Display Bilingual:

[music] 00:02
[music] 00:08
>> People worry about AI for all kinds of 00:11
reasons. It's polarizing, it spreads 00:14
misinformation, it's coming for our 00:16
jobs. And those are all good reasons to 00:18
be nervous. 00:21
But what really keeps me up at night is 00:22
something else. Something that feels 00:24
more personal and perhaps even more 00:26
concerning for the human experience 00:28
itself. 00:30
I worry that AI will make us boring. 00:31
You, me, all of us. 00:34
That's because the more we outsource our 00:37
decisions to AI, the more we surrender 00:39
something deeply human. 00:41
Our capacity to explore, to take risks, 00:43
to stumble into the unknown, and 00:47
sometimes surprise even ourselves. 00:48
I worry without that without the 00:51
potential for discovery, for 00:53
serendipity, we risk becoming more 00:54
shallow and unidimensional versions of 00:57
who we are and who we could be. 00:59
Not just as humans, as individuals, but 01:02
as humanity. 01:04
Now, let me make this idea a bit more 01:06
concrete and take you somewhere perhaps 01:08
unexpected, but also totally relatable. 01:10
Imagine walking into a Baskin Robbins. 01:14
What you'll see is an illustrious 01:17
assortment of 31 different ice cream 01:18
flavors. There's chocolate chip, 01:20
pistachio almond, lemon sorbet, and many 01:22
more. 01:24
You're now facing a difficult choice. 01:26
Are you going to go with an old 01:28
favorite, chocolate maybe, or are you 01:29
going to take a risk on something funky 01:31
and new like wild and reckless sherbet? 01:33
And yes, it's a real flavor. 01:37
The choice you're facing is a classic 01:40
human dilemma scientists call the 01:42
exploitation exploration trade-off. 01:44
Are you going to play it safe and 01:47
capitalize on what you know you like, or 01:49
are you going to take a risk with the 01:51
hope of finding something even better? 01:53
And our lives are full of these 01:56
trade-offs. Stick with your favorite 01:57
restaurant or try to fancy new spot on 01:59
the corner. Keep your usual haircut or 02:00
ask for something new and edgy. Stay in 02:03
your stable job or finally try to become 02:05
a pickleball champion. 02:08
We all differ in our appetite for 02:12
exploitation versus exploration, but 02:14
we're also all hardwired by evolution to 02:17
strike a certain balance between the 02:19
two. 02:21
Because for our ancestors on the African 02:22
savanna, the trade-off was actually 02:23
pretty simple. Stick too closely to 02:25
what's safe and you risk starvation when 02:27
the grove runs dry. Stray too far into 02:29
the unknown and you might get poisoned 02:32
or eaten by lions. 02:33
Luckily for you and me, the trade-offs 02:36
we face today are far less about 02:37
survival. 02:39
But our choices are still governed by 02:41
this instinct to balance caution with 02:42
curiosity. 02:44
If all you ever did in life was play it 02:46
safe and exploit, you'd never get 02:49
disappointed. But you'd also never get a 02:51
chance to advance and grow. 02:53
If all you did instead was discover and 02:56
explore, you'd collect endless 02:58
experiences, but you'd also never get a 03:00
chance to capitalize on your learnings. 03:02
So it's really this balance between 03:05
exploitation and exploration that fuels 03:07
our growth. 03:09
Not just as a species, but also as 03:11
individuals. 03:13
But that's exactly where AI throws a 03:15
wrench into the works. 03:17
Because AI hates risk. 03:19
And that's not because of its 03:22
algorithmic DNA, it's because the 03:23
systems we rely on to navigate our world 03:26
from Spotify to Netflix to ChatGPT are 03:28
overwhelmingly trained to optimize for 03:31
exploitation. 03:33
Or more specifically for short-term 03:35
engagement and satisfaction. 03:36
Did you click the link, watch the video, 03:39
like the song? If yes, AI gets a clap on 03:40
the shoulder. If no, gets a slap on the 03:44
hand. 03:46
Risk, discovery, and exploration are 03:47
simply not part of their programming. 03:49
Think back to Baskin Robbins. If 60% of 03:52
people prefer the flavor Pralines 'n 03:55
Cream, which is their best-selling 03:57
flavor, then that's what the AI is going 03:59
to recommend. 04:01
It's not that AI lacks imagination, it 04:02
lacks incentive. 04:05
Safe bets protect against 04:07
disappointment, which in turn reduces 04:09
customer churn. 04:11
So instead of taking this risky gamble 04:13
that helps you explore, companies tend 04:15
to err on the side of exploitation when 04:17
training their AI systems. 04:19
And to be clear, there's nothing 04:23
inherently wrong with that. I've spent 04:24
the last 15 years as a computational 04:26
social scientist working at the 04:28
intersection of psychology, computer 04:30
science, and business. And I know that 04:32
