Podcast

Rhetta Chappell (host): Hi, and welcome to Show me the data, a podcast where we discuss evidence-based decision making and the ways in which our lives interact with and create data. I’m Rhetta, your host for today, and I’m a data scientist at Griffith University. Show me the data acknowledges the Jagera peoples who are the traditional custodians of the land on which we are recording today, and we pay respect to the elders past, present and emerging. Today, I have the pleasure of speaking with two guests, Michelle Teis, who is a partner at GWI and Dr Tom Verhelst, who is the director of RIDL. Michelle is an enterprise information management strategist and she’s all about maximising the use of data to improve decision making and reduce complexity. Today’s episode is about embracing the paradox of data privacy and ethics in 2021, and both Tom and I are looking forward to this and I’m sure we’re gonna learn a lot. Hello, and welcome Michelle and Tom, really happy to have you both here today at Show me the data. Michelle, it sounds like some of the work that you’re doing at GWI has some interesting parallels and similarities with some of the work that we do at RIDL. And I wanted to ask you specifically about if you could talk about some of the projects that you’re doing in this social good and social impact space?

Michelle Teis: Absolutely. So, GWI is a boutique management consultancy that specialises in only two areas, we deal with digital transformation in the way that people work with data. But we also deal predominantly with information and data. And we help organisations solve problems with data and the information that they collect. And we’re particularly passionate about doing work that matters. So we work in child safety space, we work with homelessness data, we work with the public sector to help them improve and use the data that they’re working with. In fact, we work across all industries and sectors.

Rhetta: That’s really interesting, we kind of do similar things in the sense that we’re trying to use evidence-based solutions to address complex socio-economic problems. And we’re using the place rather than like agency or discipline as the data linking framework, do you find in the work that you’re doing that you’re also kind of taking this place-based approach? Or is it are you looking at data from a different perspective?

Michelle: We do take a place-based approach with some of our work, but not all of it. Some of it is really just about helping organizations maximize the data that they have, and getting them to recognize the value of what they can do with that data.

Rhetta: Yeah, that’s great. You recently wrote that we all need to start applying an ethical framework to decision making and that we really need to be doing this now. Or maybe even yesterday, could you explain what an ethical framework is, and maybe give us an example or some examples of how smaller organizations or government organisations might practically implement one?

Michelle: Absolutely. So ethics is all about doing the right thing, the core tenant of ethics is to do no harm. And that means no harm to individuals, or the reputation of organisations. For everybody, an ethical decision is slightly different. And an ethical framework helps to guide decision making in an organization to ensure that there is consistency across the decisions being made. So it’s a principles based approach normally, and the principles aligned to a company’s organisational values. And it just pushes people to think about are we doing the right thing? Could we do it differently? Are we using data the right way? Are we being transparent? Do we have balance in what we’re doing? Is there proportionality in the amount of data that we’re collecting. So small organizations can easily put in place a framework that they incorporate into all of their data focused projects, so that they’re forcing an ethical lens on all of their decision making.

Dr Tom Verhelst: As the sort of the ethics of a company changes? Because the ethics of a company is sort of based on the ethics and society where it sits in? And that the morals and what’s acceptable sort of changes? How do you see that? It’s sort of like a challenge, right? It’s a bit like, you post something eight years ago on Twitter, which was then sort of acceptable, and now it’s like, you know, you’re a horrible person.

Michelle: Happens all the time. Yes. So look, ethics frameworks are living documents, they need to be reviewed by organizations all the time to ensure that they do align with changing values of the community, but also the way that organizations involved in how their own values change. So you know, what you may think is ethical might be different to what I think is ethical. And so what our ethical framework does, or a data ethics framework is just helped guide consistency and make sure that we’re both thinking about the same things. And hopefully, we will come to a similar conclusion.

Tom: We have recently been working with sectors that usually are aren’t as maturing in in the data journey, partly because they haven’t had the financial resources and the width and gradually sort of the data space is becoming cheaper. So it becomes more accessible for the sort of non-standard sectors, we’ve been trying to set up data collaborative. So data cooperatives in like the community space, the human health service to space. And basically, what we’re trying to do there is, you know, you have these sectors like finance, where they share some data, they make insights across sectors, you have the same in big oil in mining, we’re trying to do the same within the sort of community and services space, it’s way more sensitive, as in, they usually focus on people that are naturally disadvantaged, otherwise, they wouldn’t be focusing on them. So often, it’s sensitive data before, it’s sort of before you can sort of makes any value out of it, it has to be sort of the sensitive data. And so we’re talking about, you know, the cases of people and how they move from one organisation to another, and then how those organisations work. You know, working in those organisations is very challenging. People have higher burnout rates and other organisations, we really still trying to sort of figure out how we should work with that sort of sensitive community data. Do you have any advice on the ethical questions that we should be asking? in those spaces, like when we when we bring these people together to share the information? What Shouldn’t we be missing?

