What are your initial thoughts on the theme we’re discussing today – what does a social contract mean in the age of data?

I have grouped my response to the topic into three ways of thinking about the social contract and how digital technologies might shape them. Before I delve into these, I’d like to make a quick, overarching point: When I talk about digitization and digital technologies, I like to talk about what tech firms are doing rather than what the technologies themselves are doing. This is because there’s a strategy here, there’s a kind of business model shaping how technologies are being used. It’s not the blind technologically-driven process evoked by a lot of the discourse on ‘what the digital is doing’. Instead, tech firms are driving the direction of these processes.

Now, onto the three ways: first of all, through democracy and public discourse. Holding politicians to account, having critical scrutiny over what politicians are doing between elections, and voting them out. This is the first intersection between the social contract and digital technology. The second has to do with productive power: the extent to which the productivity in the economy is within the bodies and minds of the population and not just in the resources or infrastructures owned by companies. And then, finally, looking at taxation. The ways in which taxation allows for risk pooling and the building of solidarity – solidarity across genders, classes, ages and races. And it’s this idea that the society and economy are stronger when we don’t just have individual solutions to things. These are the key areas I’m going to try and touch on.

Since you begin with the issue of public discourse, why don’t you tell us the principle issues that you see here? And how can they help us think about the relationship between the digital economy and our social contract?

I think when it comes to public discussions around the ways in which technology companies are shaping the social contract, there is a lot of focus on the topic of democracy and public discourse already. For instance, we’ve all seen debates about how some social media platforms, in particular, have distorted democratic debates and public discussions, are influencing elections, and so forth. It’s all true – they indeed have a lot of power to shape the way in which we talk and think about social challenges and politics, and this extends to things that are more pervasive and fundamental than elections. Take for example, the ways in which these tech firms frame the issue of feminism itself.

Great care is taken to shape the dominant discourse in a way that is not going to undermine or challenge the business interests of these platforms. So, fighting to reclaim this space is absolutely crucial.

A clear, and perhaps cheeky, example is Facebook’s COO Sheryl Sandberg’s idea of ‘leaning in’ — which many feminists have critiqued for being white, middle-class, American feminism — juxtaposed with how some of these platforms actually shape working class women’s labor. Here, I’d recommend an interesting book by Alex Wood called Despotism on Demand, where he talks about how supermarkets in the UK and the US are trying to use technologies to create labor on demand, figure out the optimal amount of labor they need at any time, and impose schedules on workers. Obviously, if you have childcare responsibilities and family responsibilities, that kind of flexibility is not going to be easy to organize your life around. What these companies are trying to enable is obviously going to have a huge effect on people, particularly women, who have such responsibilities. But these issues don’t get featured in the mainstream discussion around feminism. This is because great care is taken to shape the dominant discourse in a way that is not going to undermine or challenge the business interests of these platforms. So, fighting to reclaim this space is absolutely crucial.

So, when it comes to shaping the public discourse around technology, what do you think are the key issues to take on in order to challenge the hegemony of Big Tech in framing the social contract?

Tech firms are well resourced and extremely savvy. They have the financial clout to hire the brightest people around and they are busy lobbying (in both overt and covert ways) to frame peoples’ understandings of the world.

Moreover, by virtue of their business models, they are amassing quantitative data about the economy. With Uber, we have already seen how they use access to this data to strategically shape how academic economists understand and frame their impact. As quantitative analysis retains its dominance within the public sphere, I expect tech firms to use this control of data and modeling to assert their own interests and narratives in the years to come. We have to be wary of this.

We should also be highly sensitive to their representational politics and the way they choose to frame understandings of gender and race. As I argued before, they do so in ways that leave out discussions of class and inequality. If it was up to them, feminism would be some combination of Facebook COO Sheryl Sandberg’s Lean In and former Uber executive Meena Harris’ ‘phenomenal women’ t-shirts. Personally I prefer my feminism more critical and intersectional, but maybe that’s just me!

They [tech firms] are firing on all cylinders. So must we!

I do think that there is a rising tide of skepticism building around tech firms, which is useful. There is also very interesting work being done within heterodox economics, political economy, sociology, and law shining a critical light on their business models and public narratives, but perhaps more needs to be done to get this good work into the public consciousness. We should also be aware of the rising power of tech firms within the world of political campaigning, lobbying within trade negotiations, research funding, and media/content production. They are firing on all cylinders. So must we!

You give the example of how control over data allows these firms to also influence larger social narratives, can you expand on this a little?

Yes, this is part of a broader trend wherein research is becoming increasingly privatized and commercialized. As these tech firms embed themselves both into market infrastructures and public services, they are the ones that are able to tell us what is going on. So then, they decide whether to grant researchers access to data. In some cases, they do give access, but often, through a kind of partnership with CEOs where they control the flow of information. This will clearly significantly affect what we even know about their impact on the world, particularly if they are the only ones that have access to the knowledge of what they’re doing.

