RESUME

Inside the ultimate drugmobile

MAD MATH

Clive thompeson

Leave the driving to US

 Machines can make decisions. That doesn’t mean they’re right

So you can’t wait for a self-driving car to take away the drudgery of driving ? me neither! But consider this scenario, recently posed by neuroscientist inte your lane. Shoul your self driving car plunge off the brigade sacrificing your live to save those of the cildren ? obviously, you wna’t make the call. You’ve ceded that decision to the car’s algorithms. You batter hope that you agree with its choic. This is s dramatic dilemma, to be sure. But it’s not a completly unusual one. The thuth is, our tools.

Increasingly guid and shape our ehavior or even make decisions on our behalf. A samal but growing chorus of wriers and scholars think we’re going too far. By taking human decisionmaking out of the equation, we’re slowly stripping away deliberation-moments where we reflect on the morality of our actions.

Not all of these situations are so life-and-death. Some are quite prosaic, like the walter of new gadgets that thy tod “nudge” us into batter behavior. In this new book to save everiting, click hare, evgeny morozov casts a skeptical eye on this stuff. He tells me abaut a recent example he’s seen:A “smart fork” that monitors hou much you’re eating and warns you if you’re ovardoing it.

Fun and useful, you migh argue. But for morozov,tolls like the fork reduce your incetive to think about how you’re eting and the deeper political questions of why today’s food ecosystemis so enfattening. “instead of regulating the food industry to make food healthier,” morozov say, “we’re giving people smart forks.”

 Or as evan seliger, a philosopher at rochester  institute of tachnology,puts it, tools taht make hard things easy can make us less likely to tolerate thing that are hard. Outssourcing our self-control to “digital willpower” has consequences: use siri constanly to get instant information and you can erode your ability to by patient in the face of incomplate answers, a crucial civic virtue.

Things get even dicier when society  at large outesoursces its bigeste moral decision to tochnology. For exmple, some police departments have begun using predpol, a system that mines crime data to predict future criminal activity, guiding police to areas they might otherwise overloke. It apppears to work, cutting some crimes by up to 27 percent. It lets charonically underfunded deparemens do more with less.

But as morozov points out, the algorithms could wind up ampolifying flaws in existing law enforfcement. For example, sexual violence  is historiclly underreported, so it can’t ass easly be predicted. Remove the deliberation of what police focus an and you can wind up deforming policing. And doing “more with less,” while a worthy short-term goal, lets politicans dodge the political impact of their budgetary choices,

 And this, really, is the core of the question here: efficiency isn’t always a good thing. Tech lets us do things more easily. But this can mean doing them less reflectively too.

We’re not going to throw aut all tecnology, not should we. Efficiency isn’t always bad. Bud morozov suggests that sometimes tolls should do the oposite-they should introduce friction. For example, new parking maters reset when you drive away, so another drive can’t draft off of any remaining time. The city makes more money, obviously, but that design also compels you behavior. What if a “smart” meter instead offeredy you a choice:  gift remaining time to the next driver or to the city ? this would foreground the tiny moral trade-offs of daily life-city  versus citizen.

 Or consider the caterpillar, a prototype power strip created by german designers that detects when a plugged in device is in standby mode. Insted of tourning off the device a tradisional eff/ cienci move the caterpilar leaves in on, but start writing, the point is to draw your atention to you power usage, to porce you to turn it off yourslf and mediate on why you’re  using si much.

 These are kinds of crazy, of course. They’re not tols that solve problams. They’re tolls to make you think abaut problame-which is preciseselly the point. 

Quite        : agak

Behavior   :tingkah laku

Stripping   : pengupasan

Incentive   : insentif

Compels    : memeksa

Reamining : sisa

Anciente    : kuno

Angle        : kemarahan

Announce  : mengumumkan

Alongside  : di samping

Already     : suah

Alsle          : lorong

Ahead        : di depan

Aid            : membantu

Advanced  : maju

Drudgery   : pekerjaan yang membosankan

Accurately : akurat

Achieve     : mencapai

Accident    : kecelakaan