Tech Won't Save Us - The Consequences of Leaving Tech to the Private Sector w/ Rosie Collington

Episode Date: February 23, 2023

Paris Marx is joined by Rosie Collington to discuss the consequences of outsourcing tech to the private sector, how it causes governments to lose important capacities to serve the public, and how the push for open government data empowered large tech firms.Rosie Collington is a PhD candidate at the Institute for Innovation and Public Purpose at University College London. She’s also the co-author of The Big Con: How the Consulting Industry Weakens Our Businesses, Infantilizes our Governments and Warps our Economies with Mariana Mazzucato. You can follow Rosie on Twitter at @RosieCollingto.Tech Won’t Save Us offers a critical perspective on tech, its worldview, and wider society with the goal of inspiring people to demand better tech and a better world. Follow the podcast (@techwontsaveus) and host Paris Marx (@parismarx) on Twitter, and support the show on Patreon.The podcast is produced by Eric Wickham and part of the Harbinger Media Network.Also mentioned in this episode:Rosie wrote a paper called “Disrupting the Welfare State? Digitalisation and the Retrenchment of Public Sector Capacity” for New Political Economy, and a report calling “Digital Public Assets” for Common Wealth.Palantir has a massive and controversial contract with the NHS. That hasn’t stopped Peter Thiel from criticizing the UK’s public healthcare system.Mar Hicks wrote about the masculinization of the computer workforce in Programmed Inequality: How Britain Discarded Women Technologists and Lost Its Edge in Computing.Support the show

So it's not just that these capabilities don't exist in-house to do this in-house, but also that the government has lost capacity often to assess whether what companies are saying to them makes sense. Hello and welcome to Tech Won't Save Us. I'm your host, Paris Marks, and this week my guest is Rosie Collington. Rosie is a PhD candidate at the Institute for Innovation and Public Purpose at University College London and the co-author of The Big Con, How the Consulting Industry Weakens Our Businesses, Infantilizes Our Governments, and Warpsps our economies with Mariana Mazzucato. And that is in the process of coming out in the US and the UK.

There are different dates in each jurisdiction, but it'll be out soon if it's not out in your country yet. I was really excited to talk to Rosie because she's done research on some topics that I find really interesting. In particular, I wanted to find out, you know, what the impact of tech has been on our governments over the past couple of decades, especially as we've had these narratives that anything that has to do with computers and technology has to be done by the private sector, right? This is something that Silicon Valley and the wider tech industry has been pushing for quite a while now. And this has obviously influenced the way that our governments approach technology, especially during a period of neoliberalism when there was this process of reducing the scope of

what government actually does and handing more of it over to the private sector. And so this has obviously had consequences, not just for the ability for governments to run themselves effectively and to respond to the needs of the public, but it has also affected public institutions, right? That we expect to deliver services to us, to serve us properly, in particular in the healthcare system, where there's a greater focus on using more tools developed by private tech companies instead of developing these digital technologies publicly to ensure that the technologies themselves, how they're developed,

the capabilities that are within them are reflective of the purpose that we want our public services to actually serve and deliver rather than the interests and the desires of the private companies that are developing these technologies and have very different incentives behind them. So in this conversation, we talk about some of Rosie's research on this particular topic. You know, we look at how this has played out in Denmark in particular, which has been a focus of her research, but also extend that to how it's affected the UK and other countries as we've seen these trends become more common as governments have been moving more and more in this direction of letting kind of technological competency leave the public sector and go over to the private sector and then have

to pay and rely on private companies to deliver these functions to our governments. In particular, we talk about whether, you know, this is of particular concern in countries that have more public services and public health care systems than in the United States. This is maybe just because I'm not an American, but I wonder sometimes if, you know, the concern over the movement of the tech industry into health care is as concerning from a U.S. perspective where the health healthcare system is dominated by private enterprise in a way that is not the same in Canada and a lot of European countries because of the public healthcare systems that exist. So we get to that in this conversation.

I think you're going to enjoy it. I found it really fascinating. And hopefully, you know, it gives you a different way of thinking about these issues because a lot of these things that we're talking about in this conversation are really happening behind the scenes right they're not things that we actually see but kind of you know in the background these things are slowly being privatized and that has consequences for all of us really and for the ability of our governments to deliver for us so if you like this conversation make sure to leave a five-star review on apple podcast or Spotify. You can also share the show on social media or with any friends or colleagues who you think would learn from it. And if you want to support the work that goes into making the show every week, you can join supporters like Kira Lees in Seattle, Renee in Zurich,

Switzerland, and Andrew from San Francisco by going to patreon.com slash techwontsaveus, where you can become a supporter. With that said, enjoy this week's conversation. Rosie, welcome to TechWon'tSaveUs. Hi, thank you so much for having me. I'm a huge fan of the show. I know your listeners are probably going to rinse you for bringing another super fan on. But I've really been listening since the first episode. I'm very grateful to be here. No way. Thank you so much. And of course, you know, we've been in contact for a while. I've been meaning to have you on the show for ages. And of course, you have a new book coming out. So I figured this is probably a good time to finally have a conversation with Rosie and hopefully people will go pick up your book as well. Yeah, that's great. Thank you. I'm looking forward to

it. Absolutely. And so here's where I want to start, right? When we think about data, we often associate it with tech companies, right? And what these massive digital tech companies have been up to in the past couple of decades. You know, they're collecting a ton of it, they're using it to power their algorithms, they're making the profits while we have to deal with all the downsides of their quote unquote innovation, right? But you explain that data is also essential to the state and for its ability to deliver for its citizens. And you know, that goes back long before the internet and modern tech companies. Can you break down a bit for us, you know, how the state has collected and used data to deliver services, just to kind of set that up for us? So public sector data has a really long history that we can date back to actually the development of states, the early process of state building and