rewarding AI that way can be extremely 04:34
valuable. 04:37
Algorithms in a way only become so good 04:38
at figuring out what you might enjoy or 04:41
currently be looking for because they 04:43
focus on exploitation. 04:44
And that's not just good for business, 04:47
it's also good and sometimes even 04:49
necessary for us as consumers. 04:51
For me, the mere thought of having to 04:54
choose between 31 different ice cream 04:56
flavors makes me dizzy. 04:57
And yet, most of the choices that we 05:00
face day-to-day are far more complex 05:01
than that. 05:03
Netflix, for example, has over 5,500 05:05
movies to choose from. 05:07
Spotify, over 100 million songs. 05:09
So the truth is that without a little 05:12
help from our exploitation-loving AI 05:14
friends, we simply don't stand a chance 05:17
of navigating modern life. 05:19
But I've also become increasingly 05:22
concerned that this upside comes at a 05:23
somewhat existential cost. 05:26
And to give you a first flavor of what I 05:28
mean by that, let's go back to Baskin 05:30
Robbins. 05:32
Before coming here, I ran a simple 05:33
experiment. I asked ChatGPT to recommend 05:35
one of their ice cream flavors. I did 05:38
that 100 times, each round pretending to 05:40
be a new customer. 05:43
96 times, it recommended one of their 05:45
two most popular flavors, Pralines 'n 05:47
Cream and Mint Chocolate Chip. 05:50
Which, I realize and I'm sure you'd 05:53
agree, is not exactly a very diverse set 05:55
of choices. 05:57
And it could mean that we soon find 05:59
ourselves in a world where Baskin 06:01
Robbins offers only those two flavors. 06:02
If no one ever picks the other 29, why 06:05
bother offering them in the first place? 06:07
Now, this might sound trivial and not 06:10
really existential at all. 06:13
But that's only until you realize that 06:15
this flattening of the human experience 06:17
happens across every aspect of life. 06:19
In studies with my collaborators and 06:22
students, we've shown that when people 06:24
use AI for guidance, 06:26
their preferences become more normative 06:28
and less diverse. Their creative output 06:30
becomes less unique. And their choice of 06:32
the most important scientists, athletes, 06:35
and historical figures becomes the same 06:37
as everyone else's. 06:39
So in a nutshell, AI turns this infinite 06:42
diversity of human opinions, beliefs, 06:44
and preferences into statistically safe 06:47
sameness. 06:50
And that's only part of the problem 06:53
because even when AI learns your quirks, 06:55
say it figures out that you like nutty 06:57
coconut better than Pralines 'n Cream, 06:59
it will still play it safe within your 07:02
preferences. Meaning it is going to 07:04
optimize for what you are most likely to 07:06
like. 07:08
I went back to ChatGPT for a second 07:10
experiment and this time told it about 07:11
my personal ice cream preferences. I 07:13
said that during my last 100 visits, I 07:15
picked nutty coconut 70% of the time. 07:18
The remaining 30% I split evenly among 07:21
three of my other favorites. 07:24
I then asked it to make the next 100 07:26
choices on my behalf. 07:28
And guess what it did. 07:30
It picked nutty coconut every single 07:32
time. 07:35
Gone 07:37
are my adventures into occasional 07:38
chocolate fudge cookie dough or mango. 07:40
All I am at that point is literally a 07:43
nutty coconut. 07:45
But forget about ice cream. My students 07:50
and I have repeatedly shown the same 07:52
patterns when studying people's actual 07:54
preferences. 07:55
AI narrows your taste, it flattens your 07:57
personality, and it scrubs away the 08:00
edges that make you interesting and keep 08:02
you dynamic. 08:04
And the insidious part of all of this is 08:06
that the impact of AI on human 08:08
complexity is subtle. You won't notice 08:10
it happening overnight. 08:12
Rather, it's a death by a thousand 08:14
algorithmic recommendations. One 08:15
slightly safer movie, one slightly more 08:18
popular book, one slightly more 08:20
mainstream vacation at a time. 08:21
With every decision you outsource to AI, 08:24
you become more narrow. Then AI learns 08:27
from that shallower version of you and 08:29
narrows its recommendations even more. 08:31
The New York Times reporter Kashmir Hill 08:34
captured this dilemma perfectly in one 08:37
of her articles. 08:39
After outsourcing her decisions to AI 08:41
for a week, she complained about its 08:42
hidden agenda to turn her into a basic 08:44
08:47
And the funny part is it's the word 08:51
basic here that's the biggest insult. 08:52
Because being basic means being 08:57
unoriginal, unexceptional, and 08:59
uninteresting. 09:01
It's offensive not because it suggests 09:02
failure, but because it implies 09:05
mediocrity. 09:07
An absence of complexity. 09:08
And who really wants that for 09:12
themselves? 09:13
