Daniel Emmerson​00:02

Welcome to Foundational Impact, a podcast series that focuses on education and artificial intelligence from a non profit perspective. My name is Daniel Emmerson and I'm the Executive Director of Good Future Foundation, a nonprofit whose mission is to equip educators to confidently prepare all students, regardless of their background, to benefit from and succeed in an AI infused world.

Today's guest is Dr. Lulu Shi, who is a lecturer at the Department of Education at Oxford University and a Research Associate at the Oxford Internet Institute and Sociology Department, Oxford. She is a sociologist and her research spans technology, education, work and employment and organisations. Lulu leads a project funded by the British Educational Research Association which investigates the political and economic agenda behind the push for digitalisation of education. She has also recently completed a British Academy funded project in which she developed an index that traces edtech usage in the UK. Lulu, it's phenomenal to have you with us today.

For our listeners, I think first of all it would be great to know because we haven't had a guest in your area of work before. It would be wonderful to know a little bit about what do you do at the university, what your work involves and if we can also bring in your interest in AI to that as well, that would be wonderful.

Dr. Lulu Shi​01:33

Yeah, sure. So my background is I'm a sociologist and previously I've been working on education and work and only more recently I have a stronger focus on the digital aspect of it. So that is, for example, what does that mean when the workspace and education is more and more digitized? For example, the use of AI these days, what does that mean for society as such? And there are different areas that I'm looking into from sort of this micro level of engagements, for example in schools, in the educational space, that is what does that mean when we use more and more technology in the classroom and in other educational areas to a more macro perspective and thinking about the political economy, that is how is that space changing with new actors from tech coming in into a more traditional space where we haven't seen so much tech actors, where we have seen maybe more policymakers and traditional actors in education. So that is sort of roughly what I'm looking at. And as I mentioned my background is sociology, so I always have this sociological lens to that and ask the questions such as how does that impact societies? I'm always interested in questions such as social inequalities. So that's kind of the topic and the lens that I'm taking in my research.

Daniel Emmerson​03:01

And what does that look like for you on a day to day at the moment? Are you teaching more than you're researching or are you spending more time on research?

Dr. Lulu Shi​03:08

Yeah, both. So I am a lecturer in the Education Department at University of Oxford and I do research on the area of digital education these days. But I also teach the master's program called Digital and Social Change. And yeah, so in that sense I do both, but these go pretty much hand in hand because my research very much informs the way how I teach and also what I teach. But then I also learn quite a lot from our students who have quite a diverse background. Some of them have been working in tech sector, some of them in education sector. And yet again others come from with a more policy background. So I think teaching and research, I don't see them as super separate areas, but they really do go hand in hand.

Daniel Emmerson​03:58

And what are the aspirations for your students, for example, at the moment when they're going into this quite unknown space of education? When looking at that from a technology viewpoint, it feels like a very unpredictable field at the moment. How are you helping them to navigate that?

Dr. Lulu Shi​04:18

Yeah, do you mean the aspirations from my student side or, or more what are my aspirations for them? Sort of teaching wise, I think.

Daniel Emmerson​04:28

From their side.

Dr. Lulu Shi​04:29

From their side, I think because their background is so diverse, so their career trajectory is also going to be quite different. Some of them might want to stay in academia. So we do have former master students who now are doing PhD programme and continue with academic track and others want to join the policy space. And as you say, this is rather new or I wouldn't say it's that new because we always have used technology in education, right? Only perhaps the digital aspect or the AI aspect or generative AI aspect that is new. So this field is not yet thoroughly understood and we don't have for example much regulations around that. So we do have quite a lot of students who are interested in this regulatory space. How can we think about this? And they take what they have learned from the course then into their future workspace to inform policy, for example. But then we also have students who then go into the tech space again with a theoretical background they have learned with us. And then to think about how we can approach edtech and think about edtech that has core values such as including social justice in mind.

Daniel Emmerson​05:44

Your work covers such a huge area. I mean the number of levels that you talked about with the micro and the macro and then looking at policy and then looking at social implication, do you find that you're drawn more to the sociology side of this or is your interest as broad as the subjects that you're working in?

