Dan Angus - Director of Queensland University Technology’s Digital Media Research Centre

Keywords
Computational Social Science, Data Donation, Ethics, Self-Reporting, Digital Media, Research Methods, Advertising, Social Science, Algorithms, Data Privacy advertising, data donors, participant bias, subjective experience, research challenges, academic success, aspiring researchers, work-life balance

Summary
In this conversation, Rod Lamberts and Dan Angus delve into the emerging field of computational social science, discussing its significance, methodologies, and ethical considerations. They explore the concept of data donation, the challenges of self-reporting in research, and the role of computational methods in enhancing social science research. The discussion also touches on the insights gained from digital platforms and the complexities of researching contested spaces such as pornography and advertising. In this conversation, Dan discusses the nuances of advertising, the importance of understanding participant bias in research, and the subjective experiences that shape data collection. He emphasizes the need for interdisciplinary collaboration in academia and shares insights on measuring success in research. Dan also offers advice for aspiring researchers and reflects on the balance between professional and personal life, highlighting the importance of curiosity and community engagement.

Takeaways
Computational social science is a new interdisciplinary field.
Data donation allows for more accurate data collection.
Ethics and consent are crucial in data donation processes.
Self-reporting can lead to inaccuracies in research.
Computational methods can enhance traditional social science research.
Digital platforms provide valuable data insights.
Research in contested spaces faces unique challenges.
Positive impacts of digital content are often overlooked.
Advertising research can benefit from data donation methods.
The importance of transparency in data collection is paramount. Political advertising garners more attention than other forms.
There is a bias in who participates in research studies.
Subjective experiences of participants are valuable in research.
Resistance in research can lead to refinement of ideas.
Success in research is indicated by raising more questions.
Building relationships is key to impactful research.
Patience is essential in navigating a career path.
Curiosity drives meaningful contributions to various fields.
Balancing work and personal life is crucial for well-being.
Creating conditions for others to succeed is a priority.


Chapters

00:00 Introduction and Context
02:10 Exploring Computational Social Science
04:36 Data Donation and Ethics
09:43 Challenges of Self-Reporting
12:21 The Role of Computational Methods
14:08 Data Insights from Digital Platforms
17:53 Research in Contested Spaces
18:49 The Focus of Attention in Advertising
20:04 Understanding Data Donors and Participant Bias
22:25 The Importance of Subjective Experience in Research
23:50 Navigating Challenges in Research and Academia
29:05 Indicators of Success in Research
31:41 Advice for Aspiring Researchers
35:18 Balancing Work and Personal Life

Transcript

SPEAKER_00 0:01

Dan Angus is a man who loves his work. Just hearing him talk about it is absolutely infectious. And I was smiling for the rest of the day after our conversation in this interview. Right now he's a professor of digital communication in the School of Communication at Queensland University of Technology. And he's also the director of their Digital Media Research Centre. Dan's been involved in computer and social science research for more than twenty years, which is an excellent combination that you don't often see these days. His career has seen him leading all kinds of collaborative research projects at the intersection of computer science, design, communication, linguistics and journalism. What a wonderful, wonderful hybrid, a cross-section of so many important disciplines and approaches coming together. He's also a regular contributor to media and industry commentary on the impact of technology on society. Talking with Dan gave me a lot of food for thought. Much of it is what I would summarise as how to be a good and proper citizen in and around the STEM community. Those are, to be fair, my words, not his. He spoke passionately about his belief in the importance of not just acknowledging the people and the work that have come before, but also in paying it forward, or as he put it, putting ladders down for the people who come up behind us. Dan delights in being a field jumper and seeing where things can take him. He has a fierce devotion to reaching out across silos and sees this not so much as smashing through walls between disciplines, as working together with one another to thoughtfully remove the bricks between them, one by one. He believes in constantly scrutinizing and examining research methods and striving to be clear-sighted about what they can and cannot do. Oh, and also, he's a master brewer. And I mean master brewer. And I admit once I heard this, it took me a moment or three to get my mind back on STEM and the conversation at hand. I'm Rod Lambert, a veteran science communicator with nearly 30 years of teaching, learning, and doing SICOM under his belt. My chat with Dan coming up next on Science with Benefits. STEM sector insights from the people who know. Dan Angus, thank you extremely much for joining me. How are you?

