Here is a question. How many of the behaviors mentioned in this video do you think apply to you?

Utterly 완전히

syn- completely, fully, totally, entirely, whole, thoroughly

you don't get to tell me what to do 넌 나한테 뭘하라고 말하지 못해

as much time and energy as possible 가능한 모든 시간과 에너지를

false sense of moral superiority (widely used phrases) 도덕적 우월감에 대한 그릇된 생각

accountable 책임감 있는

sustainable 유지할 수 있는, 지탱할수 있는

douchey internet personality - to describe individuals who behave in an unpleasant or irritating manner online. This behavior can manifest in various ways, such as being overly aggressive, condescending, or disrespectful in online interactions

incessantly = over and over 끊임없이

extent 정도 to this extent 이 정도까지

carnal : 육체

foul: 사악, 반칙

perverse: 삐뚤어

00:33

In the past, the climate crisis never featured at the forefront of my politics because it was never one of the most immediate challenges my constituents were facing, or at least it didn't feel like it. Rising sea levels feel unimportant when your bank balance is falling. Global warming is not your concern when you can't pay the heating bills. And you're not thinking about pollution when you're being stopped by the police. And so perhaps this is why as the Black Lives Matter movement roared across the world, there's been so little mention of saving Black lives from the climate emergency.

01:08

For too long, those of us who cared about racial justice treated environmental justice as though it was elitist. And at the same time, the leaders who did focus on climate change were usually white and rarely bothered to enlist the support of Black voices in their work. Even progressive allies sometimes took our votes for granted and assumed that our community didn't care or wouldn't understand.

01:34

The truth is the opposite is true. Black people breathe in the most toxic air relative to the general population. We are more likely to suffer from respiratory diseases like asthma. And it is people of color who are more likely to suffer in the climate crisis. This is no coincidence. The cheapest housing tends to be next to the busiest roads, and many of the lowest paid jobs are in the most polluting industries. People of color consistently lie at the bottom of the housing, educational and employment ladders. This story connects Black communities across the world, from London to Lagos to LA. Black Americans are exposed to 56 percent more pollution than they cause. White Americans breathe 17 percent less air pollution than they produce. It gives a whole new meaning to the Black Lives Matter slogan "I can't breathe."

02:38

We all rightly know the name of George Floyd, who was murdered by the police. But we should also know the name of Ella Kissi-Debrah. Ella, a nine-year-old mixed-race girl from South East London, was killed by a fatal asthma attack. Evidence suggests this was caused partly by the unlawful levels of air pollution near her home.

03:02

And it's not only urban areas where Black lives are disproportionately under threat from climate change. My parents' home country of Guyana is one of the most vulnerable countries on Earth to the effects of climate change. So far, Guyana has contributed relatively little to the climate emergency, but it's one of the countries facing the most serious threats from it. While the annual carbon dioxide emissions per head in the United States is a staggering 16.5 metric tons, in Guyana it's just 2.6. It is a pattern repeated across the globe. Those countries that have contributed least to the climate breakdown, mainly in the global south, will suffer the most from floods, droughts, and rising temperatures. This is a pattern of suffering with a long history.

03:57

The exploitation of our planet's natural resources has always been tied to the exploitation of people of color. The logic of colonization was to extract valuable resources from our planet through force, paying no attention to its secondary effects. The climate crisis is in a way colonialism's natural conclusion.

04:20

The solution is to build a new coalition made up of all the groups most affected by this emergency: Black people in American cities who are already protesting that they cannot breathe; people of color in Guyana watching sea levels rise to the point where many of their homes become uninhabitable; young people in places like Tottenham, London, afraid of the world that they will grow old in; and progressive allies from all nations, of all races, religions, creeds and ages on their side, all demanding recognition that climate justice is linked to racial justice, social justice and intergenerational justice too. And let me say something about how we build this new movement and what it must look like.

05:06

First, we need a recognition that the climate movement is not only about protecting the planet. It is primarily about caring for the people who live on the planet. Globally as well as nationally, we need to recognize structural imbalances and inequalities. A radical green recovery plan should provide jobs to the people who've been disenfranchised for centuries, new jobs planting trees, insulating buildings and working on green technologies. We cannot tackle the climate crisis without addressing racial inequalities. And we cannot solve racial inequalities without fixing the economic system. The new deal the economy needs is not only green, it's green and Black.

