What do you say about that when people are like, I don't want to use it because I don't want to use up my portion of water or

whatnot? The first thing I'm going to say is for any individual user, the amount of resources that you are taxing through your individual use is so small in comparison to the big companies.

So from my standpoint, it's the effort is best used to leverage those tools, which I the people that are fighting back against regulation are using the tools, right? Yeah.

So to level the playing field, use those tools in order to try to put regulations on the companies so that they are either limiting their use of the AI tools or making sure that there are carbon offsets or some sort of ecological framework around those big companies' uses of the tools, right? So that, to me, I worry that people...

use that without a full appreciation of where the harm really, like who's bearing responsibility for the really large ecological disruptions, which is not really at the individual level.

It's at the level of kind of these companies and making sure that they're being managed, their carbon and their ecological use being managed in some way.

So that's the first point that I'll make.

start to play with the tools.

Mm-hmm

... purposes around 20% less than men, and that is a consistent figure that's, like, shows up across the research over and over again.

And I got really curious as to why that was.

Um, and there's this kind of, um...

There's this, um, narrative that it's like women are scared or women aren't good at tech, and I was like, "Mm, I kinda feel like it's more complicated than that." So I felt...

I went into the literature, and I felt, I found that there are so many very good reasons why women are skeptical.

You know, women ex- There's...

... of the jobs? Let's, let's talk about that figure for a moment.

Yes.

We can do a lot.

So, right.

So as I was identifying this issue, So I'm of the belief that it's very difficult to be a credible advocate on a particular topic if you don't understand that topic very deeply.

And so as I kind of saw this unfolding in AI, I was like, oh, I need to understand how these tools work.

What's the technical nature of how they're developed? Anyway, so I was looking for roots in as a non-technical person, and I found the roots that were available to me either very, not either, both very isolating and isolated and kind of landing in an impractical place, meaning I felt like I was asked to absorb all of this computer science kind of theory and When really I just kind of want, I mean, I need to know some of that as an advocate in the space.

I need to know some of that because then you have, then you identify how bias exists and is replicated, et cetera.

So can you give us a bit of a lowdown on like the ones that we should be Well, just your input on that.