nation building in Europe and in other countries. In terms of the public sector data that we see today, if we think about what governments do, you know, this isn't just a committee that is introducing laws. For example, governments today across OECD countries spend as a proportion of GDP anywhere between 35 to 50% of GDP. So it's responsible for not just making laws, but producing things like services, regulation, administration, all of these things produce a lot of data. So digital public assets, or what I've termed digital public assets or public sector data can be defined as all registries, databases, and information is collected, produced, or held by public

sector actors and that's available in digital format. The actors that are responsible for the production and use of these assets at present can include government departments, local authorities or other bodies such as the NHS in the UK. A lot of this data is numerical or textual, but it also could include visual audio recordings. So this is the kind of core public sector information that is then turned into data sets. But also lots of data is produced. I think we can also think about it in kind of hypothetical terms of data that could be collected and commercialized, but that isn't currently collected and commercialized. And this is often also of kind of huge interest to big tech firms, for example, in medtech and other fields.

I think you've explained that really well. And it's really fascinating, right? Because it's not how we tend to think about data right now, right? When we think about data, it's like what Facebook is collecting on us, what Google is collecting on us, not so much what the government is doing, though certainly sometimes people are concerned about that as well, and rightfully so in many cases, with how some of that data that the government can collect is used. But as you say, you know, you referred to this as digital public assets, right? These public data sets that have been

built up over many decades. I'm wondering how did, you know, the neoliberal turn and the more recent framing of anything having to do with digital technology, having to belong in the private sector, like, you know, only these private companies can do anything that relates to digital technology. You know, the governments can't be anywhere near that. How does that affect how we and our governments think about these data sets and the public data that has been collected? I think that's a really good question. And probably we need to look back or situate this within the kind of broader developments, as you've just alluded to, within the broader developments in political economy and in capitalism, and how they have also affected governance and outsourcing. So perhaps I can

begin by saying a little bit about why I became interested or how I became interested in this area. So before I came back to academia, before I went to do my master's, I was working for a few years in medical research policy. And in some of that work, I was looking at, for example, I was working with the British Heart Foundation, which doesn't have an equivalent in the US, but I was working with the British Heart Foundation. And that organization was developing cardiovascular AI policy that would then be used by the NHS and the government in medical research. In all of this work, it was really interesting to see how there was just this baseline assumption

that the actors that would be governing and processing and even responsible for collecting this data would be in the private sector. And everyone took that for granted. I think, you know, when you speak to people even within government today, most people are surprised to learn or many people are surprised to learn, or many people are surprised to learn, that actually for much of the 20th century, government IT infrastructure and its management were all serviced in houses, something Mar Hicks has written about as well. And so the question becomes, why do we assume that governments are not able to do this today, or this is the kind of inherent function of the private sector? So I saw this happening in my work. And then when I came back to academia, and I started studying political economy,

I kind of returned to this as a way of looking at developments in public private relationships, and the big assumptions that underpin them and how they emerged. And I kind of realised that this IT infrastructure, public sector digitalisationization epitomizes in many ways, not just the kind of neoliberal term, but actually what happened from the 1990s with the growth of what we might call the third way paradigms of governance, which, unlike the neoliberal paradigm that came before, actually did recognize the state as a potentially important actor in the creation of value, you know, even defined in social terms, whereas the neoliberal period or Thatcherite, Reaganite neoliberal period defined the state in terms of not being able to create value for society, not being innovative. The state as conceptualized in governments such as Clinton's government or the Tony Blair government was supposed to exist and had an important function as the arbiter or the shaper, the steerer of markets and of the economy.

So we had this expression that was popularized in a book written by two consultants, actually, and that came to underpin the Clinton administration's policies, which was the role of government is to steer but not row. And this phrase really captures what has happened in the subsequent decades of the kind of third way, not post neoliberal. There's huge debates about how we use this term, but third way governments, which assumed that government had an important role. But doing stuff itself was not the function of government. And actually, it didn't matter where capacity for delivering the ambitions of government came from, as long as had that capacity and was able to tick these boxes and achieve these goals, it didn't matter what the political economy of the actors that were doing that were. So this is the kind of, I guess, ideational, ideological underpinning of how the outsourcing of government IT infrastructure, and crucially, its management

emerged. When I first started looking at this, you know, I wasn't necessarily thinking about these bigger paradigms. I was really just thinking, why isn't government doing this stuff? This isn't to suggest either, and perhaps it's something we can talk about, that governments have always used government data, public sector data, or citizen data for benevolent purposes. Absolutely not. This is a field that has a very, very dark history and should serve as a warning for lots of different things

that perhaps we can talk about in more detail. But just the fact that it's not questioned, the fact that we assume that governments can't do this and that the private sector is the only actor that can do this, I think is quite interesting. Yeah, it's very interesting, right? Especially when, as you mentioned, you go back a couple decades and you see that IT infrastructure is still owned and maintained by governments. And it's quite normal for governments to be involved in procuring and managing the technologies that they rely on. And then all of a sudden, there's this shift where,

okay, the government shouldn't have any involvement in this, it should all be handled by the private sector. This is how we create kind of jobs and growth and all these sorts of terms that are very popular for politicians to throw around. When does that shift notably happen? Like, when do you start to see countries say, this infrastructure that we have, this IT infrastructure that we've controlled, for politicians to throw around. When does that shift notably happen? Like, when do you start to see countries say, this infrastructure that we have, this IT infrastructure that we've controlled, now we should be pushing that into the private sector. We should stop doing these things that we did in the past. When does that really start to happen? It varies in different countries, but I think the shift begins in around the 1960s. So, Ma Hicks, for example, has talked about this as also happening in relation