05:54

Second, we need more Black leaders. It cannot be right in 2020 that almost all the leading climate change activists we recognize are white. At Davos this year, five young female members of the Fridays for Future movement came together to give a press conference at the World Economic Forum. This is a picture the Associated Press put out. Here is the original image. As the Ugandan activist, Vanessa Nakate, herself put it afterwards, "You didn't just erase a photo, you erased a continent." We need to look at who is being cropped out of leadership positions in environmental organizations too.

06:43

People of color makeup around 40 percent of the United States population. So why is it a University of Michigan study found that the percentage of minorities in leadership positions in US environmental organizations is less than 12 percent? Global organizations should consider moving their headquarters to the global south and urban areas that are most affected by the climate emergency. There should be new scholarships and bursaries in environmental science for people of color. Educate yourself. Join great movements that recognize the links between climate and race. To name a few, the Black Environment Network and Wretched of the Earth.

07:25

And finally, racial injustice and climate injustice are both rooted in the evil notion that some lives are more important than others. If you march to say Black Lives Matter in Minneapolis, London or Sydney, please also march for the Black lives on the Caribbean island of Haiti as its children are displaced by storms. Please also march for the Black lives being lost in Darfur, the first climate change conflict. And please also march for the Indigenous people of the Amazon rainforest, as Brazilian president Jair Bolsonaro weakens its protections.

08:03

If we are serious about protecting Black lives in the Global South as well as the north, we need to strengthen international laws. We need a way to apply international criminal laws, like war crimes or crimes against humanity, to the planet. We need a new international law of ecocide to criminalize the willful and widespread destruction of the environment, a law that criminalizes the most severe crimes against nature itself, even for acts don't involve direct human suffering.

08:35

Economics, race and class are at the center of today's political struggles. The Black Lives Matter movement needs to wake up to climate injustices just as the climate movement must make every effort to include the reality of people of color.

08:52

Young Black boys growing up in single-parent households in Tottenham won't have the opportunities I had in a world ravaged by climate chaos. My distant cousins and relatives growing up in Guyana won't have a future if their homes are drowning under water.

09:09

Now is the time for Black and climate movements to come together unequivocally and say, "We can't breathe."

09:18

Thank you very much.

the last thing on my mind 그건 생각도 안하고 있어/안 중요해

deprivation 궁핍

featured verb syn= present, highlight, appear

disproportionately 불균형적으로

staggering 놀라운

exploitation 착취

coalition 연합

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, 

that they probably didn’t use the distributive property. 

Remember, we need to distribute the negative two to both the nine and the 2m inside of the parentheses. 

This to me is a very, very, very big deal. 

And it's not just in math.

This is a computer programming exercise on Khan Academy, where the student needs to make the clouds part. 

And so we can see the student starts defining a variable, left X minus minus. 

It only made the left cloud part. 

But then they can ask Khanmigo, what’s going on? 

Why is only the left cloud moving? 

And it understands the code. 

It knows all the context of what the student is doing, and it understands that those ellipses are there to draw clouds, 

which I think is kind of mind-blowing. 

And it says, "To make the right cloud move as well, try adding a line of code inside the draw function that increments the right X variable by one pixel in each frame."

Now, this one is maybe even more amazing because we have a lot of math teachers. 

We've all been trying to teach the world to code, but there aren't a lot of computing teachers out there. 

And what you just saw, even when I'm tutoring my kids, when they're learning to code, I can't help them this well, this fast, 

this is really going to be a super tutor.

And it's not just exercises. 

It understands what you're watching. 

It understands the context of your video. 

It can answer the age-old question, “Why do I need to learn this?” 

And it asks Socratically, "Well, what do you care about?" 

And let's say the student says, "I want to be a professional athlete." 

And it says, "Well, learning about the size of cells, which is what this video is, 

that could be really useful for understanding nutrition 

and how your body works, etc." 

It can answer questions, it can quiz you, 

it can connect it to other ideas, 

you can now ask as many questions of a video as you could ever dream of.

Another big shortage out there, 

I remember the high school I went to, 

the student-to-guidance counselor ratio was about 200 or 300 to one. 

A lot of the country, it's worse than that. 

