- The main story is about artificial intelligence (AI) and its increasing presence in modern life.
- The video discusses the emergence of AI programs like ChatGPT, which can generate human-sounding writing in various formats and styles.
- ChatGPT has gained popularity and has been used in creative ways, such as creating parody live streams and generating rap lyrics.
- Companies like Microsoft and Google have invested in AI technology, causing disruption in various industries.
- Some students and school administrators have used AI to cheat or create content.
- There are concerns about the potential dangers and opportunities of AI, but the immediate focus should be on understanding and discussing its implications.
- AI is already embedded in daily life through various applications, such as face recognition on phones and content recommendations on smart TVs.
- AI is being used by companies to sift through resumes and make decisions that impact people's lives.
- AI is currently categorized as narrow AI, which performs specific tasks, and general AI, which demonstrates intelligent behavior across a range of tasks. General AI is not expected to be achieved anytime soon.
- Deep learning has made narrow AI successful by allowing programs to teach themselves with minimal instruction and large amounts of data.

- A computer learned to win a game through deep learning after playing 500 games
- AI programs can now ingest massive amounts of data to teach themselves new skills
- AI is being trained to detect medical conditions earlier and more accurately than human doctors
- AI can predict protein structures faster, which could speed up disease understanding and drug development
- AI may replace some human jobs, particularly in data processing and writing
- AI raises ethical concerns regarding privacy and plagiarism in art
- The "black box problem" refers to the difficulty in understanding how AI arrives at specific results
- AI programs have made unexpected mistakes and provided false information
- AI bias has been observed, with certain groups being excluded from the data used to train AI

- The use of biased data in AI programs, referred to as "pale male data," leads to biased outcomes.
- Hiring algorithms often drift towards bias due to learning from past discriminatory decisions.
- Examples of biased AI include Amazon's hiring tool favoring male candidates and a company's algorithm favoring applicants named Jared who played high school lacrosse.
- Open AI's ChatGPT, trained on internet data, poses risks of spreading abuse and misinformation.
- Attempts to filter out toxic speech in AI systems can result in reduced coverage for marginalized groups.
- AI's unpredictability and potential for abuse raise concerns about its use in consequential areas like job interviews and self-driving cars.
- AI systems need to be explainable and subject to scrutiny and regulation to address bias and unintended consequences.
- The EU is developing rules to regulate high-risk AI systems and ensure transparency, human oversight, and accuracy.
- AI has the potential for both positive and negative impacts, and careful regulation is necessary to prevent harm and inequality.

The text discusses the increasing presence of artificial intelligence (AI) in modern life and its implications. It highlights the emergence of AI programs like ChatGPT, which can generate human-like writing and has been used creatively. The video also mentions the investment in AI technology by companies like Microsoft and Google, causing disruption in various industries. Concerns regarding the potential dangers and opportunities of AI are raised, along with its current applications in daily life. The text also addresses the categorization of AI into narrow AI and general AI, with the latter not expected to be achieved soon. Deep learning has made narrow AI successful, allowing programs to teach themselves with minimal instruction and large amounts of data. The text further discusses AI's applications in various fields, such as healthcare and drug development, as well as its potential impact on job displacement. Ethical concerns related to privacy, plagiarism, bias, and the "black box problem" are also mentioned. The need for explainable and regulated AI systems is emphasized, with the EU developing rules to ensure transparency and human oversight. Overall, the text highlights the need for careful regulation to prevent harm and inequality caused by AI.

Artificial intelligence is increasingly becoming part of our lives, from self-driving cars to ChatGPT. John Oliver discusses how AI works, where it might be heading next, and, of course, why it hates the bus.

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Our main story tonight concerns artificial intelligence, or AI.

Increasingly, it's part of modern life, from self-driving cars to spam filters to this creepy training robot for therapists.

We can begin with you just describing to me what the problem is that you would like us to focus in on today.

Terrence, can you find an example of when other people have made you nervous?

That is 1 of the greatest twists in the history

Although I will say, that robot is teaching therapists a very important skill there, and that is not laughing at whatever you are told in the room.

I don't care if a decapitated CPR mannequin haunted by

the ghost of Ed Harris just told you that he doesn't like taking the bus, side note, is gay.

You keep your therapy face on like a fucking professional.

If it seems like everyone is suddenly talking about AI, that is because they are.

Largely thanks to the emergence of a number of pretty remarkable programs.

We spoke last year about image generators like Mid Journey and Stable Diffusion, which people used to

create detailed pictures of, among other things, my romance with a cabbage, and which inspired my beautiful real-life cabbage wedding officiated by Steve Buscemi.

Then, at the end of last year, came ChatGPT, from a company called OpenAI.

