CHI HA PAURA

DELL’INTELLIGENZA

ARTIFICIALE?

Stefano Scarpetta, Director for Employment, Labour and Social Affairs, OECD

13th Edition Trento Festival Work and Technology

Trento, 31 May – 3 June

Sarà diverso questa volta ?La corsa tra Tecnologia and Istruzione

Inspired by “The race between technology and education” Pr. Goldin & Katz (Harvard)

Industrial revolution

Digital revolution

Social, labour market tension

Technology

Education

Prosperity

Prosperity

Social, labour market tension

La disoccupazione tecnologica: mito o realtà?

Employment-to-population ratios, age 15-64

4

1996, 2006 and 2016

45

50

55

60

65

70

75

80

Italy France EuropeanUnion

OECD United States G7 Canada UnitedKingdom

Japan Germany

% 20 years ago (1996) Pre-crisis level (2006) Current (2016, ↗)

I mega trends : non solo rivoluzione

digitale

5

Populations are ageing

The world has become more integrated

Share of business sector jobs sustained by consumers in

foreign markets

Old-age dependency ratio 65+/(15-64)

OECD average

The robots are coming

Estimated worldwide annual supply of industrial robots

2015

2050

0

100

200

300

400

500

600

20

03

20

04

20

05

20

06

20

07

20

08

20

09

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

18

20

19

20

20

'00

0 o

f u

nit

s

0%10%20%30%40%50%

Countries are experiencing rapid demographic change

Change in the working age population 2015-2050 (2015=100)

0,7

0,8

0,9

1

1,1

1,2

1,3

2015 2020 2025 2030 2035 2040 2045 2050

Australia (+27%)

United States (+10%)

UK (+6%)

Canada (+6%)

Korea (0%)

France (+1%)

Germany (-23%)

Italy (-23%)

Japan (-28%)

The world has become more integrated

through trade

0

10

20

30

40

50

60

Bra

zil

United S

tate

s

Japan

Austr

alia

India

Indonesia

Chin

a

Turk

ey

UK

Fra

nce

Italy

Russia

South

Afr

ica

Canada

Mexic

o

Ge

rma

ny

Ko

rea

1975 2014

0

5

10

15

20

25

30

35

40

45

50

Bra

zil

Un

ite

d S

tate

s

Ja

pa

n

Ch

ina

Au

str

alia

Ru

ssia

Ind

on

esia

Ind

ia

Ita

ly

UK

Fra

nce

Tu

rke

y

Ca

na

da

So

uth

Afr

ica

Me

xic

o

Ge

rma

ny

Ko

rea

1975 2014

A. Exports (% of GDP) B. Imports (% of GDP)

Winners take (almost) all?

Il gap di produttività tra le imprese globali più

produttive e le altre è aumentato

Labour productivity: value added per worker, 2001-2013

-10

0

10

20

30

40

50

Frontier firms

Laggard firms

-10

0

10

20

30

40

50

Frontier firms

Laggard firms

A. Manufacturing B. Services

Il futuro è già realtà

The disappearing middle: jobs by skill level (% change in employment shares 1995-2015)

Emerging skill gaps

(unweighted OECD average)

9

New vacancies for gig workers(May 2016=100)

90

100

110

120

130

140

150

May

-16

Jul-

16

Sep

-16

No

v-1

6

Jan

-17

Mar

-17

May

-17

Jul-

17

Sep

-17

No

v-1

7

Jan

-18

-0,015-0,01

-0,0050

0,0050,01

0,0150,02

Man

ufa

ctu

rin

gan

d P

rod

uct

ion

Co

mp

ute

rs a

nd

Elec

tro

nic

s

Equ

ipm

ent

Mai

nte

nan

ce

Co

mp

lex

Pro

ble

mSo

lvin

g

Stat

ic S

tren

gth

Ver

bal

Ab

iliti

es

Knowledge Skills Abilities

Source: Oxford Internet Institute, Online Labor Index

-15

-10

-5

0

5

10

15

France UnitedKingdom

Italy OECDAverage

Germany UnitedStates

Canada Japan

High skill Middle skill Low skill

Only a minority of jobs at risk of full automation(as a % of all jobs)

0

10

20

30

40

50

60Risk of significant change (50-70%)

0

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0.08

0.09

0.1

Within-sector Between-sector

Percentage-point change in polarisation between 1997 and 2007

10

La polarizzazione all’interno dei comparti

produttivi più che attraverso I cambiamenti

nella struttura produttiva

Nell’era dell’IA, il rischio di automazione è

concentrato tra I lavoratori a basse

competenze e salari

Highest risk in routine jobswith low skill and education requirement BUT low risk applies to a broad range from professionals to social workers

Automation mostly affects manufacturing industry and agriculture BUT some service sectors are highly automatable too.