Dr. Lulu Shi​06:05

I think no matter whether I take the macro or micro lens, the questions that I ask are always sociologically informed. So I think the sociology aspect always stays. That's sort of my training and this is what I'm most passionate about, research wise. But in terms of where I put currently the most focus on is I would say the political economy aspect of things. That is the larger picture, how this space is changing and this is huge. I wouldn't say that. Okay, now I understand the field, but this is really with every research project I gain a little bit more about this bigger picture.

Daniel Emmerson​06:46

So you're doing some work or you have done some work on how edtech firms are influencing education. Is there anything you might be able to share so far from this research? And is AI changing those outcomes in any way?

Dr. Lulu Shi​07:00

Yeah, so I think this is not only from my research, but from what we know from the literature so far is that there are many areas where edtech companies can shape or influence education. For example, just thinking about the new actors who are entering the field. Right. Because we use more and more technologies in education. The technologies that we use actively shape the way how we teach and learn. Right. So if you think about a certain product, a certain product may have certain templates or certain structures. And when now imagine me as a teacher, when I teach a class and I use a certain product, then I am influenced a certain way. How I teach any kind of subject like math or English. So that has a direct impact on how teachers teach and also how students learn. Because the structures or the pedagogical ways are sort of predetermined by the tech products. So that's one way I would say. Well, this is actually, I think I didn't really address your question correctly. I think this is more the micro aspect of how day to day life changes in a classroom, how teach and learning change and then on the broader level, how tech companies may shape education or education system as such. I think we can see that in how tech companies are also very much engaging in policy making or in, let's say, shaping the digitalisation of education strategies on a national level and also on local level. So for example, I think it was earlier this year, the Department for Education, they organise multiple expert table rounds, right. I was invited to one of those and that was mainly with academics and other policy institutions and think tanks and so on. It was quite academically focused, I would say. And there was another roundtable where mainly industry leaders were invited to inform policy making. So in that sense, you could see the list of companies who were invited, who in that way actively contribute to the digitisation strategy in the UK by having this consultations round. And this was something that is more visible because these materials are all online accessible, so you can actually see who said what and what are the outcomes of this consultation round. But I think there are also aspects that are less visible. There are meetings between companies and policymakers or meetings between schools and edtech companies that are not publicly advertised. So it does require quite a lot of research and work in order to find out where are the fine grained or nuanced sort of ways of shaping and influencing education.

Daniel Emmerson​10:00

I'm interested to know your thoughts about this because of course, if you have for profit companies that are, yes, sharing their knowledge and experience about, let's take AI, with government officials there is of course they have that vested interest, right, in being present at the table and building those relationships and in one way or another trying to influence that policy based on what they're building and what they're, what they're selling. The government, I hope, would, would, or the DFE would take these conversations away and be able to learn from them to an extent. But do you think that's a fair or do you think that's a reasonable trade off? When thinking about the sociological implications?

Dr. Lulu Shi​10:47

I think the answer is less binary, either yes or no. It all depends on how these negotiations take place. And I think what we need to look at is whether the values are aligned. So yes, for profit companies have different sets of values and probably different visions of what they want to achieve than let's say the Department for Education or another government department or let's say schools. So every actor groups may have their own values and own sort of priorities what they want to do. And I think in that case, if we want to have collaborations between different sectors, which can be very useful, it's all about whether these values can be aligned. Right? And from a sociological perspective, I think what I'm quite interested in is to look at whether there's any power imbalance between the different stakeholder groups, whether, let's say the private industry is dominating the discourse, or the other way around. So we need to think about a good infrastructure that keeps the power in balance in order to ensure that the values are aligned.

Daniel Emmerson​11:55

And when thinking about that value alignment, this is something that comes up quite frequently with schools, right? If they're looking to bring in some new tech, either hardware or apps or whatsoever into their teaching and learning environments, trying to align on value propositions between the companies and the schools is something that they'll take into consideration. Do you think it's possible to make those connections or are they driven, do you think, purely from a commercial perspective as far as the edtech companies are concerned?

