Profit versus the common good

OLAF GRAWERT: You collaborated with the Future Division of Daimler Inc. as part of the Drehmomente production art festival in Stuttgart. What kind of ideas were colliding with each other in such a collaboration?

CHRISTIAN VON BORRIES: The automotive group has been expanding its product range for a while now, moving away from producing cars towards becoming a developer and provider of mobility concepts. According to Dieter Zetsche, Daimler’s long-serving, recently retired CEO, this change in thinking is crucial in the race to dominate the mobility sector, which the company wants to win. Whenever a company like Daimler talks about mobility, it automatically speaks about public space and who is in charge. At this point, private and public interests are blurred, and that is what interests me as an artist: the relationship between social and corporate interests, the common good, and profit motivation. The failure of the state regulatory power became apparent when Stuttgart’s Mayor, Fritz Kuhn, sent mixed messages during a Smart City conference. On the one hand, he called for reducing inner-city individual traffic, but then maintained that jobs in the automotive industry are more important to the region than any sort of mobility concept. Immediately afterwards, the head of Daimler Financial Services, the rental and leasing division, expressed his vision of work and mobility for the future of Stuttgart with the idea of offering a single source for everything from the app to the automobile to the service itself. Images by Daimler’s Future Division illustrated this vision with renderings of traffic junctions in Stuttgart, flying cars, people walking on green strips, and two men pushing a stroller. I question this narrative of an “old future” in my practice, which is highly associative.

Data instead of taxes

ARNO BRANDLHUBER: At the same time, Daimler’s idea is limited to changing the mechanical world. It replaces workers: products are no longer produced by hand but by robotic arms. This does not really rethink the notion of mobility; the transition to a different reality seems unthinkable. An artist talk you gave at the Garage Museum of Contemporary Art in Moscow was titled “Algorithms of a Smart City and the Disappearance of the Architect.” Let’s consider the first part of the title: what does this shift from mechanical to digital algorithmic logic mean for the city, and what role does big data play?

CVB: Two aspects are especially important here: who is collecting which data and who is evaluating it? It might be that the user is society, represented by the state, for example with censuses. But in fact, data generated by the smart city is mostly amassed by private individual traffic, but then maintained that jobs in the automotive industry are more important to the region than any sort of mobility concept. Immediately afterwards, the head of Daimler Financial Services, the rental ing which data and who is evaluating it? It might be that the user is society, represented by the state, for example with censuses. But in fact, data generated by the smart city is mostly amassed by private companies. China is an exception. We all leave our mark on the city whenever we use public transportation, shop at the grocery store, and so on; we are followed by surveillance cameras. So far, our actions are not being directly correlated. What we buy at the store, or how many cigarettes we smoke, goes unnoticed without a Payback card—unlike our virtual behavior, which leads to personalized advertising, a circumstance that we are largely aware of and that we seem to have accepted.

In the United States and China, we can observe a clear tendency to cross-reference the protocols of real actions and relate them to one another. The key question is: Who is interested in what regarding the evaluation of this data on daily and public life? With tax authorities, for instance, it might help to make things more fair, and ideally, public health insurance would also be driven by good motives. But when it comes to private corporations, profit is inevitably the key driver. The field of self-driving cars is a good example of how the change from the mechanical to the virtual world has been accompanied by a change in power. Besides Chinese developers, Google is the world leader in navigation technology, without even producing vehicles. There is a clear separation between software and hardware, whereby the crucial added value lies in the implementation of the operating system, thus with Google and not with the car manufacturer.

OG: And in the same way, the city is being economized by evaluating and analyzing user behavior. For example, one of the most successful investment funds in the US bases its forecasts in urban areas on the parking lot monitoring system of the American hypermarket chain Walmart. Car brands and sizes, as well as how long and how often people park there, shed light on an area’s economic and purchasing power and development prospects, and help to confirm the value of financial assets. This location information is one of the largest and least expensive data sets.

