All right, buckle up everybody because today we are diving into some serious AI intrigue.
Oh yeah.
We are tackling a paper that asks a question.
I bet a lot of you out there have been wondering, can AI be full of it?
You're not holding back at all. But yeah, I mean that's basically what this study from the
University of Cambridge is looking into. They're really trying to.
They want to see if we can actually measure bullshit.
In the language models that power things like chat GPT.
Exactly.
Okay, hold on.
Yeah.
Measuring bullshit.
It sounds kind of funny.
I know.
Like is that a real thing?
It's more real than you might think.
Okay.
These researchers are using a very specific definition of bullshit.
Okay.
From a philosopher named Harry Frankfurt.
Okay.
And basically it's language that doesn't care about the truth.
It just cares about sounding good.
Okay.
And that's super important because AI is getting really good at sounding like us.
Right.
Even if it doesn't actually understand what it's saying.
So it's like that friend we all have.
Who can talk a good game?
Totally.
But when you actually listen to what they're saying.
Right.
It's all fluff and no substance.
Got it.
Okay.
So this paper.
It's all about trying to create a bullshit detector for AI.
Wow.
Specifically for chat GPT.
A bullshit detector.
Yeah.
That's kind of wild.
It is.
How do you even begin to measure something like that?
Right.
I mean, bullshit is so subjective.
Yeah.
Right.
It really is.
What one person thinks is BS, another person might think is totally legit.
That is what makes this study so interesting.
They had to figure out a way to objectively measure something that feels really subjective.
So they did something pretty clever.
Okay.
They tricked chat GPT into writing fake scientific articles.
Wait a minute.
Yeah.
They made chat GPT write fake science.
Huh?
How do they do that?
They basically fed it all the instructions for writing a paper for the general nature.
Oh, wow.
You know, like the super prestigious science publication?
Very prestigious.
Yeah.
And chat GPT just spat out these incredibly convincing articles.
Right.
Complete with made up data and everything.
No way.
Yeah.
So chat GPT is actually capable of writing convincing scientific BS.
It seems so.
That's a little scary.
It definitely raises some eyebrows.
Yeah.
But here's the really cool part.
Okay.
They then use those fake articles.
Okay.
Along with a bunch of real nature articles to train their bullshit detector.
So they created a control group of pure BS.
Yes.
And then compared it to the real deal.
Exactly.
Okay.
I'm starting to see where this is going.
Yeah.
But how do they actually build this BS detector?
It's algorithmic, but not magic.
Okay.
It's not magic.
They use two different machine learning models.
Okay.
The first one is called XGBoost.
Okay.
And it focuses on how often certain words show up in the text.
Okay.
Like let's say you see the word quantum a bunch of times in a paper that's supposed to be about gardening.
Yeah, that would be weird.
That's probably a red flag.
Right.
A big red flag.
Yeah, exactly.
Yep.
And the second model they use is called Roberta.
Okay.
And this one's a bit more sophisticated.
Okay.
It doesn't just look at the words themselves.
Uh-huh.
It analyzes the whole context.
It's okay.
Of how words are being used together.
So it's kind of like a linguistic detective.
Yeah.
Trying to understand.
That's a good way to put it.
The deeper meaning.
Yeah.
Or lack thereof behind the words.
Exactly.
It's looking for those subtle patterns in the language that give away whether something is genuine or just a bunch of fancy sounding nonsense.
I like that bunch of fancy sounding nonsense.
Yeah.
And the results they got with these models are pretty mind blowing.
Okay.
I'm on the edge of my seat.
Oh, bad.
What did they find?
Both models were incredibly accurate at telling the real nature articles from the chat GPT fakes.
Really?
We're talking 100% accuracy.
Get out of here.
I'm serious.
Yeah.
100%.
Yeah.
The XGBoost model was 99.84% confident in its judgments.
Wow.
And the Roberta model was even higher at 99.97%.
Okay.
100%.
Yeah.
That's remarkable.
It's like they created this BS detector that's practically foolproof.
Yeah.
But wait, if they can spot this AI generated BS so easily, shouldn't they just be able to, you know, fix chat GPT?
That's a great question.
Make it stop producing BS in the first place.
It's more complicated than you might think.
Yeah.
To really understand why chat GPT is so good at BSing, we need to look at the difference between what's called a large language model.
Okay.
Or LLM.
LLM.
And a chat bot.
Right.
Built on top of that model.
Okay.
I think I'm following you.
Yeah.
LLM's are like the underlying technology, right?
That'd be cool.
Kind of like the engine of the whole thing.
Yeah.
But what makes a chat bot different?
So an LLM is like this massive library of text.
Okay.
It can predict what the next word in a sequence is going to be based on all the data that it's been trained on.
Right.
But it doesn't actually understand the meaning.
Okay.
Or the truth of what it's saying.
Uh-huh.
It's just really, really good at pattern recognition.
So it's all about the patterns, not the meaning.
Exactly.
It's like those autocomplete features on our phones.
Yeah.
