Okay, so get ready for this.
We're gonna be exploring a future
where scientific discoveries happen like crazy fast.
All thanks to AI.
I bet you're probably thinking AI in science.
Yeah, is that even possible?
Exactly.
Well, get ready to have your mind blown
because we're going deep into this
leading astrophysicists video essay.
Oh, cool.
And he shares all these insights
along with some other scientists too.
And it's pretty mind blowing.
It's not just science fiction anymore.
Yeah.
I mean, AI is already changing research.
Really?
Oh yeah.
Like how so?
Well, the impact is like growing super fast,
especially in fields like astronomy,
where researchers are dealing with these massive data sets.
So it's like AI is giving scientists these superpowers
to analyze information.
That would just take humans forever.
Exactly.
Think about it.
Okay.
Telescopes are gathering mountains of data every night.
Right.
So AI can like sift through that data and identify patterns.
And even make predictions way faster.
That's crazy.
And more efficiently than humans ever could.
Okay, so AI is like a super powered research assistant then.
Yeah, that's a good way to put it.
But wait, isn't all AI basically the same?
Not quite.
The way AI is being used in science,
it's like evolved over time.
Oh, okay.
You can think of it as three distinct waves.
Three waves.
Okay, I'm intrigued.
So the first wave involved like simpler neural networks,
mainly used for tasks like classifying objects
or predicting outcomes.
Then came the second wave with more sophisticated networks,
capable of things like image recognition.
Oh, cool.
You know, like self-driving cars use that.
Right, right.
So that's the second wave.
Okay, so we're in the third wave now.
Yeah, we are.
What's so special about that one?
Well, this third wave is all about unsupervised
and generative deep learning.
Oh, wow.
This is where things get really interesting.
These AI models can learn from huge amounts of data,
unlabeled data, finding complex patterns
and relationships that humans might miss.
Okay.
And they can generate new data.
Really?
Like images, texts, even code.
So it's not just about analyzing existing information,
but actually like creating new knowledge.
Wow.
That's pretty wild.
It is.
There's a lot of people here deep learning
and they just think of chat GPT.
Yeah.
Is that right?
You're right to think of it.
Okay.
Chat GPT is like a prime example of this third wave.
Okay.
It's a generative AI model.
Uh-huh.
That can understand and generate human language.
So it's like super versatile.
Super versatile.
Okay, but chat GPT is mainly known for
like writing essays and poems, right?
Yeah.
How does that apply to actual science?
Well, imagine using chat GPT
to summarize complex research papers.
Okay.
Translate scientific articles.
Into different languages.
Or even like help write sections of manuscripts
or grant proposals.
No, that's a good idea.
And in fact, it's already happening.
Really?
One study found.
Okay.
That 30% of scientists are already using AI tools.
What?
30%.
That's a lot.
It is, it is.
But hold on.
Yeah.
If AI is helping write scientific papers.
Yeah.
Doesn't that raise some ethical questions?
Of course.
Like who gets credit for the work?
Right.
That's a key question being debated right now.
Yeah.
Should AI be listed as a co-author?
That's so interesting.
Some journals are even banning the use of AI.
Really?
Altogether.
Wow.
Because of concerns about plagiarism and accountability.
Yeah, that makes sense.
But on the flip side.
Yeah.
Imagine a future where AI can analyze tons of data.
Okay.
And generate draft sections of a paper.
Wow.
Freeing up scientists to focus on the big picture.
Okay. I see both sides of that.
Yeah.
On one hand, it seems unfair to give AI authorship.
Right.
If it's just a tool.
But on the other hand, if AI can help scientists
be more efficient and productive.
Yeah.
And productive.
That could lead to more breakthroughs, right?
Exactly.
Yeah.
It's a complex issue.
And there are no easy answers.
Yeah.
What's clear is that AI is already impacting research.
Right.
In profound ways.
Yeah.
And it's not just about writing, right?
Right.
It's about other parts of research.
Yeah. Like what?
Like collecting data, designing experiments,
or even peer review.
Yeah.
Can AI play a role there too?
Absolutely.
Yeah.
Let's take the example of data analysis in astronomy.
Okay.
AI can help identify patterns.
Uh-huh.
In the massive amounts of data collected by telescopes.