AB: But there was no intention to give data access to third parties when the parking lot cameras were first installed. The information is collected and, in some ways, interchangeable. The rise of selflearning software has revealed the importance of data and its availability. And with that, the question of interpretation becomes relevant: Where does this qualitative transition happen? What happens if this data—be it random, generated by Google or, in the case of China, governmentmanaged—affect the analogue city and urban planning?

CVB: This example shows the successful correlation of data. At the same time, we can observe that the key role lies not with the software developer but with the data analyst. Data analysts do not program applications, but use data patterns to establish correlations between the behavior of people and objects. Do I take the car, the bike, or do I walk? Do I leave the house at all? To whom do I talk when riding the bus? In the past, urban planning, and with it a sense of responsibility, has been centralized without consideration for the actual residents. For example, where homes and roads are built, or how much real estate is available for public housing or private ownership. Future planning might be based on population data—a diverse data set that could help shape how the city of the future might look.

At the same time, our role is shifting from that of citizen to user. We are no longer part of a society, but a community, a homogeneous bubble. The development of Toronto’s waterfront shows quite clearly that this economization of the environment by private companies is not being perceived as a threat. Sidewalk Labs, a subsidiary of Alphabet and sister company of Google, is developing a whole neighborhood there (see Bianca Wylie, p. 124–129). We need to consider where the line is between Alphabet’s interests (apart from profit) and an idealistic urban development concept.

Data as power

OG: Publicprivate partnerships like those at the Toronto waterfront are on the rise. Ever more infrastructure and urban development projects are conceived and implemented according to this model. In Germany, a similar tool exists: urban planning contracts. What do these alliances of elected representatives with private companies mean for the city? The withdrawal of the state as we know it?

CVB: It would be too easy to say that it’s bad just because it’s Google. Google makes life easier—that’s a fact. And now Google is building an entire city neighborhood. This step from the virtual to the real world is absolutely logical. For me, the physical presence of the large technology companies at the World Economic Forum 2018 in Davos was a crystal clear signal. For the first time, Google, Facebook, and Palantir have their own buildings in prime inner-city locations. This was a self-confident spatial expression of power and influence: the companies took their place alongside the nation-states, with the difference that access to their representative offices is limited. If you want to visit them “at their home,” you needed an invitation.

It’s interesting to compare this with China, where there is no moral and political differentiation between the private enterprise and the centralized state. Although the big internet companies are managed privately and traded on stock exchanges, the state has direct rights of access. This leads to state-controlled information and data centralization. The state has contributed considerably to the development of new technologies such as AI through targeted financial support or participation. Since state structures were often perceived in the past as acting in ways that were arbitrary, unauthorized, or corrupt, today there is less the fear of Big Brother than the hope for a new, more objective approach.

AI is communist

AB: In your film, AI is the Answer—What was the Question? Peter Thiel, founder of PayPal and Palantir, says that “crypto is libertarian and AI is communist.” What does he mean by that?

CVB: Of course, he is arguing from a libertarian perspective and advocates cryptocurrency as the ideal decentralized system. For him, the idea of central intelligence, as in China, is per se authoritarian and therefore communist. This would make an AI-based and controlled smart city à la Google authorifidant, and his liberal-market approaches that seek to remove all forms of state regulation. In his view, the role of governments should be limited to protecting private property. Logically, the next step would be to withdraw to islands outside national territories. This new business idea is called seasteading. It is the authoritarian, too. At the same time, there are hints of a new Cold War, not least over resources, because both technologies consume vast amounts of energy. This has a direct impact on the states involved.

But for Thiel it is also about an idea of the physical society. Its advocates speak of decentralized database-based technology and always refer to Milton Friedman, Ronald Reagan’s economist and conefidant, and his liberal-market approaches that seek to remove all forms of state regulation. In his view, the role of governments should be limited to protecting private property. Logically, the next step would be to withdraw to islands outside national territories. This new business idea is called seasteading. It is the epitome of a libertarian society, where any variant of social system is possible: it could be a socialist state, but it could also be an authoritarian one.

