Elizabeth Thompson, Trinity Communications
Who doesn’t dream of owning a house that automatically closes the windows when it starts to rain, or a car that copes with traffic so you don’t have to? The science fiction of yesterday is today’s reality, and even better days are on the horizon.
Such is the promise of “smartness.” It’s touted as the answer to all of humanity’s problems, a path not just to prosperity but to the very survival of our species.
Is a smart future inevitable, though? What would a world constructed by smartness look like, and is it the best future we can imagine?
These are the questions Robert Mitchell, professor of English, and his colleague Orit Halpern, Lighthouse Professor and Chair of Digital Cultures and Societal Change at Technische Universität Dresden, ask in their new book, The Smartness Mandate, released in January 2023 from MIT Press. Mitchell and Halpern examine the economic, social, and political ramifications of “smartness,” arguing for caution in our headlong rush to embrace this new way of organizing our world.
The following interview with Professor Mitchell has been edited for length.
I also like and depend completely on the smart features of my devices! I would often literally be lost without my smart phone, since every time I visit a new city I use Google Maps not just to find my way around, but also find some place to eat that other people seem to have liked, I use Lyft to get to and from the train station or airport, and so on. I’m also signed up for the “smart” option through my electrical utility, I hope that smart medicine can provide me with better health care, and I often find the recommendation engines on sites like Netflix and Amazon very helpful. In short: ours is not a book that says “wait, you’re all being tricked: smart technologies are terrible!”
What intrigued my co-author and me is the sense that everything ought to be made “smart.” Smart cities are a great example of this, as the idea of building a smart city from the ground up is that it then would be possible to use smart technologies to “optimize” every urban process and interaction, from our private lives in our apartments, to public and private transportation, to the electrical grid, to health care, to K-12 and university education and perhaps politics itself. The idea is that if we could optimize everything, we would not only enjoy our lives more, but we would also be able to significantly reduce our use of energy and material resources — pretty important goals in the face of global warming. This is why we describe smartness as a “mandate,” since smartness is increasingly presented not just as something that makes life a bit easier and more fun, but rather as something we really have to do to save ourselves from ecological disaster and other kinds of threats. So we wondered: what exactly is “smartness,” and how and why has it come to be not only a desirable goal, but something that must be implemented everywhere?
The phrase “demo or die” is often attributed to Nicholas Negroponte, the founding director of the MIT Media Lab. The phrase was his spin on, and his criticism of, the traditional academic saying, “publish or perish.” He meant that, instead of just publishing theoretical papers about new media technologies, his group should be actually showing, by means of a “demo” version of a software program or technology, that an idea works in real life.
Negroponte’s practice of “demo”-ing projects encouraged us to think fairly narrowly about change (and evolution) in terms of business models and practices, and to accept that life will always be lived in the “demo” phase. The point of the demo is to get more funding, whether it’s for a lab or a start-up company. One can get more funding even if it doesn’t work that well, since the funding is based on the demo’s promise.
What we see happening in the case of smartness is that this idea of a provisional demo moves out from the research lab and becomes our permanent condition: there is no “final” version of the smart city, for example, just provisional versions that are always changing as smartness learns from past mistakes. In the case of cities, this is a huge departure from past ideas of architecture and urban planning, which were oriented towards structures that would remain stable for a long time.
Smartness as a mandate — this sense that we must make as many technologies and social process as smart as possible — depends upon the idea that the future is primarily a source of threats and disasters, rather than a time in which social problems can be solved. In the face of our current global ecological condition, global warming, the spread everywhere of microplastics and “forever chemicals,” the accelerating extinction of plant and animal species, and so on, it’s admittedly pretty hard not to share this gloomy sense of the future!
From this perspective, it may seem like we need smart technologies, since part of what makes them “smart” is that, by means of lots of sensors and learning algorithms, they can constantly help us adapt to whatever threats the future throws at us. This ability of smart systems to learn and adapt constantly in the face of crises, threats and disasters is often described as “resilience.”