If commercial interests are shaping what we measure and what we choose to be interested in, we’re going to have a very distorted vision of sustainability or ideas of the good life.

Moreover, there’s a sense that what is being measured is itself driven purely by commercial interests. So, for example, in my current research with my colleagues Gianluca Iazzolino and Marion Ouma, we’re looking at agriculture and digitization in the US and Kenya. The research shows that there is a lot of interest in digitizing and quantifying environmental impacts, particularly carbon capture, but not looking at how these things are shaping, for example, local markets, local tax bases, race and work or – in the case of California – gender impacts. There are lots of things that we could be measuring with the data being produced but if commercial interests are shaping what we measure and what we choose to be interested in, we’re going to have a very distorted vision of sustainability or ideas of the good life.

Of course, it’s not just the narrative. The way data is employed has a strong bearing on issues of access and equity, especially when we look at algorithmic biases. These models end up having to formulate and reflect what a normal user might be, and this can create an exclusionary bias that can become self-fulfilling. For example, think about credit worthiness. If the ideal person that an algorithm is trained to give loans to is a white, middle-class man in a kind of low-risk environment, and you don’t give credit to other people because they deviate from this standard, this reinforces a number of entrenched inequalities over time. So, governments need to have access to algorithms and data for oversight to make sure that such discriminatory practices do not occur.

The second area that you wanted to touch upon was the idea that ‘productive power’ could be used as a focal point to think about digital technology and the social contract. What do you mean by this?

So, the key issue here is the extent to which the productive locus of the economy is in the bodies and minds of populations. I think something is sometimes missed when we think about the origins of the welfare states. We think of their emergence as a triumph of democracy, but we don’t think about the fact that a lot of what constitutes the welfare state model was introduced in order to increase the productivity of the workforce, to make sure that workers were healthy and well educated, that women and men have access to child care so they can be productive in the economy.

What is occurring now, which is very pertinent to a discussion about the social contract, is the way in which some of these tech firms are trying to decrease the need for skills and knowledge among workers – a process which may be an attempt to shift the skill base away from workers and onto platforms. And I think that this is something we’re missing when we talk about democracy – what happens when people are no longer valuable to managers in the same way as before? When you don’t really need people to be skilled or healthy, you don’t really need women to have access to child care? How strong is our democracy going to be if workers don’t have that productive power? And the power to hold back and withdraw their skills and labor?

Another aspect that is tied to this – something that my colleagues Sohini Kar and Kate Meagher have talked about – is tech firms often rely on invisible labor in order to scale up, and that is often the labor of women. For example, Sohini looks at financialization in India. We think of financialization and digitization as these very quantified, impersonal technologies that are just being rolled out. But Sohini’s work, and Kate’s work, shows how people are in the midst of rolling these systems out and people are the ones enforcing compliance and this is often very low-paid, precarious, risky, and socially-challenging work, when it comes to something like getting back loans from borrowers. A lot of this labor is not valued and is not seen as something that needs to be compensated adequately. I think, particularly in the context of the Covid-19 pandemic, a lot of these platforms require the invisible labor of essential workers in order to function and, at the moment, their labor isn’t being economically valued in a particularly strong way.

You make an interesting point about an attempted de-skilling of the workforce, in order to move productive capacity out of the bodies of workers and into platforms themselves. Can you expand on this idea with some examples?

Sure, a very easy example is the taxi industry. In the pre-Uber/Lyft age, taxi drivers needed to know the city in order to understand its geography, traffic, and market demand. Now, any driver is as good as any other because the platform tells them where to go and what to charge.

We see technology companies trying to restructure labor and skill in other sectors as well, including health and education. They seek to replace well-trained (and relatively well-remunerated) teachers, doctors, and nurses with new systems of centralized technical expertise and less skilled workers who act as a kind of human interface between the user and the platform.

I don’t think these changes will happen overnight and there will be a lot of hidden challenges that will thwart ambitions along the way. But I do think the pandemic and the big push towards online work will help drive these restructuring processes, slowly reducing the need for skilled workers and making us all ‘more flexible’ and replaceable in the process.

The history of Western (imperial) democracy is as much about labor power and market dynamics, as it is about voting and political parties! If we automate the need for human skills, I am not sure what kind of a democracy we can expect in our post-capitalist utopia.

Tech bros would have us believe the answer to this automation and restructuring is basic income grants and dividends, but it is not at all clear to me that citizens will really be able to retain their political power if they lose the ability to disrupt production processes. As scholars like Charles Lindblom and Timothy Mitchell remind us, the history of Western (imperial) democracy is as much about labor power and market dynamics, as it is about voting and political parties! If we automate the need for human skills, I am not sure what kind of a democracy we can expect in our post-capitalist utopia.

What can be done to counter and oppose such a process of de-skilling? Are there examples of resistance to this? What kind of alliances would be needed to effectively challenge it?

I think there are some things that workers and citizens within high income countries can do to refocus their governments on human well-being, as opposed to profit and efficiency. These societies have built up strong public finances and relatively well-functioning democracies. They also represent the most lucrative consumer markets in the world.

