research that shows that people believe things more easily when there’s a graph next to it, even if the graph is completely irrelevant. so it’s it’s that question of, you know, what are they why are they showing me a graph? What what’s the point here? What are they trying to achieve and and is it do I want to take it on board? I like that.
This has been a fascinating conversation. I’m really grateful for you sharing your time and expertise expertise. And that brings us to the last question, which is my favorite. What excites you about data?
Crystal (39:55)
It’s never the same. The same graph, the same ethnographic vignette, the same statistics, the same interview snippet. Even this transcribed conversation that we will have here, if read by a different person from a different perspective, in a different time, in a different language, can be interpreted differently. So it’s not neutral, it’s not the same, which means you are able to revisit the same thing over time and space and glean different insights.
Linda (40:28)
That’s wonderful. Thank you so much. It’s been a wonderful conversation.
Crystal (40:32)
Thank you for having me, Linda. It’s been a joy.