SPEAKER_01 2:17

What what have you been up to? Yeah, so this week I find myself in Melbourne. So normally I'm in Brisbane at Queensland University of Technology and the center I run there, which is a digital media research center. But this week I'm down here in uh in Melbourne for the Summer Institute of Computational Social Science. Computational Social Science. Yeah. Yeah. It's a new. Tell me a bit about that. Yeah. Yeah. So uh like anything, I mean, like, is there really a pure discipline in in any way, shape, or form? I mean, everything's philosophy, right? But no, computational social science is a relatively new discipline that I kind of feel like I I I was there at the start. I didn't, it was not called computational social science, but it basically, as the title sounds, it's a mashup of kind of theory and practice methods that come more from a computational perspective, together with um the same question theory methods that come more from a social science perspective. And so you find that a lot of the work in this kind of nexus, it's stuff that's interested about the role of algorithms in society. So news recommender systems or the ways that various kinds of things we do are mediated through more kind of computational systems. So there's often questions about the impact of computation in society. Right. But also there's this kind of idea that there's a bunch of ways in which in traditional social science we can embrace the use of computational methods to help with things like data collection, to help with analysis of data, um, and also to help with interpretation, visualization, and communication of that. So this it's weird because it's winter, obviously, in Australia, but the Summer Institute was set up in the Northern Hemisphere. So actually came out of Princeton and some of the other American institutions. And it's a two-week institute for largely ECRs to get a handle on computational social science research methods and trainings. Some of the crew that I know very well through my involvement in the Australian Internet Observatory and our ADMS Center have been involved in setting this up. And I've got to meet a huge number of really awesome ECRs who are doing work in computational social science and give a couple of sessions and workshops. So it's been a really fun week so far. And I've still got a couple of things to go, so it's great. You wouldn't know what to do with rest time, would you? No, I don't. I don't really. It's like the brain, I say this always to my own students as well, is like it's not like your brain just turns off when you leave the office. So we're always thinking about something, and there's always also I find this that my inspiration for the kinds of questions I ask and the things I do are informed in what happens outside of the four walls of the of the university in terms of the various groups I come into contact with. So, you know, absolutely, you you've got to be embedded in your society and and your community. So some of the work that we've been going through this week are in things like data donation. So the ways in which we can work with participants. So normally where we might say just use a survey method or an interview protocol, we can also now get participants to request data from the platforms they use, get that data, and then submit it through a secure portal so we can get a very granular account of, say, the ads that they've been encountering, the kinds of content that they're receiving in their recommended feeds, things like this that give us another lens to look at their activities. And we can use that for conversations with them, for interviews and all kinds of things.

SPEAKER_00 5:55

So if you can you give me a more specific example just to help me get my head around it.

SPEAKER_01 5:59

Yeah, totally. So if we're interested, say news consumption, right? So we we've got a study where we think, all right, it's really important to know how much are Australians encountering news in this particular moment. Um we know that people are encountering news not just through directly going to the ABC app or something else like that. They're encountering it as a peers, say, in a variety of their social media feeds. Now, to get an accurate assessment of that, you can't walk behind the person as they're walking along with their mobile phone in hand or when they're sitting down at their desk. So what's another way? Not yet, not yet. I'm sure the days behind the camera, but you could try it, but you're not gonna get very far. But what's another way in which we can get a proxy there? Now, I have a big issue with sometimes how the field overuses self-report, and particularly news consumption, because news consumption is seen as like a normatively good thing to do. You know, we get this slight sense of like news consumption good, right? So when you ask people about how much news do you consume in a week, they're gonna go, oh yeah, I I do a lot. It's the same as like when you go to the doctor and ask how many alcoholic drinks do you consume in a week. Oh, none, no, no, no, no, no. I don't touch the stuff, right? And so this is a thing in social science, is we need more accurate signals. And so that accuracy can come from the actual raw trace data itself. Yeah. And so within those platforms that we use, thanks to some EU regulations, you can actually, as a user of those platforms, request the data from the platform that they keep about you. And that can include things like what content you've consumed. There's a project at the moment that colleagues at QT and also University of Sydney are doing on TikTok, trying to get like cultural baseline for Australia and how we engage with a platform like TikTok. But say TikTok data as a as a data download. If I go into TikTok under my account, click on the give me my data, it comes down as this big long list of the URLs of the actual TikTok videos and pieces of content. Now we can resolve those and then we can classify and say, is that news content or is that not news content? And after doing that, we could then come up with a judgment about actually, Dan, within a week, this is how much news content you consume on TikTok. We can do that for, say, Instagram, we do it for Facebook, we can do it on YouTube. And once you do it for enough platforms, you start to get a more complete picture about the fact that, yeah, I'm consuming news across a variety of platforms.