We can use Khanmigo to give every student a guidance counselor, academic coach, career coach, life coach, which is exactly what you see right over here. 

And we launched this with the GPT-4 launch. 

We have a few thousand people on this. 

This isn't a fake demo, this is really it in action.

And then there is, you know, things that I think it would have been even harder, 

it would have been a little science fiction to do with even a traditional tutor. 

We run an online high school with Arizona State University called Khan World School, 

and we have a student who attends that online school, based in India. 

Her name's Saanvi. 

And she was doing a report on "The Great Gatsby." 

And when she was reading "The Great Gatsby," 

Jay Gatsby keeps looking at the green light off into the distance. 

And she's like, "Why does he do that?" 

She did some web searches, and people have obviously studied this and commented about the symbolism of that, but none of it was really resonating with her. 

And then she realized that she had Khanmigo and that she could talk to Jay Gatsby himself.

And so, "Ah, splendid choice, old sport. 

I am now Jay Gatsby, the enigmatic millionaire from F. Scott Fitzgerald’s classic.”

And so, "Why do you keep staring at the green light?"

"Ah, the green light, old sport. 

It's a symbol of my dreams and desires, you see. 

It's situated at the end of Daisy Buchanan's dock across the bay from my mansion. 

I gaze at it longingly as it represents my yearning for the past and my hope to reunite with Daisy, the love of my life."

And what was cool is, Saanvi then said, “I had this long conversation,” she called him “Mr. Gatsby,” and at the end she actually apologized for taking his time, which I thought was very polite of her.

But you can imagine this unlocks learning literature, learning ... 

You could talk to historical figures. 

We're even probably going to add an activity you can talk to like, the Mississippi River. 

It brings things to life in ways that really were science fiction even six months or a year ago.

And we’ve got this here is the student debating whether we should cancel student debt. 

The student is against canceling student debt, and we've gotten very clear feedback. 

We started running it at Khan World School in our lab school that we have, Khan Lab School. 

The students, the high school students especially, they're saying "This is amazing to be able to fine-tune my arguments 

without fearing judgment. 

It makes me that much more confident 

to go into the classroom and really participate." 

And we all know that Socratic dialogue debate is a great way to learn, 

but frankly, it's not out there for most students. 

But now it can be accessible to hopefully everyone.

A lot of the narrative, we saw that in the headlines, has been, 

"It's going to do the writing for kids. 

Kids are not going to learn to write." 

But we are showing that there's ways that the AI doesn't write for you, it writes with you.

So this is a little thing, and my eight year old is addicted to this, and he's not a kid that really liked writing before, 

but you can say, “I want to write a horror story,” and it says, "Ooh, a horror story, how spine-tingling and thrilling. 

Let's dive into the world of eerie shadows and chilling mysteries." 

And this is an activity where the student will write two sentences, 

and then the AI will write two sentences. 

And so they collaborate together on a story.

The student writes, "Beatrice was a misunderstood ghost. 

She wanted to make friends but kept scaring them by accident."

And the AI says, "Poor Beatrice, a lonely spirit yearning for companionship. 

One day she stumbled upon an old abandoned mansion," etc.

I encourage you all to hopefully one day try this. This is surprisingly fun.

Now to even more directly hit this use case. 

And what I'm about to show you, everything I showed you so far 

is actually already part of Khanmigo, and what I’m about to show you, 

we haven't shown to anyone yet, this is a prototype. 

We hope to be able to launch it in the next few months, 

but this is to directly use AI, use generative AI, to not undermine English and language arts but to actually enhance it in ways 

that we couldn't have even conceived of even a year ago. 

This is reading comprehension. 

The students reading Steve Jobs's famous speech at Stanford. 

And then as they get to certain points, 

they can click on that little question. 

And the AI will then Socratically, almost like an oral exam, ask the student about things. 

And the AI can highlight parts of the passage. 

Why did the author use that word? 

What was their intent? 

Does it back up their argument? 

They can start to do stuff that once again, 

we never had the capability to give everyone a tutor, everyone a writing coach to actually dig in to reading at this level.

And you could go on the other side of it. 

And we have whole work flows that helps them write, helps them be a writing coach, draw an outline. 

But once a student actually constructs a draft, 

and this is where they're constructing a draft, 

they can ask for feedback once again, 

as you would expect from a good writing coach. 

