Please put me to put me at ease.

Yeah, I mean, specifically within Elsevier, where this starts to raise its ugly head is in our submissions.

So we get author submissions for new research to publish science.

And the ability for someone to create what I'll call fake science, fake research has just exponentially increased.

It's so easy.

It's so easy to create fake research.

And while we have these tools that can create, you know, really harm to the scientific community, if we're not careful, if we're not responsible, we can use these same tools, though, to detect it.

So A couple of you just jump in and tell us examples of how you are going about applying the technology power to do faster, cheaper, better every single day.

... just what AI has brought to the sector in terms of, uh, both its benefits and its, well, its challenges.

challenges.Right.

Right, so benefits, uh, as we talked about, is being able to, to really comb through so much literature that's out there and bring to the surface what the researcher's really interested in.

So understanding the goals, understanding what literature is out there, and trying to, to bring that to the forefront to the, to the researcher, and also to have it supported.

So any statement, any claim that you are generating with AI, you have to have the provenance, you have to have the ability to, to link back, um, to the original source to show where this came from.

And giving the researcher, um, you know, the ability to include literature, to exclude literature, to really be in control still, because it is still, you know, their human judgment that's important, um, is, is super important with, uh, with generative AI.

But being able to preserve the, um, the nuance that comes with scientific research, you know, because it's not...

But no, I see where you're coming from.