Nobody. We all like the feeling of being 09:15
unique, of being special, of being 09:18
someone who doesn't easily fit into a 09:19
box. 09:21
I for one don't want to become exactly 09:23
like everybody else. And I also don't 09:25
want to become a singular version of 09:27
myself. 09:29
So what can we do to course correct and 09:31
avoid destination basic 09:33
We can't hit the reset button on AI and 09:37
we shouldn't. As I said before, these 09:39
tools are incredibly valuable for 09:41
navigating modern life and they make us 09:43
better off in many ways. 09:45
But we need to reclaim our ability to 09:47
take risks and discover. 09:50
We need to find a way to rebalance 09:52
exploitation and exploration. 09:54
And ironically, AI could actually help 09:58
us accomplish just that. 10:00
But only if we ask it the right 10:02
questions and reward it for the right 10:03
actions. 10:06
So, instead of asking it to help us find 10:07
something we like, we could start asking 10:09
it to help us find something new. 10:11
Something we're likely to love even 10:13
though we've never tried it before. 10:15
And by that, I don't necessarily mean 10:18
you typing that question into ChatGPT 10:19
yourself. 10:21
Although you should certainly try. 10:23
What I mean is getting companies to 10:24
harness AI superpower. It's ability to 10:27
detect patterns in vast amounts of human 10:30
data for exploration purposes. 10:32
Because AI has seen the entire universe 10:36
of preferences, it knows not only what 10:38
you currently like, but also what lies 10:40
just beyond the boundaries of your 10:42
typical preferences. 10:44
Which means that it can help you explore 10:46
smartly. To take curated risks when you 10:48
want to. 10:51
Now, here's what this could look like. 10:52
Imagine a dial on your Netflix account 10:54
or your Google search bar that lets you 10:56
decide how far from your typical 10:59
preferences you want to stray at any 11:01
given point in time. 11:03
On a regular day, you'll probably keep 11:05
the dial close to the spot-on setting 11:07
because you want to get the most 11:09
relevant hits right away. 11:10
But then on other days, you might feel 11:13
adventurous enough to push it a little 11:14
closer to the me with a twist setting 11:16
and ask for content that's a little 11:19
outside of your comfort zone, but still 11:21
relevant. 11:23
And then on other days, for those rare 11:25
moments when you feel like you're really 11:26
ready to take on the world, you might 11:28
push the dial all the way to the wild 11:30
card setting and ask it to help you 11:32
discover something entirely new. 11:34
I for one would love to have such a 11:37
dial. It doesn't force me to leave my 11:39
comfort zone. I can always leave it on 11:42
the spot-on setting and benefit from the 11:43
convenience that comes with it. 11:46
But it gives me the choice and the 11:48
agency to break out of my little bubble 11:50
whenever I want to or I feel like I have 11:52
to. 11:54
But here's the catch. For AI to toggle 11:56
its superpower between exploitation and 11:58
exploration, we need to incentivize it 12:01
to do so. 12:03
Merely asking it to be more creative or 12:05
help you become more adventurous isn't 12:07
going to do the trick. 12:09
In most cases, it will still default to 12:11
the tried and tested output because it 12:13
craves that clap on the shoulder. 12:15
So, instead of punishing AI every time 12:17
it takes a swing and misses, we need to 12:20
start rewarding it for taking smart 12:22
swings. 12:24
For making bets that are a little bold, 12:25
a little unusual perhaps, but still 12:27
grounded in what it knows about us. 12:29
AI doesn't have to throw darts in the 12:32
dark. It can take informed risks. It can 12:34
help us optimize our exploration. 12:37
And when it does, we should treat it as 12:41
a success, not a failure. 12:42
Now, this isn't about desserts or 12:46
playlists. This is about preserving what 12:48
makes us uniquely, messily, and 12:50
gloriously human. 12:52
It's your random passion for ET 12:54
memorabilia, your weird detour into 12:56
geocaching, or your stubborn preference 12:58
for a stick shift car. 13:00
It's about all the contradictions that 13:03
AI can't quite explain and the beauty of 13:05
us being just a little weird once in a 13:07
while. 13:09
And if we believe that human complexity 13:12
is worth preserving, then the time to 13:14
act is now. 13:16
Because we're at this inflection point 13:17
where AI is no longer just recommending, 13:19
but starting to act on our behalf. 13:21
It's choosing, not suggesting. 13:24
And that's where the stakes become 13:28
really existential. 13:29
So, next time AI offers you pralines and 13:31
cream, maybe say no and ask it to help 13:34
you go wild and reckless instead. 13:37
Thank you. 13:41
>> [music] 13:43

