What’s going to happen next year? Or the year after that? Or even in five years’ time? If only we could foretell the future, we could do something about it now. If we care about the world, we can make it better by promoting specific social, political, or economic changes…or, if we are less socially-minded, we can simply profit through our foresight. Yet, none of us can look into the future. But that doesn’t stop people from making a good living as futurists and visionaries, research institutes, think tanks, and other organizations attracting funding by predicting and promoting future trends, or investors making financial claims promising better-than-average future returns. Nowhere are such future promises and visions more prevalent than within the political economy of science and technology, especially in an era dominated by Big Tech firms like Apple, Amazon, Microsoft, Alphabet/Google, and Meta/Facebook.

Techno-economic promises are powerful. Hopes of new digital and algorithmic technologies glitter especially brightly in the narratives of institutions like the World Economic Forum (WEF) when it promotes a world radically altered by smart cities, blockchain, the Internet of Things, and a never-ending stream of transformative ‘cyber-physical systems’. Presenting these promises as a Fourth Industrial Revolution – 4IR if you’re okay with yet another management buzzword – the WEF has reframed itself since the mid-2010s as a bastion of technological visions for a brighter future, driven by the ideas of its founder and Executive Chairperson, Klaus Schwab. According to Schwab, we can expect a world of “Ubiquitous, mobile super-computing. Intelligent robots. Self-driving cars. Neuro-technological brain enhancements. Genetic editing. The evidence of dramatic change is all around us and it’s happening at exponential speed”. It is important to remember that the WEF and Schwab are offering more than promises.

The funny thing about such technological promises is that they generally don’t come true.  Self-driving cars – and other sundry marvels – are about as likely to work and become commonplace as the flying cars envisioned decades ago as populating our skies today. While such technological visions seldom materialize, they do serve a political-economic function. Visions of future technologies open the way for policy makers, politicians, businesses, international institutions, and others like the WEF to generate expectations that then come to configure how we even think about the future, especially when it comes to techno-economic change. By making promises, entities like the WEF and their founder can force changes in policies, regulations, and institutions today in order to bring about their preferred future visions. And this has significant implications for how we understand techno-economic change and its consequences.

The vision underpinning the 4IR promoted by Schwab and the WEF, for example, depends on narratives of constant and unstoppable technological and political-economic transformations of our world and lives. Technology will, in their vision, radically alter the way we live and, moreover, should live our lives.

There is a dark side to the technological futures the WEF envisions. The vision underpinning the 4IR promoted by Schwab and the WEF, for example, depends on narratives of constant and unstoppable technological and political-economic transformations of our world and lives. Technology will, in their vision, radically alter the way we live and, moreover, should live our lives.  A key example of this radical transformation is the rollout of the so-called Internet of Things (IoT), which is premised on the wholesale extension of digital surveillance into our lives through the tracking, collecting, and exploitation of digital data about everything we do. For those who don’t know what IoT entails, it’s basically the insertion of digital tags, monitors, and processors in every object in our world so that we can better tweak their performance as we use them. Want to increase your food buying efficiency? Then buy a ‘smart’ refrigerator to tell you – or, more likely, your food deliverer – when to buy more tomatoes. Want to increase your washing efficiency? Then put a chip in your clothes to tell your washing machine how best to wash them. And so on, throughout every aspect of our lives.  Radio-frequency identification (RFID) technologies are already ubiquitous – having taken off in a big way since 2012 according to media researcher Jordan Frith – and are often embedded in clothing, smartphones, gate sensors, bank cards, travel passes, and such. But current RFID technologies are often passive and limited in their data processor, while IoT is premised on upping the role of digital technologies so they can both collect more data and communicate with more parts of an ever-widening digital ecosystem.

Now, this might seem useful – and it might be, if we were able to carefully think and plan its implementation and potential social impacts. But, right now, IoT technologies seem to be increasingly deployed and configured as yet another techno-economic tollbooth to extract further economic rents. The Twitter account Internet of Shit gets at some of the absurdities of these attempts to extend rentiership into every aspect of our lives. Their phrase, “put a chip in it”, reflects the myriad attempts of businesses to exploit the range of emerging digital technologies to make money from our lives, whatever the consequences. Cars, smartphones, televisions, grills, and other everyday objects are being held ransom through subscription requirements that disable their functionality if their owners don’t cough up. All of this is enabled by a range of digital and algorithmic technologies designed specifically with this task in mind – to extract these rents. As legal scholars Aaron Perzanowski and Jason Schultz point out, it really is the “end of ownership” as we know it.

Which brings me back to Klaus Schwab and the WEF. As the 4IR is rolled out as a policy solution to the social problem de jeur, it ends up supporting the ubiquitous deployment of digital and algorithmic technologies that will enable businesses “to monitor and optimize assets and activities to a very granular level” – to use the words of Schwab. What does this mean? At its heart, it means the transformation of almost everything around us and about us into a political-economic asset that can be controlled, traded, and capitalized on the basis of its future revenue streams. There are two important dimensions to this assetization of our social lives: how are things turned into assets? And how does this transformation configure and constrain our futures? A growing interest in different assetization processes is outlined in a book I recently co-edited with sociologist Fabian Muniesa called Assetization: Turning Things into Assets in Technoscientific Capitalism – it is also open access, so anyone can read it. Our aim with the book is to show how many things – almost anything, in fact – can be turned into an asset with the right techno-economic knowledge claims, calculative practices, technical devices, organizations, and so on. An asset, though, is more than a simple property claim; it is, more fundamentally, a political claim on the future, especially through the right to future revenues. And this creates a political and policy dilemma when it comes to IoT and its extension of data collection and exploitation.