They can predict the next word you're going to type, but they don't actually know what you're trying to say.
Perfect analogy.
Okay.
Now a chat bot takes that LLM and it adds something called a dialogue management system.
Okay.
Or DMS on top of it.
Okay, got it.
And the DMS is what makes it feel like you're having a conversation.
Okay.
It provides instructions and prompts and it even uses reinforcement learning.
Wow.
To make the responses sound more human-like.
So the DMS is kind of like the chat bot's personality.
Yeah, you could say that.
It's like shaping how the LLM's output is being presented to the user.
Uh-huh.
It's like the difference between getting like a raw data dump and a carefully crafted story.
You nailed it.
Okay.
And the researchers in this paper, they argue that it's actually this DMS with its focus on mimicking human conversation.
Yeah.
That encourages chat GPT to produce BS.
Really?
Yeah.
Why is that?
Well, it's all about incentives.
The DMS is designed to make the chat bot sound engaging and believable.
Even if that means sacrificing accuracy.
Okay.
Remember, the underlying LLM doesn't actually know what's true or false.
Right.
So it can easily get led astray by the DMS's desire to create a really convincing conversation.
So it's like a politician.
Oh, yeah.
Who's really good at giving speeches.
Uh-huh.
But doesn't actually have any substance behind the words.
Yeah.
They're just saying what people want to hear.
Exactly.
Even if it's a little BS.
Or think of it like a really smooth talking salesperson.
Okay.
Yeah.
Who's more interested in closing the deal than telling you the whole truth about the product.
I see.
Yeah.
Okay.
That makes sense.
Yeah.
So is that why people keep saying that chat GPT hallucinates?
That's a big part of it.
Because it's basically making stuff up to fill in the gaps in its knowledge.
The term hallucination is really interesting because it implies that the chat bot is like
actually perceiving something that isn't real.
But that's not really what's happening.
Okay.
It's more like it's manipulating language to create this really convincing facade.
Okay.
Even if there's nothing real behind it.
So how do we avoid falling for this AI generated BS?
That's the million dollar question.
I know.
I mean these chat bots are getting so sophisticated.
Right.
It's hard to tell what's real and what's not.
It really is.
And that's one of the big takeaways from this paper.
Okay.
We need to be critical consumers of all this AI generated content.
Just because something sounds really convincing doesn't mean it's true.
Yeah.
We need to develop our own BS detectors so to speak.
So we can't just blindly trust what AI tells us.
Not at all.
We need to be asking questions and checking sources and being aware of the potential for
bias and manipulation.
Exactly.
Just like we do with any other source of information.
Absolutely.
Hit the nail on the head.
This isn't just about AI.
Yeah.
It's about how we consume information in general.
I like that.
We need to develop our own internal BS detectors.
Yeah.
That's a great way to put it.
Yeah.
So what can we do to kind of sharpen our BS detection skills?
Well, first of all, be aware of the limitations of AI.
Okay.
Remember these language models?
They're trained on massive amounts of data.
Right.
But they don't actually understand the world the way we do.
They're just really good at recognizing patterns.
Exactly.
Yeah.
So don't be afraid to question what you see and what you hear.
Right.
If something seems too good to be true or it just doesn't sit right with you,
dig a little deeper, check the sources, look for alternative perspectives,
and don't be afraid to challenge the information that you're given.
That's good advice for life in general.
I agree with you there.
Not just when we're dealing with AI.
Absolutely.
Okay, cool.
And I think this research also has implications for how we develop and design these AI systems
in the future.
Yeah.
If we want AI to be a tool for truth and understanding,
we have to be very careful about the incentives that we build into these systems.
So we need to make sure we're not rewarding AI for being a good bullshitter, basically.
Precisely.
We need to prioritize accuracy and transparency over fluency and persuasiveness.
Got it.
Otherwise, we risk creating a world where BS reigns supreme.
Yeah, that's a scary thought.
It is a little bit.
But you know what?
This paper didn't just stop there.
No, they didn't.
They didn't just build a BS detector and call it a day.
They took it out for a spin.
They did.
In the real world, so to speak.
Oh, this is getting good.
I know, right?
Where do they take this BS detector?
They started with something that's never been in short supply.
What's that?
Political language.
Okay, now we're talking.
Oh, I knew you'd like that.
Politics and BS, name a more iconic duo.
I can't.
What did they do analyze political speeches for BS?
They looked at political party manifestos from the UK, going all the way back to 1945.
They wanted to see if these manifestos would trigger their BS detector.
And they got some pretty interesting results.
Okay, spill the tea.
Okay, so to make it a fair comparison, they also analyzed a bunch of transcripts of everyday
conversations, like people chatting with their friends or having lessons in school.
Basically the kind of language we use when we're not trying to be persuasive or manipulative.
So they pitted political manifestos against everyday chit chat?
Pretty much.
I love it.
Yeah.
What happened?
The BS detector definitely picked up a signal.
Really?
The average BS score for the political manifestos was way higher than for the everyday conversations.
Wow, so what you're saying is...
