Imagine it, a smart city, full of sensors and connected technology. Rules are not necessary, because the city controls itself. Garbage is collected when the bins are full, traffic lights set to give way to pedestrians – or a fast flow of cars during rush hour. Residents ask permission for an event to the rest of the residents via crowdsourcing. It may seem a bit far-fetched, but this is exactly what Sidewalks Labs, a subsidiary of Google, is going to build for $50 million in Toronto, Canada.
On a former industrial estate that is a bit deserted, the ‘most measurable community in the world’ must be created. Because all data collected by these systems goes directly back to the city. With all this feedback, the systems learn what works and what does not. Quayside, as the neighbourhood is called, is for many a tech-believer a dream come true.
Not everyone is keen on the idea of a Google-city. Shoshana Zuboff, an emeritus professor at Harvard Business School, is a good example of this. “This is a dry run for a Google-city where democracy is a thing of the past. Who owns the data? And do users have anything to say about this? Do we want a society in which everything is automated?”
The Age of Surveillance Capitalism
Zuboff spent the past seven years, ‘more or less’ seven days a week writing her new book: The Age of Surveillance Capitalism. In which Zuboff describes a form of capitalism in which companies follow users by collecting data, predicting their behaviour and reselling this information: “Surveillance capitalists claim human experiences, such as a walk with the dog, as raw data that they translate into behavioural data. With machine learning, these become prediction products, predicting what you will do now, later and ever. By trading these predictions they earn big money.”
Zuboff’s book presentation marks the launch of the international CPDP Congress on data protection and democracy in Brussels. During the evening she tells the audience in Les Halles what she is trying to achieve with her work and why she wrote the book.
In her book, she compares the earnings model of tech giants with that of large factories in the twentieth century, where the big players then profited greatly from cheap labour and the invention of steam engines. The only thing that mattered was profit, Zuboff sees something like that happening now: “It doesn’t matter if these companies make you happy with their app or service, it’s about the data you produce when you use their products. It’s about the predictions they can make about your behaviour and the money it brings them. Privacy is alien to them.”
People who ‘fall for it nonetheless’ and click agree without thinking about it, call as a defence ‘that they have nothing to hide anyway’. Zuboff sighs deeply before answering: “Nonsense. If you have nothing to hide, you are nothing. What drives you as a person? What motivates you? What are your dreams? It is about who you are as a human being, your inner motives. The problem is also that these kinds of companies know everything about you, but their processes are designed so that you know as little as possible about their way of working. That creates an unfair situation. The distribution of power that results from this knowledge is not equal.” Moreover, Zuboff states: “Companies predict your future and influence your behaviour purely for profit. The power to predict and adapt human behaviour is unprecedented. But if you are guided in your choices, you lose your sovereignty, in a democracy in which you have to make your own choices, this is dangerous.”
How do we solve this?
What does she think is needed to restrict this system? Zuboff: “First, it is important to name and describe the problem. That’s why I wrote this book. I’m sure many people have no idea that their personal experiences are used to predict and guide their behaviour. Even our sleep is converted into data and you have no control over what companies do with it, this market is about us, but is not for us.”
Laws can help: “The GDPR is a good start, but that is far from sufficient. Maybe we should go to a model that redistributes the wealth of data? I don’t know. But at least we need to talk about it to change our view of this phenomenon. Because asking companies to stop collecting data is like asking a giraffe to shorten its neck”, Zuboff looks away and smiles: “I may sound very pessimistic, but I have every hope that we can solve this. Look at the industrial revolution and capitalism, that has also worked out well. Besides, it is not determinism that we cannot avoid. This is a problem developed by people, be it by a design error or a blind urge for profit, anyway, people are going to solve it again.”
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