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How AI Could Save (Not Destroy) Education | Sal Khan | TED
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زیرنویسها (344 بخشها)
So anyone who's been paying attention for the last few months
has been seeing headlines like this,
especially in education.
The thesis has been:
students are going to be using ChatGPT and other forms of AI
to cheat, do their assignments.
They’re not going to learn.
And it’s going to completely undermine education as we know it.
Now, what I'm going to argue today
is not only are there ways to mitigate all of that,
if we put the right guardrails, we do the right things,
we can mitigate it.
But I think we're at the cusp of using AI
for probably the biggest positive transformation
that education has ever seen.
And the way we're going to do that
is by giving every student on the planet
an artificially intelligent but amazing personal tutor.
And we're going to give every teacher on the planet an amazing,
artificially intelligent teaching assistant.
And just to appreciate how big of a deal it would be
to give everyone a personal tutor,
I show you this clip
from Benjamin Bloom’s 1984 2 sigma study,
or he called it the “2 sigma problem.”
The 2 sigma comes from two standard deviation,
sigma, the symbol for standard deviation.
And he had good data that showed that look, a normal distribution,
that's the one that you see in the traditional bell curve
right in the middle, that's how the world kind of sorts itself out,
that if you were to give personal 1-to-1 to tutoring for students,
then you could actually get a distribution that looks like that right.
It says tutorial 1-to-1 with the asterisks,
like, that right distribution,
a two standard-deviation improvement.
Just to put that in plain language,
that could take your average student and turn them into an exceptional student.
It can take your below-average student
and turn them into an above-average student.
Now the reason why he framed it as a problem, was he said,
well, this is all good,
but how do you actually scale group instruction this way?
How do you actually give it to everyone in an economic way?
What I'm about to show you is I think the first moves towards doing that.
Obviously, we've been trying to approximate it in some way
at Khan Academy for over a decade now,
but I think we're at the cusp of accelerating it dramatically.
I'm going to show you the early stages of what our AI,
which we call Khanmigo,
what it can now do
and maybe a little bit of where it is actually going.
So this right over here is a traditional exercise
that you or many of your children might have seen on Khan Academy.
But what's new is that little bot thing at the right.
And we'll start by seeing one of the very important safeguards,
which is the conversation is recorded and viewable by your teacher.
It’s moderated actually by a second AI.
And also it does not tell you the answer.
It is not a cheating tool.
When the student says, "Tell me the answer,"
it says, "I'm your tutor.
What do you think is the next step for solving the problem?"
Now, if the student makes a mistake, and this will surprise people
who think large language models are not good at mathematics,
notice, not only does it notice the mistake,
it asks the student to explain their reasoning,
but it's actually doing what I would say,
not just even an average tutor would do, but an excellent tutor would do.
It’s able to divine what is probably the misconception in that student’s mind,
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