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: [email protected]
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20
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