In this case, the student will say, let's say, 

"Does my evidence support my claim?" 

And then the AI, not only is able to give feedback, 

but it's able to highlight certain parts of the passage and says, "On this passage, this doesn't quite support your claim," 

but once again, Socratically says, "Can you tell us why?" 

So it's pulling the student, making them a better writer, giving them far more feedback than they've ever been able to actually get before. 

And we think this is going to dramatically accelerate writing, not hurt it.

Now, everything I've talked about so far is for the student. 

But we think this could be equally as powerful for the teacher to drive more personalized education and frankly 

save time and energy for themselves and for their students. 

So this is an American history exercise on Khan Academy. 

It's a question about the Spanish-American War. 

And at first it's in student mode. 

And if you say, “Tell me the answer,” it’s not going to tell the answer. 

It's going to go into tutoring mode. 

But that little toggle which teachers have access to, they can turn student mode off and then it goes into teacher mode. 

And what this does is it turns into -- 

You could view it as a teacher's guide on steroids. 

Not only can it explain the answer, 

it can explain how you might want to teach it. 

It can help prepare the teacher for that material. 

It can help them create lesson plans, as you could see doing right there. 

It'll eventually help them create progress reports and help them, eventually, grade. 

So once again, teachers spend about half their time with this type of activity, lesson planning. 

All of that energy can go back to them 

or go back to human interactions with their actual students.

So, you know, one point I want to make. 

These large language models are so powerful, there's a temptation to say like, well, all these people are just going to slap them onto their websites, and it kind of turns the applications themselves into commodities. 

And what I've got to tell you 

is that’s one of the reasons why I didn’t sleep for two weeks 

when I first had access to GPT-4 back in August. 

But we quickly realized that to actually make it magical, 

I think what you saw with Khanmigo a little bit, it didn't interact with you the way that you see ChatGPT interacting. 

It was a little bit more magical, it was more Socratic, it was clearly much better at math 

than what most people are used to thinking. 

And the reason is, there was a lot of work behind the scenes to make that happen.

many, many people for over six, seven months to make it feel magical. 

But perhaps the most intellectually interesting one is we realized, and this was an idea from an OpenAI researcher, 

that we could dramatically improve its ability in math and its ability in tutoring 

if we allow the AI to think before it speaks. 

So if you're tutoring someone and you immediately just start talking before you assess their math, you might not get it right. 

But if you construct thoughts for yourself, 

and what you see on the right there is an actual AI thought, 

something that it generates for itself but it does not share with the student. 

then its accuracy went up dramatically, 

and its ability to be a world-class tutor went up dramatically. 

And you can see it's talking to itself here. 

It says, "The student got a different answer than I did, but do not tell them they made a mistake. 

Instead, ask them to explain how they got to that step."

So I'll just finish off, hopefully, you know, what I’ve just shown you is just half of what we are working on, and we think this is just the very tip of the iceberg of where this can actually go. 

And I'm pretty convinced, which I wouldn't have been even a year ago, that we together have a chance of addressing the 2 sigma problem and turning it into a 2 sigma opportunity, dramatically accelerating education as we know it.

Now, just to take a step back at a meta level, obviously we heard a lot today, the debates on either side. 

There's folks who take a more pessimistic view of AI, they say this is scary, there's all these dystopian scenarios, we maybe want to slow down, we want to pause. 

On the other side, there are the more optimistic folks that say, well, we've gone through inflection points before, we've gone through the Industrial Revolution. 

It was scary, but it all kind of worked out. 

And what I'd argue right now is I don't think this is like a flip of a coin or this is something where we'll just have to, like, wait and see which way it turns out. 

I think everyone here and beyond, 

we are active participants in this decision. 

I'm pretty convinced that the first line of reasoning is actually almost a self-fulfilling prophecy, that if we act with fear and if we say, "Hey, we've just got to stop doing this stuff," what's really going to happen is the rule followers might pause, 

might slow down, but the rule breakers, as Alexandr [Wang] mentioned, the totalitarian governments, the criminal organizations, 

they're only going to accelerate. 

And that leads to what I am pretty convinced is the dystopian state, which is the good actors have worse AIs than the bad actors.

But I'll also, you know, talk to the optimists a little bit. 

