Anthony Goldbloom: The jobs we'll lose to machines -- and the ones we won't
Anthony Goldbloom: Les emplois que nous perdrons (ou pas) au profit des machines
Anthony Goldbloom crowdsources solutions to difficult problems using machine learning. Full bio
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and her dad is a lawyer.
et son père est avocat.
are going to look dramatically different.
auront dramatiquement changé.
did a study on the future of work.
de l'université d'Oxford
sur l'avenir du travail.
in every two jobs have a high risk
sur deux avait de forts risques
de ces disruptions.
of this disruption.
of artificial intelligence.
la plus puissante.
that humans can do.
comportements humains.
on the cutting edge of machine learning.
de l'apprentissage automatique.
hundreds of thousands of experts
des centaines de milliers d'experts
for industry and academia.
industriels et académiques.
on what machines can do,
de ce que les machines peuvent faire,
automate or threaten.
automatiser ou menacer.
into industry in the early '90s.
au début des années 1990.
étaient assez simples :
credit risk from loan applications,
relatifs aux demandeurs de crédit,
handwritten characters from zip codes.
les codes postaux manuscrits.
dramatic breakthroughs.
fait des avancées spectaculaires.
of far, far more complex tasks.
d'effectuer des tâches plus complexes.
that could grade high-school essays.
les dissertations de lycéens.
were able to match the grades
pouvaient égaler les notes
an even more difficult challenge.
le défi était encore plus difficile.
and diagnose an eye disease
diagnostiquer une maladie oculaire
were able to match the diagnoses
faisaient les mêmes diagnostics
machines are going to outperform humans
les machines peuvent surpasser les humains
over a 40-year career.
en 40 ans de carrière.
or see millions of eyes
des millions de dissertations,
against machines
concurrencer les machines
that machines can't do.
que les machines ne peuvent pas faire.
very little progress
they haven't seen many times before.
n'ont pas déjà vu nombre de fois.
of machine learning
de l'apprentissage automatique
from large volumes of past data.
d'un important volume de données passées.
seemingly disparate threads
des idées apparemment disparates
jusqu'alors inconnus.
working on radar during World War II,
pendant la Seconde Guerre Mondiale
was melting his chocolate bar.
faisait fondre son chocolat.
of electromagnetic radiation
des radiations électromagnétiques
the microwave oven.
le four à micro-ondes.
example of creativity.
de créativité.
happens for each of us in small ways
se produit de plein de façons,
novel situations,
on the human tasks
for the future of work?
pour le futur du travail ?
in the answer to a single question:
réside dans une seule question :
to frequent, high-volume tasks,
cet emploi peut-il être réduit
tackling novel situations?
la gestion de nouvelles situations ?
machines are getting smarter and smarter.
les machines s'améliorent encore.
They diagnose certain diseases.
et font des diagnostics.
they're going to conduct our audits,
elles conduiront nos audits
from legal contracts.
des contrats légaux standards.
for complex tax structuring,
pour la structuration fiscale complexe,
on novel situations.
sur les situations nouvelles.
needs to grab consumers' attention.
attirer l'attention des consommateurs.
finding gaps in the market,
c'est percer le marché,
the copy behind our marketing campaigns,
ces campagnes de promotion
our business strategy.
nos stratégies commerciales.
ahead of the machines.
de l'avance sur les machines.
ABOUT THE SPEAKER
Anthony Goldbloom - Machine learning expertAnthony Goldbloom crowdsources solutions to difficult problems using machine learning.
Why you should listen
Anthony Goldbloom is the co-founder and CEO of Kaggle. Kaggle hosts machine learning competitions, where data scientists download data and upload solutions to difficult problems. Kaggle has a community of over 600,000 data scientists and has worked with companies ranging Facebook to GE on problems ranging from predicting friendships to flight arrival times.
Before Kaggle, Anthony worked as an econometrician at the Reserve Bank of Australia, and before that the Australian Treasury. In 2011 and 2012, Forbes named Anthony one of the 30 under 30 in technology; in 2013 the MIT Tech Review named him one of top 35 innovators under the age of 35, and the University of Melbourne awarded him an Alumni of Distinction Award. He holds a first call honors degree in Econometrics from the University of Melbourne.
Anthony Goldbloom | Speaker | TED.com