SPEAKER_00 8:30

And I asked there's a question in the back of my mind, I've probably got it wrong. So you mentioned data donation, and I assume this links to the ethics of this. So do people have to request their own data and then give it to you? Is that how works?

SPEAKER_01 8:42

That's exactly it. Yeah, you've absolutely nailed it. The idea is they request the data from the platform, yeah, and then they the data comes to you a few days later sometimes. So it gets essentially packaged by the platform itself, and then you download onto your device, and then you approach it. Now, we've built a platform here in Australia through the Australian Internet Observatory to handle this side of it, which is the actual ethics and consent and the actual donation process. Because obviously, in a data download package that you get can be a lot of very personal data. But but quite honestly, it's things that you want to make sure the participants have a clear idea about what it is they're about to upload. And so what we do is we've got screens that allow a rendering of some of that information, but importantly, it's all on what we call client side. So the data hasn't actually left the device of the user at that point. So it's able to kind of render all of that information in a way that they can understand it and they know what they're consenting to, and then they can choose what they want to donate and send. So after it it goes through those various screens where it shows them they review the material. Once they're happy to donate it, then they click through, and it's only at that point that it will be transferred to the servers of our systems, which of course are as secure as they can be, same as any kind of research data collection process. So it's a very active consent process and actually more active than some of the other ways we used to collect data.

SPEAKER_00 10:15

So, two questions. I'm an old survey guy from ages back, and one thing surveys are great for is rhetorical power. What they're not great for is actually really helping you capture any individual. But the self-report issue, if people quite reasonably and ethically can tweak their own stuff before they send it to you, are you not in a self-report bind anyway?

SPEAKER_01 10:46

Yes, to some degree. So there's been more studies done on this, and particularly from the European context, because that's where this method is, it's really emerged from Europe. And I was at a symposium end of last year in Munich on data donation. And that's one of the issues that is often discussed is to what extent do people delete before they submit? And there's more work happening right now in trying to get an understanding of what is it that people will not consent to share when they do donate data of that form. And a lot of it comes down to the study design. So the idea of trust, how you're going to treat that data, the anonymity around it. And so there's data donation that can be done more or less anonymously. And so data donations, the package you get, depending on the platform, can be quite personal. So they could include, for example, direct messages, things like this. And so we are incredibly careful about that. So for a lot of those, it's like a hard no, and there's no no way in which that even functionally, if someone clicked the button to send, it would essentially hit a brick wall and say, no, bounce, you're not able to give that back. So we can specify like what aspects of that package are wanting, like we want to be able to accept. Um but on the flip side, yes, you're absolutely right that it's up to the participant what they effectively consent to provide. And so yeah, but you get away from that idea of asking people subjectively, how much time have you spent on, or to what degree do you read this? Like, what do you click on? You're getting past that because you're talking about something that's closer to kind of the ground truth of the actual behavior on the device.

SPEAKER_00 12:28

Yeah, look, I can see that. And and oh God, so many questions. We need nine hours for this.

