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
