Tina Eliassi-Rad

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154 appearances 1 recordings 1 series first heard Jan 2025 last heard Jan 2025

Tina Eliassi-Rad’s voice in public audio — every appearance, attributed to the second.

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Sean Carroll's Mindscape: Science, Society, Philosophy, Culture, Arts, and Ideas · 301 | Tina Eliassi-Rad on Al, Networks, and Epistemic Instability · 13 Jan 2025 podcast

Yeah, maybe. Yeah, we didn't do any kind of causal stuff, right? Like a lot of the work, a lot of the hype that's happening now in AI and machine learning, they're all on the correlation side, not on the causation side. So we didn't look at that at all about what causes what. That's very difficult. And I haven't touched the field of causation in part because I'm married to a philosopher.

Because every time I try to approach the topic, I just heard nightmares. And so I haven't gone that way yet.

Yeah, I think that there's some of that. I think the best way of using this is perhaps government policy. Right. When government issues a policy and then like maybe 20 years from that, you have if you have good data, you could see, OK, what has been some of the correlations that have come about based on this policy?

And then maybe, you know, the actual social scientists and political scientists can then draw some causal diagrams from what we find. Because the one thing is, Usually like from the computer science, AI, machine learning, we treat causation and correlation as if binary, right? As it's like a coin this way or that way. But that is really not the case, right? It's more of a spectrum.

And so if you have a model that is producing robust predictions, there is some underlying causal model. You just don't know it. And then maybe that could steer you into the right direction. for that kind of work. But we didn't look at that for this particular work.

Yeah, I am very interested in the feedback that we were talking about and how do we capture that feedback between, for example, when I go and I'm using Amazon and Amazon is making me these recommendations and then I buy things, I tell my friends and then all of that data goes back into Amazon and how much does my contributions or my friends' contributions amplifying what Amazon is doing?

And so there's some of that going on. And then there's also in terms of like society is a complex system and the place of these tools in these systems. So the tools that help us spread misinformation and disinformation make our society unstable in that then you're not quite sure. what you are reading is true or not, right?

So right now with the fires in LA, there's a lot of misinformation and disinformation going on. And it's like, Who do I believe? And maybe like you believe LA Times and you believe, you know, what you read in CA.gov and so on and so forth, but not what you're seeing on Instagram.

And so there's this notion of the place of these AI tools within our society and whether they're making our society better or worse. And by better or worse here, I mean stable versus not stable, more chaotic. And I think we can all agree that we would like to live in societies that are more stable than not, right? So there's some of that that is going on.

And I have a new project along those lines, which actually touches on philosophy, which is called epistemic instability, which is what are some stability conditions of what you know? So if you genuinely know that whales are mammals, no matter what I show you, perhaps I won't be able to convince you that a whale laid an egg. You're like a whale is a mammal and mammals do not lay eggs. Right.

And you're very sure about it. Right. But then you start talking to me and to chat GPT. And maybe if you don't know something, then you're like, as, as well as you thought, right. Then I, then you're malleable. Right. Then I can like change your mind. And then now you have groups of people who are talking to these within themselves and with, These generative AI tools.

And then basically you go from like individual to groups to this hypergraph notion. And what I'm interested in is when our phase transitions in this hypergraph in terms of what the society believe, like maybe the society believe that vaccines are good. Right. And now all of a sudden the society doesn't believe the vaccines are good.

And what are the leading indicators of those kinds of phase transitions in our society as it's being modeled by conversations formally represented as these hypergraphs?

But now, even if you're on the fringe, because of the information technology that we have, you can connect to other people who are on the fringe and then you believe, oh, no, we're bigger than the fringe. We're actually in the middle. Right. And then that kind of thing spreads. Right. So that is one of the things I'm interested in.

Regarding gay marriage, one of the things that was interesting is I was talking to a philosopher who I just taught for a very long time at the Ohio State University, and he was teaching ethics and issues related to gay marriage and abortion, et cetera.

And he was saying that with gay marriage, similar to what you were saying, he saw a shift in terms of opinions for or against gay marriage, mostly for, but he didn't see any change when it came to abortion. And I think that had to do with the vagueness of when is, let's call the thing a baby, right? When is the actual fetus a baby or whatever, you know?

And so, and that vagueness, because like we could all agree that maybe like the day before you're about to give birth, obviously you're not going to do anything. We all believe it's a baby. But that vagueness is something that doesn't shift the opinion on abortion so much for or against. And I like that vagueness aspect of it.

So there are certain things that are vague and maybe you will never have that kind of phase transition. And then there are certain things like the vaccine where like there are people on the fringe that our information technology allows them to connect to each other. And so it feels like a bigger thing.

And then maybe there are other aspects of information that really do make people change their mind just based on talking to other people. And so they're not as sure or as stable in their knowledge.

So it's a work in progress right now for us on this. I'm trying to stay away from making it a psychology or a social science problem because then you get all these confounding factors. And that's what I said. It has more tentacles to philosophy. So in terms of what people ought to do in terms of their knowledge and how sure they are of their knowledge.

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