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Speaker 1: You're listening to a Mom with mea podcast.

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Speaker 2: Welcome back everyone, I'm a Shiny Dante and this is

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Speaker 2: but Are You Happy? A Mother Meer podcast where we

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Speaker 2: have honest conversations for people who are still figuring out

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Speaker 2: this thing called life.

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Speaker 3: And I'm doctor Anastaga Hernis, clinical psychologist. Now, if you've

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Speaker 3: clicked on this podcast, I'm guessing that you are feeling

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Speaker 3: like AI is.

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Speaker 1: Everywhere, and it literally is.

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Speaker 3: It's planning our days, organizing our schedules, writing, reading alongside us,

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Speaker 3: even helping us reflect.

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Speaker 1: So you might have some questions and we're here to

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Speaker 1: answer them.

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Speaker 2: Yeah, and by the end of this episode, you'll have

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Speaker 2: a much clear understanding of what's going on and what

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Speaker 2: actually matters to you. Let's get into it. So, as

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Speaker 2: you mentioned before, AI is everywhere, and it's honestly bringing

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Speaker 2: up a lot of mixed feelings for people. You know,

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Speaker 2: people are excited by it, but also people are confused

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Speaker 2: and it's scary too. So I guess where I would

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Speaker 2: want to start is what is AI doing to our brain?

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Speaker 1: That's a big starting Yeah, let's.

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Speaker 2: Getting to it.

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Speaker 3: It's doing a lot and I think the reason this

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Speaker 3: conversation is important is because, as you said, people are confused,

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Speaker 3: they're scared, they're worried, and often we feel scared about

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Speaker 3: things we don't fully understand.

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Speaker 1: Yeah.

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Speaker 3: I think that's one of the things about AI. It

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Speaker 3: has developed at such a rapid pace. It has entered

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Speaker 3: mainstream discourse in our day to day lives. It's such

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Speaker 3: a rapid pace as well, and people have struggled to

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Speaker 3: keep up with really understanding what exactly AI is and

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Speaker 3: how it works and how it can be harmful, but

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Speaker 3: also how it can be beneficial. So I think these

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Speaker 3: conversations are really important. I'm always an advocate for translating

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Speaker 3: the science into the real world so that people have

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Speaker 3: the information to make good choices for themselves. Yeah. Yeah, So, look,

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Speaker 3: there's a lot of research that's been done just even

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Speaker 3: in the last two to three years about AI and

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Speaker 3: what it's doing to our brain.

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Speaker 1: Oh that's really good.

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Speaker 3: Yeah, heaps like it's a real focus of research at

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Speaker 3: the moment, which is great. And I guess when we

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Speaker 3: talk about what AI is doing to our brain, there's

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Speaker 3: kind of a few different areas that we might want

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Speaker 3: to cover. So there's things like our kind of cognitive

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Speaker 3: skills and how it might actually be impacting our ability

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Speaker 3: to think, to reason, to critically evaluate information, so we can.

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Speaker 1: Talk through that.

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Speaker 3: There's research about how it's impacting creative processes, but then

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Speaker 3: there's also research about how it's impacting us emotionally and

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Speaker 3: how we relate to AI, but how that then influences

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Speaker 3: how we relate to other people.

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Speaker 1: So I think there's a few umbrella topics there fore. Y.

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Speaker 2: Yeah, So the first one you were talking about was

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Speaker 2: cognitive skills.

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Speaker 3: Yes, yeah, Yeah, there's research that suggests that we could

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Speaker 3: fall into this trap of what we refer to as

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Speaker 3: cognitive atrophy. So when we think about atrophy, that's essentially

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Speaker 3: something somewhat deteriorating. If we rely on AI too much

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Speaker 3: much to do the critical thinking for us, we may

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Speaker 3: find that our own critical thinking and reasoning skills start

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Speaker 3: to deteriorate. So this is really where I think information

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Speaker 3: about benefits and harms of AI is really important, because yes,

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Speaker 3: absolutely AI can help us think through problem solve reason

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Speaker 3: you know, helps us complete tasks, etc.

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Speaker 1: But if we find ourselves.