Dr. Lulu Shi​12:31

Again, I think a blanket answer might be ignoring some of the nuances there, because every company is different and we do see that companies, that there are many companies around that do have this social justice goal in their company visions. Right. And then it depends on how do these companies sort of evaluate their, their own values and also how open they are to work with schools. And also, again, schools are not all the same. We have schools who may have one set of values that is more important than other sets of values. Because I think in the end we also need to think about what is education, what are the purposes of education, and schools interpret that differently. What we do see, though, I think an overall trend in the UK is that educational purposes are very much human capital oriented these days. That is, we do have a very strong orientation towards equipping students with skills that they need for the labor market. So the labor market is a very prominent goal for the education system and for the most schools. But then we also have other values in education, such as nurturing social relationships, that students learn the social aspect of things, and that students also learn to become politically engaged citizens and how to navigate in a democratic system. So depending on school, one set of values may be more dominant or prominent than other sets of values. So how to align these values between schools and edtech company really depends on the individual schools and edtech companies, what kind of values they have. So I don't think that there's one answer of how we should be aligning these values or whether this is possible. It's sort of a case by case question that we need to investigate.

Daniel Emmerson​14:22

And that's also the same, I suppose, in the world of work. Right. I know you've done a lot of research into both paid and unpaid labor and the role of AI in those spaces. I was wondering if you could talk to us a little bit about that.

Dr. Lulu Shi​14:39

Yeah, that was a different project. So it didn't. That project did not have anything to do with education. It was led by a colleague of mine at the Oxford Internet Institute, Professor Ekaterina Hertog. And that project was trying to predict how much of unpaid labor in the domestic setting can be automated in the near future. So that was the research project more on the work side of things. And the background of this project is that we do have a lot of studies and literature on predicting the future of paid work because there is this kind of, I guess, hype also in the media that discusses are robots going to replace us? Are we all going to be unemployed? So there's this fear that machines are going to make us unemployed. But there's much, much less focus on what is actually happening in the domestic setting where we do unpaid domestic work. And this is quite surprising because we do actually spend about the same or the same amount of time doing unpaid work as paid work. And that varies, of course, across countries. And also there are gender differences how much we do unpaid work. But that was sort of the motivation to do that project, to, to answer the side of things that has not really been researched. And what we did is we interviewed experts in, who are working in tech and we ask them to predict the amount of automation of very specific tasks that are being carried out at home, that is as part of unpaid domestic work. So, for example, we would ask for cooking. What do you think will be automated in the next five and then in the next 10 years, if you think about cooking? And we will give a very precise definition of what is cooking and describe cooking in terms of what are the subtasks. So for example, picking vegetables, chopping vegetables, and all of that, so that everyone's on the same page and has the same definition and can think about the same compositions of a certain task. And then we aggregated that across all the experts predictions. So that was the project. However, what we actually wanted to say is not this number. Now I don't exactly remember what was the number, but it was below 50%. It was close to, I think 50% of the amount of unpaid domestic work is likely to be automated in the next 10 years. So that was actually not our main message. That's why I don't exactly remember the number. Our main message was actually that social predictions are social. So there's no objective prediction. We cannot really say that this is going to be automated by that extent. And it's basically a critique of. There's a term technological determinism, which describes that there is just this one way of technological progress and we are getting there no matter what. So we actually wanted to criticize this technological determinism by saying that how the future will be is actually shaped by us. So it's shaped by actors who are in power to shape the future and the development of technology. And the way how we demonstrated this is we compared different experts' predictions. For example,we compared how female experts predicted the future versus male experts. And there were indeed differences. We also compared experts sitting in the UK and experts in Japan. What are those differences between two countries and two different cultures? And it turned out that UK male experts have the most optimistic vision of the future in terms of they gave us the highest prediction of the amount of work that is likely to be automated. So they were more optimistic than female experts in the UK, but in Japan the picture was actually the other way around. So in Japan we had female experts who were more optimistic than male experts. And the reason for this is. So we don't know for sure, but our hypothesis in this paper is that your prediction is grounded in your personal experience or that we need to understand predictions as a social position. So in Japan, the gender gendered labor division is much more extreme than in the UK. So women do much more unpaid labor than men in Japan, also in the UK, but it's just the difference is smaller. So in the qualitative answers we saw that male Japanese expertswould justify their low prediction of automation by saying that this is going to be very costly, so there will not be a market for this automation. And therefore I predict that the degree of automation is going to be quite low. And female experts, on the other hand, were actually saying the same thing. They were saying the cost of this automation is going to be quite high. However, it's going to be totally worth it because currently, from my experience, I'm doing double work, right? I'm doing all the housework and I'm also doing paid work. So there's a real incentive to push this kind of technologies. So that was sort of the core message, what we wanted to say with that paper, that instead of technological determinism, we need to understand what are the social needs. And the conclusion of that is also that we need to shape technology in a democratic way. Because if we only have one homogenous group that is developing tech, let's say Japanese men in that example, then the future of unpaid work is going to be looking different than if we have a group of female Japanese experts developing technology for unpaid domestic work.

