Li-Lian Ang
speaker
308 appearances
1 recordings
1 series
first heard Apr 2026
last heard 2 Apr
Li-Lian Ang’s voice in public audio — every appearance, attributed to the second.
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recordings per month · last 12 monthsRecordings per month over the last 12 months — 1 in all, peaking in Apr 2026 with 1.
Appearances
the better that we teach them how to solve problems and split apart into different agents who think and break down the problem to different things because it's useful for them to help us with other work.
It's just going to therefore increase their ability to then solve these problems overall, which is kind of crazy.
This is a strategy that some people feel excited about, which is like, if we can
differentially accelerate or like put more resources into defenders being able to better use or develop ai systems that are much better at defending then they will always have the upside against an attacker and the kind of like limitation to this strategy is like where is the limit of this at one at what point will will it like reach a ceiling uh where it just can't
have that much of advantage against an attacker.
And
Will we need something way more robust, like formally verifiable mechanisms that make a system secure no matter what kind of attack?
Because lots of cyber attacks rely on the fact that you will never meet this edge case, or this is just really unlikely.
Because the more secure you try to make a system, the less user-friendly that it becomes.
The harder it is for you to edit the code or understand what it's doing.
And so you're making a trade-off of how usable this thing is or how easy it is for a person to interact with it against some security risk.
And will this mean that one day there will be a paradigm shift with how we think about cybersecurity overall?
And I think this kind of, like, ties into, like, this overall, like, idea of, like, what makes this, like, dual-use technology really difficult is that it's not so much of, like, there is, like, a definite solution that, you know, like, all we need to do is, like, find this golden rule for how we should be developing AI systems and then everything will work out just fine.
Because that's just not how it works.
It's, like, it's way too complex, right?
for you to just say, like, there's just like one path forward.
It's more of like, what are the trade-offs that we're willing to make to be able to use this technology in such a way where we gain a lot more of the benefits than kind of the harms, like in a very like hand way, so to say.
One is about what people call sometimes gradual disempowerment or like you can also conceive of it as like massive job loss or like what are people going to do when AI systems do all the jobs that people usually do?
And it's kind of like the way it.
things feel like they're going where if ai systems are so good i mean you see this mostly with like software engineering right now like if ai systems are so good at spinning up apps like designing like web pages doing the whole like code review what's gonna happen to all the software engineers um and you know like extrapolate this like other fields what's gonna happen to this like entire field of people what are they gonna do or like where will they go
Showing 81–100 of 308 · page 5 of 16
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