In her essay, technology historian Orit Halpern expands on the concept of smartness that shapes Lawrence Lek’s world-building in NOX

Many cities around the world aspire to smartness — Berlin, Dubai, Singapore, New York, Nanjing. There is a regularly repeated protocol to these speculations usually carried out by planners, policy makers, large developers and tech corporations. Making a city smart usually involves constructing a dense net of sensors, often embedded in and around more traditional infrastructures throughout the urban environment, such as transportation systems, electrical grids and water systems. The city also solicits the distributed input of its inhabitants through active technological means, such as smartphone apps. Finally, high-end computing and learning algorithms are deployed to analyse the resulting data, with the goal of optimising urban technical, social and political processes. Preceding all of this usually comes speculative capital, generated through advanced marketing campaigns, and, of course, the arcane mechanisms of real-estate development. Sovereign wealth funds, hedge funds, incredible amounts of leveraged assets and futures trading are all involved in making urban territory available for computing. Smartness has become the new frontier for both capital and territorial control.

Cities have long been central to geopolitics, technology and ideas of human subjectivity and agency. The very term ‘city’ in English derives from the Latin civitas, which, in the context of ancient Rome, referred to the collective body of citizens united by law and social responsibility. The city in Western tradition was imagined as the seat of the demos, meaning “populace,” and the polis, meaning “city state,” where humans were separated from nature. This separation is central to the concept of the political as realm of human action, and the city as the site in which human agency and politics are enacted.

Smartness rests on the fundamental assumption that such ideas of human agency and spatial containment are now obsolete. The central idea in artificial intelligence (AI) is that humans can no longer exercise agency autonomously without a new form of nature — mainly technology. We might then assume smart cities will not replicate earlier concepts of the urban.

It is perhaps a marker of this new form of territory that, perhaps counter-intuitively, a smart city is not synonymous with a utopian — or even a specific — ‘form’ of the city. The smart city has no stable ideal form for the foreseeable future. The smart city is constantly evolving through data, and therefore capable of speciation and mutation. There is no endpoint to the smart city, it is infinitely extendable and changeable.

In this sense, the smart city is quite unlike utopian cities as they were imagined in modernity, when it was presumed that a specific form — such as Le Corbusier’s ‘Radiant City’ or the concentric circles of Ebenezer Howard’s garden cities or Oscar Niemeyer and Joaquim Cardozo’s planned city of Brasília — would enable a specific goal. Such goals could include the integration of humans into natural processes, colonial domination, economic growth, an increase in collective happiness or democratic political participation. Rather, a city is ‘smart’ when it achieves the capacity to adjust to any new and unexpected threats and possibilities that may emerge from the city’s ecological, political, social and economic environments (a capacity that is generally referred to in planning documents with the term ‘resilience’). In short, a smart city is a site of perpetual learning, and a city is smart when it achieves the capacity to do so. In the smart city, fantasies of directed and agential political revolution are replaced by responsive evolution.

As the smart city constantly adapts, the people who live in it also have to adjust. The inhabitants of a smart city necessarily become perpetual learners. However, the smart city’s smartness is not supposed to be imposed upon its urban inhabitants from above; rather, it is supposed to result from the combination of the inhabitants’ unique individual perspectives and choices. Smartness presumes that these acts of combination cannot be accomplished by humans alone, but require the assistance of computing processes — and, more specifically, of algorithms that teach the smart city (and its inhabitants) new ways in which to learn. Very much like ‘the market’ of neoliberal economic theory, smartness optimises processes by combining multiple perspectives in a way that cannot be achieved by any group of human planners. For some of its advocates, the ability of smartness to automate the combination of an enormous number of individual perspectives makes it possible to imagine that one could perhaps replace politics — that messy realm of self-interest, which often only seems fully open to a select few—with technological processes that could actually achieve what democracy only promises.

Smartness is then predicated on the assumption that humans have incomplete information and need the guidance of the market, now social network, or perhaps the state. In neoliberal regimes, such networks are assumed to be self-organising and ‘free’ but never planned (and certainly not by the government). In the Sinofuturist universe of Lawrence Lek’s work, such imaginaries take the inverse mirror, perhaps guided by bureaucratic policy, but still emerging from population-level data through networks. Smartness means participation but not necessarily representation or power. Utopia can never be reached, only versioned.

This dream of smartness as a route to freedom (or sovereignty) through surveillance and perpetual learning is the marker of contemporary political economies (platforms), geopolitics and individual self-fashioning. Contemporary initiatives such as the Digital Silk Road, smart border systems, disinformation campaigns and quantified self apps are but some of the systems and political tactics beyond cities that exemplify this contemporary technical situation.

One might say for smart machine systems learning is not education. Learning is about behaviors and tasks. Our narratives and stories of sentiment, empathy and compassion are turned into statistical patterns of key words and phrases, that are then used to train the next set of humans or machines in hating, loving, caring and so forth. This transformation into a world of networks based on behaviourism makes our conditioning the very substance that scales between ourselves and our vast technical systems.

These considerations are felt within the deeper layers of Lek’s worldbuilding in NOX. Voice logs slowly mount a sense of the smart infrastructure operating in the background, a form of governance felt through the parameters deemed acceptable or deviant. Further, Lek has structured particular modes of interaction within the locative sound experience and the training simulation game that themselves incorporate behavioural conditioning.

What it means to be trained, and to learn, are central questions in envisioning what forms of life and being are permitted to exist and flourish. Is learning a mode of behavioural conditioning and training solely directed towards goal-oriented behaviour? or something else? Ultimately, the challenge we must engage with is how to imagine new ways to learn through our collective relations to both human and nonhuman others beyond the parameters of our own conditioning and towards envisioning new forms of connection to others — machines, humans and animals — in our world.