However, the challenge facing other societies is much more difficult. These countries are largely dependent on the global economy for investment, technology, and market access. It was hard enough for countries to economically develop within this very competitive global economy even before the age of hyper-efficient platforms and global production networks. If you exclude China and India from the analysis of global inequality and divergence, the world is getting more and more unequal.

However, I can offer some very humble practical suggestions. My late colleague Thandika Mkandawire made a really important observation that the digitization hype has so far focused too much on the issue of transaction costs, and has distracted us from the question of production costs. If you only focus on removing market barriers (through investments in roads and internet connectivity) but do not invest in production capacities (electricity, water, waste, etc.), then you are effectively going to make your economy super-efficient for trade, but you will not be helping your domestic producers compete with producers elsewhere and really capture value from the global economy.

I see the same dynamic in terms of education. Investments in higher education and training (particularly data science) are happily increasing in many low- and middle-income countries. Part of this expansion, however, is being driven by commercialization within universities and there are not enough attempts to coordinate the demand and supply of skills. If you invest in training and skills but you do nothing to help support the development of domestic firms to absorb those skills, you are not going to shift your economy into higher value parts of the global economy; you are just going to create graduate unemployment.

It is really important, therefore, for policy-makers to see digital infrastructures and knowledge systems within this broader production space, and to synchronize training and investments in digitization with industrial policy and investments in other key infrastructures. This is a key interest of mine, which I am exploring in the book I am writing right now! Hopefully I will have more to say by the end of the year!

We look forward to reading it! So can you close us off with the third area you wanted to address?

Right, so, the last thing I want to talk about is this issue of risk pooling and solidarity: both the inability to tax companies, and something that Torben Iversen and Philipp Rehm, have written about in a page – when we have better information about people’s risks and costs, there’s a kind of individualization, a tailoring going on.

So, in place of a system where we pool our risk and everybody pays the same amount because we don’t know exactly what people’s health risks are, we’re now moving to a situation where companies can know exactly how much you cost in terms of insurance; they can provide education for your children that is perfectly tailored to their needs; or they can provide you with a safe risk-free transport service. We’re seeing a lot of public infrastructures being undermined by this individualization.

Particularly when we think of debates around private health care in the US right now, and the fact that just being a woman is a preexisting condition, how willing are men going to be to pay extra money for women to have health care for things that don’t affect them personally? We can think about the interactions here of gender, class, and race. The way, for example, Uber talks about how it’s minimizing risk for women when these are upper-class women that can afford private transportation. What happens to the wider public transport system and for women who can’t afford to take private transport if public options start disappearing?

So many business models within the tech world are built around giving people better, more individual, more tailored, less expensive, personal solutions. This is typically something that we were unable to do in the past and risk pooling was a way of financing these services. However, if it becomes more and more possible to individually calculate costs and risks, this is definitely going to have a big impact on women and other groups who typically benefit more from risk pooling because of the way inequalities are structured within society.

Thanks a lot Laura, is there anything else you’d like to talk about that we haven’t covered?

Well, to conclude, I’d want to touch upon one of the first points I made. I think we should always be mindful of certain basic questions – what is technology? Where is technology to blame and where is the problem with tech firms and the wider forces that they’re interacting with?

So, for example, the way in which there is a singular emphasis on shareholder value in evaluating the worth of companies and their economic activities. I think this is a larger structural dynamic responsible for the trajectory of technological and economic transformation we are witnessing, and we must understand this context to properly conceive of new developments in the digital economy.

I would argue that platformization fits into longer-term processes of firm restructuring and automation, partly driven by the shareholder value revolution within business. As managers come under pressure to improve efficiency and deliver ‘value’ to their shareholders, they are constantly looking for ways to re-organize production to eliminate the need for skill (thereby allowing them to shift production to cheaper workforces either at home, or abroad) and to shift mental processes away from workers (who may go on strike!) onto technical infrastructures (who may never unionize! God bless inanimate objects!).

In earlier decades, this kind of logic was first applied to manufacturing and then to business processes, and today, the global economy is characterized by globally-stretched production networks across international boundaries. To a large extent, platformization is expanding the same logics to those parts of the economy that require proximity to the customer base, in areas such as transport, personal services, education, and health.

I believe that the best visual metaphor for these dynamics is a giant sponge. These technologies are allowing firms to squeeze ‘inefficiency’ out of the market and production system, both monetarily (the distributed wages and profits of workers and small businesses) and intellectually (all the skill requirements distributed in the system). The system becomes highly efficient but obviously creates huge distributional effects on the economy (not just in terms of wages but also in terms of saving and consumer demand). The outcome of this ‘big squeeze’ is a nice puddle of profits, logistical power, and potential investment capital. This puddle could be invested in productive and redistributed ways, but it could also be extracted into the pockets of private shareholders.

This is the second interview from our special issue on A New Social Contract for the Data Age.