Michelle: So first of all, I’m a big fan of data cooperatives or collectives in that I think the use of shared resources and shared data can lead to common, or consult common interests and bring great benefit to those people that are members of the collective. And ethically, it actually changes the dynamic of what you’re doing with data. So when you bring people together into a cooperative, you have different ranges of stakeholders. And so you need to consider from an ethical perspective, who all of those stakeholders are, and whether the decisions that you’re making or the products that you’re creating are gonna adversely impact any of those stakeholders, whether or not there’s any bias bought in that would impact one particular part of the cooperative above another. You need to look at the transparency of what you’re doing, and making sure that people understand exactly what is happening with data, particularly if it’s personal or sensitive data. So have they given you consent for primary use of or primary collection use? And then are you using it for a secondary purpose? And if so, are you being transparent about that secondary purpose? And does everyone understand what the outcomes of that could potentially be? So there’s lots of things you need to consider how much data you’re collecting whether or not you’ve got more data than you actually need? Have, you got the minimum set so that you’re not sort of over collecting data, and you’re not using it appropriately, looking at third party access to that data, considering you know, who should access it and whether or not they have the right to see the data that you have. So there’s lots of things you need to consider

Rhetta: in most of the work that we do. And this kind of ties into this data collaborative work. Our idea was to we’re taking individualised data, but then we’re aggregating it up to some level that makes it so that you can individually identify different organisations or different people, how do you balance this trade-off between useful and anonymous data? So it’s kind of playing on that idea of like the privacy versus utility trade off? And how do you balance this in the work that you do?

Michelle: it’s one of the biggest challenges that we have today, I think is when you start to anonymise data, you do reduce the utility of that data. And so it’s about understanding the context of what you’re trying to do. And the context in which you’re collecting data, and the context in which your stakeholders operate. And I think you need to find a balance. So the more the more you anonymise data, people believe that you’re actually protecting the personal information of individuals. That’s not always the case, when you are aggregating. It is always possible these days because of the volume and the veracity of data collected, and the advancements in technology to re identify people in that set. And so that’s where your ethics comes into play, you actually need to sit down and put that ethical lens over what you were doing with the data, how you’re planning to use it, whether or not there is potential for harm, whether or not there’s balance and proportionality, whether any biases creeping in, and overall, respecting people’s privacy.

Tom: I think you made like a very interesting point, because before the start of like a conflict arising, there’s the you’re very right, like you should ask yourself, what are you collecting? And are you not over collecting? But then to be able to answer questions around, you know, his drive around, reduce the bias or afterwards asking different questions. It’s sort of creates tension. Because you don’t want to over collect, you don’t want to look at the most sensitive. But then if you abstract or if you have, you’ve scaled down what you’re collecting, you’re sort of putting yourself a bit at risk with your conclusions or your analysis.

Michelle: Yeah, you’re also reducing, you know, potential for, for greater outcomes. But it’s just a matter of finding what is the right balance, and it is a current challenge and the federal government have acknowledged that and are currently reviewing the Privacy Act. One of the considerations in that review is whether or not people should have to give consent for every potential use of their data. So instead of doing general consent to say I, I agreed you’re collecting my data for this use, and I understand that you might use it for X, Y, and Z, but actually getting informed consent for every potential use.

Rhetta: That makes it tricky, I guess, but it makes sense.

Tom: Yeah, it’s very, it’s very interesting. So it leads nicely into our next question where, like, within academia and government, very often, we have very rigorous ethical processes, which are sometimes a frustration for, I mean, they have their purpose, and they’re very valid. While in commercials in the commercial space, sometimes that is not as required. I mean, there’s definitely examples of, I think, see examples in the financial sector in the mobility data sector where, you know, there’s not, the process is not as as rigid what a stick. It makes those type of it makes it quite interesting how sort of academia and government can sort of learn from the commercial or business sector because they look a lot more Lean and Agile, and they seem to be answering questions a lot quicker for you, since you’ve worked in academia A while ago, but now in business, have you observed that too, is that something that you think I can, I can learn from?