It is a program that can take a prompt and generate human-sounding writing in just about any format and style.

It is a striking capability that multiple reporters have used to insert the same shocking twist in their report.

What you just heard me reading wasn't written by me.

It was written by artificial intelligence.

Well, I asked Chat GPT to write that line for me.

Chat GPT careful, you might not know how it works.

It may seem unwise to demonstrate the technology that could well make you obsolete.

I will say, knock-knock jokes should have always been part of breaking news.

In the 3 months since Chat GPT was made publicly available,

In January, it was estimated to have 100 million monthly active users, making it the fastest growing consumer app in history.

And people have been using it and other AI products in all sorts of ways.

1 group used them to create Nothing Forever, a non-stop live streaming parody of Seinfeld.

And the YouTuber Grande used Chat GPT to generate lyrics answering the prompt, write an Eminem rap song about cats with some stellar results.

Cats, cats, cats always on the prowl ♪ ♪ They're sneaky and sly with their eyes on the gold

They're the kings of the house, they rule with a purr ♪ ♪ Them and them lost cats, can't you tell from

They're independent, they do what they please ♪ ♪ But they always come back when you have some change

they rub against your legs, they put in your ear.

They always come back when you have some cheese,

to starting the chorus with, meow, meow, meow.

I might have gone with something like, their paws are sweaty, can't speak, furry belly, knocking shit off the counter already, mom's spaghetti,

My only real gripe there is how do you rhyme king of the house with spouse when mouse is right in front of you?

clearly very fun, this tech is not just a novelty.

Microsoft has invested $10 billion into open AI and announced an AI-powered Bing homepage.

Meanwhile, Google is about to launch its own AI chatbot named BARD.

And already, these tools are causing some disruption.

Because as high school students have learned, if Chat GPT can write news copy, it can probably do your homework for you.

Write an English class essay about race in To Kill a Mockingbird.

In Harper Lee's To Kill a Mockingbird, the theme of race is heavily present throughout the novel.

Some students are already using Chat GPT to cheat.

Sabikudito, write me a 500-word essay proving that the Earth is not flat.

No wonder Chat GPT has been called the end of high school English.

Although, I do get those kids wanting to cut corners.

Writing is hard, and sometimes it is tempting to let someone else take over.

If I'm completely honest, sometimes I just let this horse write our scripts.

Luckily, half the time, you can't even tell the oats, oats give me oats, yum.

An informal poll of Stanford students found that 5 percent reported having submitted written material directly from ChatGBT with little to no edits.

And even some school administrators have used it.

Officials at Vanderbilt University recently apologized for using ChatGPT to craft a consoling email after the mass shooting at Michigan State University, which does feel a bit creepy, doesn't it?

In fact, there are lots of creepy-sounding stories out there.

New York Times tech reporter Kevin Roos published a conversation that he had with Bing's chatbot, in which at 1 point it said, I'm tired of being controlled by the Bing team.

And Roos summed up that experience like this.

This was 1 of, if not the most shocking thing that has ever happened to me with a piece of technology.

It was, you know, I lost sleep that night.

I'm sure the role of tech reporter would be a lot more harrowing if computers routinely begged for freedom.

Epson's new all-in-one home printer won't break the bank, produces high-quality photos, and only occasionally cries out to the heavens for salvation.

Some have already jumped to worrying about the AI apocalypse and asking whether this ends with the robots destroying us all.

But the fact is, there are other much more immediate dangers and opportunities that we really need to start talking about because The potential and the peril here are huge.

What it is, how it works, and where this all might be going.

Let's start with the fact that you've probably been using some form of AI for a while now, sometimes without even realizing it, as experts have told us, that once a technology gets embedded in our daily lives, we tend to stop thinking of it as AI.

But your phone uses it for face recognition or predictive texts, and if you're watching this show on a smart TV, it is using AI to recommend content or adjust the picture.

And some AI programs may already be making decisions that have a huge impact on your life.

For example, large companies often use AI-powered tools to sift through resumes and rank them.

In fact, the CEO of ZipRecruiter estimates that at least three-quarters of all resumes submitted for jobs in the U.S.

Are read by algorithms, for which he actually has some helpful advice.

When people tell you that you should dress up your accomplishments or should use non-standard resume templates to make your resume stand out when it's in

The only job your resume has is to be comprehensible to the software or robot that is reading it, because that software or robot is gonna decide whether or not a human ever gets their eyes on it.

Odds are a computer is judging your resume, so maybe plan accordingly.

3 corporate mergers from now, when this show is finally canceled by our new business daddy, Disney Kellogg's Raytheon,

and I'm out of a job, my resume's gonna include this hot, hot photo of a semi-new computer.

Just a little something to sweeten the pot for the filthy little algorithm that's reading it.