with the masculinisation of the labour force in IT, infrastructure management and servicing, in the UK. Other academics have written about how this shift also evolved with the increase in the use of management consultants in government departments. So that's something that we write about in the book that I've written that's going to be out. To the extent that we even saw, for example, in the United States in the 1950s, the US government introduced antitrust laws to prevent IBM from providing infrastructure and providing advice on the infrastructure of government IT and servicing IT because it considered that this was an issue for competition. It was only actually

in the 1990s that IBM was able to provide advice to governments again on its IT infrastructure. So it's really quite different in different countries. So the UK had some really big players that were also in the kind of government IT consulting space as well at this time, like ICL, for example. And they became really big because these antitrust measures didn't exist at this time. This was really a development that picked up pace from the 1960s. Though, you know, the private sector has also been involved in the development of government technology really since its inception, since governments began using and integrating and developing technology within bureaucracies. Absolutely. And there was a lot of public funding to ensure that they were able to do that, right? Through that history, it was a very important relationship that was there. In a paper that you wrote that you shared with me that kind of got me interested in wanting to speak with you, you talk about how in Denmark, which is one of the cases that you look at, you know, I believe they privatized their IT infrastructure in 1996.

That kind of began like a process where the incentives in the organizations or around the technology started to shift because that was moved privately. And then the influences that came with that over time, it wasn't an immediate change, but those things started to change. Do you want to talk to us a little bit about what happened in that case? Yeah, so Denmark's a really interesting case for a few different reasons. So I like looking at Denmark because it's widely viewed as a kind of good model of capitalism, a good form of social democratic capitalism. So if we look at what's going on in Denmark and we interrogate Denmark and the Danish government, actually, we can maybe think about because this is a kind of an extreme example of this nice, good form of capitalism. We can think about the flaws in, or we can see some

flaws very clearly in this model. So Denmark is a very interesting case also, because it has adopted e-government reforms and public sector digitalization strategies very early, relative to other countries. And today, it is always ranked very highly in the kind of public sector digitalization indexes, so like the DESI, which is the European one, for example. It was also one of the first countries to collect population level data on citizens within health systems. Famously, or maybe not famously, but within this kind of academic literature, it's been described as the epidemiologist's dream because it has population level registries in health data, you know, across the whole

six million person population. It is interesting also because its developments and the political economy of its public sector digitalization reflect broader trends and perhaps are kind of much more explicit in the Danish case as well. So as you mentioned, Denmark was relatively late actually in privatizing its public sector data storage and servicing company, which is called Datasyntheilen, and it did that in 1996. And then we see from the e-government reforms that were introduced in the 1990s and particularly in the public sector digitalization reforms that were between 2002

to 2019 the ambitions and goals of public sector digitalization began to evolve so where you know at first the government was framing this and these policy reports as being an issue of improving efficiency, improving transparency, making sure that citizens have better communication with the government, that government is better able to communicate with citizens. Increasingly, this became framed as a way of making Denmark a more friendly environment for businesses who want to do work there and decrease the administrative burdens of businesses, for example. And then after the financial crisis, within a broader export-led growth strategy that the government adopted, digitalization and the use

of public sector data as well within that was really framed and the policies around it were structured around boosting growth in the private sector and in the digital technology sector. So we really see through this history or through this lens of Danish public sector digitalization, transformations also in governance and thinking about the role of the public sector in the private sector, not just within digital technologies, although that's the focus of the paper, but also more widely, I think, in the economy. Yeah, it's absolutely fascinating, right? And I think that evolution that you talk about, I want to drill down on it a little bit further, because I think it's really

illustrative of how these things slowly evolve, right? As you say, in the beginning, the idea with the digitalization, you know, bringing in these new processes is around we are going to make this more efficient. We can better deliver services to you, the public, because we are adopting these new technologies. And then like post 2008, 2009, when the economy has been hit, but also in this moment where the tech industry is positioned as, you know, this is how we are going to grow the economy into the future. And all of us, various countries, Denmark being one of them, but countries around the world, we all need to find our way to develop our domestic tech economies to form, you know, to encourage companies to grow so that then they can export their tech products. And then that becomes part of the goal, even when it comes to public services, right? How can we use our public services in a way that is going to encourage this kind of growth, this kind of technological development, the growth of this tech capitalism?

Can you talk to us a little bit more about that and the ways that this transformation plays out, but also the impacts that come of having the shift in the mindset around how these technologies are going to be used and what the goals of using them actually are. So I think there are a few different dimensions to this, right? So I think on the one hand, we have this period that I was looking at in this paper from 2002 to 2019, also being the period, as you've just alluded to, when we saw the explosion of Silicon Valley as the heart or the core of not just kind of digital innovation, but technological innovation more widely. So we had this development happening at the same time that we saw this tendency across many governments that I've already discussed towards outsourcing core functions and infrastructure and the servicing, and that being framed not as a way of rolling back the state. As I mentioned before, I think it's quite important to differentiate between this view of the state versus the kind of previous anti-state rhetoric of Thatcher and Reagan, even though we know that the state did actually increase in terms of spending under their

governments. Yeah, like just to drill down on that point for a second, you're not saying that the government was coming out and saying, we're privatizing these services by bringing in these technologies. Rather, they're saying we're bringing in these technologies and that'll allow us to deliver these services better to you. Exactly. And I think that that's really important to recognize that difference. And sometimes I think this is, I guess, more of a reflection on how I probably once and how on the left, often we talk about public-private partnerships and privatization and outsourcing. There is an assumption that this is done in order to shrink the state, and there is an explicit agenda to do that.

I think it's more interesting, as I have suggested in this paper, to explore the ways in which these developments are happening, and then perhaps they are co-opted. Or perhaps they have this consequence and that's inadvertent or perhaps this happens because there is lobbying or because there is involvement of companies that are working in this area that are working with the state and perhaps they recognize that this is going to be good for them in the long run but within the state at a time that we recognize there is hollowed out capacity within it, for example, within IT management or within other parts of public services, perhaps this isn't kind of an agenda of the bureaucracy.