Right.
Helping researchers find new objects.
Oh.
Or events.
So AI is like a super powered detective.
Yeah.
It includes in space.
That's a great analogy.
And think about designing experiments.
Yeah.
AI can help scientists optimize their setups.
Right.
By analyzing previous data.
Exactly.
And suggesting parameters.
That's right.
That are most likely to yield results.
Yeah. Meaningful results.
Right.
This can save a lot of time and resources.
That's amazing.
Allowing scientists to conduct more experiments.
That's fascinating.
Yeah.
So AI can actually make science more efficient
and innovative.
Yeah. More efficient.
More innovative.
What about peer review?
Oh, that's interesting.
That crucial process.
Yeah. Checking research.
For its published.
Right.
Can AI really contribute there?
That's where things get really interesting.
Okay.
Imagine an AI system.
Yeah.
That can analyze a manuscript.
Mm-hmm.
Identify its key findings and contributions.
Right.
And even suggest potential reviewers.
Wow.
Or experts in the field.
Wait. So instead of journals struggling
to find reviewers.
Yeah.
AI could streamline the whole process.
Exactly.
And speed up the publication timeline.
Exactly.
AI could even help with tasks like checking for plagiarism.
Oh.
Okay.
Identifying statistical errors
or highlighting ethical concerns.
Yeah. Yeah.
Of course, human oversight would still be essential.
Right.
But AI could reduce the workload
for editors and reviewers.
That makes a lot of sense.
Yeah.
But what about the concern that journals
might start selling their archives of.
Oh, yeah.
Reviewer comments and author responses.
Right.
To train these AI models.
Yeah.
It seems a little sketchy.
It's a valid concern.
Yeah.
As AI becomes more integrated into research.
Right.
We need to be mindful of the potential consequences.
Yeah.
And make sure that ethical considerations
are front and center.
For sure.
Yeah.
It sounds like we're on the verge of a major shift.
We are.
In how science is done.
Totally.
But where do humans fit into all of this?
Right.
If AI can do so much.
Uh-huh.
Does that mean the end of the human scientist?
Well, that's the big question, right?
Yeah.
This astrophysicist, he's really grappling with this.
Yeah.
He talks about how for a lot of scientists,
research is driven by this.
Like this curiosity.
Right.
You know, this need to understand the universe.
What they understand.
It's like this fundamental.
Yeah, like a human drive.
Human drive.
Totally.
Right.
Yeah.
It draws a lot of us to like science podcasts,
documentaries, all that stuff.
Yeah, we crave that.
Yeah, you crave that.
Uh-huh.
Moment.
Uh-huh.
I'm all over.
A feeling of understanding something new about the world.
Exactly.
And that's where things get interesting.
Okay.
What happens if AI starts making all these ground breaking
discoveries that are so complex,
so beyond human comprehension,
that we can't even grasp them?
So it's like, is it even a discovery?
If humans can't understand it, does it even matter?
Right.
It raises some deep questions.
Yeah.
About like the nature of knowledge and discovery.
Yeah, for sure.
And it makes you think about the role of scientists.
Yeah.
If AI can churn out all this research,
what makes a human scientist valuable?
Right.
And what about science communication?
Like all those amazing science communicators out there
who can explain these complex topics
in a way that's both accurate,
but also engaging.
Could an AI ever do that?
Would we even want it to?
That's where the scientists in the video
had some really different opinions.
Some were skeptical that AI could ever truly replicate
human intuition and creativity,
especially in fields like physics,
where so much is based on physical experience
and experimentation.
Right.
Like one scientist brought up
Einstein's thought experiment.
Oh, yeah?
About writing in a falling elevator.
Yeah.
He argued that an AI without a physical body
could never truly grasp
what it feels like to be weightless.
Yeah.
To experience gravity in that way.
It's a really thought provoking point.
Yeah.
How can an AI without those experiences.
Yeah.
Develop this deep understanding.
Right.
Of the physical laws that govern our universe.
But this is where I get tripped up.
Yeah.
Even if AI can't have those aha moments.
Like those original insights.
Right.
What if it's really good at connecting existing ideas
in new and surprising ways?
Yeah, that's interesting.
Couldn't that lead to huge advances?
Absolutely.