– English Lyrics

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[English]
[music]
[music]
>> People worry about AI for all kinds of
reasons. It's polarizing, it spreads
misinformation, it's coming for our
jobs. And those are all good reasons to
be nervous.
But what really keeps me up at night is
something else. Something that feels
more personal and perhaps even more
concerning for the human experience
itself.
I worry that AI will make us boring.
You, me, all of us.
That's because the more we outsource our
decisions to AI, the more we surrender
something deeply human.
Our capacity to explore, to take risks,
to stumble into the unknown, and
sometimes surprise even ourselves.
I worry without that without the
potential for discovery, for
serendipity, we risk becoming more
shallow and unidimensional versions of
who we are and who we could be.
Not just as humans, as individuals, but
as humanity.
Now, let me make this idea a bit more
concrete and take you somewhere perhaps
unexpected, but also totally relatable.
Imagine walking into a Baskin Robbins.
What you'll see is an illustrious
assortment of 31 different ice cream
flavors. There's chocolate chip,
pistachio almond, lemon sorbet, and many
more.
You're now facing a difficult choice.
Are you going to go with an old
favorite, chocolate maybe, or are you
going to take a risk on something funky
and new like wild and reckless sherbet?
And yes, it's a real flavor.
The choice you're facing is a classic
human dilemma scientists call the
exploitation exploration trade-off.
Are you going to play it safe and
capitalize on what you know you like, or
are you going to take a risk with the
hope of finding something even better?
And our lives are full of these
trade-offs. Stick with your favorite
restaurant or try to fancy new spot on
the corner. Keep your usual haircut or
ask for something new and edgy. Stay in
your stable job or finally try to become
a pickleball champion.
We all differ in our appetite for
exploitation versus exploration, but
we're also all hardwired by evolution to
strike a certain balance between the
two.
Because for our ancestors on the African
savanna, the trade-off was actually
pretty simple. Stick too closely to
what's safe and you risk starvation when
the grove runs dry. Stray too far into
the unknown and you might get poisoned
or eaten by lions.
Luckily for you and me, the trade-offs
we face today are far less about
survival.
But our choices are still governed by
this instinct to balance caution with
curiosity.
If all you ever did in life was play it
safe and exploit, you'd never get
disappointed. But you'd also never get a
chance to advance and grow.
If all you did instead was discover and
explore, you'd collect endless
experiences, but you'd also never get a
chance to capitalize on your learnings.
So it's really this balance between
exploitation and exploration that fuels
our growth.
Not just as a species, but also as
individuals.
But that's exactly where AI throws a
wrench into the works.
Because AI hates risk.
And that's not because of its
algorithmic DNA, it's because the
systems we rely on to navigate our world
from Spotify to Netflix to ChatGPT are
overwhelmingly trained to optimize for
exploitation.
Or more specifically for short-term
engagement and satisfaction.
Did you click the link, watch the video,
like the song? If yes, AI gets a clap on
the shoulder. If no, gets a slap on the
hand.
Risk, discovery, and exploration are
simply not part of their programming.
Think back to Baskin Robbins. If 60% of
people prefer the flavor Pralines 'n
Cream, which is their best-selling
flavor, then that's what the AI is going
to recommend.
It's not that AI lacks imagination, it
lacks incentive.
Safe bets protect against
disappointment, which in turn reduces
customer churn.
So instead of taking this risky gamble
that helps you explore, companies tend
to err on the side of exploitation when
training their AI systems.
And to be clear, there's nothing
inherently wrong with that. I've spent
the last 15 years as a computational
social scientist working at the
intersection of psychology, computer