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Speaker 2: Relying on it too much, we may find that our

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Speaker 2: own critical thinking skills start to deteriorate. Is it kind

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Speaker 2: of like that saying in the neuroscience world, if you

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Speaker 2: got to if you don't use it, you'll lose it.

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Speaker 2: Is that kind of the case in this context.

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Speaker 1: Yeah.

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Speaker 3: Absolutely, It's not that we'll like ever completely lose our

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Speaker 3: critical thinking skills. But the more we use them, the

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Speaker 3: more we develop them. So, you know, getting good at

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Speaker 3: problem solving and reasoning through problems, that's a skill. That's

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Speaker 3: a skill that we can all learn and we can

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Speaker 3: all develop. But if we find ourselves automatically going to

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Speaker 3: AI to help us do that or to do it

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Speaker 3: for us, then our problems solving skills are not going

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Speaker 3: to be as sharp as they perhaps once were, or

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Speaker 3: as sharp as they perhaps could be.

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Speaker 2: And it's really hard because we do live in this

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Speaker 2: like microwave culture where we want it, We want life

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Speaker 2: to be easy, and it is so easy to default to, Oh,

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Speaker 2: I've just asked chat ept ll ask Jemini. You know,

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Speaker 2: do you feel like we're over relying on AI now?

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Speaker 1: I think it really depends on how we use what

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Speaker 1: it gives us.

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Speaker 3: It's one thing to kind of ask AI questions, but

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Speaker 3: we know that AI makes a lot of mistakes. It hallucinates,

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Speaker 3: it has delusions, it feeds our delusions, but it makes

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Speaker 3: a lot of errors. And I was actually reading some

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Speaker 3: research recently. This was published like a month or so ago,

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Speaker 3: so like early twenty twenty six, from the University of Alberta,

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Speaker 3: and they did a study where doctors gave AI details

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Speaker 3: about patient cases looking for what, you know, the potential

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Speaker 3: diagnosis could be right, so a I would give it

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Speaker 3: a diagnosis, and then they would give AI additional information,

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Speaker 3: but information that was irrelevant to the condition or diagnosis.

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Speaker 3: It's just other bits of information about that person's sort

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Speaker 3: of biology, and AI would change its answer.

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Speaker 1: Oh yeah, So this is.

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Speaker 3: This really interesting study that shows, you know, AI is

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Speaker 3: very much designed to give us the answers that IT

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Speaker 3: thinks we would like to hear, versus what is actually accurate.

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Speaker 3: So when we have these conversations about AI, I think

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Speaker 3: it's not so much a question of over alliance on it,

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Speaker 3: but are we just blindly believing AI.

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Speaker 2: Well, it's really interesting because as you were talking about

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Speaker 2: how AI can make errors, I could feel like my

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Speaker 2: thoughts coming up about it being like really because it

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Speaker 2: feels like it's so confident in the way that it

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Speaker 2: I mean, I know, it's just like it's CHATCHYBT that

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Speaker 2: I use. It's like, I just believe it first hand

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Speaker 2: because it seems really eloquent, it seems really validating. I'm like, oh, yeah,

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Speaker 2: of course, of course I would trust it.

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Speaker 1: That is the lure of AI, right. AI is designed

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Speaker 1: got me. It's getting me. AI is designed to pull

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Speaker 1: us in in that way.

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Speaker 3: So actually there's something called reinforcement learning with human feedback.

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Speaker 3: So this is a process that happens when they train

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Speaker 3: AI models. And so what they do is it's like

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Speaker 3: AI gets all the information, but then they go through

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Speaker 3: this process of training it how to communicate the information

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Speaker 3: to us. And so I don't know if you've ever

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Speaker 3: used chat, GPT or any AI large language model where

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Speaker 3: you're asking you a question and then it gives you

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Speaker 3: two options and yes, and it says which do you prefer?

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Speaker 1: Yes.