OG: Algorithms are represented by people who pursue their own ideologies, prejudices, and agendas. Among other things, James Bridle writes about the influence of developers and analysts in his book New Dark Age: Technology and the End of the Future. It explores the agency of coders and codes (see James Bridle, p. 184–191).

AB: In this context, Wendy Chun uses the sociological concept of homophily to explain the effects of algorithms such as those of Facebook. People are divided into homogeneous groups because they are easier to address. Is the smart city homogenous per se?

CVB: Machine learning is based on statistics. Statistics of user data, existing spaces, situations, environments. However, statistics in market logic also mean that the largest group will and must always get larger. Minorities therefore become marginalized, which poses a danger, as does the lack of accountability. Although we know which algorithms AI is based on, the levels of decision-making and potential influences remain opaque. Coders can influence the behavior of machine learning (ML) by exposing the algorithm to specific training stimuli. For example, many image- and text-classification algorithms are trained by optimizing the accuracy of a particular record using data that has been manually labeled by humans (labeled data in supervised learning). The selection of the data set and the characteristics it depicts have a significant influence on this. We can neither intervene nor disagree, which further contributes to the homogenization of groups and society.

The question is how Facebook would think and understand the city. It is highly speculative to maintain that the smart city is homogenous per se. Perhaps we should look at the physical spaces that Facebook has built for itself and their logic. Frank Gehry’s corporate headquarters design is so interesting because, although the company hired one of the best-known trademark architects, Gehry didn’t deliver his iconic architectural language in this case. This project is completely untypical for Gehry, but one could argue that he understood Facebook—almost in the same way that Mark Zuckerberg dresses—according to the norm-core principle: architectural indeterminacy. It’s about the lowest common denominator that works globally and can be reproduced, similar to an IKEA lamp or a T-shirt by H&M. A degree of ambiguity similar to Facebook’s can be observed at the Toronto waterfront. Canada represents a business-friendly middle course between regulatory Europe and the private capitalism of the United States, a hybrid testing ground that works globally while anticipating a high degree of participation. In Canada, a different type of data generation than in the US is possible: one that is voluntary, proactive, and bilateral. This leads to architectures that, on the one hand, do not disturb anyone, and on the other hand, are generated for different and rapidly changing uses. The focus on function in ML helps us to understand why some behavioral mechanisms of algorithms are spreading and continuing, while others are decreasing and disappearing. The function highly depends on adapting the behavior to the environment data, not the other way around, as Google’s Sidewalk Labs claims. Successful behaviors (improving the multi-functionality of architecture, for example) are copied by developers of other software and hardware, or further developed to spread on ML algorithms. This dynamic is ultimately determined by the success of institutions such as corporations, hospitals, municipalities, and universities—Foucault’s spaces of enclosure—which program and use AI to homogenize human behavior.

AB: If we assume that the images of architecture in this case serve to generate resonances, which then are used as data in urban planning, architecture becomes an instrument while at the same time losing its social functions.

CVB: Exactly! First, architecture becomes an instrument of statistics and then provides information about user behavior. The role of the architect no longer exists in this scenario, or it is limited to the design of unconnected buildings in the urban space that are predetermined by algorithms.

Users and providers

OG: In addition to Orit Halpern, you refer in your lectures to Keller Easterling. You all agree that there is a marginalization of certain undesirable populations, usually the working class. Your film also shows the Louvre Abu Dhabi, where workers are standing and waiting almost invisibly. What do these pictures tell us?

CVB: For years, I’ve been collecting footage of cleaning staff in apparently senseless cleaning situations. These clips reveal something that is usually hidden: that even though we all use mobility sharing services, nobody knows who cleans, refuels, or services the cars. And if you change your computer chip or repair your smartwatch, again, the repair worker will remain unseen—invisible and underpaid. Given such structural conditions, our class system and the neoliberal politics behind it cannot last much longer. In already uncertain times, in which society is becoming increasingly polarized—here the rich, there the poor—we are now being confronted with new ideas and forms of living. But how will established companies and start-ups respond to the displacement of the middle class from the city centers? Google, Amazon, or Baidu may have no interest in this and ideally prevent ghettos of any kind. Might it be possible to use an algorithm to counteract this current development?