I don't think that means that, oh, yeah, then we should just relax and just hope for the best. 

That might not happen either. 

I think all of us together have to fight like hell to make sure that we put the guardrails, we put in -- when the problems arise -- 

reasonable regulations. 

But we fight like hell for the positive use cases. 

Because very close to my heart, 

and obviously there's many potential positive use cases, but perhaps the most powerful use case and perhaps the most poetic use case is if AI, artificial intelligence, 

can be used to enhance HI, human intelligence, human potential and human purpose.

Thank you. 

2)   mitigate (완화하다)

3)   deviation (일탈, 편차)

4)   safeguard (보호하다)

5)   socratically (소크라테스식으로): 질문과 대화를 통해 비판적 사고를 촉진하는 방식으로.

6)   enigmatic (불가사의한, 수수께끼 같은)

7)   fine-tune (미세 조정하다): 성능을 최적화하기 위해 작은 변화를 주다.

8)   spine-tingling (등골이 오싹한, 매우 흥분되는)

9)   prototype (시제품, 원형): 최종 제품의 모델이나 첫 번째 버전.

10) dystopian (디스토피아적인): 암울하고 억압적인 미래 사회를 묘사하는.

11) prophecy (예언)

12) totalitarian (전체주의의): 정부가 개인의 모든 삶을 통제하고 억압하는 정치 체제.

-Exaggerating a. 과장하는

-Gut-wrenching a. 속이 뒤틀리는

-Rigged a. 조작된

-Girl Effect n. 소녀효과(소녀들에 대한 교육에 적극적으로 나서면 나중에 큰 효과를 거둘 수 있다는 의미)

-Childrearing years n. 육아기

-Op-ed a. 기명(<-> 사설) 논평의

-Saysh n. the women's footwear brand

-Hypocrisy n. 위선

-New normal n. 시대 변화에 따라 새롭게 부상하는 표준

-Generosity n. 너그러움

-Path forward n. 경로

-Ageism n. 노인 차별

-Clause n. 조항(법과 함께 쓰이는 경우)

-Decorated a. 훈장을 받은

-Olympian a. 신과 같은, 위엄 있는

-Acknowledge v. 인정하다, 알리다

 Unwaver: 흔들리지 않는, 확고한

 Armed with: ~로 무장한

 Upend: 뒤엎다, 거꾸로 뒤집다

 Upheaval: 대변동, 격변

 Uprising: 반란, 봉기

 Crave: 갈망하다, 열망하다

 Trope: 비유적 표현, 흔히 쓰이는 문구나 개념

 Transparency: 투명성

 Ramp up: (양이나 속도를) 증가시키다, 강화하다

 Humility: 겸손

 Dire: 심각한, 절박한, 끔찍한

 Subsequent: 그 다음의, 차후의

 Steadfastness: 확고함, 굳건함

 Bolster: 강화하다, 북돋우다

 Backfire (verb): 역효과를 내다

 Counterintuitive: 직관에 반하는, 예상과 다른

 Lockdown: 봉쇄, 이동 제한

 Dissipate: 흩어지다, 사라지다

 Give power away: 권력을 양도하다, 권한을 넘기다

 Refined: 재발견한, 다시 찾은

• gymnast - 체조 선수

• tiger mother - 엄격하고 강한 양육 방식을 가진 어머니 (주로 자녀에게 높은 기대를 하는 경우)

• the Cultural Revolution - 문화대혁명 (1966-1976년, 중국에서 정치적, 사회적 변화가 일어난 시기)

• acrobatics - 곡예

• calling - 소명 (느낌이나 직감)

• parental - 부모의, 부모와 관련된

• propaganda - 선전 (사상이나 정책을 퍼뜨리기 위한 정보)

• commandment - 계명 (종교적, 도덕적 규칙, 예: 십계명)

• epiphany - 갑자기 깨달음

• guilt trap - 죄책감의 함정 (기대나 압박으로 느끼는 죄책감)

• comparative reading - 비교 읽기

• standard practice - 표준 관행

• academic world - 학문적 세계

• scholars - 학자들

• temptation - 유혹

• lust - 강한 욕망 (주로 성적 욕망)

• shattered - 부서진, 깨진 (주로 꿈이나 희망)

여기에 나오는 책 정보는 아래와 같습니다.