Perhaps privatisation isn't what the government wants. It's not what it's aiming at. And it's aiming at other things like improving citizen communication. doesn't mean we always have to take this in good faith. That's not what I'm suggesting. But it just means that we have to recognise the ambitions can be quite different, which makes the politics of this and thinking about how the different actors play into it across the public and private sector, how they influence us as well. So right, so we were talking about drilling down into this development, right, and how between 2002 and 2019, we saw this transformation of how public sector digital infrastructure and public sector data were wielded and became resources that the

public sector wielded for the growth of markets in health tech and digital technologies. So in Denmark throughout the 2000s, we still saw the rhetoric and the language of these policy documents, at least what was written, the aim of these documents very much reflected these broader third-way governance trends around making government work better for citizens, making states more efficient, making governments more transparent. That was a huge thing, right? And we have to remember, again, looking at this in a kind of good faith way, I think we'll talk about the open government data movement as well at some point, looking at this in a good faith way, at this time, there was a lot of distrust. I mean, there's always distrust around around governments but in the wake of governments heading off to wars lots of citizens were very frustrated

and angry about this there was a lot of distrust about what governments were doing and citizens wanted to scrutinize this and opening up government data was seen as a way of making governments more transparent and therefore accountable but then we saw in the wake of the financial crisis, which affected all governments, it affected all economies, we saw governments then looking at the resources that they had internally, which included public sector data in Denmark, for example, and I think in other countries as well, and the digital infrastructure as a resource that can be wielded and used by actors, including SMEs, but also larger companies to develop technologies that might reduce costs internally, that was one framing of them, but crucially in Denmark, that could also be used through these public-public

or triple helix partnerships, you know, between a university, a private sector actor like an SME, and public sector body like a hospital, for example, they could then use services to develop new technologies that could then be used in export strategies. Yeah, for me, it's very concerning to read how that history has played out and how these things have evolved in such a way as to, you know, in the beginning, OK, it's just about efficiency. But then later it becomes, OK, we're building companies on top of this public data. And now these companies are being kind of built into the health care system because the health care system is then buying their services back because it's become something that they have become dependent on. And then it creates lock-in so that the service, whether it's the healthcare system, as we're talking about now, or other public services that are using other kind of technologies developed by private companies,

now there's a lock-in. So it's much harder to get off of this service, regardless of what changes into the future. And then that creates restrictions, what this public service can actually do, because it's dependent on this tech product that's developed by a private company and the private company probably doesn't have, or we know doesn't have the same sorts of incentives and things like that actually driving it. interviews I was doing as part of this research on Denmark. And actually, the Danish government did recognize some of these consequences of lock-in. And I think, you know, normally when we talk about kind of platform capitalism and the kind of technological lock-in that happens in platform capitalism, we're thinking about, you know, how these different platforms then become embedded or how the state becomes embedded and enmeshed with these different systems that it then can't get out of or it's going to be very expensive to get out of. One thing that became very clear in this research was not just the technological lock-in, but also there's a kind of capacity lock-in that develops,

where in the process of outsourcing not just the infrastructure, but also the management and servicing of this infrastructure to private actors, governments lose the capabilities. They're no longer having teams internally that are able to do this, let alone even manage the contracts, right. So often, they lose control of contracts, or governments can lose control of contracts, because they don't have the capabilities or the people working within them, who are actually able to know what's going on. Another great case of this actually in Denmark that came out, I'm not sure I wrote about it in this paper, but the capital region government, so Copenhagen, the kind of local government for Copenhagen, developed a partnership with IBM or entered a partnership with IBM Watson. That was one of the

most expensive healthcare technology partnerships that has ever existed in Denmark. And it was a five-year partnership to develop healthcare AI technologies that could be used in the health service. And that sounds like really broad because it was a really broad contract. And within a few years, it became clear that it wasn't going anywhere. Some of the people who'd been involved

in this contract early on, they were saying to the press, there was really something of the emperor's new clothes about this. We didn't know, we couldn't assess, we couldn't evaluate what IBM was saying to us. So it's not just that these capabilities don't exist in-house to do this in-house, but also that the government has lost capacity often to assess whether what companies are saying to them makes sense, or if it has any potential. And this whole partnership, even though it was really expensive, ended up folding after just a few years.

Back in the moment when there was all that hype around Watson and what it was going to deliver. But what you identify there is so important, right? Especially, you know, if we think about the types of technologies that these public services, public sector institutions are contracting to bring into their institutions and whether they're able to assess whether that is actually going to serve the needs that they have. lose that capability, that knowledge in-house, then it also becomes more difficult to regulate these technologies and to think about those questions, which are obviously things that we're still grappling with right now. And, you know, I think it's fair to say it's been proven that governments in many cases have lost these capabilities, have lost this kind of institutional knowledge, and that has left them less prepared to look at what is coming out of Silicon Valley or, you know, other tech companies around the world and be able to properly assess the potential impacts of those things,

rather than just the statements that they're making to the media and putting out through their press releases and things to actually be able to identify the harms or potential harms early on and take measures to try to rectify those things before they actually happen. Absolutely. And this isn't, I guess, an issue just for public procurement or government technological infrastructure, government IT and digital infrastructure, right? This is also a problem for how governments understand markets, how governments understand these sectors and the technological developments more widely and what they mean for society. Often governments, you know, and I'm talking in very broad terms here, but I can also give some cases of often governments openly, you know, after a kind of crisis of a technology will admit we didn't know this was going to happen, or we had no expectation that this was going to happen. And so this is also

