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The future of jobs - Contenido educativo

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Subido el 8 de febrero de 2022 por Eva M.

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The future of some jobs.

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And now, work. What will you be doing as a job in the future? 00:00:04
Well, 50 years ago, the world of work was pretty easy to understand. 00:00:09
You either did manual work, which basically meant supervising machines, 00:00:12
or you worked in an office, which basically meant doing a lot of typing 00:00:17
or getting somebody else to do a lot of typing for you. 00:00:20
Bottom line, people were integral to the workforce, but no more. 00:00:23
Because in the 1970s, machines got clever. 00:00:29
Car plants were filled with robots, 00:00:33
helplines were answered by computers 00:00:35
and almost all bank clerks became extinct. 00:00:37
But I suspect that most of you are saying, 00:00:40
well, a robot couldn't possibly take my job. 00:00:42
But are you sure? 00:00:45
Have a look at this. 00:00:46
We sent Dr Zoe Williams to check out a piece of software 00:00:50
which is rumoured to diagnose illnesses faster 00:00:53
and more accurately than human medical professionals. 00:00:56
so should I be worried as a GP the thought that a robot or artificial intelligence could take 00:01:00
my job just seems crazy I mean I've spent six years at medical school ten years practicing 00:01:08
as a doctor now surely all of that can't be boiled down to a few lines of code Babylon 00:01:14
health are a medical tech company they've just received sixty million dollars of funding to 00:01:23
develop an AI doctor the system works by asking questions but anyone can ask 00:01:29
questions if it's going to replace me I really want to put it through its paces 00:01:37
I'm gonna pose as a patient and give myself an imaginary condition and I'm 00:01:42
not going to tell anybody I'm just gonna write it down and then we can see just 00:01:47
how accurate the machine really is may I ask please what's troubling you today 00:01:54
I'm feeling tired all the time so as well as feeling tired I've been feeling 00:02:00
kind of weak let's tell the computer that and I've also been feeling a bit of 00:02:08
dizziness is it okay to ask do you have painful 00:02:17
periods there we go I said so painful periods as well do you get breathless on exertion yes I do 00:02:22
thanks I've noted this so I've given the computer all of my symptoms now and it's come up with a 00:02:31
diagnosis so let's see if it's correct here's my bit of paper from earlier and you can see that I 00:02:39
I have put down fibroids and the computer has said 00:02:47
uterine leiomyoma, which is actually the same thing. 00:02:52
That's impressive, but how's it done? 00:02:57
Time to face down the evil genius 00:03:01
hell-bent on replacing me with my laptop. 00:03:03
So you start off with a knowledge base, 00:03:06
and this is essentially a medical database 00:03:10
which contains hundreds of millions of medical concepts. 00:03:12
That's kind of like being at medical school 00:03:15
and all the knowledge that is inputted into the brain. 00:03:17
Exactly, so this might be all of the textbooks 00:03:20
which you've read at medical school, 00:03:22
all of the papers which you've read at medical school, 00:03:23
and then apply it to all of that information. 00:03:25
We'll apply a set of methods known as machine learning methods. 00:03:27
Machine learning is the ability of computers 00:03:33
to take vast amounts of data and make sense of it themselves. 00:03:36
Like this network of medical information 00:03:41
which the computer uses to make a diagnosis. 00:03:44
What those circles represent are diseases, symptoms and risk factors, and what those 00:03:47
lines represent are the relationships between those. So based on that the computer has taught 00:03:53
itself actually how strongly related those diseases, symptoms and risk factors are. 00:03:58
OK, so that's how it determines the probability is from looking at past real life cases? 00:04:03
Absolutely, and that's why this is machine learning. 00:04:08
the network learns about more and more symptoms and diseases, it's tested and refined by a team 00:04:15
of doctors and programmers. It's early days, but the company sees a big future for their virtual 00:04:20
medic. We will do with healthcare what, say, Google did with information. It'll be in your 00:04:27
phone, it'll be in the devices you understand, you carry with you. Do you think that a machine 00:04:33
could ever replace my role as a GP? 00:04:38
I don't think this is a competition between machines and humans. 00:04:42
This is machines being an aid to humans. 00:04:46
Half of the world's population has no access 00:04:49
or very, very little access to doctors, right? 00:04:52
Imagine if you could see so many more, 00:04:56
because the machines do the easier part, they save your time. 00:04:58
But can a machine put its hand on your shoulder and say, 00:05:02
Trust me, I look after you. That's a different story. 00:05:05
It's not just in medicine that software's on the march. 00:05:10
In banking, AI is approving or not approving loan applications 00:05:14
and even making investment decisions. 00:05:18
And with autonomous vehicles on the horizon, 00:05:22
many who drive for a living will soon be superseded. 00:05:25
What you need to know about the future 00:05:30
is that no job is immune from the influence of artificial intelligence. 00:05:32
And if it doesn't take your job, 00:05:37
then it's likely to change the way in which you do it. 00:05:38
Idioma/s:
en
Autor/es:
Speak-out
Subido por:
Eva M.
Licencia:
Reconocimiento - No comercial
Visualizaciones:
120
Fecha:
8 de febrero de 2022 - 18:18
Visibilidad:
Público
Centro:
EOI E.O.I. MADRID-VILLAVERDE
Duración:
05′ 48″
Relación de aspecto:
1.78:1
Resolución:
800x450 píxeles
Tamaño:
131.70 MBytes

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