SPEAKER_01 12:36

I did computer science and now I'm in humanities and social science, and I love this part of it. I love developing and teasing the edges of methods, of ways of studying and doing and challenging the fields. You know, all fields that we have, I think, across the academy have particular ways of doing, seeing and such. And it can be really hard sometimes because there's very good reasons why certain kinds of routines set in place, certain kinds of theories have their moment. But sometimes I do like to rock those foundations a little bit and challenge assumptions. And so, you know, just because it's been done a particular way, say in political science or in communication or wherever, since, you know, it's been a field, doesn't necessarily mean it's the best way to do it. And particularly now with the advantages you do get with some computational methods, it's making it clear to people you can kind of have your cake and eat it too. You can keep the rigor and the tradition of the way that you have been doing it. But look, here's a bit extra that this gives you as well. I liked when I talk about computational methods to those who've had less experience with it, is it very carefully to say this is not about replacing you. And it's not about replacing your judgment, your interpretive capabilities. In fact, that's even more important. But what it is about is possibly removing mundane spade work that is boring, dull, and you're probably gonna do it badly because it's so repetitive. Or it's about enhancing your judgment or finding other ways to look at your data that can aid your interpretation in some way. And so if it's not actually genuinely doing that, it's probably not a good method.

SPEAKER_00 14:10

Yeah. This is cool. Okay, uh two things. One what what this makes me think of, and bear with me because I'm gonna invoke Pornhub here, because in uh another podcast I do called A Little Bit of Science, we do all these small stories from science and related fields. And one of the ones that grabbed me a couple of years ago was how Pornhub are really good at putting out these huge data sets about what countries download what kinds of things. And there's this huge country-by-country breakdown. And me having the mind of a 15-year-old boy, I find that all very entertaining. But what it made me think about was also there was a I can't remember what the field was called. It sounds like a fledgling version of this where people would stop surveying other people and they'd look at their search histories instead, because at least that shows where people are actually looking. And it's exactly the problem you were talking about. Someone says, of course, I only looked up the The Guardian and I only look at the pure news sources when in fact they're just all over the Daily Mirror, and the search histories make that clear. And they may not realize the extent to which they're doing this. Am I right in saying this is kind of like a that was a very fledgling version of the stuff that you do now where you're really diving deeper?

SPEAKER_01 15:17

Yeah, kind of. And there's a couple of things there that I would unpack. One is that we always have to be careful about the rhetorical power sometimes that is apparent. Let's think about Spotify Unwrapped as another example of that. So Spotify Unwrapped gives like a database digest of your year on Spotify. And those kinds of things, like Spotify Unwrapped has been criticized as kind of normalizing surveillance in a way that it says it tries to make cute this idea of, hey, we know exactly everything you listen to, your likes, dislikes, tastes, and such. And so it's kind of like has been seen from a critical perspective as kind of normalizing surveillance. So there is always a rhetorical power and questions that one can ask when a company in this digital space reveals a big data set or drops a big data set down on everyone that it's it's trying to sphere a conversation in a particular way. And I'm always interested in where data isn't, where the data sets don't exist and as to why that is. So where do we need to dig harder to find the stuff that we need to be able to answer a question? And since you mentioned it, like in the Digital Media Research Center, we do work on um pornography, on other kinds of observed sexual content, sexual health information, and others. And that is a very obviously contested space because it's political. I mean, all spaces are political, but some more than others. Yeah. And it's very interesting when we talk about data and research in those areas, that it's one of those ones where there's often a lot of contestation and you're thinking about what data do I need to get to be able to make a point around this particular consumption practice or that. And that actually, for many cases, if it comes to porn consumption or others, actually, in most cases, it's incredibly benign, pleasurable, fair, and all that. But again, the field will often do these things where to publish, you're looking for risks and harms. And it's hard to publish a paper that says, look, everyone's using this and actually just enjoying it and getting along and it's everything's fine. You know, that's it's just fine, it's just normal, right? That doesn't sell. And that's my that's often a critique of the way that research operates is it's often looking in deficits too much rather than in empowerment, positivity ways that they're doing so. There are exceptions, of course, like so you know, work of colleagues like in this space, Zara Stardust and colleagues down here in Melbourne, like Kath Albury and others, who look in terms of particularly in sexual health spaces and pornography and this, in terms of positive impacts that we need to talk about and genuinely talk about in a very mature way. But yeah, unfortunately, those are contested spaces. So they're off acting, talking about the deficit.

