Econ_June_09

The Economist

June 9th 2018

Leaders 13

better recovery. It reduced its budget deficit, cleaned up its

banks and freed its labour market. Thanks to growth that has

exceeded 3% a year since 2015, Spain’s output is now above its

pre-crisis level. Italy, by contrast, has been slowtodealwith the

losses at its banks, and its labour-market reforms have been

timid. Its recovery is among the weakest in the euro zone, and

output still languishes below the pre-crisis peak.

Bust and boom

The difference lies in political leadership. In many ways, Mr

Rajoy has served his country well. Taking office in December

2011, in the teeth of the crisis, he administered tough medicine

consistently. Until this month a remarkable political survivor,

he hadmanaged to hold on to powerwithout a parliamentary

majority for two and a half years.

He had his limitations. His pigheadedness meant that he

could not stop the drama in Catalonia from turning into a cri-

sis, culminating in a unilateral declaration of independence

last October. That prompted direct rule from Madrid, lifted

only now that the separatists, who won a regional election in

December, have at last agreed on a new government. Above

all, Mr Rajoy could never throw off the shadow of old corrup-

tion scandals in his People’s Party. A court verdict on some of

these triggered the censuremotion that destroyed him.

Yet he leaves Spain in better shape than Italy—not just eco-

nomically but politically. Italy’s big problem is that the elector-

ate has lost confidence in mainstream politics. Well over half

the voters at the election inMarch chose parties from the polit-

ical extremes. Italy has had no equivalent of France’s presi-

dent, Emmanuel Macron, to reconstitute the splintered centre.

In Spain, too, established parties have suffered at the hands

of insurgents. One new lot, Podemos, is anti-capitalist and left-

wing (it wants to scrap the labour reforms, among other

things), but it has struggled to reach 20% in polls. By contrast,

the other newcomer, Ciudadanos, is broadly liberal and some-

what technocratic. It belongs to the centre and has become its

country’s most popular party. Crucially, Spain has no signifi-

cant movement on the nationalist right, unlike Italy, France

and many others, including Poland and Hungary. Indeed, tol-

erance of refugees and migrants has been an impressive fea-

ture of Spanish democracy.

Difficulties lie ahead. Unemployment, and the debt stock,

are still too high. The Catalan crisis continues to fester. But Mr

Sánchez promises tomaintain both the old government’s bud-

get and, it seems, its labour reform. He also looks a better bet

than the stubborn Mr Rajoy to explore political solutions in

Catalonia. In due course, these may require new constitution-

al changes. Progress will not be easy, and Mr Sánchez may not

get far before hisweakparliamentary position derails him. But

Spain’s politics look more stable than Italy’s, with its fading

mainstream parties and the pantomime-horse of populists in

government. Hard reform and economic recovery have pre-

vented greater political instability. For that, at least, Spaniards

owe

muchas gracias

to dourMr Rajoy.

ADIOLOGISTS, say the pes-

simists, will be first against

the wall when the machines

take over. Analysing medical

images is a natural fit for “deep

learning”, an artificial-intelli-

gence (

) technique which first

attracted attention for its ability

to teach computers to recognise objects in pictures. A variety

of companies hope that bringing

into the clinic will make

diagnosis faster and cheaper. The machines may even be able

to see nuances that humans cannot, assessing how risky a pa-

tient’s cancer is simply by looking at a scan.

Some

researchers think that human beings can be dis-

pensed with entirely. “It’s quite obvious that we should stop

training radiologists,” saidGeoffreyHinton, an

luminary, in

2016. In November Andrew Ng, another superstar researcher,

when discussing

’s ability to diagnose pneumonia from

chest

-rays, wondered whether “radiologists should be wor-

ried about their jobs”. Given howwidely applicable machine

learning seems to be, such pronouncements are bound to

alarmwhite-collarworkers, fromengineers to lawyers.

In fact the application of

to medicine suggests that the

story is more complicated. Machine learning will indeed

change many fields, allowing the rapid analysis of enormous

piles of data to uncover insights that people might overlook.

But it is not about to make humans redundant. And radiology,

the very field that is used as a cautionary tale about the robo-

pocalypse, showswhy.

One is the nature of

itself. The field is suffusedwithhype.

Some papers show artificial radiologists outperforming the

ones in white coats (see Science section). Others, though, still

put the humans ahead. The machines may eventually take an

unambiguous lead. But it is important to remember that

, for

the foreseeable future, will remain “narrow”, not general. No

human is as good at mental arithmetic as a $10 pocket calcula-

tor, but that is all the calculator can do. Deep learning is broad-

er. It is a pattern-recognition technique, and patterns are every-

where in nature. But in the end it, too, is limited—a sort of

electronic idiot-savant which excels at one particular mental

task but is baffled by others. Instead ofwonderingwhether

can replace a job, it is better to ponderwhether it could replace

humans at a specific task.

The human touch

That leads to a second reason for optimism: the nature ofwork.

Most jobs involve many tasks, even if that is not always obvi-

ous to outsiders. Spreadsheets have yet to send the accoun-

tants to the dole queue, because there is more to accountancy

thanmaking columns of figures add up. Radiologists analyse a

lot ofimages. But theyalsodecidewhich images shouldbe tak-

en, confer on tricky diagnoses, discuss treatment plans with

their patients, translate the conclusions of the research litera-

ture into the messy business of real-life practice, and so on.

AI, radiology and the future of work

Images aren’t everything

Clevermachineswill makeworkersmore productivemore often than theywill replace them