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Will AI Take Your Job in the Next 10 Years? Wrong Question | Vinciane Beauchene | TED - Video học tiếng Anh
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Will AI Take Your Job in the Next 10 Years? Wrong Question | Vinciane Beauchene | TED
Will AI Take Your Job in the Next 10 Years? Wrong Question | Vinciane Beauchene | TED
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Phụ đề (209)
0:04
Back in the 50s, Alan Turing came up with an idea.
0:09
If you couldn't tell if you were talking to a machine or a human,
0:14
it meant the machine must be intelligent.
0:17
He coined the Turing test.
0:20
Today, most chatbots pass the test easily.
0:25
But here's the catch.
0:27
I believe the test was wrong.
0:30
Because talking isn't what's going to change the world.
0:34
Doing is.
0:36
That's why I ask a slightly different question
0:39
to the leaders I work with.
0:41
On a daily basis, my role is to reshape organizations,
0:45
trying to find the right mix of strategy, tech and talent.
0:52
And my obsession is to make sure
0:54
that talents do not get out of the equation.
0:58
So the question I ask my clients is:
1:02
if an AI could take over all of your team's tasks,
1:07
who would you keep
1:09
and why?
1:11
That question is strategic.
1:13
And the answer matters to me, not just intellectually,
1:17
but because I have two daughters at home.
1:20
They are five and nine.
1:22
And right now, as you can see, they feel invincible.
1:26
But I keep wondering:
1:28
What is the world of work they will step into?
1:32
We need to build a future where humans matter more, not less.
1:38
Now let me try to illustrate how this is playing out in the field.
1:43
A consumer goods client of mine is all in on AI.
1:48
They didn't want to just deploy the next algo.
1:51
They wanted to rethink the selling process itself.
1:56
The trigger was agents.
1:59
Have you heard about agents?
2:01
They are the latest generation of AI:
2:05
more autonomous,
2:06
able to connect across systems,
2:09
to plan, to take action, to learn, to adapt.
2:12
The James Bond of AI.
2:15
And applied to the selling process,
2:18
you get an agent that is able to target the customer,
2:22
make recommendations, negotiate, close the deal.
2:26
All this with no human intervention.
2:30
A fully autonomous sales engine.
2:34
And it was technically feasible.
2:37
But then an exec asked,
2:40
"Hmm, if the machine does all of this,
2:45
then what remains for humans?"
2:47
This cracked everything open
2:49
because when we looked deeper at their most loyal customers,
2:54
we saw they weren’t sticking around because of prices or products
2:58
but because of how the sales rep made them feel.
3:03
So we flipped the model around.
3:06
Humans were no longer going to be about pushing products.
3:10
They were going to be about building relationship,
3:13
belonging, loyalty.
3:17
Very concretely, this meant new skills,
3:20
new incentives, a very different mindset.
3:24
Well it changed everything.
3:26
But it worked.
3:28
Because in the age of AI, human value isn't gone.
3:33
It's just moved.
3:35
Now I’m not talking about copilots anymore.
3:38
For a while the narrative has been
3:41
AI will augment us, not replace us.
3:45
Well this is not where the tech is going today.
3:48
And I believe we have real hard work to do
3:51
if we want this narrative to stay true.
3:55
So I'll say a few words about what I think needs to be done
3:58
in a second.
3:59
But first, let me tackle three myths that I think are holding us back.
4:05
I call them "head in the sand" ideology.
4:10
Number one.
4:12
"All of this is overblown. We'll adapt."
4:16
Yes. We've adapted to electricity,
4:20
the industrial revolution, the internet.
4:23
But we've done so on the back of generations
4:26
that did not have the training nor the time to adapt.
4:30
And in the case of this revolution, time is of the essence.
4:35
You may think you have time because agents are just emerging.
4:39
And it's a fact.
4:40
Our research shows that today only 13 percent of companies
4:45
have embedded agents in their workflows.
4:49
But tech moves exponentially.
4:51
Humans, they crawl linearly.
4:54
If you don't prepare now, you'll struggle to keep up.
4:59
And I'm not talking about science fiction.
5:01
I'm not talking about AGI,
5:03
artificial general intelligence,
5:06
this moment where AI will be smarter than us.
5:10
I'm referring here to ACI,
5:13
artificial capable intelligence.
5:17
The moment when AI will be able to take on
5:21
ambiguous, complex goals
5:24
with minimal oversight.
5:26
And while AGI is speculative,
5:29
ACI is a deadline.
5:32
While we spend hours debating about superintelligence and consciousness,
5:38
we miss the milestones that ACI is meeting with increasing frequency.
5:44
ACI will change how work is done and by whom.
5:49
Let's shape it, not wait and see.
5:52
Now myth number two.