SPEAKER_00 17:57

So basically, unless it's outrageous and you know uh weird in very huge inverter quote sexual practices, no one cares. The media's just not that interested. Is that the problem?

SPEAKER_01 18:07

There's always there's always that.

SPEAKER_00 18:08

That's right, are journals less interested as well? Are academic journals less interested?

SPEAKER_01 18:12

Yeah, sometimes, sometimes. I'd like to think not as much as news media or others. Another example of this that's that's actually a bit easier to grapple with is we do a lot of work on advertising at the moment. And so we're examining through data donations, through other, we've developed a mobile app that captures ads as they're seen by people on their mobile phones, again, through very, very strict guardrails and consent processes. But it's interesting in the space of advertising, when you start talking about, say, political advertising, journalists and others and civil society groups, their ears poke up and they're like, yes, absolutely, let's talk about that. But less attention on, say, alcohol marketing, gambling, fast foods, greenwashing, um, predatory financial lenders, scams. So it's not that there aren't civil society groups and others that are absolutely interested. We work with most of them here in Australia. But what's really interesting is when I say political ads, everyone kind of stands to attention. If I talk about all the other ads, there's not as much interest there. And that attention span of where real harms occur, where risks occur, where positivity is, it's that is one case of one domain where attention is very focused on a very, very narrow range.

SPEAKER_00 19:28

Yeah, look, I I want to say I'm surprised. I'm not. I wanted to ask earlier, but I didn't want to stop you because it's really interesting. But um, is there a typical kind of data donor, or is it all walks of life?

SPEAKER_01 19:38

This is a really good question. So we've done a few of these studies, and one of the early ones we did on ads, we had a plug-in that people could download onto their browser. And when it was on their browser, when they're in Facebook, it would find the ads in the Facebook page, donate them to us. Um, a really, really successful project. Right. Um, we partnered very close with ABC on that one, and we, of course, then got a very ABC audience. So through the ABC, they did a call out, hey, help be a citizen scientist, download this plugin, it'll sniff out the ads, it'll send them, and you're going to contribute to research. And I did the stats on it and did the population modeling, which was super fun. Um, and I basically got the most typical ABC audience. So it was everything that you would expect an ABC audience to look like. Now, look, there was there there's always the edges of that, but that's what we got. So that's volunteer through a particular promotional channel. So that's gonna bias who signs up. We've done some more work in the second phase of that with the mobile ads app, where we've been going through a recruitment kind of survey firm to do proper balanced participant recruitment. And we've got, you know, really good sign-ups and people downloading using the mobile tool. But you tend to find in those populations, you get people in those panels who are sometimes professional panel takers. So people who sign up for a lot of studies. And so one interesting thing in that is that I think I can say this without giving too much away, is that you see ads for scientific studies, right? In their ad dates. So people who signed up for your study are getting ads for the next study. And and so that's an interesting one too, in terms of your bias. Um, so yeah, it's really hard. I mean, I'd love the the perfect kind of cross-representative sample of everyone that I need to do my study. It's not gonna happen. And so what we always do, of course, is account for bias. So there's limitations of what we can say. But for those who do sign up, we often find some very interesting things.

SPEAKER_00 21:41

Oh, look, I have no doubt. I mean, I used to, when supervising PhD students, particularly doing large surveys, they'd say, I didn't find anything. I said, No, you did. You did. You found stuff. But what you've got to do is adjust your headspace to say, here are the kinds of people I can talk about. Not I didn't find anything about the people I wanted. And that Still seems to blow people's minds. You know, even quite experienced researchers. No, you didn't find anything. You just found it about this kind of human. And that's okay. But be open about that.