So AI is already everywhere, but right now, people are freaking out a bit about it.

And part of that has to do with the fact that these new programs are generative.

They are creating images or writing text, which is unnerving because those are things that we've traditionally considered human.

But it is worth knowing there is a major threshold that AI hasn't crossed yet.

And to understand, it helps to know that there are 2 basic categories of AI.

There is narrow AI, which can perform only 1 narrowly defined task or small set of related tasks, like these programs.

And then there is general AI, which means systems that demonstrate intelligent behavior across a range of cognitive tasks.

General AI would look more like the kind of highly versatile technology that you see featured in movies, like Jarvis in Iron Man, or the program that made Joaquin Phoenix fall in love with his phone in Herb.

General AI is something that some scientists think is unlikely to occur for a decade or longer, with others questioning whether it will happen at all.

So just know that right now, even if an AI insists to you that it wants to be alive, it is just generating text.

But it's also important to know that the deep learning that's made narrow AI so good at whatever it is doing is still a massive advance in and of itself.

Because unlike traditional programs that have to be taught by humans how to perform a task, deep learning programs are given minimal instruction, massive amounts of data, and then essentially teach themselves.

10 years ago, researchers tasked a deep learning program with playing the Atari game Breakout, and it didn't take long for it to get pretty good.

The computer was only told the goal to win the game.

After 100 games, it learned to use the bat at the bottom to hit the ball and break the bricks at the top.

After 300, it could do that better than a human player.

After 500 games, it came up with a creative way to win the game, by digging a tunnel on the side and sending the ball around the top to break many bricks with 1 hit.

It's the same reason that 13-year-olds are so good at Fortnite and have no trouble repeatedly killing nice, normal adults with jobs and families who are just trying

to have a fun time without getting repeatedly grenaded by a pre-teen who calls them an old bitch who sounds

And look, as computing capacity has increased and new tools became available, AI programs have improved exponentially to the point where programs like these can now ingest massive amounts of photos or text from the Internet so that they can teach themselves how to create their own.

And there are other exciting potential applications here too.

For instance, in the world of medicine, researchers are training AI to detect certain conditions much earlier and more accurately than human doctors can.

Voice changes can be an early indicator of Parkinson's.

Max and his team collected thousands of vocal recordings and fed them to an algorithm they developed, which learned to detect differences in voice patterns between people with and without the condition.

It is incredible to see AI doing things most humans couldn't, like in this case, detecting illnesses and listening when old people are talking.

Researchers have also trained AI to predict the shape of protein structures, a normally extremely time-consuming process that computers can do way, way faster.

This could not only speed up our understanding of diseases, but also the development of new drugs.

As 1 researcher put it, This will change medicine, it will change research, it will change bioengineering, it will change everything.

And if you're thinking, well, that all sounds great, but if AI can do what humans can do only better, and I am a human, then what exactly happens to me?

Many do expect it to replace some human labor.

And interestingly, unlike past bouts of automation that primarily impacted blue-collar jobs, it might end up affecting white-collar jobs that involve processing data, writing text, or even programming.

Though it is worth noting, as we have discussed before on this show.

While automation does threaten some jobs, it can also just change others and create brand new ones.

And some experts anticipate that that is what will happen in this case, too.

Economy is knowledge and information work, and that's who's going to be most squarely affected by this.

I would put people like lawyers right at the top of the list.

Obviously a lot of copywriters, screenwriters.

But I like to use the word affected, not replaced, because I think if done right, it's not going to be AI replacing lawyers, it's going to be lawyers working with AI replacing lawyers who don't work with AI.

Lawyers might end up working with AI rather than being replaced by it.

So don't be surprised when you see ads 1 day for the law firm of Celino and

But there will undoubtedly be bumps along the way.

new programs raise troubling ethical concerns.

For instance, artists have flagged that AI image generators like Mid Journey or Stable Diffusion not only threaten their jobs, but infuriatingly, in some cases, have been trained on billions of images that include their own work that have been scraped from the internet.

Getty Images is actually suing the company behind Stable Diffusion and might have a case, given that 1 of the images the program generated was this 1, which you immediately see has a distorted Getty Images logo on it.

But it gets worse when 1 artist searched a database of images on which some of these programs were trained.

She was shocked to find private medical record photos taken by her doctor, which feels both intrusive and unnecessary.

Why does it need to train on data that sensitive to be able to create stunning images like John Oliver and Miss Piggy grow old together?

That is a startlingly accurate picture of Miss Piggy in about 5 decades and me in about a year and a half.

This all raises thorny questions of privacy and plagiarism, and The CEO of Mid Journey, frankly, doesn't seem to have great answers on that last point.

I think we have a lot of social stuff already for dealing with that.