Michelle: Absolutely, so had the privilege of working across both academia, the commercial world, and also in the government, non public sector, and all three of them have things that they could learn from each other. So academia has, you know, a long history of collecting research and doing research, and they’ve always known how to manage research data, doesn’t mean they necessarily always do it. But they’ve always known the rules around research data, and, you know, establishing good governance about that, storing it in the right way, having human ethics committees and taking a risk approach to the use of data. Universities have always been great at that. In the commercial sector, they’re very revenue driven. And so they’re trying to do more with data for less because revenue is is the primary focus. So they make their decisions a lot quicker, they process things a lot quicker, they don’t have the detailed level of structure that government has so and on the other side, government’s very compliant, driven. So they’re slow to make decisions. They’re hesitant to share data, because it’s driven by taxpayers money, and they want to make sure that they aren’t doing the right thing by the taxpayers, and therefore, there’s a lot of red tape around their decision making.

Tom: Yeah, we’ve, I’ve really observed some very interesting. The last last year in particular, I’ve seen two departments buying data that basically would standardly be provided by census. But they wanted more accurate, they wanted more contemporary, they’ve, they’ve really paid a constant amount of money to companies to provide them with that sort of information, which I think is very interesting. It’s a very interesting trend. Because you’re right, they are slow in their collecting data, and they’re sharing. So they’re sort of looking at business to provide insights for government to make decisions.

Michelle: But they’re also recognising that data holds a lot of power, and therefore access to the right data can really inform decisions and make for a better public service.

Rhetta: So, Michelle, to finish up, we’re going to ask you a question that we’d like to ask all of our guests. And I’m not sure if it’s better to think of a specific project or just in general, if you could get access to one data set, and I guess, based on our conversation may be ethical and policy concerns aside, that would really unlock some really fruitful insights for you. What would that dataset be?

Michelle: Great question. For me, it would be around consumer behaviour. So, understanding why people do things when they do things and looking at trends and patterns across communities. I think that that would be incredibly informative. It would inform retail patterns, it would inform education patterns, it would inform, you know, job roles and changes in job role. I just think I don’t know if that data set actually exists. But yeah, consumer behaviours are incredibly interesting.

Rhetta: So maybe some banking data, but we almost need every bank’s data like you mean like patterns or….

Michelle: imagine that, banks sharing data. Yeah. Yeah. Yeah. But yeah, consumer patterns, really interesting area and you know, so many different opportunities would come out of them.

Rhetta: Great. Well, thank you so much for your time, Michelle, and you too, Tom. And that’s it. To listen to more episodes of show me the data, head to your favourite podcast provider, or visit our website, RIDL.com.au, and look for the podcast. We hope that by sharing these conversations about data and evidence-based decision making, we can help to inform a more inclusive, ethical and forward-thinking future. Making data matter is what we’re all about. And we’d love to hear why data matters to you. To get in touch. You can tweet us @G_RIDL. Send us an email or if you prefer, just send us a letter by carrier pigeon. Thank you for listening, and that’s it til next time, take care and stay safe.

Rhetta Chappell (host): Hi, and welcome to Show me the data, a podcast where we discuss evidence-based decision making and the ways in which our lives interact with and create data. I’m Rhetta, your host for today, and I’m a data scientist at Griffith University. Show me the data acknowledges the Jagera peoples who are the traditional custodians of the land on which we are recording today. And we pay respect to the elders past, present and emerging. Today on Show me the data, I’m joined by Professor Shayrn Rundle-Thiele, founding director of Social Marketing @Griffith University, where we’ll be discussing how data informs and drives interventions focused on changing individual and group behaviours. Welcome, and thank you so much for taking the time today Sharyn, and I’m really looking forward to this conversation. So let’s jump right in. You’re the founding director of Social Marketing @Griffith, and from my understanding social marketing seems to have a focus on changing both individual and group behaviours. So to change the way people behave, do you first need to change the way that they think? Or are there other ways to encourage behaviour change?

Professor Sharyn Rundle-Thiele: There’s a whole host of ways we can actually encourage behaviour change. People are social beasts, and we tend to watch what other people do. And we care about what other people think we should do. So some of our work will involve appealing to you giving you information, and from that, some people act. For others, it’s giving them a motivation, like a reason why, and that’s enough for them to act. And then for yet others seeing someone else doing it is how they then move and actually do the behaviours and the things themselves. So that’s just talking about people, and if we’re trying to change ourselves and the patterns of what we do. But there’s also other work in terms of actually working across groups, and social settings, or regions and areas where we work across the people and the stakeholders themselves to try and actually then also gain support to actually make the changes needed to support people to be able to do a behaviour that they want to do.