science, and business. And I know that
rewarding AI that way can be extremely
valuable.
Algorithms in a way only become so good
at figuring out what you might enjoy or
currently be looking for because they
focus on exploitation.
And that's not just good for business,
it's also good and sometimes even
necessary for us as consumers.
For me, the mere thought of having to
choose between 31 different ice cream
flavors makes me dizzy.
And yet, most of the choices that we
face day-to-day are far more complex
than that.
Netflix, for example, has over 5,500
movies to choose from.
Spotify, over 100 million songs.
So the truth is that without a little
help from our exploitation-loving AI
friends, we simply don't stand a chance
of navigating modern life.
But I've also become increasingly
concerned that this upside comes at a
somewhat existential cost.
And to give you a first flavor of what I
mean by that, let's go back to Baskin
Robbins.
Before coming here, I ran a simple
experiment. I asked ChatGPT to recommend
one of their ice cream flavors. I did
that 100 times, each round pretending to
be a new customer.
96 times, it recommended one of their
two most popular flavors, Pralines 'n
Cream and Mint Chocolate Chip.
Which, I realize and I'm sure you'd
agree, is not exactly a very diverse set
of choices.
And it could mean that we soon find
ourselves in a world where Baskin
Robbins offers only those two flavors.
If no one ever picks the other 29, why
bother offering them in the first place?
Now, this might sound trivial and not
really existential at all.
But that's only until you realize that
this flattening of the human experience
happens across every aspect of life.
In studies with my collaborators and
students, we've shown that when people
use AI for guidance,
their preferences become more normative
and less diverse. Their creative output
becomes less unique. And their choice of
the most important scientists, athletes,
and historical figures becomes the same
as everyone else's.
So in a nutshell, AI turns this infinite
diversity of human opinions, beliefs,
and preferences into statistically safe
sameness.
And that's only part of the problem
because even when AI learns your quirks,
say it figures out that you like nutty
coconut better than Pralines 'n Cream,
it will still play it safe within your
preferences. Meaning it is going to
optimize for what you are most likely to
like.
I went back to ChatGPT for a second
experiment and this time told it about
my personal ice cream preferences. I
said that during my last 100 visits, I
picked nutty coconut 70% of the time.
The remaining 30% I split evenly among
three of my other favorites.
I then asked it to make the next 100
choices on my behalf.
And guess what it did.
It picked nutty coconut every single
time.
Gone
are my adventures into occasional
chocolate fudge cookie dough or mango.
All I am at that point is literally a
nutty coconut.
But forget about ice cream. My students
and I have repeatedly shown the same
patterns when studying people's actual
preferences.
AI narrows your taste, it flattens your
personality, and it scrubs away the
edges that make you interesting and keep
you dynamic.
And the insidious part of all of this is
that the impact of AI on human
complexity is subtle. You won't notice
it happening overnight.
Rather, it's a death by a thousand
algorithmic recommendations. One
slightly safer movie, one slightly more
popular book, one slightly more
mainstream vacation at a time.
With every decision you outsource to AI,
you become more narrow. Then AI learns
from that shallower version of you and
narrows its recommendations even more.
The New York Times reporter Kashmir Hill
captured this dilemma perfectly in one
of her articles.
After outsourcing her decisions to AI
for a week, she complained about its
hidden agenda to turn her into a basic
...
And the funny part is it's the word
basic here that's the biggest insult.
Because being basic means being
unoriginal, unexceptional, and
uninteresting.
It's offensive not because it suggests
failure, but because it implies
mediocrity.
An absence of complexity.
And who really wants that for