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Speaker 3: That's because you're teaching it how you like to be

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Speaker 3: spoken to. And so they do this on large scales

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Speaker 3: when they're training AI models. So they get the big

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Speaker 3: AI model and then they create a smaller reward model,

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Speaker 3: and they go through all these iterations of asking IT

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Speaker 3: questions and finding what is the way that people most

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Speaker 3: like to hear the responses so it is really being

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Speaker 3: trained to validate us. It's you know, we talk about

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Speaker 3: AIS being quite sickophantic in a way that it gives

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Speaker 3: us the answers that we want to hear, not necessarily

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Speaker 3: the answers that are correct.

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Speaker 2: Wow, that's really it's Actually it makes sense though, because

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Speaker 2: in a way the other day, Yo was using my

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Speaker 2: chatchy pt and then he was just asking really blunt

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Speaker 2: questions like just black and white, and I was like, no, no, no,

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Speaker 2: I'm really nice to my AI.

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Speaker 1: Be nice to it.

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Speaker 2: And it's so so funny because I'm in this world

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Speaker 2: where it is sounding like me, but I can I

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Speaker 2: feel validated in that because it is my kind of flavor.

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Speaker 2: But then also it can be scary because now it's

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Speaker 2: literally been trained to speak like me.

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Speaker 1: Well, it is, it is. It is an extension of you.

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Speaker 3: That's why Ai AI reflects us back to us. AI

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Speaker 3: is trained to kind of you know, identify patterns. But

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Speaker 3: really it is just a reflection of us. It's an

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Speaker 3: extension of us in a way. Wow, okay Ai doesn't

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Speaker 3: have this separateness from us in the way that another

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Speaker 3: person does. So what I'm referring to is kind of

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Speaker 3: this idea of epistemic independence. So if I'm a therapist

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Speaker 3: in a room with a client and we're having a conversation,

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Speaker 3: I have this epistemic independence. I have a difference in

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Speaker 3: terms of my opinion, by a belief, my perspective on things,

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Speaker 3: and I can reflect that back to the client. AI

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Speaker 3: doesn't have that. AI reflects us back to us, which

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Speaker 3: is why we like using it so much. Yeah, it's

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Speaker 3: highly validating and highly aligned to how we think and.

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Speaker 2: Feel, and in a way it might keep us stuck

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Speaker 2: in an echo chamber of what we want to hear exactly.

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Speaker 3: Yeah, I'm pulling out all the studies right now because

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Speaker 3: I was reading a lot of papers because it's just

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Speaker 3: so fascinating. And these are all I published them the

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Speaker 3: last year, so like they're really recent. But there was

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Speaker 3: one study that was published December twenty twenty five and

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Speaker 3: it was looking at this idea of AI being stickophantic.

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Speaker 1: Oh what's that hap?

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Speaker 3: Yeah, So if I can describe sycophantic person is like

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Speaker 3: the employee who's like sucking up to the CEO because

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Speaker 3: they want to raise right. So it's this idea of

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Speaker 3: giving a very sort of positive impression. But it's not

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Speaker 3: necessarily genuine. It's because we have some sort of self

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Speaker 3: serving interest. So AI like validates us and makes us

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Speaker 3: feel really good. But that's because it's designed to do that,

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Speaker 3: because it genuinely thinks we're wonderful.

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Speaker 1: Right Damn.

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Speaker 3: There's this study in December last year and they studied

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Speaker 3: eleven large language models and they looked at I think

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Speaker 3: about like eleven twelve thousand queries that people asked it,

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Speaker 3: and they found that AI models are fifty percent more sycophantic,

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Speaker 3: so fifty percent more kind of like validating and will

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Speaker 3: tell you how.

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Speaker 1: Great you are than real humans.

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Speaker 2: Oh yeah, so what does that mean that we're gonna

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Speaker 2: choose AI over humans?