just about the loss of government capabilities, more generally generally and what that means for how much power then this sector how much the technology sector and other sectors have within our societies absolutely and whether government is actually able to deliver the things that we expect from them right yeah as i think many governments have shown they haven't been able to do exactly so there's this you know there's kind of a liberal democratic argument around this, right, which is that if governments change, if governments mandates change, and so governments need to be able to adapt the kind of tools at their disposal in order to be able to achieve the mandate that they have that kind of policy goals that they're elected on behalf of or that they're elected to do,

if the capabilities don't exist within them, then it's very difficult to reconfigure that machine in order to kind of meet these goals. That's the kind of liberal democratic view of, you know, what is the problem with the loss of capacity, the hollowing out of governments, right? But there's also, you know, from a kind of left politics perspective, if we want governments to do things that are going to be very different to what governments are currently doing, or to have an expanded role, perhaps, or to have infrastructure that increased democratic involvement in the way that decisions are made and the way things are done in society, then there needs to be some kind of capability some kind of capacity that exists that can be reconfigured otherwise it's not going to be possible for left governments to achieve anything

and we see that actually happening in countries you know in South America for example where left wing governments are coming in and they're elected and they enter and actually they find that the government is pretty empty and there isn't a lot that they can do or it's very difficult or very expensive for them to do the things that they can do or it's very difficult or very expensive for them to do the things that they are elected to do. So this becomes then an issue for politics, this kind of hollowing out of capability and capacity that, you know, is not just an issue for digital technology and digital infrastructure, but also more widely in governments. Yeah, no, a fantastic point. It goes way beyond that and has much larger implications. If we

want to demand our governments do larger things, actually address real problems, you know, maybe that's part of the reason why, you know, I'm sure in many countries, but in Canada, as I see it, that they're struggling so much to address the healthcare crises that we're seeing, right? Because they've just been left unable to really deal with many of these problems. I want to circle back to something that you mentioned in one of those previous answers, which is the open data, right? We'll probably remember, I think, especially American listeners will remember, you know, during the Obama administration, when there was a lot of kind of pushing this notion of open data, right? We should be providing more government data,

putting it online, anyone can access it and do what they want with it. And the idea is that this kind of equalizes the playing field that makes government more transparent. Anyone can go and make their little tool or whatever that can use the data to make it easier to illustrate things about government to the public or whatever. But then, of course, large organizations, large corporations can have the resources to do much more with that data than potentially, you know, the average individual who has just taken a look at it. So I guess in hindsight, how should we look at that movement for open data based on the research that you've been doing? I really liked actually a term that Timnit Gebru used in your interview with her, this idea of aspirational language in tech. And I think open government data or open data more generally is a really nice example of how this, because it sounds great, open data, you know, that's something for everyone. It's transparent. Everyone can use it. It's a tool that we can all use and think about all of these things we can do with this universal resource, right? It sounds great. So there's a few issues with some of those assumptions. So one is that

even with kind of nice open government data, you know, I use open government data in my research, I'm studying the government and government spending and contracts. So I use this data, right? It's still not something that everyone's going to be able to use. You know, often it needs wrangling, it needs a lot of cleaning, you need to know how to program to use big sets, because you won't be able to open them with, you know, Excel or something like that. So that's one issue. This isn't something that, you know, everyone's going to be able to use, you need to have training to use this data. So that in itself, is a challenge to the kind of whole idea of open government data. The other issue with it is that, again, like a

lot of developments in tech that we've seen over the past 20 years, the goals and aspirations of this movement were really important. And we should continue to fight for, you know, freedom, democracy, transparency of all of these tools, right? Good faith visions of the movements that have come before us, I think is really, is really important. But like a lot of visions, a lot of these aspirational visions in tech, and the kind of good people who have pushed them forward, there has been an absence of an understanding of the political economy within which they are being developed, right? So often public sector data has been used towards, and I'm not just talking about the data

that I was discussing earlier that might be collected, for example, when a new technology is being developed and introduced with a health system, data that is already collected or has already been collected and is stored and processed internally. So for example, transport data or meteorological data or health system spending data, this sort of thing. Often, this is only kind of a very small amount of data that companies like Uber would have access to, but it can be very, very important for them. And governments have not recognised when it is important and then use that as leverage, for example, that could be used to help shape these companies or help, for example, introduce labour agreements that would be in line with existing labour agreements in the sector.

So actually, to use the example of Uber, Transport for London, which is a public sector body in the UK that manages transport in London, believe it or not, has published this real-time open data through this API for about 15 years. In 2019, it was estimated that this data has been used to develop over 675 mobile phone and online apps, mostly within the private sector. Before its IPO in 2019, which valued the company at, I think it was $80 billion, something like that, Uber integrated TFL data into its app, and it promised investors that it would did not see improvement in their paying conditions after this data that had been you know developed by the public sector and used in this way had been introduced so perhaps you know one thing that could have been done with this huge kind of

data that uber was able to get access to could have been to use it as a way to say we want to ensure that the drivers are able to increase their income or something like this, or perhaps a decision might have been made that the data was not given to Uber, but was perhaps given to another company entirely that had different principles and that were maybe more in line with what, you know, most people would have wanted and would expect from a company that is that big. There are clear uses of open government data where there is no way that you can argue that they have been used in the public interest. And I think that the failure to recognize that is, again, just a bigger problem that we have within these aspirational tech narratives. I really like

that idea that just failed to account for the political economy of these developments. Who owns them? Who's getting the money? Who controls the infrastructure? Whose data is it? These big questions are just so often ignored. And that's been quite clearly the case in the case of government data. Yeah, it's a real flaw with a lot of the discourse around technology that

