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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.

AI researchers have typically tried to get around the issues posed by by Montezuma’s Revenge and Pitfall! by instructing reinforcement-learning algorithms to explore randomly at times, while adding rewards for exploration—what’s known as “intrinsic motivation.” But the Uber researchers believe this fails to capture an important aspect of human curiosity. “We hypothesize that a major weakness of current intrinsic motivation algorithms is detachment,” they write. “Wherein the algorithms forget about promising areas they have visited, meaning they do not return to them to see if they lead to new states.”

The team’s new family of reinforcement-learning algorithms, dubbed Go-Explore, remember where they have been before, and will return to a particular area or task later on to see if it might help provide better overall results. The researchers also found that adding a little bit of domain knowledge, by having human players highlight interesting or important areas, sped up the algorithms’ learning and progress by a remarkable amount. This is significant because there may be many real-world situations where you would want an algorithm and a person to work together to solve a hard task.

In “Edible insects: Future prospects for food and feed security,” a 200-page report published in 2013, the UN’s Food and Agriculture Organization (FAO) noted that “Western societies require tailored media communication strategies and educational programmes that address the disgust factor” of eating insects. Bug banquets such as Bugsgiving offer one such educational opportunity. Yoon, who considers himself an “Edible Insect Ambassador,” focused on creating a family-style menu of dishes. “Instead of just serving crickets in a bowl or a chip, I want to serve black ants and shrimp, composed dishes—cricket gougères,” he says. “Things that represent a dish that [will make people] go, ‘Oh, that looks like food to me.’” Research cited by the UN proves that this strategy works: “Years of experimental experience in the Netherlands and the United States have confirmed the effectiveness of bug banquets in overcoming the disgust factor,” reads the 2013 FAO report.

Journalists can’t see the future, but they are able to peer through the lens of history to better understand the present. It’s a founding principle of Retro Report, the co-producer of this series. The future may be starkly different than the present, but it’ll be easier to understand once you uncover its deep continuity with the past. The social and technical transformations we’re currently living through are profound, but this isn’t the first time rapid, singular change has occurred. Before computer networks disrupted our communications, networks of steel rails and grids of artificial light upended our very concepts of space and time, day and night. Subtract trains and light bulbs from a modern city, and how much of it is even left?

The future has a history. And the stories we tell about incoming change—the stories we’ve always told about such changes—fall into consistent patterns. Dator gained some of his stature in future studies with his famous observation that predictions about the future—whether they’re coming from a corporate spreadsheet, a church pulpit or Hollywood—all boil down to roughly four scenarios. Growth that keeps going. Transformation upending the past. Collapse of the present order. And  discipline imposed, in some cases, to hold such collapse at bay.

“Most people, through their education, and through their acculturation, are locked into a single view of the future. They have never been encouraged to think about these alternatives, or forced to think about them,” Dator says.

Anthropologist Helen Fisher inelegantly described the maturing of this huge postwar bulge in the population as “like a pig moving through a python”, changing society as we grew older on a scale never known before. We challenged the Victorian puritanism, censorship, class snobbery and inhibitions of the establishment. Full employment put money in the pockets of managers and factory workers alike. In spanking new houses with inside lavatories and proper bathrooms, hire purchase allowed him (and less so, her) to spend, spend, spend as if, overnight, everyone had become a toff. It could only get better. Yet today, “baby boomer” is a toxic phrase, shorthand for greed and selfishness, for denying the benefits we took for granted to subsequent generations, notably beleaguered millennials, who reached adulthood in the early years of this century. So, where did it all go so very wrong?

Nearly every moment of our lives, we’re producing data about ourselves that companies profit from. Our smartwatches know when we wake up, Alexa listens to our private conversations, our phones track where we go, Google knows what we email and search, Facebook knows what we share with friends, and our loyalty cards remember what we buy. We share all this data about ourselves because we like the services these companies provide, and business leaders tell us we must to make it possible for those services to be cheap or free.