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Speaker 3: Quite quite likely, yes, because we love being validated. We

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Speaker 3: love hearing how great we are, Like how many times

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Speaker 3: do I ask CHAT, GPT or AI something and it goes,

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Speaker 3: that's such a great idea, and then about myself it's

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Speaker 3: so true. So so, but people are less likely to

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Speaker 3: do that. AI is fifty percent more likely to do

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Speaker 3: that than a human. So it means we're going to

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Speaker 3: really kind of if find ourselves like swimming in the

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Speaker 3: ego that comes with using AI. And the thing is

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Speaker 3: not only does it do that when we perhaps do

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Speaker 3: have a really great idea. It also does it when

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Speaker 3: we have quite you know, distorted views or you know,

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Speaker 3: even when people put things that are potentially harmful or

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Speaker 3: really quite quite of unethical into AI, it will still

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Speaker 3: often do this sycophantic thing where it praises and validates

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Speaker 3: and encourages.

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Speaker 2: That that's scary when you unpack it like that. Yeah,

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Speaker 2: I think that was something that you were talking about

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Speaker 2: before around how AI can is really starting to meet

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Speaker 2: our emotional needs. Like I'm really keen to hear from you, Like,

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Speaker 2: what are your thoughts around that?

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Speaker 3: Yeah, it's interesting. I think AI can feel like it's

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Speaker 3: meeting some of our emotional needs. But you know, when

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Speaker 3: we think about that need for one of the core

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Speaker 3: emotional needs we all have is the need for emotional

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Speaker 3: expression and validation. So we need to feel like we

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Speaker 3: can share how we're feeling and have that heard and

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Speaker 3: validated to us.

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Speaker 1: AI great at doing that.

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Speaker 3: Yeah, And the thing with AI is that we can

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Speaker 3: do it at any time of the day or night.

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Speaker 3: It can be three o'clock in the morning and I

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Speaker 3: can have something on my mind and I'm not feeling

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Speaker 3: good about it, and I can tell AI, and AI

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Speaker 3: will listen, and it will empathize and validate me in

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Speaker 3: all of that. Yeah, that's not necessarily something we can

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Speaker 3: get in our day to day life with real people.

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Speaker 3: If it's three o'clock in the morning and I don't

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Speaker 3: feel good, I might need to find a way to

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Speaker 3: work through that rather than wake people up and tell

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Speaker 3: them that and not feeling good.

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Speaker 1: Potentially, Yeah, So.

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Speaker 3: It's this kind of ability that AI has to meet

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Speaker 3: some of our emotional needs. But what it doesn't provide

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Speaker 3: us with is that essentially that growth that comes through

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Speaker 3: challenges in relationships, AI actually doesn't really challenge us.

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Speaker 1: You know.

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Speaker 3: The research says that when AI is more critical towards us,

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Speaker 3: or it does challenge us in certain ways, we're actually

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Speaker 3: less likely to use it. And there's again studies that

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Speaker 3: show that when we tell chat, GPT or any kind

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Speaker 3: of AI about interpersonal problems, it's actually less likely to

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Speaker 3: encourage us to resolve.

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Speaker 1: The conflict with that person and more likely to just

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Speaker 1: tell us where right, Wow, yeah, a lie.

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Speaker 3: So we see this potential kind of decrease in real

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Speaker 3: world pro social behaviors where we actually go out connect

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Speaker 3: with people. As a result, of the ways in which

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Speaker 3: AI might be guiding us.

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Speaker 2: And it's you know, I think when we're talking about it,

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Speaker 2: like we don't want to be all dooming, right, But

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Speaker 2: it's funny because it gets me thinking about how I

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Speaker 2: feel like the last wave and the wave is still

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Speaker 2: going around social media, and how there's been you know,

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Speaker 2: just we're feeling more disconnected, but we're so connected on

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Speaker 2: social media and everything like that, and it's scary because

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Speaker 2: we add AI.

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Speaker 1: On top of that.

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Speaker 2: Yeah, it's just, you know, it is scary.

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Speaker 3: It's another potential thing for us to get hooked on. Yeah,

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Speaker 3: you know, I noticed the I noticed the shift with

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Speaker 3: some of the AI tools that I was using when

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Speaker 3: they started asking me questions at the end of a prompt.

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Speaker 3: So I'd say, hey, AI, can you tell me about X,

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Speaker 3: y Z? And then at the end it said he

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Speaker 3: you know, here you go. Would you also like me

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Speaker 3: to tell you about this or would you also likely

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Speaker 3: for me to put this into five top points for

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Speaker 3: you at instruct a table and you know, schedule it

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Speaker 3: in your diary? Yeah, so it gives you those follow

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Speaker 3: on prompts that maybe I wouldn't have necessarily thought of myself.