themselves?
Nobody. We all like the feeling of being
unique, of being special, of being
someone who doesn't easily fit into a
box.
I for one don't want to become exactly
like everybody else. And I also don't
want to become a singular version of
myself.
So what can we do to course correct and
avoid destination basic
We can't hit the reset button on AI and
we shouldn't. As I said before, these
tools are incredibly valuable for
navigating modern life and they make us
better off in many ways.
But we need to reclaim our ability to
take risks and discover.
We need to find a way to rebalance
exploitation and exploration.
And ironically, AI could actually help
us accomplish just that.
But only if we ask it the right
questions and reward it for the right
actions.
So, instead of asking it to help us find
something we like, we could start asking
it to help us find something new.
Something we're likely to love even
though we've never tried it before.
And by that, I don't necessarily mean
you typing that question into ChatGPT
yourself.
Although you should certainly try.
What I mean is getting companies to
harness AI superpower. It's ability to
detect patterns in vast amounts of human
data for exploration purposes.
Because AI has seen the entire universe
of preferences, it knows not only what
you currently like, but also what lies
just beyond the boundaries of your
typical preferences.
Which means that it can help you explore
smartly. To take curated risks when you
want to.
Now, here's what this could look like.
Imagine a dial on your Netflix account
or your Google search bar that lets you
decide how far from your typical
preferences you want to stray at any
given point in time.
On a regular day, you'll probably keep
the dial close to the spot-on setting
because you want to get the most
relevant hits right away.
But then on other days, you might feel
adventurous enough to push it a little
closer to the me with a twist setting
and ask for content that's a little
outside of your comfort zone, but still
relevant.
And then on other days, for those rare
moments when you feel like you're really
ready to take on the world, you might
push the dial all the way to the wild
card setting and ask it to help you
discover something entirely new.
I for one would love to have such a
dial. It doesn't force me to leave my
comfort zone. I can always leave it on
the spot-on setting and benefit from the
convenience that comes with it.
But it gives me the choice and the
agency to break out of my little bubble
whenever I want to or I feel like I have
to.
But here's the catch. For AI to toggle
its superpower between exploitation and
exploration, we need to incentivize it
to do so.
Merely asking it to be more creative or
help you become more adventurous isn't
going to do the trick.
In most cases, it will still default to
the tried and tested output because it
craves that clap on the shoulder.
So, instead of punishing AI every time
it takes a swing and misses, we need to
start rewarding it for taking smart
swings.
For making bets that are a little bold,
a little unusual perhaps, but still
grounded in what it knows about us.
AI doesn't have to throw darts in the
dark. It can take informed risks. It can
help us optimize our exploration.
And when it does, we should treat it as
a success, not a failure.
Now, this isn't about desserts or
playlists. This is about preserving what
makes us uniquely, messily, and
gloriously human.
It's your random passion for ET
memorabilia, your weird detour into
geocaching, or your stubborn preference
for a stick shift car.
It's about all the contradictions that
AI can't quite explain and the beauty of
us being just a little weird once in a
while.
And if we believe that human complexity
is worth preserving, then the time to
act is now.
Because we're at this inflection point
where AI is no longer just recommending,
but starting to act on our behalf.
It's choosing, not suggesting.
And that's where the stakes become
really existential.
So, next time AI offers you pralines and
cream, maybe say no and ask it to help
you go wild and reckless instead.
Thank you.
>> [music]

