Episode Transcript
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Speaker 1 (00:00):
Welcome to the deep dive.
Speaker 2 (00:01):
Glad to be diving in today.
Speaker 1 (00:02):
We're really getting into something quite critical and it's evolving fast.
We're looking at the intersection of artificial intelligence and biological threats.
Speaker 2 (00:12):
It's a huge area and definitely timely.
Speaker 1 (00:14):
Absolutely, so our mission for you listening is to explore
the source material we've gathered and try to really understand
what people mean by the dual nature of AI when
it comes to biosecurity.
Speaker 2 (00:27):
Yeah, that's really the key phrase, isn't it dual use technology?
Because AI is well, it's such a powerful tool. It
can do amazing things, speeding up drug discovery, helping us
understand diseases like never before. That's the huge positive side.
Speaker 1 (00:42):
But there's the flip side.
Speaker 2 (00:43):
Exactly, the very same power, the same AI capabilities could
potentially be misused. Think about creating new bioweapons, and.
Speaker 1 (00:51):
You know, biological warfare isn't new, it's an old threat. Unfortunately,
nations have thought about this stuff for centuries. But AI
feels like it's fundamentally changing the game. It's not just
making old threats easier, perhaps, but it seems like it's
enabling new ways well to think about and even test
biological agents at a scale, at a scale humans just
(01:12):
couldn't manage alone creating totally new pathways for harm.
Speaker 2 (01:16):
And what really jumps out from the sources is how
this duality plays out in practice. AI can genuinely fast
track finding treatments for terrible diseases, which is fantastic absolutely,
but that identical algorithmic power could also theoretically help someone
design a novel pathogen, maybe one that's even more vierlin.
Speaker 1 (01:37):
So it really boils down to the accessibility and maybe
manipulation of complex information, doesn't it.
Speaker 2 (01:43):
Yeah, I think so.
Speaker 1 (01:43):
Our sources talk about how these large language models, the lms,
can learn from massive amounts of scientific literature and potentially
spot novel genetic sequences or biological pathways that could be
targeted or exploited.
Speaker 2 (01:56):
And then you have the other side, the biological design
tools or BDTs. These use generative AI to actually design
things like new proteins, maybe even whole viral structures from
the ground up, optimizing them for specific effects.
Speaker 1 (02:11):
And those effects could be therapeutic or and.
Speaker 2 (02:13):
This is the worry pathogenic. It's important to be clear though,
these AA tools aren't like automatically creating bioweapons. In a vacuum.
Speaker 1 (02:21):
No, definitely not.
Speaker 2 (02:23):
But they dramatically simplify and speed up the ideas phase
the design process.
Speaker 1 (02:28):
Which really brings up a core question. If the AI
itself isn't inherently bad, it's just a very sophisticated tool,
how do we actually manage its use?
Speaker 2 (02:37):
That's the million dollar question. The big concern here is
that AI might seriously lower the barrier to entry for
developing bioweapons.
Speaker 1 (02:44):
Making it easier for more people, more groups.
Speaker 2 (02:47):
Potentially yes, yea, even those without deep traditional biological expertise
might be able to leverage these tools.
Speaker 1 (02:53):
One source called this the democratization of knowledge, which sounds.
Speaker 2 (02:56):
Good but has a dark side in this context.
Speaker 1 (02:59):
Exactly, it's like giving everyone access to a super advanced
biological design lab. Some we'll do amazing things for medicine, but.
Speaker 2 (03:06):
Others might, whether they mean to or not, create something dangerous.
The sheer analytic power is well, it's unsettling. AI can
just churn through enormous data sets, define potential weapon.
Speaker 1 (03:18):
Candidates, help design new toxins right, maybe.
Speaker 2 (03:21):
More effective ones, and even potentially figure out ways around
existing security measures.
Speaker 1 (03:26):
And it's not just the you know, the most advanced
cutting edge AI we need to worry about, is it.
Speaker 2 (03:31):
That's a really crucial point from the research. Even less
sophisticated AI models, if you task them with analyzing biological data,
might stumble upon or suggest dangerous pathways completely by accis accidentally.
Speaker 1 (03:44):
Wow.
Speaker 2 (03:45):
Yeah, it implies we need to be incredibly careful about
how we train these models, how we deploy them, and
how we monitor what they're doing just to avoid nasty surprises.
Speaker 1 (03:53):
That accidental discovery angle is Yeah, that's something, and it
links to another key factor, doesn't it? AI getting better?
Speaker 2 (04:01):
No, absolutely not.
Speaker 1 (04:02):
Basic progress in biology itself is also changing the threat landscape.
Think about synthetic biology, where scientists can design and build
new biological parts, devices, systems, and that field is becoming
more accessible too. You can order custom DNA online relatively easily.
Now there are even DIY gene editing kits.
Speaker 2 (04:21):
Out there, which clearly compounds the risk when you combine
it with powerful AI.
Speaker 1 (04:26):
Right, So you have AI suggesting possibilities and then increasingly
accessible tools to potentially build them.
Speaker 2 (04:33):
Now, let's connect that back. Having these powerful tools doesn't
automatically mean someone can successfully weaponize a pathogen. That still
takes a lot expertise, resources, containment, delivery.