Daniel Emmerson​21:01

This is absolutely fascinating research, certainly, but it's also something that we're finding to be of interest for a lot of students, particularly those coming towards the end of their studies at school, where they can see how technology is impacting what they are already doing on a day to day basis. And there is this perhaps trepidation about whether or not what they are doing will be worth something in the future and how this is going to impact the world of either paid or unpaid work. Finding or looking for certainty around that space is almost impossible. But I'm keen to know your thoughts on that and how you might address some of those concerns from students about the future of work and automation.

Dr. Lulu Shi​21:48

I think it's a valid concern because there is uncertainty. Right. But rather than thinking or rather than feeling powerless, maybe we can turn around the discourse and say, maybe we need to find agency and we are going to shape the future, because the future is going to be how we're shaping it. Again, I think it's important to think away from this technological determinism. So there are studies that are saying this profession is going to be automated away by so and so percentage. But this is all based on what we're seeing now, what is happening now, and what has happened in history. Right. But there's no sort of guarantee that things are indeed going to go that way if we, as a collective, decide otherwise. So I would like to encourage young people to have this agency and to actively shape how the future should be. And this is very difficult. I can see that, because as an individual you do feel, or you can feel quite powerless. But I think it's important to think about how can we collectively organise ourselves to think about, for example, social movement can be a very useful tool to engage in this sort of discourse and to actively shape how we want to make a pathway for the future. So I think this moment of decision making, we can also see that in history. Now, if we think about the Industrial Revolution, I think this is something many people would say, this is inevitable. We had to have that, but maybe it wasn't really the case. Right. We took the path because people who were at the time in power had the power to determine that the future will go in one way and not the other. But we did see a lot of resistance. However, these resistance failed, but they didn't have to fail. It's all about how we organise ourselves. So I think in that way, shaping the future and also related to thinking about technology, it is deeply political. It is not something that is scientific or not purely scientific. Yes, it involves a lot of science, how we design technologies, what is possible. But technology is deeply, deeply political.

Daniel Emmerson​24:16

I think having that sense of agency, trepidation, but also being mindful of the impact of being able to shape your own future as far as the world of work is concerned, is a positive enough, I think, way for us to wrap up this episode. Lulu?

Dr. Lulu Shi​24:34

Sounds good.

Daniel Emmerson​24:35

Always such a pleasure listening to you and chatting with you. Very, very grateful for you being part of Foundational Impact and looking forward to catching up again very soon. Lulu, thank you so much.

Dr. Lulu Shi​24:49

Yeah, thank you so much for the invitation, Daniel. That was a pleasure.

Voiceover​24:52

That's it for this episode. Don't forget, the next episode is coming out soon, so make sure you click that option to follow or subscribe. It just means you won't miss it. But in the meantime, thank you for being here, and we'll see you next time.

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