Our new issue, “After Bernie,” is out now. Our questions are simple: what did Bernie accomplish, why did he fail, what is his legacy, and how should we continue the struggle for democratic socialism? Get a discounted print subscription today !

Discussions about digital privacy often evoke images of whistle-blowers, journalists, and intelligence agencies. But beyond this, it can sometimes feel as though the business model of corporate data mining presents few negative consequences in our daily lives. The omniscient machinery of state surveillance is rarely an issue visited upon us personally. Amazon, Google, and Facebook are overwhelmingly convenient, well-designed platforms that can be enjoyable to use. It is perfectly possible to worry about the surveillance state in the abstract but, at the same time, think of ourselves as having little to hide personally and, therefore, not much to worry about. For these reasons, it is easy to tolerate technologies of surveillance in their various forms as a fact of life in the twenty-first century. Just like some people can experience the effects of climate change as pleasantly warmer weather, the insidious potential of mass surveillance often manifests itself as convenience and improved consumer experiences. The importance of systemic and collective privacy can start to fade from view — but at what cost?

Digital Oppression While we struggle to articulate compelling defenses of privacy, those in power have had little difficulty understanding its significance. The structures of class society are being encoded into our experience of online life at a rapid pace, something that is only possible because of our political ambivalence about privacy’s value. Most recently, this disconnect was made clear in a report by the United Nations special rapporteur on extreme poverty, which highlighted how technology is being used by governments in various oppressive ways in the digitization of welfare services. This phenomenon takes many forms. Algorithmic decision-making is being applied in all sorts of government programs in the United States — from identifying children at risk, to allocating housing, to assisting with parole applications. In Canada, the government has automated processes associated with immigration and refugee systems. One-third of councils in the UK use algorithmic technology to help determine benefit claims, identify fraud, and manage social services. Governments in India, Kenya, and South Africa have set up national identity and welfare schemes that incorporate biometric data like fingerprints and retina scanning. In recent times, the Australian government issued hundreds of thousands of incorrect debt notices to welfare recipients, an outcome of a flawed data-matching algorithm that used tax returns to identify potential overpayments. The digital upgrade of welfare delivery is often presented by government as a neutral, even benign, phenomenon, which allows services to be optimized and resources to be spent efficiently. The reality, according to the special rapporteur’s report, is that these transformations are “revolutionary [and] politically-driven.” It is a reality in which “citizens become ever more visible to their governments, but not the other way around.” Such a rebalance of power is the mundane, insidious consequence of living in a society without any respect for privacy. Critics of such programs have faced retaliation from the government and harassment by state agencies. Disputing automated decisions can be virtually impossible, at times comically so, as individuals get caught up in bureaucratic loops. Rather than ameliorating inequality, Virginia Eubanks’s book, Automating Inequality , illustrates how these programs exacerbate it. Such programs do not seek to eradicate poverty. Rather, they aim to manage the poor, confining them to a cycle of stigmatization and entrenched disadvantage. ‘Technologies of poverty management are not neutral,” she writes. “They are shaped by our nation’s fear of economic insecurity and hatred of the poor; they in turn shape the politics and experience of poverty.” This is not just about government agencies — industry has been quick to capitalize on state investments in digital infrastructure. The notorious Palantir, the data-mining company started by Peter Thiel, has been used in predictive policing operations for authorities in the United States and cost-reduction strategies for local councils in the UK. Palantir’s products generate analytics from disparate data sets — including social media and government sources. The market for biometric technology is estimated to be worth up to $50 billion by 2024, with security and government sectors of North America representing a significant share. It’s not just specialized tech companies that are set to profit from this. Major platforms like Amazon and Microsoft are working variously with prisons, ICE, and a Chinese military-run university on facial recognition software. Other popular platforms sell information to governments directly — think of Uber selling routing and logistical data, or Toronto outsourcing its city planning to Google. The business of surveillance capitalism is now about more than just selling advertising: it’s about finding new markets for data. Increasingly, purchasers in this marketplace will include governments, who are developing their own methods for using this data in ways that are unaccountable and often deeply worrying. The development of such markets is the logical extension of the web economy, which has long found ways to monetize class division. The entire business model of surveillance capitalism operates by making judgments about us based on our collective traits and stereotypes drawn from our membership of particular social groups. Joseph Turow has written about how our lives in the digital age are framed by consumption, which produces and reproduces our sense of identity. Online advertising “has embarked on a fundamental and systematic process of social discrimination,” according to Turow, and the effect is to create what he calls “reputation silos,” which can “accelerate the distance people feel between one another.”