SPEAKER_01 22:09

Yeah, absolutely. And I mean, a lot of what we're doing, we're not trying to do big end studies here where we're trying to do big correlative or causal relationships. It's much more mixed methods. It's far more qualitative. So we're interested in, frankly, what is out there. And for these individuals that have signed up for our various studies, uh, what is their experience? And now that is a subjective experience, but it's still an experience of a real person here in Australia. And that's worth knowing about. And so I think there is still a huge amount of power there. This is great.

SPEAKER_00 22:40

Okay, I've got another question for you, obviously. Yeah. Um, if there is one thing you could fix today about what you do, like one that you go, oh, if I just solve that, everything else would be better, stronger, faster, more interesting, etc. Is there a particular bugbear for what you do?

SPEAKER_01 22:55

Not really. The big things that keep me awake is not in my own domain of research. It's more the broader policy landscape. Uh a lot of our work is trying to change society for the better. We're trying to do things, we're trying to evidence, you know, various kinds of technologies or things in a way that governments can regulate well, that we as citizens are more informed about the things that we're using. And so that's much of what we do. So my concerns don't tend to rest on the level of my colleagues doing or not doing the right thing. I don't know if it's just because I'm a field jumper. I started in engineering, did science. Through my undergrad, I did research in everything from astrophysics to photonics to computer science to physiology. And so I had a broad taste then, and then specialized in computer science and wacky AI stuff before broadening back out to humanities and social science. So journalism, comms, media studies. And so I've moved everywhere and almost all at once. But sometimes I still find that there are academics who are a little bit too insular in terms of their way on the highway, like their one field has all the answers. So that's my butt. For academics listening, please just be a bit more open-minded about the value and disciplinary expertise. Um so speaking as someone who identifies as a computer scientist, at least at one point in time, computer scientists can sometimes be the worst in terms of trying to insert themselves pretty much everywhere. And I like to think, like in this emergence of computational social science, there is a bit of a recognition that we need to be a bit more gentle here and develop this slowly, get the right people in the room. You know, we're not the first in this space. There's been a long history of theory building and methodology and such that existed across these disciplines. And let's try and bring it together in a way that's not violent. Um, so that's the only thing I'd say in the academic space. But yeah, I mean, yeah, my my concerns situate elsewhere sometimes in terms of what governments and and societies are doing.

SPEAKER_00 25:03

Yeah, very interesting. I started in psychology, and this is a classic. Everyone knows psychology is behind everything. And I move into anthropology and health. Everyone knows anthropology is behind everything. And now I'm moving into science communication. Oh, it's all about comms. And I thought, while there are arguments for all this, let's historiax and recognize we've all got something behind something. This is great. Um, exactly what you were saying. They can really identify that's what I'm saying.

SPEAKER_01 25:24

And then bringing our spirit comes along and says, no, it's all of you together. All of you. We're the only ones who can actually piece it together well and understand if you pull this lever, this other thing happens.

SPEAKER_00 25:34

So stay curious about each other's fields, perhaps.

SPEAKER_01 25:37

It's a curiosity. When I look at mentors who've helped me along the way, the ones that I respect the deepest are those that have that genuine curiosity. They can recognize their limits and reach over that boundary. I was involved in another center of excellence at one point with some wonderful people and some brilliant scholars, very, very revered scholars in Australia. And one who is a strong mentor of mine was largely responsible for the emergence of this because there was someone who was able to reach across that boundary, to recognize there's something interesting happening here, but it goes outside my domain of expertise. And to really understand it, I'm gonna need those people in the room to help me break through that barrier rather than kind of approaching and going, well, I'm just gonna keep pushing and knocking down that wall in that kind of violent way. I'm gonna actually get the people in the room that have looked at it from the other side, and together we'll actually neatly remove this brick by brick and merge these two spaces together. And I like that. I like thinking about when you hit a limit of a field, that's the point to reach over and go, hey, is there someone on the other side of this that can help us build back the other way?