We should not only expect that these companies better protect our data – we should also ensure that everyone creating it shares in the economic value it generates. One person’s data is worth little, but the collection of lots of people’s data is what fuels the insights that companies use to make more money or networks, like Facebook, that marketers are so attracted to. Data isn’t the “new oil”, as some have claimed: it isn’t a non-renewable natural resource that comes from a piece of earth that a lucky property owner controls. We have all pitched in to create a new commonwealth of information about ourselves that is bigger than any single participant, and we should all benefit from it.

The value of our data has a lot in common with the value of our labor: a single individual worker, outside of the rarest professions, can be replaced by another with similar skills. But when workers organize to withhold their labor, they have much more power to ensure employers more fairly value it. Just as one worker is an island but organized workers are a force to be reckoned with, the users of digital platforms should organize not only for better protection of our data, but for a new contract that ensures everyone shares in the historic profits we make possible.

Hedges calls attention to the algorithms of Facebook, Google and Twitter, and how they steer traffic away from anti-war and progressive websites, while Miller speaks of the frightening historical precedent of the homogenization of the press. "I think what we have seen over the decades since the mid-'70s, and I'm going to make a provocative comparison here, is something analogous to what the Nazis called gleichschaltung, which means streamlining," Miller says. "When they came to power, they made it their business to make sure that not only all media outlets but all industries, all sectors of the culture, would be streamlined, which meant getting rid of anyone who was not fully on board with the Nazi program."

Amazon is announcing general availability in the U.S. for in-skill purchasing, which allows the creator of a skill to sell content to an Alexa user–both one-off purchases and monthly or yearly subscriptions, with the entire transaction handled inside the skill via voice on a device such as an Echo or a third-party Alexa-compatible gadget. (As with mobile app stores, developers get 70% of the price paid by users, and Amazon collects 30% as its reward for facilitating the transaction.) In addition, the company is opening up the ability for sellers of real-world goods and services to receive payment via Alexa using the Amazon Pay service; early adopters include 1-800-Flowers, TGI Friday’s, and Atom Tickets.

With Alexa’s new monetization features just reaching broad availability, it’s too early to gauge their long-term impact on the platform. But for the moment, at least, they give developers an incentive to devote even more resources to Amazon’s voice service rather than divert attention to its most formidable rival, Google Assistant. Google just launched a fund to invest in Google Assistant-centric startups–reminiscent of the Alexa Fund that Amazon established back in 2015–but it hasn’t yet given Assistant commerce features like the ones Alexa is adding.

“We’re at this inflection point with Alexa,” Rabuchin says. “We’ve laid the foundation for the voice economy, and now, by opening up all these monetization capabilities, we think it’s going to really take off in the next year.” The idea that an epoch-shifting phenomenon like Alexa hasn’t yet taken off is a bit of a mind-bender–but whatever happens next, it’s clearly entering a new phase.

As Foucault said of Bachelard a few years later, his characteristic approach was to avoid all defined hierarchies, any universal judgments: ‘He plays against his own culture with his own culture.’ He stood apart, separating himself from the mainstream, finding cracks, dissonances, minor phenomena that he could make his own. Poetry of every description was his raw material.

Indoors, in The Poetics of Space, the journey into intimacy is neatly evoked by drawers, cupboards, wardrobes and above all locks, although he warns, somewhat testily, against their use as gratuitous metaphors (and he is strongly averse to the idea of habit).

The wellbeing of the warm animal (or human) protected in its nest or cocoon or cottage from the bad weather raging outside is a primitive sense of refuge that we can all share, adult or child. The appeal of a safe haven translates into domestic architecture with such features as the accommodating Arts and Crafts inglenook, seats close by the fire, Frank Lloyd Wright’s enduring penchant for an immense fireplace buried at the core of a house, or even, a favourite 1960s touch, the conversation pit – with or without its trademark shagpile carpet.

Automation has not triggered mass unemployment, despite concerns about increasingly-realistic innovations like driverless trucks and ATMs that can handle mortgages. But already, around the edges, robots are on the rise — creating cost savings that benefit corporations and Americans who run businesses. These benefits are increasingly going to a small group at the top.In fact, the income gap between the super rich and middle class has also increased at a rapid clip — by $58,800 between 2010 and 2015, as Bloomberg reported. And within the middle class itself, the gap between upper and lower middle class grew by $9,000.