Big data as public space

AB: What kinds of attempts are already being made to influence the public space?

CVB: Until not so long ago, we lived under the impression that public space belonged to everyone. An intermediate step away from this was marked by the creation of commercialized, semi-public spaces such as the Mercedes Benz Plaza in front of the Mercedes Benz Arena (previously the O2 Arena), in Berlin. The square was opened by Ramona Pop, the Green Party’s Senator for Economy, Energy, and Enterprises, with the words: “This is a typical Berlin district as we envision it.” Police standing on a nearby street confirmed what was already apparent: that public servants don’t have jurisdiction over the premises because it is a private space, where safety is privately addressed and regulated.

The World Cup in Russia in 2018 clearly shows the direction this development is taking. There, a facial recognition software called FindFace was used nationwide, with a recognition rate of 97 percent. Everyone who visited the FIFA World Cup had an RFID chip in their tickets that had to be carried outside the stadiums as well. This may sound like old technology, but it already anticipates a future in which people identified through chips can cross borders or pay for their groceries at the supermarket without waiting in line—in short, life without friction or limitations. This form of space and its acceptance marks the intersection of big data and public space .Critics of this technology are countered with the argument that the technology fosters public safety by enabling cross-references with the data of well-known hooligans. China makes a similar argument in defense of its social credit system. There, big data is already part of everyday life: those who behave inappropriately are prohibited from using the express train, for instance. The policies are often justified by using examples of people from marginalized groups. These are just a few examples illustrating how data affects public space.

AB: Sidewalk Labs uses a selfdeveloped, open source software called Replica to simulate and plan entire cities. They offer it to municipalities and city planners and, in return, receive labeled data to verify their algorithmic forecasts based on realtime database systems. Keller Easterling calls these unseen powers that govern the space of everyday life “extrastatecraft.” Does that mean that European nationstates cannot compete with the superior power of global tech companies?

CVB: Exactly, state administrations have no similar spheres of influence or comparable resources. We need to think about treating and controlling technology companies as supra-state structures. So far, China is the exception, because this one-party state is organized top-down by default. While this is not the rule in politics, this tendency is inscribed in technologies. Now you might ask: What then is the task for architects in China?

Society and its architecture as an algorithm

AB: The Sidewalk Labs CEO, Daniel Doctoroff, was Deputy Mayor of New York and responsible for implementing the communications network LinkNYC, which replaced all phone booths in New York with free WiFi (see Michaela Friedberg, p. 204–209). LinkNYC also belongs primarily to the Alphabet group. This drew sharp criticism from the population. How can one still have a dialogue at eye level in the face of this overwhelming economic power?

CVB: To understand the complexity of this business and its reach, you have to consider a second level and ask: What social functions do Alphabet’s technologies and offerings correspond to? These would be state responsibilities such as public transport, public hospitals, and public health insurance. At the planned Quayside district by Sidewalk Labs along the Toronto waterfront, these tasks are to be performed by private companies. But this is not about traditional privatization, it is about full access to our habitats and the subcutaneous control of our behavior. You have to understand their business model. In Google’s exploitation logic, all city and state functions will seem to be free of charge, like a search query. The privatized service is just the tool to get data in return. So it might be too simple to ask what tasks architects can still fulfill in this scenario. Shouldn’t we be asking where and how society is actually operating? You cannot act independently of the system; without Alphabet, Amazon, and the like, the situation can hardly be changed. We have to use their tools and think about what we can do with them and what our role should be. You are architects with the software at your disposal: use it and see what comes out of it, and what that means to you! We are certainly embedded, and there is probably no alternative. At best, it expands our utopian horizon. To look at it positively, the Quayside district might ultimately be the architecture that wins the Pritzker Prize because no architect could ever imagine it. Maybe big data will give us a vision of society that we never would have come up with ourselves.