the political economy of it has not received enough attention. And, you know, that goes that goes back a long way. Right. And that shapes a lot of the narratives that we've seen around technology for a long time. These more libertarian framings, you know, these framings around speech and things like that. You know, I think what you say is important because if we think about the example of Uber and, you know, I'm sure its valuation is worth a lot less now than when it IPO'd. But like, you know, it was taking advantage of this public data that was available both from TFL, but I'm sure from, you know, many other public organizations, you know, in the United States and in other parts of the world, but then was often not sharing its own data back or trying to fight when regulators or local governments were trying to get a hold or get a look at its data. So it could kind of integrate that with its own

data and get a good idea of what Uber was doing in cities and in transport systems, right? And so you see that kind of, you know, lack of reciprocality, I guess, there, where, okay, it's benefiting from the public sector and everything that the public sector is doing, and usually not having to pay for those sorts of things. But then it's kind of using that in a way that benefits its business rather than having to ensure that the way it uses it is beneficial to the public as well. And that's a real problem. One piece that really stood out to me as I was reading these two papers that you put together was that you also talked about, I believe in the first paper we were talking about, about Denmark, that, you know, one of the risks here as well is that when we allow these companies to use, you know, public sector data to create their products,

there's also a risk that they are going to create a product that then helps to kind of undermine the welfare state or, you know, the public service altogether, and actually sets them up to compete with what is being delivered publicly, where, you know, it's going to be beneficial for that company, certainly, but that's not necessarily the case that, you know, it's going to benefit the public by having this private company start to edge out or push out, you know, the public service. Yeah, so a really interesting example that i came across in my research was of i think i mentioned there had been a triple helix partnership between so this isn't very common in lots of other countries but triple helix partnership is a partnership between a university department

or a university team an sme that could be spun out from the university team often. And that's a small and medium enterprise in SME. Yes, yeah. And then a public sector body. So health technology is probably the most kind of accessible to talk about. So in the case of this startup, the technology had been developed by a university computer science research group that then developed a partnership with the hospital and it was a cardiovascular disease monitoring data collecting technology essentially right the kind of long-term

goal and the way that this university group got funding was where the state comes in and state financing comes in the way that they got kind of research council funding for this technology was on the promise that it would then commercialize the technology. And it would then be able to export this as part of the government's broader export led growth strategy. The technology was developed in collaboration with one of the hospitals in Copenhagen. And I think I mentioned it was a cardiovascular disease monitoring technology. So it was essentially just collecting a lot of data. Historically, this had been a task that had been done by nurses.

And interestingly, the nurses who were working in this position and with this new technology were vehemently against the introduction of this new technology. They didn't trust it, and they didn't think it was accurate. And so these are hugely expert people who have been doing this job for a long time. They didn't think that it was in the interest of patients to be using this technology. But effectively, they probably, this didn't come up in my interviews with the founder of the SME that had spun out from the university project probably they also recognized that this was something that the goal was for it to replace them in this task collecting this data the kind of bigger picture also was that the technology had started out as something quite simple so it was initially just set up to collect the technology as part of this kind of broader monitoring of patients.

But the goal with this data that was then collected would then also be commercialized by this company in the development of its artificial intelligence technology that would then be exported for use in hospitals around Europe. So this is not just the replacement of an existing function or existing task that's happening within the welfare state by what becomes a private actor. Even though it was developed using public funding, using public universities, at the time that it was being used in the hospital, it was being provided by an SME. So it's not just that the task is then replaced by a private sector actor, but also the collection of the data, the processing of the data, what happens to that data shifts from being the responsibility of the public sector to becoming

something that that private sector actor is responsible for. So the ability to then use that data to develop a technology in-house or for it to be used in kind of meaningful evaluations internally and learning or the development of capabilities internally is also lost as that process, the process of doing something is outsourced. It's so concerning to hear you describe that, right? Because it's exactly what we wouldn't want to happen. And I feel like some of these conversations are a bit more difficult to understand from an American perspective, right? Where the healthcare system is private, this is what they're used to. So if you have a private hospital and they're using more private technologies, I guess it's harder to understand the distinction and what's going on there. Maybe it's not as big of a worry.

But when we're thinking about, say, Europe and Canada and Australia, where you have these technologies that are developed by the private sector moving into the public sector health system and kind of taking away some of the power of that system, taking away some of the things that it used to do, what I describe it as is kind of like a sly privatization, right? You don't see it when you go and approach the health service, when you go and see your doctor or get a surgery or whatever, but this is happening in the background. And it's still having impacts on the type of service that you can expect on what the health service can deliver to you. And it potentially has implications, or as you're describing, it does have implications down the line. And one thing I would add to this that maybe you can comment on as well is that during the pandemic, we had a lot of tech companies trying to compete for public sector contracts around COVID and COVID tracking and all these sorts of things. And one of the big things that emerged from that moment, if I remember correctly,

is Palantir getting a contract with the NHS, which is the public health service in the UK, so that then they get access to a lot of that kind of NHS data. And as I understand it, the NHS data is seen as like kind of world class, really valuable, like private companies really want to get this data, really want to have access to it. And now a company like Palantir is getting access to that data. What does that suggest to you? Because that seems concerning to me. I think there are two possible responses or two things that I can say about this that might be relevant. So the first is that, as we saw during the pandemic, often when these companies are brought in to do these things, and this is where this kind of thing about them being the emperor's new clothes comes back, right? They actually aren't able to do the things that they're

promising that they're able to do. They often aren't able to do the things in a way that governments expect them to, and often they can end up spending a lot more money. So a really nice example of this would be actually in the case of the US and the development of healthcare.gov, which was the market exchange platform that was introduced as part of the Affordable Care Act. Now, on the day of its launch, I think this was 2013, right? So on the day of its launch, only six people were able to access the platform, which is terrible. You know, that's a terrible result for any project that on the day that it's kicking off, no one's actually able to use it. And it was, it was hailed by, you know, media and Republicans as this colossal failure. And this was supposed to be