Yeah.
Like AI could be incredible at spotting patterns
and connections across massive data sets.
Right.
Things that humans might miss.
Right.
It could even combine insights from
different fields of science.
In ways we wouldn't even imagine.
Wow.
Like you know that saying.
Yeah.
Creativity is just connecting things.
Right.
Exactly.
So maybe it's not about AI replacing scientists.
But about AI becoming this powerful tool.
Yeah.
That helps us see things in new ways.
Make those connections faster.
Exactly.
And ultimately accelerate discovery.
Totally.
And this is where the human element
becomes even more critical.
Okay.
Think about it.
Okay.
Interpret those findings.
Right.
Explain what they mean.
Right.
Communicate that knowledge.
It's like even if AI is making the discoveries.
Yeah.
We still need humans to make sense of it all.
Make sense of it all.
Tell the story of science in a way
that's compelling and meaningful.
And to teach the next generation of scientists.
Yeah.
How to work with these tools.
That's a good point.
Right.
Yeah.
Makes you wonder if universities will evolve.
Yeah.
This is places where we mainly focus on training humans.
Okay.
To collaborate with AI.
Right.
Rather than trying to compete with it.
That's a really wild thought.
It is.
If AI can outperform humans.
Yeah.
In so many research tasks.
What does that mean for the future of universities?
Will they become more about teaching critical thinking.
Creativity.
Commutation skills.
It's certainly a possibility.
Yeah.
It raises another question.
Okay.
What happens to the traditional research university.
Right.
If AI becomes the primary driver of discovery.
Does it become obsolete.
Yeah.
Or does it transform into something new.
Yeah.
This is really making me rethink.
Uh huh.
The whole purpose of higher education.
Yeah.
And that's what's so exciting about this topic.
Mm hmm.
It forces us to confront these questions.
Yeah.
About the nature of science.
Right.
The role of technology.
Yeah.
And what it means to be human.
Right.
In a world increasingly shaped by AI.
Yeah.
That's so true.
It feels like we're at this crossroads right.
Like on one path.
Yeah.
We have AI revolutionizing science.
Everly.
Leading to all these discoveries we never could have imagined.
Yeah.
But then on the other path.
Yeah.
There's this fear of losing that human connection.
That makes science meaningful.
It's a tough one.
Yeah.
And the astrophysicist ends his video
with this really inspiring message.
He says, the future of science isn't predetermined.
Right.
It's something we create.
Oh, I like that.
Yeah.
It's not about letting AI dictate the future.
Yeah.
It's about us.
Yeah.
Making choices about how we want to integrate AI.
Exactly.
What role we want it to play.
We need to have these conversations.
Think about the ethical implications.
Right.
And create guidelines.
Yeah.
For how AI is used in research.
So like what kind of question should we be asking?
Well, like how do we ensure accountability
when AI is involved?
I think it's a good one.
How do we protect against bias?
Right.
And how do we preserve the human element of discovery?
Yeah, we were just talking about that.
So it's like.
It's like we're writing the rules
for this whole new era of science.
Wow.
And it's up to us to get it right.
That's a lot of pressure.
It is.
But OK, let's get back to that core question.
Can AI really empower scientists?
Right.
Still preserving the joy of discovery.
That's the question, isn't it?
Yeah.
And it's not an easy one to answer.
I guess not.
It's going to require a lot of thought, collaboration
between scientists, ethicists, policymakers, the public,
everyone.
And that's where you come in.
You got it.
Our listeners.
Yeah, we want to hear from you.
What are your hopes and concerns about AI in science?
Yeah, what do you think?
What kind of future do you envision?
Do you think AI will enhance human understanding?
Yeah.
Or lead to a more detached, less human-centered approach?
So share your thoughts.
Yeah.
Join the conversation.
Because the future of science isn't something happening to us.
Right.
It's something we're creating together.
Exactly.
Well, on that note, I think we've reached the end.
The end of our deep dive.
Of our deep dive into AI and the future of science.
It's been a journey.
It really has.
Hopefully you learned something new.
Yeah, gained a new perspective.
Maybe even felt the spark of curiosity.
For sure.
Keep asking those big questions.
Stay curious.
And remember, the future of science is in our hands.
Until next time.
Keep exploring.