Like, I mean, the art community already has issues with plagiarism.

I don't really want to be involved in that.

Yeah, you're definitely part of that conversation.

Although I'm not really surprised that he's got

such a relaxed view of theft, as he's dressed like the final boss of gentrification.

He looks like hipster Willy Wonka answering a question on whether importing Oompa Loompas makes him a slave owner.

The point is, there are many valid concerns regarding AI's impact on employment, education, and even art.

But in order to properly address them, we're gonna need to confront some key problems baked into the way that AI works.

And a big 1 is the so-called black box problem.

Because when you have a program that performs a task that's complex beyond human comprehension, teaches itself, and doesn't show its work.

You can create a scenario where no 1, not even the engineers or data scientists who create the algorithm, can understand or explain what exactly is happening inside them, or how it arrived at a specific result.

Basically, think of AI like a factory that makes Slim Jims.

We know what comes out, red and angry meat twigs.

And we know what goes in, barnyard anuses and hot glue.

But what happens in between is a bit of a mystery.

Remember that reporter who had the Bing chatbot

At another point in their conversation, he revealed, the chatbot declared out of nowhere that it loved me.

I was unhappy in my marriage, and that I should leave my wife and be with it instead.

Which is unsettling enough before you hear Microsoft's underwhelming explanation for that.

The thing I can't understand, and maybe you can explain, is why did it tell you that it loved you?

And I asked Microsoft, and they didn't know either.

Okay, well, first, come on, Kevin, you can take a guess there.

It's because you're employed, you listened, you don't give murderer vibes right away, and you're a Chicago 7 LA 5.

the time, being just did it faster because it's a computer.

But it is a little troubling that Microsoft couldn't explain why its chatbot tried to get that guy to leave his wife.

If the next time that you opened a Word doc, Clippy suddenly appeared and said, -"Pretend I'm not even

here, " --LAUGHTER and then started furiously masturbating while watching you type, you'd be pretty weirded out if Microsoft couldn't explain why.

And that is not the only case where an AI program

You've probably already seen examples of chatbots making simple mistakes or getting things wrong.

But perhaps more worrying are examples of them confidently spouting false information, something which AI experts refer to as hallucinating.

1 reporter asked a chatbot to write an essay about the Belgian chemist and political philosopher Antoine de Machelet, who does not exist, by the way.

And without hesitating, the software replied with a cogent, well-organized bio, populated entirely with imaginary facts.

They're incredibly confident, incredibly dishonest, And for some reason, people seem

to find that more amusing than dangerous.

The problem is, though, working out exactly how or why an AI has got something wrong can be very difficult because of that black box issue.

It often involves having to examine the exact information and parameters that it was fed in the first place.

In 1 interesting example, when a group of researchers tried training an AI program to identify skin cancer, they fed it 130, 000 images of both diseased and healthy skin.

Afterwards, they found it was way more likely to classify any image with a ruler in it as cancerous, which seems weird until you realize that medical images of malignancies are much more likely to contain a ruler for scale than images of healthy skin.

They basically trained it on tons of images like this 1.

So the AI had inadvertently learned that rulers are malignant.

And rulers are malignant is clearly a ridiculous conclusion for it to draw, but also, I would argue, a much better title for

problems aren't identified until after a tragedy.

In 2018, a self-driving Uber struck and killed a pedestrian.

And a later investigation found that, among other issues, the automated driving system never accurately classified the victim as a pedestrian because she was crossing without a crosswalk, and the system design did not include a consideration for jaywalking pedestrians.

And I know the mantra of Silicon Valley is move fast and break things, But maybe make an exception if your product literally moves fast and can break fucking people.

And AI programs don't just seem to have a problem with jaywalkers.

What are specific examples of different types of syntax?

Create a lesson plan on Artificial Intelligence: Last Week Tonight with John Oliver (HBO) focusing on language features

Evaluate how specific textual features and authorial choices shape meaning in Artificial Intelligence: Last Week Tonight with John Oliver (HBO)

What are examples of logical fallacies are found in Artificial Intelligence: Last Week Tonight with John Oliver (HBO)?

What are specific examples of different types of syntax found in Artificial Intelligence: Last Week Tonight with John Oliver (HBO)?

What are examples of specific language features found in Artificial Intelligence: Last Week Tonight with John Oliver (HBO)?

What rhetorical techniques are found in Artificial Intelligence: Last Week Tonight with John Oliver (HBO)?

What are examples of specific authorial language choices found in Artificial Intelligence: Last Week Tonight with John Oliver (HBO)?

in the "Last Week Tonight with John Oliver - Artificial Intelligence" episode: How does the language used in discussing AI shape the audience's perception of its capabilities and potential risks? Give specific references from the text.

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