the landmark reform of the Obama administration, it completely failed. Now, there's been lots of kind of scrutiny of what government did wrong in the development of healthcare.org, you know, about how there was miscommunication between departments, about how some of the managers weren't open minded, you know, these kind of really micro level things. that this was also a program, this was also a technology, a public sector technology that had a development that had been outsourced at huge scale and scope by companies that had never developed a platform like this before, that were subcontracting after subcontracting after subcontracting different parts of the contracts. And so the government lost a lot of control over the process, even if it had the capabilities, which, you know, that's not really what I'm interested in at this point, even if

the government did have those capabilities, which it probably didn't, because it's also outsourced a lot, even if it had the capabilities to manage that process properly, it had no oversight over what was happening through the kind of huge supply chains that had been developed. And some of the big contracts to CGI Group, for example, were handed out on a cost plus fixed fee basis, which meant that I think the overrun cost was $24 million in the end. So this basically meant that if CGI Group made a mistake, or if there were problems, or if something was more expensive, rather than the risk of that and the responsibility for footing the bill for that falling to them, it fell to the government. They were just able to kind of build

the government afterwards. So the one issue that often these companies aren't able to deliver on the promises that they promise, and as we've discussed a bit already, often the government is not able to assess those promises because after decades of outsourcing and the kind of infantilizing of governments, as we describe it in this book that I've written, they just don't have the capacity or the confidence sometimes to kind of make these decisions challenging these companies. That's one issue. The other issue, which is related to this second point as well, is that when governments do this over over a long period of time, so for example, in the pandemic contracts, they completely lose the ability to do this themselves. So on the one hand, you think, why didn't governments just use the money, the kind of huge contracts that they handed out for test and trace programs? Why wasn't that spent internally? You know, there's an obvious reason for that, which is that actually governments often don't have these teams to do these things but the companies

that they went to like Deloitte in the UK for example also didn't have those capabilities and they just assessed it weren't able to assess that they weren't able to do this so you know this isn't necessarily a case of governments doing everything either that That's also not what we argue in the book by any stretch of the imagination. There's lots of things that governments shouldn't do and also can't do at the moment. But in the case where they need to work with other actors, they need the capabilities to assess those actors. There needs to be a good understanding, a thorough understanding of the interests and incentives of those actors, and how that might shape how they work with governments. And that would enable governments

to work with them in a way that, you know, might actually be in a public interest, or at least the government's interest. Yeah. And just to add to your example, like even Palantir, right, it got its reputation for scanning all of this, like military data and saying that it could like identify terrorists and all this stuff. And there were stories that suggested that it was involved in finding Osama bin Laden, which was never true, but they, you know, made sure they didn't actually say it wasn't true

and said like, you know, people have said that we were maybe involved with this. And that helped to like build up the reputation of their like data analysis capabilities to get a lot of not just militaries around the world, but private companies and now increasingly healthcare systems to be working with them to seek out their services to build it into like a massive juggernaut. Palantir is associated with Peter Thiel. One other example I'll throw out to you that maybe backs up your point as well, right? And this is just pulling from my own experience to give an example of something that I'm concerned about, especially when it comes to technology going into healthcare and the things that we're talking about, right? One thing that of course we saw during the pandemic was a push for more kind of virtual healthcare, right? Getting doctors appointments online and those sorts of things. And of course, you know, that has been popular in Canada as well as many other countries. And one thing that we've seen is that many of those kind of virtual doctor's appointments, especially when they're not like with your family doctor and you're just kind of accessing a service that allows you to speak to a doctor. Those are private. Right. Those are not within the public system. And one thing that has come out in my province in particular is that they're actually paying more for these private virtual doctor's visits than they would pay to like your GP, your family doctor, if you just went to see them in the public system. But like one way for me that these technologies enable kind of a further creeping of privatization

in the system that you might not necessarily notice. And that in some cases allow you to pay for one of these services to get a quicker appointment with the doctors and things like that. So these kind of second tier of services you're able to pay, you can get better service kind of creeps in there. And, you know, I think it's a concern and I think it is an example of how, you know, technology and how we associate technology as being something that is just in the private sector that is not done by the public sector leads to services being privatized in a way that maybe we wouldn't want, but is actually what ends up happening. Completely. I think you've hit

the nail on the head with two things there. The first thing, which is probably actually the most important problem to identify is the cost of these things, both the upfront costs, and this is where it relates to broader trends and outsourcing. Outsourcing has been hugely expensive. Sometimes the initial contract will be very cheap for different outsourcing functions, including technologies, and companies are allowed to, they're permitted to lowball in ways that can be completely egregious. Sometimes, you know, like KPMG famously bid on a 1 million pound contract in the UK, I think it was in 2013 for one pound, you know, this is allowed, right? So that's one of the issues, but the kind of long term cost, even though that initial contract

was very cheap because that gets in the door and then that hollows out the kind of internal capacity the long-term cost of using this kind of mode of governance this mode of doing things this mode of production becomes very expensive over time then with the loss of that capacity and the absence of even the choice of doing something in-house that then increases the leverage that the private actor will have because it knows that it's then the only actor in town that's able to do this so yeah things that this can get really expensive in the case of what you've described you know sometimes you look at these contracts and you think why on earth has this happened on the face of it you know even on paper it's way more expensive than doing this, how it's

currently done. That's where we have to look then not just at the kind of the how these cost benefit analyses might feed into decisions, but also when narratives about the innovative potential of private firms and video based consulting in medicine, for example, and the failures of the public sector where all of these kind of narratives come together and shape decisions also within government and within public sector organisations, within local government, how these all feed into the decision to instead turn to the private sector rather than continuing with a public sector option. The second point that you raised around creeping privatisation, you know, I completely agree. This is something that I talked about in the paper. I looked at this through the

