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Simply defined, gamification is the use of game elements – point-scoring, levels, competition with others, measurable evidence of accomplishment, ratings and rules of play – in non-game contexts. Games deliver an instantaneous, visceral experience of success and reward, and they are increasingly used in the workplace to promote emotional engagement with the work process, to increase workers’ psychological investment in completing otherwise uninspiring tasks, and to influence, or “nudge”, workers’ behaviour.

According to Burawoy, production at Allied was deliberately organised by management to encourage workers to play the game. When work took the form of a game, Burawoy observed, something interesting happened: workers’ primary source of conflict was no longer with the boss. Instead, tensions were dispersed between workers (the scheduling man, the truckers, the inspectors), between operators and their machines, and between operators and their own physical limitations (their stamina, precision of movement, focus). The battle to beat the quota also transformed a monotonous, soul-crushing job into an exciting outlet for workers to exercise their creativity, speed and skill. Workers attached notions of status and prestige to their output, and the game presented them with a series of choices throughout the day, affording them a sense of relative autonomy and control. It tapped into a worker’s desire for self-determination and self-expression. Then, it directed that desire towards the production of profit for their employer.

Former Google “design ethicist” Tristan Harris has also described how the “pull-to-refresh” mechanism used in most social media feeds mimics the clever architecture of a slot machine: users never know when they are going to experience gratification – a dozen new likes or retweets – but they know that gratification will eventually come. This unpredictability is addictive: behavioural psychologists have long understood that gambling uses variable reinforcement schedules – unpredictable intervals of uncertainty, anticipation and feedback – to condition players into playing just one more round.

Today, states grapple with decarceration and deinstitutionalization, not necessarily because of an ethical recognition of the continuing harm of confinement and segregation, or because of an understanding of the intertwined histories of capitalism, white supremacy, ableism, and punishment in the United States, but because of a desire to curb public spending on social services. These include the very services that people need as alternatives to more oppressive edifices and as preventive measures to winding up in such places. While public neighborhood urban schools, public housing, and mental health clinics are shuttered, private companies and “not for profit” services partially fill the void.

Alternatives emerge when facilities shut their doors. Closures, as prison justice organizer Angela Davis suggests, provide an opportunity for not only a “radical imagining” of the kind of social landscape desperately needed—but also the moment to build it. As people move between different forms and scales of cages, and as patterns of surveillance and punishment morph, new forms of capture do emerge and yet resistance is also possible. The state often refuses to offer services in place of the ones that were shuttered, leaving the responsibility to the individual (or her family and the market). This is a moment to collectively demand, fund, and build public infrastructure that will move everyone closer towards a world that does not rely on segregation and confinement, or access to private capital, as its mode of dealing with structural inequities.

The human brain has always loved the dopamine rush of notifications, in any form; recent research indicates the unpredictable but ubiquitous updates of Gmail or Twitter carry the same neurological effect as rocking a slot machine. While Internet use is "not addictive in the same way as pharmacological substances are," as cognitive scientist Tom Stafford noted in 2013, we continually chase those unpredictable payoffs on Facebook and Instagram in ways that tend to mirror gambling or sex addictions, even if "Internet addiction" writ large currently holds an ambiguous position in the Diagnostic and Statistical Manual of Mental Disorders.

For products whose fundamental business proposition is harnessing attention, building those so-called "compulsion loops" isn't an accident of technology—it's the whole point. Indeed, observers have argued since Parker's "human psychology" flub last year that Facebook has not just meticulously measured, but fundamentally altered human behavior, and nascent technology ventures emboldened by Facebook's world-changing success have sought to translate the behavioral tricks that psychologist B.F. Skinner applied to the gambling kiosk to every mobile app under the sun. "When a gambler feels favored by luck, dopamine is released," Natasha Schüll, author of Addiction by Design: Machine Gambling in Las Vegas, told the Guardian in March. All Facebook managed to do was find a way to miniaturize the captivating logic of the slot machine—with no cost to the user but their time and attention.

While the human brain is tremendously plastic, that doesn't mean Facebook is savagely rewiring the human brain. Indeed, the Facebook users in the Cal State–Fullerton study "showed greater activation of their amygdala and striatum, brain regions that are involved in impulsive behavior," as Live Science's Tia Ghose reported at the time. Ghose continued: "But unlike in the brains of cocaine addicts, for instance, the Facebook users showed no quieting of the brain systems responsible for inhibition in the prefrontal cortex." Facebook isn't fundamentally rewiring the structure of the human brain, but its ubiquity has the same relative effect by kicking our rewards centers into overdrive.

Artificial intelligence may have cracked the code on certain tasks that typically require human smarts, but in order to learn, these algorithms need vast quantities of data that humans have produced. They hoover up that information, rummage around in search of commonalities and correlations, and then offer a classification or prediction (whether that lesion is cancerous, whether you’ll default on your loan) based on the patterns they detect. Yet they’re only as clever as the data they’re trained on, which means that our limitations—our biases, our blind spots, our inattention—become theirs as well.

The majority of AI systems used in commercial applications—the ones that mediate our access to services like jobs, credit, and loans— are proprietary, their algorithms and training data kept hidden from public view. That makes it exceptionally difficult for an individual to interrogate the decisions of a machine or to know when an algorithm, trained on historical examples checkered by human bias, is stacked against them. And forget about trying to prove that AI systems may be violating human rights legislation.

Data is essential to the operation of an AI system. And the more complicated the system—the more layers in the neural nets, to translate speech or identify faces or calculate the likelihood someone defaults on a loan—the more data must be collected.

By measuring the eye movements of the test subjects, the scientists, from the University of Zurich and ETH Zurich, found that all the men, regardless of their environmental stance, paid less attention to negative imagery when stressed. This was true even for those men who were interested in climate change and considered themselves pro-environment