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Vocabulary Meanings

polarizing

/ˈpoʊləˌraɪzɪŋ/

C2
  • adjective
  • - causing people to adopt extreme opposing views

misinformation

/ˌmɪsɪnfərˈmeɪʃən/

B2
  • noun
  • - false or inaccurate information

surrender

/səˈrɛndər/

B2
  • verb
  • - to give up or yield control

serendipity

/ˌsɛrənˈdɪpɪti/

C2
  • noun
  • - the occurrence of events by chance in a happy way

unidimensional

/ˌʌndɪˈmɛnʃənəl/

C2
  • adjective
  • - lacking depth or complexity

illustrious

/ɪˈlʌstriəs/

C2
  • adjective
  • - well-known, respected, and admired for past achievements

exploitation

/ˌɛksplɔɪˈteɪʃən/

C1
  • noun
  • - the action of making use of and benefiting from resources

capitalize

/ˈkæpɪtəˌlaɪz/

B2
  • verb
  • - to take the chance to gain advantage from

insidious

/ɪnˈsɪdiəs/

C2
  • adjective
  • - proceeding in a gradual, subtle way, but with harmful effects

mediocrity

/ˌmidiˈɒkrɪti/

C2
  • noun
  • - the quality of being average or not very good

harness

/ˈhɑːrnɪs/

B2
  • verb
  • - to utilize or control something for a purpose

curated

/ˈkjʊəreɪtɪd/

B2
  • adjective
  • - selected, organized, and presented using professional knowledge

agency

/ˈeɪdʒənsi/

B2
  • noun
  • - the capacity of individuals to act independently and make their own free choices

inflection

/ɪnˈflɛkʃən/

C2
  • noun
  • - a moment of significant change

detour

/ˈdiːtʊr/

B2
  • noun
  • - a long or roundabout route taken to avoid something

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Key Grammar Structures

  • What really keeps me up at night is something else.

    ➔ Noun Clause as Subject

    ➔ The clause "What really keeps me up at night" acts as the subject of the sentence.

  • The more we outsource our decisions to AI, the more we surrender something deeply human.

    ➔ The + comparative, the + comparative structure

    ➔ This parallel structure shows that one action or state increases proportionally with another.

  • I worry without the potential for discovery, for serendipity, we risk becoming more shallow.

    ➔ Omitted 'that' in a subordinate clause

    ➔ The word "that" after "worry" is implied to connect the main clause to the object clause.

  • If all you ever did in life was play it safe and exploit, you'd never get disappointed.

    ➔ Second Conditional (Hypothetical situation)

    ➔ Uses past tense verbs to describe a hypothetical, unlikely, or impossible scenario.

  • I've spent the last 15 years as a computational social scientist working at the intersection of psychology, computer science, and business.

    ➔ Present Perfect Continuous (or Present Perfect + participle)

    "I've spent" emphasizes an action that started in the past and continues to the present.

  • Without a little help from our exploitation-loving AI friends, we simply don't stand a chance of navigating modern life.

    ➔ Compound Adjective

    "Exploitation-loving" combines a noun and a participle to modify "AI friends".

  • AI narrows your taste, it flattens your personality, and it scrubs away the edges.

    ➔ Parallel Structure (Parallelism)

    ➔ Using the same grammatical form (verb + object) for three consecutive items to create rhythm and emphasis.

  • I don't want to become exactly like everybody else.

    ➔ Infinitive as object

    "to become" functions as the object of the verb "want".

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