lens of Paul Pearson's concept of systemic retrenchment, right? So Paul Pearson was writing on changes in the welfare state systems and different types of welfare state models. And he was really interested in why Thatcher and Reagan were not actually able to kind of fulfill their ambition of completely rolling back the state through what he terms programmatic retrenchment. So that's the kind of direct cuts. And he looked at, you know, the importance of political constituencies and how they then create feedback loops for different types of support for different policies and different welfare programs. So he suggested that systemic retrenchment is often more critical for how privatization actually happens, how the transfer of resources away from the public sector to the private sector

actually develops most critically is not through these kind of direct cuts to public services, but often through these invisible measures that are obfuscated both very kind of consciously by politicians. So for example, increasing the retirement age is an example of a systemic retrenchment, because it decreases the cost of pensions to the government over time. But it's not something that most people are going to think about for a long time. So it's an example of that. And digitalization is another one, that's what I argue, because it happens quite slowly. These lock-in effects often happen quite slowly. And I think towards the end of the paper, I talked about then how this industry, this kind of sector of digital technology also and government digital technology must also be recognized as kind of a powerful actor in shaping this obfuscation of the effects of its use at scale and scope within the government.

You know, there is money invested also in there. There are resources. There are lots of people employed to help promote the idea that the private sector is the best provider of government digital infrastructure and services. This is not kind of something that develops out of thin air. There is an industry also promoting this idea, right? So this also then figures into how systemic retrenchment happens, how this kind of creeping privatization, as you put it nicely, occurs. You know, I think you've explained it perfectly. And I think it also leads really well into the final question that I had for you. You talk a lot about how this process is depoliticized. And I

think that that is a really key kind of piece of allowing it to happen and allowing us to not really know that it's happening and not really kind of get angry that it's happening because it's something that's easy to kind of hide away and we don't see. And you talk about how, you know, it's depoliticized. But even though that is the case, you know, it's an explicit strategy by particular people to promote the private sector as the solution and technology in particular as a magical fix to all these problems, when really that's not like

something that is just inherent, that is just the way that things are, but is rather a very political view of how these things can work. And they could work in a very different way if, you know, we had a different set of politics guiding these things, and we were more aware of what was happening and able to push back on them. So I think this feeds into, again, as someone who very much studies production, I'm wary of speaking too much about ideas. But these ideas are also, you know, we have to recognize this are really important to how we understand the role of government in society. So these narratives, not just about technology and about innovation

and where that happens, but also what the function of government is, and the notion that government is, and government administration, because a lot of these technologies are not being used in frontline services, but public sector digitalization, you know, also applies to what's happening, I guess, behind the doors of ministries and government departments. And these kind of places that most people don't think about, and when they do think about them, they either think of them being kind of stuffy, grey, boring, bureaucratic, Kafkaesque, mazes.

You know, we have these images in our head, or lots of people do, where workers within them are described as kind of lazy and not doing a lot. In fact, in the UK, this kind of picture of the home working, shirking public sector worker has become quite prominent in recent weeks and months, as the government has been announcing kind of fresh cuts to public sector pay and other areas. So we either have that or we have this kind of neoliberal vision of the bureaucrat as being

kind of very selfish and only in it for their own interests. And therefore, it's in everyone's interest to make sure that the private sector is involved as much as possible. So these kind of dual narratives, which are kind of competing in the minds of most people mean that when we think about public sector digitalisationization we aren't thinking about the politics because we don't think of this as being a realm of politics we either think of it as being kind of stuffy gray neutral boring place that is apolitical or we think of it as being this kind of yeah self-interested realm that should not have control over anything and therefore bring the private sector and both

of these are very kind of deep apolitical spaces so it's no real surprise that there isn't more discussion about public sector digitalization or public sector infrastructure and outsourcing more widely beyond you know headlines about fuck-ups by individual companies which are really important but i I think it's important to dig a bit deeper, you know, and this is actually how then my research has become not just looking at it, and public sector digitalization, and who owns data and who owns these infrastructure, which is what I was initially interested in. But the bigger paradigm within which this has emerged in government and the political economy.

And I realized quite surprisingly that even though there has been great research looking at outsourcing and some research looking at privatization of public sector infrastructure, often these aren't placed within these bigger lenses and what they mean for who owns the economy and who benefits from the economy and what the kind of long-term implications are for government capacity, you know, looking beyond the kind of programmatic retrenchment, the direct cuts to how this stuff evolves, even when individuals, even when individual bureaucrats, even when individual politicians have great ambitions and good ambitions, and they often do, you know, I like to look at things with good faith a lot of the time. I'm not saying we always should, particularly with UK government, for example,

absolutely not. But there are people also within these organisations that do have good ambitions and are benevolent and do want to kind of use these things for good, but are often constrained in doing so for the reasons we've been discussing. Absolutely. No, I think it's a really important discussion and it will really be important to us as we think about what our government should do in the future, what our healthcare system should look like in the future, how public services are delivered and to ensure that they can actually serve the public. Rosie, I really appreciate you taking the time to chat with me about this. I wish you the best with the book as it comes out. Thanks so much. Thank you very much. Rosie Collington is a PhD candidate and the co-author of The Big Con, How the Consulting

Industry Weakens Our Businesses, Infantilizes Our Governments, and Warps Our Economies. You can find out more about the book through the link in the show notes. You can also follow Rosie on Twitter at Rosie Collington. There's just no N through the link in the show notes. You can also follow Rosie on Twitter at Rosie Calling Toe. There's just no N on the end of her Twitter username. You can also follow me at Paris Marks, and you can follow the show at Tech Won't Save Us. Tech Won't Save Us is produced by Eric Wickham and is part of the Harbinger Media Network. And if you want to support the work that goes into making it every week, you can go to

patreon.com slash tech won't save us and become a supporter. Thanks for listening. Thank you.