5:54
"Soft skills are our sweet spot."
5:59
Yes, it's lovely to believe
6:01
that empathy, creativity are uniquely ours.
6:06
But evidence says otherwise.
6:09
More and more humans like to interact with AI
6:14
because they feel it's more empathic.
6:18
And why not?
6:19
I mean, AI
6:22
doesn't get tired,
6:24
doesn't get cranky,
6:26
doesn't judge you.
6:28
So this moat we thought was ours,
6:31
it's shrinking.
6:33
And we need to stop asking what AI can't do
6:36
and focus on where humans make a difference and why.
6:43
At this stage,
6:45
I'm sure you would love me to come up
6:47
with the list of human qualities that will remain ours forever.
6:53
But my point is, there is no universal list.
6:56
Each company needs to figure it out based on its strategic positioning.
7:02
This is hard, uncomfortable work,
7:05
but it's work that you as leaders need to take on.
7:10
Now myth number three.
7:13
My preferred one. I'm French.
7:14
"We need to protect jobs."
7:18
Yes. I see where this one is coming from.
7:21
Today, 41 percent of employees believe
7:25
that their job will vanish in the next decade because of AI.
7:30
But protecting jobs is like anchoring a boat in a storm.
7:34
Jobs are fixed.
7:37
The human potential to grow and adapt, on the other hand, is not.
7:41
This is where we need to invest.
7:44
The challenge is our organizations are not geared for that today.
7:48
Org charts are static.
7:49
Career paths are narrow.
7:51
Training is occasional.
7:53
This system will fall apart
7:55
the day that the boundaries of jobs start melting away fast.
8:01
So what do we need to do?
8:05
Let me take you to an ideal company.
8:08
Not a theoretical one, just the blend of the boldest clients I've worked with.
8:14
First, they don't start with tech.
8:18
They start with strategy.
8:21
They focus on the outcomes that truly differentiate them on the market.
8:26
They understand how agents
8:28
will allow them to deliver against those outcomes
8:31
in totally different ways.
8:34
And they look at where people still make a difference for the better.
8:39
As you can see, this is not incremental redesign of your operating model.
8:45
It's radical AI-first reinvention.
8:49
And we did this work for an industrial goods client of mine.
8:53
Imagine having to go through 50 “hack a future” workshops,
8:57
looking at how AI is going to disrupt each of your businesses,
9:01
each of your function.
9:03
Comfortable? It is not.
9:06
But it allowed the leaders to align on a vision of where agents win,
9:11
people matter and how best to pair them.
9:15
Now once you have this vision,
9:17
you want to translate it into a workforce model.
9:21
How many people do I need?
9:23
With what skills?
9:25
No more guesswork, just informed, intentional reinvention.
9:30
A multiyear skills forecast.
9:33
And this is something we built
9:35
for a consumer goods client that was facing a massive challenge.
9:39
Imagine having to reformulate your entire product portfolio
9:44
while keeping the leadership and innovation.
9:47
Of course, AI unlocked the productivity that was required,
9:52
but the work was much deeper.
9:54
They needed to reinvent the role of the researcher.
9:58
From chemist to data-driven biologist,
10:01
from solo expert to multifunctional teammates.
10:05
And they made it happen
10:07
because they mapped very precisely the future skills that they needed,
10:11
and they built a very effective upskilling and mobility engine.
10:17
Then you want to publicly commit
10:21
to taking your talents to their fullest potential.
10:25
Now I know what you're going to tell me.
10:27
Vinciane, why would we invest in talent
10:30
if an AI can do their job faster, cheaper
10:35
and without complaining?
10:38
Well because the day that interacting with an AI becomes the new norm,
10:43
a commodity,
10:45
the interaction with humans is going to take an entire new meaning.
10:50
Trust, authenticity, accountability.
10:55
Those are the values we will anchor on.
10:58
So the smartest companies will invest in talent.
11:03
Not only tech talent, all talent.
11:06
Not once, but systematically.
11:09
And they will protect time to learn.
11:13
Because today, while freelancers spend on average four hours per week learning,
11:18
employees spend
11:20
none.
11:22
So no, the future isn't about being more human.
11:26
It's about building the systems
11:28
that will allow humans to do what matters most.
11:31
This is not a story about job loss.
11:35
It is a story about human differentiation.
11:39
AI will keep on climbing. That is not up to us.
11:42
But how fast we climb with it, that is up to us.
11:47
So we need to stop asking: Will there still be jobs for humans?
11:52
And focus on answering: What do we want humans to be best at?
11:59
Because in the age of AI,
12:01
being human isn't a fallback,
12:04
it's a practice.
12:06
Let's make it exceptional.
12:10
Thank you.
12:11
(Applause)