SPEAKER_00 26:47

So then how do you know when you've done a good job in your field? You talked about wanting to change things and influence and impact. And of course, a lot of us want to do that coming from the CICOM space. Wanting to change is it's just the reality. Anyone who says they're not trying to change people is why my mind lying about it when they're doing these kinds of jobs. But for you, when do you look at it and go, that worked? We've done something that made a difference, or this is what we intended to do, and we've done a good job.

SPEAKER_01 27:11

Yeah, there's a few things that I've picked up along the way that make me think I'm on to something like you're pushing in the right direction. And that's one where you meet challenge because I think sometimes you know you're kind of at the edge of something when there's a bit of resistance, and sometimes resistance can be healthy because it helps you really refine the ideas, try different ways of explaining it, really kind of push that way. When those who are established and respected within that singular discipline turn around and go, look, you've made me really think hard about this, or I'm thinking differently, or you've provoked me in a particular way that I'm now thinking about this differently. That's always a good tell. Yeah, yeah. If what you're doing raises more questions than it answers, that's often a really good tell that you're onto something of importance. But then I think ultimately that you get invited back, that people are willing to continue to have the conversation with you, that you've spent the time to build the relationship. I mean, this is part of it too. I like to think in the work that we do when it's good, it doesn't just stop at the paper getting published. Like there's an investment, right? And there's that that investment needs to last. That you're not just gonna wander in and go, oh, look at you all, you know, you haven't figured this out yet. I'm gonna solve this and then solve, and then you're at straight out the site, wandering to another discipline to go and solve their problems. Um and look, not all physicists, right? Not all physicists, but they can be very much guilty of this of you know why wading in, solving the problem, and then poop, they're out the other side and on their way. And so I think there is a sense of like, you know, going, moving gently, building respect, um, doing things in ways that build coalitions. I think the best, the best is always when I leave it having learned something from the other discipline that I didn't know before. So I've now moved my own thinking, and that side has also done the same. And there's been that mutual exchange of perspective. Um, they're all markers of success in my mind.

SPEAKER_00 29:12

So much better than someone saying, well, if I get an X percent increase in measure Y, I'm like, well, sure, but come on, I'd be more imaginative. If someone wanted to be you or get into this like you have, have you got any advice for where do you think they should start? Where where's a good kickoff?

SPEAKER_01 29:27

Yeah, look, um I am here through random chance and luck, to be honest. Like, and hard work and grit, obviously. But no, the guiding hand. It's wild, actually. There's been a few key moments. So I remember when I was applying for my undergrad degrees, I wanted to do robotics. And it was a phone call from a professor at Swinburne who was an astrophysicist that changed my mind to go and do research and development, right? So already at that point, the kind of a hand of fate just playing its role in kind of going, no, actually, Dan, you're gonna go this way. And then when I was finishing my PhD um in AI and taking a role at University of Queensland, which was in a completely different branch of that space. Like I was doing stuff in optimization, the postdoc was in natural language processing and visualization. And so I I worked really closely with a couple of mentors there. Um, and I was starting almost from the ground up. Like, you know, I hadn't done a lot of work in NLP. You know, you do a PhD, you can learn quickly, then that's the point of it. But it wasn't my home discipline. And so you're already then being prepared to kind of jump to something else, right? But then over the way, start to build roots in a few spaces to try and really make sure I had a strong foundation through which I could give value into projects. Yeah, just being able to go with where there are opportunities in front of you. That that's what has defined, I think, my career is jumping onto things with good people where, okay, it's not necessarily a hundred percent what I want to do, but it's something that I can see there's value, and probably as I work through it, I'm gonna get a lot of satisfaction from it. And it's gonna push me and make me better.

SPEAKER_00 31:06

I relate not as not as uh fervently, but I've had a similar experience where you kind of go, huh, I didn't expected that, but that could be interesting. And off I wonder. And it always ends up working somehow, and it always ends up bringing back in things you did even though you didn't necessarily realize they connected, which is delightful for those of us who've managed to do that at all.