Rhetta: Okay, great. So, it sounds like you have a very kind of multi layered approach. And you’re obviously monitoring things as they go and as things are happening. And then they’re establishing norms or kind of picking off of what’s working and what’s not working. And so, with that, I’d be really curious, because we work with a lot of different data in a lot of different contexts, as I’m sure you do, too. What sort of processes and methodologies do you follow when you’re collecting data to figure out if this is working, or if we need to try a new approach?

Sharyn: So, data is really critical in helping us understand what people do. And a lot of researchers who have first-hand experience of talking to people, and whether it’s interviews or surveys, actually understand that there’s a lot of biases in the work if we actually ask people. So, the more we survey and try and understand what people are doing, they’ll self-report, and then they tend to under report things that we actually really want to know about. Or they over report the things that maybe they think they’re doing well. And it’s not actually the case at all. So, our world is one of breaking through the data. And if you compare itself report to any real data, like what people are actually doing, whether it’s how we look for things on Facebook, how we go to Google to get information. We’re even flawed as humans, and we don’t remember everything. So, some of it’s not even that we’re trying to make ourselves look good, we just don’t remember. So, data is critical, because it teaches us what people are doing. It doesn’t necessarily help us understand how to move people forward. And so, we see this wonderful term insight. And that’s the talent, I think, to break through a lot of data, and understand across a lot of information, what’s really important, what stands out, and what help might move more people the fastest. And that’s a bit of a talent. So, we’ve got a lot of data analysts who can give us a lot of information. But then understanding from the data, where to go next, I think still is an area where the human minds always going to be needed to get the understanding of where to go next.

Rhetta: Yeah, that’s really interesting. And something that we work with a lot at RIDL also, it’s like balancing this like self-reported survey data, with like big human movement data to see like, is what the people are saying, is that matching up in these kind of indelible data sources that are maybe a little bit more trustworthy? But then there’s obviously ethical concerns with using these types of data. And so then there, and obviously, survey generated ideas are a bit easier to collect in some instances. So, I’d be interested to hear from you. Do you think there’s any contexts within which it’s inappropriate to try to collect data or to use a data driven approach? Or is it like, okay, across the board? Or how do you choose which type of data you’re going to do use when I guess?

Sharyn: I think, coming out of commercial backgrounds and moving into social science and behaviour change work, there’s a lot of discussion around ethicality, morality in the social change space, that I think sometimes aren’t conversations that are really happening in the commercial world. And if you go out and transact using your bank account, you know, you’ve got your cards and you just swiping everywhere you go. All of that tracks all of that’s used to sell you more products. How ethical is that? Are we having those conversations hard enough and well enough, I would like to think that if we do have true good outcomes that we’re calling for, and not just political will to get a change, that sometimes I think it’s incumbent on us that data is like an asset. And it is already like governments and agencies right across our nation and globally, are custodians of these assets. And keeping them locked away, I think is also an injustice. Because making that data accessible and open, and allowing more agencies to act and operate from it are probably incumbent on us to actually make a better future. Because looking at patterns, getting across agencies, and breaking people out of their silos and stopping the biases that we’re living with, would really help have the conversations we need to be having. Because I today will have a conversation with one agency that’s about obesity. With another agency, it might be about traffic congestion. And then with yet another agency, it’s about abuse or mental health, yet they’re all intersected. We’re not mapping that well enough. We don’t talk it well enough, yet. We operate in this big ecosystem. And we should be actually combining some of these issues. Because if I can get people to be more physically active, so if they naturally start walking to and from work, or catching public transport in between, we’ve reduced traffic congestion, we’ve actually got people more active. And in doing so we’ve got we’ve actually addressed the mental health issues as well, because they’re starting to have daily conversations in transit, that normally they wouldn’t have. And they’re building a social network. So we’re not looking at the bigger picture well enough. And the data and the access that we have allows us to do that. And we should be doing that.