An asset, though, is more than a simple property claim; it is, more fundamentally, a political claim on the future, especially through the right to future revenues. And this creates a political and policy dilemma when it comes to IoT and its extension of data collection and exploitation.

There are several problematic aspects to the new digital and algorithmic technologies underpinning IoT (as well as blockchain, smart cities, non-fungible tokens, and other future visions). First, they entail and depend on the continuous mass collection and analysis of digital data, particularly personal data – our names, personal histories, daily activities and behaviors, likes and dislikes, and so on. And by massive, I mean massive. Everything we do becomes valuable when it is recorded in a digital database because it can be fed into data analytics to make inferential predictions and judgments about our actions – ‘what will Johnny buy next’ – and because the very capacity to digitally record all of our actions open up an array of possibilities for assetizing social life itself, which I come back to below. Second, this massification of data collection and its exploitation has a self-reinforcing effect in which the largest collectors – principally Big Tech firms – can create their own data enclaves of incredibly socially-useful data – for example, information on how often people use a particular transit line or road and for what reasons – that are valuable precisely because of the limitations Big Tech places on accessing that data. It is not surprising, then, to find that these Big Tech firms are now some of the world’s largest and most powerful firms, as a recent report by SOMO demonstrates. Finally, the development of algorithmic technologies – commonly referred to as Artificial Intelligence (AI) – are dominated by corporate concerns and imperatives, especially those of Big Tech firms precisely because of their monopolistic data enclaves. Meredith Whittaker, co-founder of the AI Now Institute, argues that researchers are dependent on these data enclaves and the computing power of these Big Tech firms to do their research, which not only entrenches their market power (by limiting the rise of competitors) but gives them the capacity to shape the very future of these important technologies.

The implications of the rollout of IoT, smart cities, AI, and a whole array of other digital technologies is that everything in our lives could be progressively transformed into an asset that someone can own, trade, and capitalize.

This has profound implications, something I’ve been researching for the last few years with a number of colleagues – see here. It looks like innovation and our technological futures are being driven by the wholesale assetization of social life itself; of everything we do freely today and many things we can’t even think of in the future.  What might this mean in practice? I don’t need to go much further than the ideas of Klaus Schwab himself who posited that: “The ability to predict the performance of an asset also offers new opportunities to price services. Assets with high throughput such as lifts or walkways can be priced by asset performance”. The implications of the rollout of IoT, smart cities, AI, and a whole array of other digital technologies is that everything in our lives could be progressively transformed into an asset that someone can own, trade, and capitalize.  As the Schwab quote illustrates, with the right technical and political-economic devices, we can turn mundane objects into money-generating resources; for example, a stairway could be monetized through digital sensors that connect to our smartphones, collects our personal data, and charges us every time we go up or down the stairs. The same could apply to elevators, escalators, doors, corridors, pavements, crossing lights, and much more. Every aspect of our lives could be monetized this way.

Another emerging example of this assetization of social life is the way that our schools and education institutions are being transformed through the deployment of so-called educational technology, or ‘EdTech’. Again, the WEF is very keen on this transformation of education through the introduction of new digital technologies that can “create better systems and data flows”. EdTech itself ranges from online program management for students (e.g. Moodle), through organizational software (e.g. Teams) to teaching platforms (e.g. MOOCs), and all of it has been turbocharged by the Covid pandemic, as online learning has had to replace in-person instruction. I am currently working on a project led by Dr. Janja Komljenovic at Lancaster University examining the ways that EdTech is underpinned by the creeping assetization of our universities. It is turning students, educators, and institutions themselves into yet another money-making opportunity for business. Much of EdTech – and especially the WEF vision of it – is premised on the idea that the market is the best mechanism for solving our societal problems, but that is not even the worst part of this transformation. As Dr. Komljenovic points out in her previous work, EdTech entails new digital platforms that not only charge subscription fees for use but also collect data from students, educators, and institutions on top of that. Universities are going to find themselves locked into a future in which they can’t extricate themselves from EdTech providers without losing access to all the data and information they need to operate. And that’s leaving aside the problems with consolidation in EdTech and emergence of monopolies that can charge what they like. Basically, what this means is that students will go through their schooling and university years, and all the data collected about them will be turned into a private asset that EdTech firms can exploit.

Assetization is not a technical or neutral process, it is inherently political and it is inherently contestable, if we so desire.

There are many other examples I could consider – and have done so in ongoing research – but the fundamental point that I want to get across is that all of this is a choice. Assets are made. Someone or some organization has to turn our social lives into an asset that they can monetize, capitalize, and exploit. Assetization is not a technical or neutral process, it is inherently political and it is inherently contestable, if we so desire. Understanding how it happens – how people turn our lives into assets – is critically important because it helps us to identify where we can intervene in the process to disrupt it, or to stop it, or to ensure that it is done democratically and in support of some sort of social good, if it has to be done at all. Assetization is one of the most important issues of our day because it’s about who gets to own the future and how they do so.