Category: ideas

“In many scientific fields, from genetics to economics to palaeobiology, a kind of implicit trust is placed in the images and the algorithms that produce them. Often viewers have almost no idea how they were constructed. The complexity of computers has made data-analysis a black-box, something it’s hard for humans to peer into. At the same time, computer jockeys such as my dad have achieved a new cultural status – if not quite Indiana Jones, they still have a kind of power and authority most of us can’t access. Increasingly, with the advances in machine-learning and AI, even those authorities are sometimes mystified by how their algorithms work.”

Last month, a team from the digital agency AKQA and the Misk Global Forum attended several panels at the World Economic Forum and used each discussion as inspiration to illustrate a job that could exist by 2030. Many of the jobs seem more like science fiction than reality, but a few are actually pretty grounded in where technology seems to be headed.

Yes, it probably does (same for Louis CK or writers now being accused of misogyny, abuse, and more). “Saying ‘I always hated his work’ might be a cheap hipster pose, but it also might be bitterness born of long-suppressed, impotent anger. If you’ve grown used to being shamed or condescended to for caring about an ugly thread that everyone else seemed to be overlooking, the sudden shift is gratifying, but also exhausting.”

Why would the politicians who make those decisions think this was a good one? “The council said in a statement that fines can be ‘off-putting for customers,’ and it hopes the change, which will see library fines eliminated across Trafford for all ages from April, will lead to ‘a further increase in usage of libraries across the borough.'”

In a recent book, The Hard Thing About Hard Things, the tech investor Ben Horowitz adds a twist: “The Law of Crappy People”. As soon as someone on a given rung at a company gets as good as the worst person the next rung up, he or she may expect a promotion. Yet, if it’s granted, the firm’s talent levels will gradually slide downhill. No one person need be peculiarly crappy for this to occur; bureaucracies just tend to be crappier than the sum of their parts.

“According to The Wall Street Journal, printers are among the most in-demand objects in ‘rage rooms,’ where people pay to smash things with sledgehammers; Battle Sports, a rage-room facility in Toronto, goes through fifteen a week. … Unsurprisingly, the engineers who specialize in paper jams see them differently. Engineers tend to work in narrow subspecialties, but solving a jam requires knowledge of physics, chemistry, mechanical engineering, computer programming, and interface design.”

If you’re a jerk, it’s useful to have a midlife crisis; it gives your irresponsible behavior an existential sheen. Almost certainly, the term is overused.

“These networks clearly aren’t cheating in the way that the digesting duck was. But does all this biological inspiration mean that they work like the brain? One way to approach this question is to look more closely at their performance. To this end, scientists are studying ‘adversarial examples’ – real images that programmers alter so that the machine makes a mistake. Very small tweaks to images can be catastrophic: changing a few pixels on an image of a teapot, for example, can make the network label it an ostrich. It’s a mistake a human would never make, and suggests that something about these networks is functioning differently from the human brain.”

“If innovation is founded on data rather than human ideas, the firms that benefit are the ones that have access to the most data. Therefore, in many instances, innovation will no longer be a countervailing force to market concentration and scale. Instead, innovation will be a force that furthers them.”

Despite the current limitations, fashion seems ripe for an AI invasion; it’s an arena that has great data sets on customers’ interests, and there is a lot of money at stake. Amazon, for one, is already working on AI systems to provide a leg up in spotting fashion trends, and it has also done some work with GANs (see “Amazon Has Developed an AI Fashion Designer”). Alibaba, meanwhile, just debuted FashionAI, a technology that can recommend items to shoppers on the basis of what they brought into the dressing room.