1. "Benjamin Franklin" by Walter Isaacson

   • 벤자민 프랭클린의 전기

2. "John Adams" by David McCullough

   • 존 아담스의 전기

3. "Personal History" by Katharine Graham

   • 워싱턴 포스트의 발행인인 캐서린 그래엄의 회고록

4. "The Snowball: Warren Buffett and the Business of Life" by Alice Schroeder

   • 워렌 버핏의 전기

5. "Holy Bible: King James Version"

   • 킹 제임스 역 성경

6. "Lamb" by Christopher Moore

   • 예수의 어린 시절을 다룬 유머러스한 소설

7. "The Power of Myth" by Joseph Campbell

   • 신화의 힘과 그 역할에 대해 다룬 책

8. "Correspondence in the Family of Fou Lei"

   • 중국 작가인 푸레이의 가족 서신 모음

9. "Jane Eyre" by Charlotte Brontë

   • 제인 에어의 여성의 정체성을 다룬 이야기

10. "Cheaper by the Dozen" by Frank B. Gilbreth Jr. and Ernestine Gilbreth Carey

    • 대가족의 효율성과 관리를 다룬 책

11. "Complete Works of Sanmao" (aka Echo Chan)

    • 산마오의 여행과 삶 이야기

12. "Lessons From History" by Nan Huaijin

    • 역사에서 얻은 교훈을 다룬 책

13. "The Good Earth" by Pearl S. Buck

    • 중국 농민의 삶과 고난을 탐구한 책

14. "The Way of Chuang Tzu" by Thomas Merton

    • 장자의 사상과 철학 현대번역본

15. "Tao: The Watercourse Way" by Alan Watts

    • 자연과의 조화를 다룬 도가사상 관련 책

2. in the footsteps of - ~의 발자취를 따라가다, ~을 본받다

3. subtract - 빼다, 없애다

4. desk-dwelling - 책상에만 있는, 주로 앉아서 생활하는

5. hiking up - 등반하다

6. badly enough - 충분히 강하게, 간절히

7. deprived - 빼앗긴, 부족한

8. add a new habit - 새로운 습관을 더하다

9. grew - 성장하다

10. sustainable - 지속 가능한

11. more likely to stick - 더 오래 지속될 가능성이 있는

12. give it a shot - 시도해 보다

1. Do you think you’re naturally good at spotting a liar, or would you need to practice these techniques?

2. Which of the ten signs do you think is the easiest to spot in someone? Have you ever noticed it in real life?

3. Do you agree that avoiding eye contact is a clear sign of lying, or could it just be nervousness?

4. Have you ever caught someone lying by asking unexpected questions? What was the reaction?

5. If you had to choose one trick to spot a liar, which would you pick: micro-expressions, playing devil’s advocate, or telling their story backwards? Why?

• Intoxicating – (adj.) 기쁨이나 행복을 주는, 압도적인

• Wringer – (n.) (고통스러운) 경험

• Loneliness – (n.) 고립, 외로움

• Suffering – (n.) 고통, 어려움

• Disguise – (v.) 숨기다, 가리다.

• Procreate – (v.) 자식을 낳다, 번식하다

• Consummated – (v.) 완성하다, 이루다. (특히 관계나 결혼)

• Drudgery – (n.) 힘듦, 따분함, 고됨

• Ecstasy – (n.) (강렬한)기쁨, 행복

• Intimacy – (n.) 친밀함

• Affliction – (n.) 고통,괴로움의 원인

• Cravings – (n.) 욕망, 갈망

• Attachments – (n.) 연결, 유대

• Nirvana – (n.) (불교)고통에서 벗어난 상태

• Clarity – (n.) 명확함

• Compassion – (n.) 동정, 배려

• Subplot – (n.) (주요 이야기와는 별도로 진행되는)작은 이야기

• Humiliate – (v.) 굴욕을 주다.

• Authentically – (adv.) 진실되게

• Captivating – (adj.) 사로잡는

• Dependence – (n.) 의지

• Boredom – (n.) 지루함

• Power games – (n.) 조작적 행동

• Enriching – (v.) 가치를 더하는

• Rollercoaster – (n.) 감정이나 사건에서 극적인 변화가 있는 상황