Speaker 1 (04:45):
Sure, they're still hurdles, big ones.
Speaker 2 (04:47):
The convergence the powerful AI plus more accessible biocapabilities, it
creates a whole new risk profile. It makes those what
if scenarios feel much more plausible and potentially scale.
Speaker 1 (05:00):
So okay, given this whole changing picture, what do we do?
How do we navigate this future? The sources seem to
really stress that we need to urgently address the gaps
we have in AI regulation right now.
Speaker 2 (05:10):
We definitely do, but it's such a delicate balancing act.
How do you put effective oversight in place without just
completely stifling all the amazing innovation AI is bringing to
medicine and life sciences.
Speaker 1 (05:21):
Yeah, that's the tightrope.
Speaker 2 (05:22):
Proactive monitoring of how AI is developing seems essential, and
regulations around the supply chain, especially for synthetic biology stuff,
probably need a serious rethink.
Speaker 1 (05:34):
What about testing these systems?
Speaker 2 (05:35):
That comes up strongly too. The idea of red teaming exercises.
Speaker 1 (05:40):
So like ethical hacking for BIOAI.
Speaker 2 (05:43):
Kind of basically you get experts to actively try and
misuse these AI tools to find weak spots or ways
they could be used to design bioweapons, to find.
Speaker 1 (05:53):
The vulnerabilities before someone malicious does exactly.
Speaker 2 (05:57):
The idea is to push the developers of these AI
systems to build in strong safeguards right from the start,
not just assume everyone will use them for good.
Speaker 1 (06:05):
The EUAI Act gets mentioned as one approach for thinking
about risk level.
Speaker 2 (06:09):
It does, but a.
Speaker 1 (06:10):
Huge problem is just the speed AI, especially these large
language models. They evolve so incredibly fast it's really hard
for laws and regulations to keep up.
Speaker 2 (06:19):
You set up a framework and boom.
Speaker 1 (06:20):
The tech's already moved onto something.
Speaker 2 (06:21):
New, which points to an interesting alternative approach that some
sources discuss. Instead of trying to regulate the AI models themselves,
which are like moving targets, maybe focus more on the
components that are easier to track and control, like DNA synthesis.
Speaker 1 (06:36):
Ah, so control the physical ingredients essentially sort of.
Speaker 2 (06:39):
Yeah, by having really rigorous controls on the inputs needed
for biological creation, maybe we can rebuild some of those
barriers to making bioweapons that AI might otherwise be tearing down.
Speaker 1 (06:50):
That line of thinking feels really important because imagine, imagine
AI helps someone design a totally new pathogen, something our
current prior defense systems aren't e looking for can't detect.
Speaker 2 (07:01):
That's a genuinely scary thought.
Speaker 1 (07:03):
It means our existing ways of detecting threats responding to
outbreaks they might just not be enough.
Speaker 2 (07:08):
It implies we have to rapidly update how we screen
requests for biological synthesis. We need to really evaluate and
probably enhance our existing biolage programs.
Speaker 1 (07:18):
And invest heavily in early warning systems designed specifically for
these novel perhaps AI designed agents.
Speaker 2 (07:25):
Absolutely. Look, we saw with COVID nineteen how disruptive even
a natural occurring outbreak can be on a global.
Speaker 1 (07:32):
Scale understatement of the century, right, So.
Speaker 2 (07:35):
We have to be far far better prepared for any
kind of major biological event, whether it's natural or it
comes from a lab. And we had to take the
threat potentially amplified by AI incredibly seriously.
Speaker 1 (07:47):
Okay, so we've covered a lot of ground here on
AI and biological threats. You can really see the complexity,
this massive potential for good running right alongside some really
significant risks.
Speaker 2 (07:59):
Yeah. I think the central theme that keeps coming up
is just how crucial it is that we really understand
how AI is fundamentally changing the whole biosecurity picture.
Speaker 1 (08:07):
And the core challenge seems to be that balancing act
we mentioned.
Speaker 2 (08:10):
Definitely, how do we keep hold of and even accelerate
AI's benefits for science.
Speaker 1 (08:15):
And medicine, like finding new drugs faster.
Speaker 2 (08:17):
While at the same time very rigorously managing the risks
that creates, especially this risk of making it easier to
develop bio weapons.
Speaker 1 (08:24):
And the sources we looked at are pretty clear on this.
What's needed is massive collaboration across disciplines.
Speaker 2 (08:30):
You need the tech people, the biologists, the security experts,
public health folks, international policymakers.
Speaker 1 (08:37):
Everyone talking to each other.
Speaker 2 (08:38):
Working together trying to actually get ahead of these AI
biosecurity risks. A huge task, it really.
Speaker 1 (08:45):
Is, but it feels absolutely essential for well for global safety.
Speaker 2 (08:50):
So thinking about all this, the speed of AI, how
it can boost both defense and offense, it leaves you
with a question, doesn't it. What specific fixed steps do
you listening to this think are the most vital things
society needs to do right now to stay ahead of
this challenge as it keeps evolving.
Speaker 1 (09:07):
That's definitely something I'm all over. Understanding this topic is
just so crucial for our future safety. We really hope
this deep dive has to clarify things, maybe illuminated the
complex nature of AI and biosecurity and got you thinking
about what needs to happen next.