The World Of Professional Creativity

The intersection between commerce, technology and culture has long been a place of anxiety and foreboding. Marxist critics in the 1940s denounced the assembly-line approach to filmmaking that Hollywood had pioneered; in the ’60s, we feared the rise of television’s ‘‘vast wasteland’’; the ’80s demonized the record executives who were making money off violent rap lyrics and ‘‘Darling Nikki’’; in the ’90s, critics accused bookstore chains and Walmart of undermining the subtle curations of independent bookshops and record stores.

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Take a look at your own media consumption, and you can most likely see the logic of the argument. Just calculate for a second how many things you used to pay for that now arrive free of charge: all those Spotify playlists that were once $15 CDs; the countless hours of YouTube videos your kids watch each week; online articles that once required a magazine subscription or a few bucks at the newsstand. And even when you do manage to pull out a credit card, the amounts are shrinking: $9 for an e-book that used to be a $20 hardcover. If the prices of traditional media keep falling, then it seems logical to critics that we will end up in a world in which no one has an economic incentive to follow creative passions. The thrust of this argument is simple and bleak: that the digital economy creates a kind of structural impossibility that art will make money in the future. The world of professional creativity, the critics fear, will soon be swallowed by the profusion of amateurs, or the collapse of prices in an age of infinite and instant reproduction will cheapen art so that no one will be able to quit their day jobs to make it — or both.

And yet Steven Johnson, in The New York Times, continues this essay by making the argument for the creative apocalypse that wasn't: "in the digital economy, it was supposed to be impossible to make money by making art. Instead, creative careers are thriving — but in complicated and unexpected ways."

Wil Reynolds: The Hidden Danger of Confusing Outputs for Outcome

Reynolds started Seer Interactive—a leading SEO and online marketing agency—in a small apartment back in 2002. Since then, the company has grown to more than 100 people. But scaling the company was not without its growing pains. In this energetic talk, Reynolds shares how he learned to put a "lid on his hustle" and made sure his values weren't compromised as his company grew. "Getting things done means giving things up," he says. "It can't all fit. You need to have the border."

Christoph Niemann: How to Overcome the 3 Fears Every Creative Faces

There are three primary fears creatives, like artist, illustrator, and author Christoph Niemann, face: the fear of not being good enough, the fear that our work will be irrelevant, and the fear of running out of ideas. Niemann explains how these fears are very real, but that there are solutions we can apply to each.

Teaching Machines to Understand Us→

The first time Yann LeCun revolutionized artificial intelligence, it was a false dawn. It was 1995, and for almost a decade, the young Frenchman had been dedicated to what many computer scientists considered a bad idea: that crudely mimicking certain features of the brain was the best way to bring about intelligent machines. But LeCun had shown that this approach could produce something strikingly smart—and useful. Working at Bell Labs, he made software that roughly simulated neurons and learned to read handwritten text by looking at many different examples. Bell Labs’ corporate parent, AT&T, used it to sell the first machines capable of reading the handwriting on checks and written forms. To LeCun and a few fellow believers in artificial neural networks, it seemed to mark the beginning of an era in which machines could learn many other skills previously limited to humans. It wasn’t.

That's how the fantastic featured story by Tom Simonite begins in the latest issue of MIT Technology Review. It is definitely worth the read. 

Polite Robots Show Glimmer Of Self-Awareness

Popular Science: 

The robots were programed to think that two of them had been given a “dumbing pill” that would make them unable to speak (actually just a button that silenced them). However, they didn't know exactly which two of them had been silenced. When the robots were asked to answer which two had been given the pill, all of them tried to respond: “I don’t know.” Since only one was actually able to utter the words, it heard its own voice and recognized it wasn't among the two who had been silenced. That robot then responded: “Sorry, I know now. I was able to prove that I was not given a dumbing pill.”