The risk of automation falls monotonically with hourly wages

The risk of automation also falls with educational attainment

No evidence of polarisation or rising risk at the high end: automation risk declines with skills, education and hourly wages

Young people are the most at risk of automation, followed by older workers, with disappearing student jobs and entry positions.

Share of jobs at risk of automation, by industry and gender

20 industries with the highest share of jobs at risk, 29 OECD countries/regions

Non è chiaro se le donne saranno

svantaggiate rispetto agli uomini

50 40 30 20 10 0 10 20 30 40 50

EducationComputer programming, consultancy and…

Public administration and defenceSocial work activities without accommodation

Human health activitiesFinancial service activities

Manufacture of computer, electronic and…Legal and accounting activities

Residential care activitiesInsurance, reinsurance and pension funding

Manufacture of machinery and equipment…Manufacture of motor vehicles, trailers and…Wholesale trade, except of motor vehicles…

Specialized construction activitiesManufacture of fabricated metal products

Manufacture of food productsLand transport and transport via pipelines

Wholesale and retail trade and repair of…Retail trade, except of motor vehicles and…

Food and beverage service activities

Male share (average risk of automation) Female share (average risk of automation)

0 2,5 5 7,5 10

Employment…

High

Low

Sha

re o

f job

s at

ris

k

L’adozione delle nuove tecnologie non è inevitabile

In which areas is the application of robots most/least acceptable?

-80

-60

-40

-20

0

20

40

60

Are

as o

f ro

bo

ts u

sage

ind

ex

Source: Eurobarometer.

In molti paesi la precarizzazione del lavoro è

già una realtà

0

5

10

15

20

25

USA

AU

S

GB

R

JPN

RU

S

DEU

TUR

CA

N

ITA

FRA

MEX

KO

R

1995 2015

0

1

2

3

4

5

6

7

8

9

102

00

5

20

06

20

07

20

08

20

09

20

10

20

11

20

12

20

13

20

14

20

15

%

ITAESPAUS

FRA

GBR

DEU

USA

TUR

RUS

Share of involuntary part-time workers

(as a share of total employment)Share of temporary employment

(as a share of dependent employment)

I lavoratori autonomi hanno una probabilità

maggiore di avere una remunerazione al di

sotto del salario minimo

0

5

10

15

20

25

30

35

40

PRT POL HUN GRC CZE ESP SVK NLD USA IRL GBR EST BEL LVA LUX FRA SVN

Employee Own-account workers

Source: OECD estimates based on EU-SILC for EU countries and the March Supplement of the CPS for the United States.

Proportion of workers below 75% of the minimum wage

16

Molti lavoratori non sono pronti al

nuovo mondo del lavoro digitale

Share of 25-34 and 55-64 year-olds performing at Level 2 or 3 in problem solving

in technology-rich environments

150

170

190

210

230

250

270

290

310

330Less than upper secondary Upper secondary Tertiary

Il livello di istruzione non coincide con il livello

di competenze (giovani 25-34 anni):

Cambiamento incrementale, o rivoluzione copernicana?

18

Social dialogue: Strengthen or reinvent?Social protection: Repair or replace?

Lifelong learning: from rhetoric to reality Regulation: Balancing flexibility with security

Providing better

guidance on how to classify workers

Reducing incentives to take up new forms

of work

A better balance in burden of proof of

work status

Ensuring fair pay for

work

Participation rate in training (%)

Effective access to social protection for the self-employed Trade union members as a % of all employees

18

0

5

10

15

20

25

30

35

40

Europeanunion

Japan

UnitedStates

020406080

100

high skilled low skilled

• Need a level playing field between businesses – success should be linked

to superior product/service/business model, not to avoidance of

tax/regulation

• In the end, business will foot the bill through higher taxes

• Over-use of such employment arrangements could also have negative

effects on productivity

Migliori regole per la gig economy, anche per

le imprese e non solo per I lavoratori!

19

Grazie

Contatti: Stefano.Scarpetta@oecd.org

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