An example we discuss in our book is New York City’s Hudson Yards, which is a “smart” subsection of that city. It has the ability to adjust to many kinds of crises: if New York City floods in a storm, key parts of the infrastructure will seal themselves off; if there is a terrorist attack that knocks out power, it has its own microturbines that can cool and warm the buildings; and so on. One obvious problem with this approach to smartness is that only a very small, very wealthy part of the city will be able protect itself from these threats. But the other, and we think much bigger problem, is that smartness as a project almost seems to need this idea of constant threats to justify itself. This makes it very hard to see the future as anything but an avalanche of disasters just waiting to be triggered. We’re hoping our book can connect some of the techniques of smartness to more optimistic senses of the future.
Smartness is about optimizing all kinds of processes: selecting a consumer product, how energy is used across an electrical grid, discovering new medical therapies and drugs and figuring out which drugs work for which individuals and which do not, and so on. This can save money and resources and can in principle be easier on the natural environment than other processes.
Smartness is also about learning. It's not just a one-time optimization that is then supposed to last forever, but rather a constant process of semi-automated computer learning from previous attempts at optimization. Moreover, the way that smartness seeks to learn is in principle inclusive. Instead of assuming an expert knows best, and so that expert can and should plan everything for us, smartness assumes that learning happens most effectively when computers bring together huge populations of individual perspectives. Instead of assuming that some peoples’ perspectives can be ignored, smartness seeks to be inclusive — though this inclusion is always mediated through algorithms.
There are shortcomings of specific smart technologies — for example, the algorithms employed may have a racial, class, gender or other bias. These are important limitations, but since smartness is about learning, advocates of a smart technology can claim that the next iteration or demo or the technology will be better.
We’re more concerned with the implicit assumptions about how smartness is created. Smartness is often filtered through a “market” model, which makes it seem like the natural way to enable computer-assisted learning multiple perspectives is by having people register choices through purchases. Prices become the only way — and at least the default way — to combine individual perspectives.
In addition, understanding the appeal of smartness primarily in terms of threats limits the possibilities of smart technologies. Orienting ourselves toward disasters, even in the name of enabling resilience, tends to encourage us to think in terms of security and borders, which in turn may work against the inclusiveness upon which smartness is supposedly based.
We’re painfully aware that “smartness” is a much catchier term than “biopolitical learning consensus,” but we used that phase to hold on to what we find helpful about smartness, while at the same time moving away from what we see as its the negative aspects.
To start, we find the word “learning” much more useful than “smartness.” Learning — more specifically, computer-mediated learning — is what smartness is all about. However, the term “smartness” has come to suggest that only computer-mediated learning is important, whereas we want to stress that computer-mediated and assisted learning is one among many modes of learning.
In place of the “mandate” that we become smart, we think it better to aim for “consensus.” Consensus implies political processes of discussion, give and take and compromise, rather than submitting to mandates. The process of coming to a consensus can also be oriented toward a positive future that we hope to create, rather than an attempt to create all-purpose resilience in the face of whatever disasters the future will bring.
The term “biopolitical” is often used to describe efforts to govern people at the level of a population (the COVID-19 pandemic is a great example). It stresses the importance for smartness of synthesizing whole populations of perspectives, though we’re also suggesting that these processes don’t have to be solely oriented toward “controlling” people.
The term “biopolitical” also underscores that our individual bodies and natural environments are inextricably linked by our technologies. These linkages happen in complicated and sometimes contradictory ways: for example, though smart technologies intend to optimize the use of resources, the sourcing and transportation of the minerals that go into their construction and the energy associated with their usage are not always factored into that optimization. We use the term biopolitical to focus attention on this wider frame of smart technologies — not just what they do for (or to) populations of people, but also where the materials for the construction of smart technologies come from and where these resources go when it’s time for the next smart “demo.”
We’re hoping “biopolitical learning consensus” will help readers think differently about the elements of smartness. Through case studies, our book presents understandings of infrastructure beyond market-based models: for example, drawing on the work of Winona LaDuke and Deborah Cowen, we contrast the market-based smart electrical grid model with a very different approach to electrical infrastructure developed by indigenous groups in Canada and the US. Others rethink smartness by connecting it not to the “nature red in tooth and claw” version of biological evolution that stands behind the “demo or die” phrase, but to less violent natural processes, such as Suzanne Simard’s work on the “smartness” of forests. We hope that these alternative visions will encourage our readers to reimagine smartness.