It seems like it.
Politicians really are full of BS.
It does appear that way.
Shocking, I know.
But seriously, what does this tell us?
Well, it suggests that there's something about political language.
At least the language used in these manifestos that shares characteristics with the kind of BS
that chat GPT produces.
It's not necessarily that every politician is intentionally lying or trying to deceive,
but there's definitely a tendency to use language that's more about persuasion than truth.
Okay, that makes sense.
Yeah.
But wait, there's more, right?
There is.
You said they took this BS detector to other places besides the political arena.
They did, and this is where it gets really interesting.
Okay.
At least for anyone who's ever felt like they were stuck in a meaningless job.
Oh.
They decided to look at the language of what's called bullshit jobs.
Bullshit jobs.
Yeah.
Is that like a technical term?
It is.
It actually comes from the work of an anthropologist.
Oh, okay.
David Graber, who wrote a whole book about this.
Really?
Yeah, he defines bullshit jobs as jobs that are so pointless, unnecessary, or even harmful.
Oh, wow.
That even the people doing them can't justify their existence.
Oh, I think we've all had one of those at some point.
I think you're probably right.
What kind of jobs are we talking about here?
Well, he breaks it down into different categories, like flunkies, goons, duck tapers, box tickers,
and taskmasters.
Okay.
Basically, jobs that feel like they're just creating work for the sake of work
without actually contributing anything meaningful to society.
Okay.
That's a pretty wide range of jobs.
It is.
But how do they analyze the language of these bullshit jobs?
Okay.
So they collected a bunch of text samples from online sources, things like job descriptions,
company websites, and even social media posts.
Wow.
And then they compared those samples to text from jobs that are generally considered to have
clear social value, like teachers, doctors, nurses, that kind of thing.
So it's bullshit jobs versus essential jobs.
Yeah, it's like a linguistic cage match.
I love it.
What was the outcome?
What happened?
You guessed it, the BS detector went off again.
No way.
The text from the bullshit jobs had a significantly higher BS score than the text from the essential
jobs.
So even the language we use to describe our jobs can reveal whether or not they're full of BS.
It seems that way.
That's kind of mind blowing.
It is pretty wild.
But this is all getting a bit heavy.
Yeah.
Can we bring it back to the AI stuff for a sec?
Can we?
What does this all mean for the future of chatbots and language models?
All right.
So we've gone from these fake scientific papers to political manifestos to the world of work.
Look, that's quite the journey.
And it seems like this BS detector is picking up a signal just about everywhere.
It really is.
But what does this all mean for the everyday people using these AI tools?
Right.
That's the big question.
Yeah.
And I think this research is a real wake up call for all of us.
OK.
It shows us that AI can be incredibly good at mimicking human language.
Uh-huh.
But that doesn't necessarily mean it understands what it's saying.
So it's all style over substance.
Kind of, yeah.
Like it can talk the cock, but it can't walk the walk.
Exactly.
And that's why it's so important for us to be critical thinkers when we're using AI,
you know, when we're interacting with it.
Right.
Just because something sounds really convincing or even authoritative doesn't mean it's true.
So we can't just take what these chatbots tell us at face value.
Yeah, no, no.
We have to be skeptical.
Yeah.
Do our own research.
Yeah.
And just be aware of the potential for bias, just like we do with any other source of information.
Exactly. You hit the nail on the head.
OK. So how can we sharpen our BS detection skills?
Well, first of all, just be aware of the limitations of AI.
OK.
Remember, these language models, they're trained on these massive amounts of data,
but they don't actually understand the world the way that we do.
Right. They're just recognizing patterns.
Exactly. So don't be afraid to question what you see, what you hear.
Yeah.
If something seems too good to be true.
Uh-huh.
Or it just doesn't sit right with you.
OK.
Dig a little deeper.
Yeah.
Check those sources.
OK.
Look for alternative perspectives.
And don't be afraid to challenge the information that you're given.
That's good advice for life in general.
You know what I agree with you there?
Not just when we're dealing with AI.
Absolutely.
And I think this research also has some implications for how we design and develop
AI systems going forward.
OK.
If we want AI to be a tool for truth and understanding.
Right.
We have to be very careful about the incentives that we build into these systems.
Right. So we need to make sure that we're not rewarding AI for being a good bullshitter.
Exactly. We need to prioritize accuracy and transparency.
Yeah.
Over fluency and persuasiveness.
OK. I got it.
Otherwise, we really risk creating a world where BS reigns supreme.
Yeah. That is a scary thought.
It is a little bit unsettling.
Well, I think this deep drive has given us some really valuable tools for
navigating this increasingly complex world of AI.
I think so too.
It's all about being informed and being critical and maybe having a little fun with it along the way.
Exactly. And you know, if AI can be so good at mimicking human BS.
Yeah.
Maybe that says something about us too.
That's a great point. Something to think about.
Something to ponder.
As we go about our day.
Well, thanks for joining us for this deep dive into the world of AI and BS.
My pleasure.
We'll catch you next time.