SPEAKER_01 31:22

It's wonderful. I learned this early because I'm a pretty extroverted person in that I'd be in a room and I'd be immediately going, Oh, I could solve that. And yeah, look, we could do this and we could do this and we could do this. Yeah. Having learned to now sit back and just let, just watch a little bit more, wait a little bit, learn, listen, and then offer, and then be like, okay, I think there's something here that I that you could find helpful. Um, you're not always going to get it right from the start, but I think going in genuinely with an attitude that you're gonna learn a lot, um, but you're genuine in your pursuit, like you've got something to give and a contribution to make, but yeah, do it. Because like I don't have enough years on this planet to experience and go into all the various disciplines that I would love to spend some time in. So I'm thinking how many I can do, right? But um You're doing well so far, it sounds like digging off a few. But um, but no, that's that's the yeah, genuine curiosity I think is is the key here.

SPEAKER_00 32:21

So my final question then is do you ever sleep? And more to the point, when you're not doing this or thinking about this work, do you listen to terrible podcasts, watch jump TV, read bad books? What do you do when you're not thinking about your your field?

SPEAKER_01 32:37

Look, I try and keep a barrier around the work as much as I can, but look, it does escape sometimes. There's crunch periods, grant writing, other deadlines. You know, it's probably more than a 40-hour week, if I'm going to be perfectly honest. But I'm not I'm not grinding through the weekends every weekend. I've got a young family, uh, two girls in in high school, and so I I like to spend a lot of time with them. For myself, I love riding a bike. I love doing track cycling and and road cycling. I love brewing beer. I'm a fairly accomplished home brewer and um do love enjoying that. I enjoy my garden at home and I enjoy getting involved in my community. We've had some big wins in, you know, really bad things that have governments have wanted to do in our communities, and we've managed to make a difference. So I like I can utilize the stuff I know from what I do in social science to kind of impact and improve my community. And so yeah, I get to hold my head up high when I walk through my neighborhood and see it's like we saved that, or you know, we changed that. So yeah, that's nice. But yeah, you're not the first to to want to comment that it's like, Dan, do you actually sleep? Um it's like, I'll sleep when I'm dead. Sleep when I'm dead. It's like too much, too much to do while I'm here.

SPEAKER_00 33:46

Oh, that's wonderful. Your your your energy and enthusiasm is entirely infectious, even though we're talking over what, about 1100 kilometers distance. But um you've pepped me up at the end of the day. Is there anything you'd wished I'd asked you that you'd want to like append here?

SPEAKER_01 34:01

No, I I just feel like I I always think about this. I feel incredibly privileged to have like just kind of, as I said, that that hand of fate has kind of steered me, guided me. And the other thing as well is that I'm indebted, as I think any academic is, to the ones who've come before. And so much of this I owe to those that saw possibility or opened or kind of laid the tracks down in front. All I've done is just roll down those. Um, and so I think the the thing that I consider now is like much of what I do is about how do I pay that forward or create conditions that allow others with that same drive, that same curiosity, the same kind of questions and attitudes to do the same behind. And how do we make sure there's as many of those ladders put down as possible for the diverse array of young careers scholars who are, you know, all trying to make their own mark. And I think that's the thing at the end of it. The thing that keeps me dry, like, you know, particularly now, is really trying to force governments and society to recognize the value of this. You know, for every dollar that we invest in science, you get three dollars of value back, plus all the other societal benefits and such around. And so I see myself as many others, probably at this stage of career on a mission to grow the pot. You know, we need more of this. Society absolutely needs more of this, and I'm spending most of my time trying to create the conditions where we can grow that pot to allow more of this good stuff to happen.

SPEAKER_00 35:28

God, you're too damn good. I feel terrible. I've got to lift my game. Having spoken with you, I realize there's about 80% more things I should have been doing. But no, honestly, fantastic conversation, mate. I really appreciated it. Dan Angus, thank you hugely. This has been Science with Benefits, and I'm Rod Lamberts. If you enjoyed the show, please like, rate, share. You all know the drill by now. Also, if there's someone you think I should talk to, it might even be you. Drop me a line either via LinkedIn or on email. Rod.lamberts, Lambert with an S, at anu.edu.au. Talk to you soon.