Rhetta: Yeah, that’s so interesting. And I think it’s so important. There’s some new legislation coming about, which potentially could give universities the ability to be this kind of data linkage authority or have this this ability. And I’m not I’m not sure what the appetite in the Australian public is, but it seems like universities might be a really great option for this. Because he said, like commercial, like, is that ethical to be using this data? Or should government have it, that’s maybe not the right place, either, because political parties change, people have different tastes. So maybe this is a great opportunity for us here to have this whole holistic thought like process around data, linking the sources together, we know people don’t exist in little vacuums only entered acting with different points at certain times. It’s we were whole humans, and we need this whole experience. We want people to understand this as a whole, I guess as well. When you find an intervention that works, maybe it’s a highly segmented group or a community. How do you scale that up? So how do you include like, if you’re focusing on the obesity people, or the people that you’re working with in this obesity context, and that works there? And it works within this community? How would you then scale that up to maybe across Queensland or across Australia? Or is that just not something we do, because people are unique and within their communities,

Sharyn: I think there’s political will that has to be built. And that goes back to that really early point around behavioural change, and how it starts to reshape how we operate and what we actually do. So, if you can get it, for example, if you’re working in one local government area, and you get a proof of concept, and then you get the wheel between a couple of government areas to get together, that gets the attention of the state and or the federal level, and scaling up becomes possible. And another approach is not so much to imagine that you’re coming into the world to change it all yourself. And that actually our job, it’s incumbent on us to prove it can be done in a different way. And there’s potentially roll that out through the existing players who are already doing this work, teaching them how building capacity, ensuring they’re empowered to actually take that and do that. And then it’s having the right consequences and the right outcome. When you look at some of our work, and going back to the earlier point on who should own the data, I’m not sure it should be any one source. And that may be more transparency across all of that is actually needed to avoid any power and politics conversation. Because any government could be criticised using it for advantage in a political vote. And likewise, I think any university could be charged with using it for rankings. So, I think for all of us, the better the system gets at ensuring that it’s my data that I give out. And as an individual, I don’t want to be identified. And I think it’s incumbent on all of us to protect identities. And I certainly know through my work with data analysts and people who work with data that they’re very careful about that. That it’s not about sharing an individual’s identity, but it’s about protecting them but using what we know to start to interrogate better, so that instead of having constant conversations around, there’s no money and we can’t it’s like yes, we can, how can we and how are we reallocating resources better to achieve the common goals across players that have come together,

Rhetta: How has the COVID 19 pandemic impacted the way that you work or the way that your clients work with regards to data, we at riddle have noticed that a lot more people are wanting to start doing things with their data and start making smart decisions with maybe less resources. Have you noticed that in your area of social marketing?

Sharyn: I think there’s no one entity person or anything anywhere that has not been touched by COVID-19 lock downs, and all of the issues that have actually come about over the past sort of year or certainly 18 months in other parts of the world, how we actually access data, I think we’ve become a lot more open to online sharing. It’s for sales technologically to improve that in and of itself means more people can actually do it more. And it’s had people asking different questions about different ways of working. So yes, it’s had a huge effect. And

Rhetta: I feel like social marketing is so great for this kind of point in time as well, like you’re really embracing, like the human aspect and testing things out. Does this work? Do people respond to this? Do they want that, and I hope that you guys are being included in a lot of these Queensland Health Initiatives with regards to I’m not sure if you are, but maybe with the vaccine rollout or the economic recovery, and helping us I guess, do this in a way that is inclusive, and I guess forward thinking,

Sharyn: Now I can definitely speak on behalf of our group, we are doing more work in 2021, than we’ve ever been doing before at any point in history. So wherever we’re lucky to have someone work with us in partnership, our role is to walk in and see if we can help create Win Win solutions. And creating it is not us creating it, it’s that we essentially just facilitate the people we’re working with and help them see a solution that works for all of them. Yes,

Rhetta: Excellent. And I guess to finish off, I’ll just ask you one question. If you could have access to any data set and like the Don’t worry about morals, or ethics or anything like that, that would just really help to maybe crack open some insights into maybe one area or just in general, do you have like a dream data set that you guys could get your hands on

Sharyn: all the way? For me, it’s going back to the store scanner, data, bank data, and all of the retail shopping data that I used to have access to when I was working commercially. It actually taught me a lot about how people behave. I didn’t need to go and ask people at that moment in time. Today, I’m not left with that same luxury of data that I used to have. And I would love to have that capacity back again.

Rhetta: Yeah, great answer. Thank you so much.

Sharyn: You’re welcome. Thanks for having me.

Rhetta: To listen to more episodes of show me the data, head to your favourite podcast provider or visit our website, RIDL.com.au and look for the podcast tab. We hope that by sharing these conversations, about data and evidence-based decision making, we can help to inform a more inclusive, ethical and forward thinking future. Making data matter is what we’re all about. And we’d love to hear why data matters to you. To get in touch. You can tweet us @G_RIDL , send us an email or if you prefer just send us a letter by carrier pigeon. Thank you for listening, and that’s it til next time, take care and stay safe.