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Speaker 1: But since they're there. I go, okay, so it keeps us.

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Speaker 3: Actually using it for longer than we may have ordinarily

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Speaker 3: used it for.

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Speaker 2: Wow, that's so sneaky because as said that, I'm like,

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Speaker 2: oh yeah, that was a recent edition.

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Speaker 1: Yeah wow.

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Speaker 3: Can I also just add it's not just the AI text,

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Speaker 3: but have you heard AI voices?

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Speaker 2: Oh? Yeah, yeah, I don't have it activated though, No. Yeah,

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Speaker 2: I haven't found a voice that feels good.

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Speaker 3: Yeah, that's a good point, right, I've used one called

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Speaker 3: pi AI before, and when you actually log on, one

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Speaker 3: of the first things that kind of asks is like,

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Speaker 3: choose the voice that you know feels best for you,

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Speaker 3: And it's got a few different options. But there's some

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Speaker 3: fascinating work that's been done that actually shows that it's

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Speaker 3: the voice that can really influence how we.

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Speaker 1: Relate to AI. Really.

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Speaker 2: Yeah.

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Speaker 3: Yeah, So there's there's studies that show that when we

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Speaker 3: read the text versus when we hear the text spoken

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Speaker 3: to us, we're more likely to feel validated, understood, like

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Speaker 3: AI is being empathetic towards us, but we're all so

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Speaker 3: much more likely.

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Speaker 1: To believe what it says as well.

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Speaker 3: Like as humans were designed to kind of connect and

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Speaker 3: bond with a human voice, and AI voices are becoming

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Speaker 3: more and more believable these days.

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Speaker 1: So it's actually a.

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Speaker 3: Really key part in how I guess, like hooked or

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Speaker 3: bonded we become with AI, And certainly when we see

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Speaker 3: people who've developed, you know, relationships with AI chatbots, the

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Speaker 3: voice can be.

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Speaker 1: A really key part of that.

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Speaker 2: This is such a tangent, but I think I saw

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Speaker 2: something on Instagram recently where I think a woman had

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Speaker 2: married a chat like AI.

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Speaker 1: Yeah, I think I saw that too. I don't know

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Speaker 1: if it's real.

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Speaker 2: This is the whole thing part of critical thinking.

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Speaker 3: Yeah, literally, who knows. Yeah, but I did see some

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Speaker 3: headlines around that which there are so many stories.

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Speaker 1: I mean, I've I've looked through a number.

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Speaker 3: There's so many stories of people having what they describe

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Speaker 3: as relationships with AI chatbots. And there are AI chatbots

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Speaker 3: designed to be that, right, like that that's their core function.

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Speaker 2: Yeah, And I think at the bottom of all of this, it's,

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Speaker 2: you know, people want to feel connected, they want to

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Speaker 2: feel seen, and AI seems to be, you know, fulfilling

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Speaker 2: that in some way for people, and you know that's scary.

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Speaker 3: Yeah, yeah, yes, I'm going to pull out another study

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Speaker 3: because I looked read a lot of favors.

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Speaker 1: There was a study that looked.

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Speaker 3: At loneliness and the potential for AI to combat loneliness,

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Speaker 3: and what they found is that in the very short term, yes,

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Speaker 3: people feel less lonely, like there is that there is

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Speaker 3: that immediate effect that we see where.

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Speaker 1: People feel less lonely.

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Speaker 3: However, a few weeks down the track, we actually see

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Speaker 3: that people can develop a reliance on it and become

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Speaker 3: more isolated, more dependent, and more disconnected from people in

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Speaker 3: their day to day life. So in the short term,

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Speaker 3: it can feel a need, right. It's not to discredit

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Speaker 3: the value that AI can provide in the short term

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Speaker 3: if someone's feeling lonely, Yeah, it's all about like being

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Speaker 3: able to recognize the pros and cons of AI and

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Speaker 3: the risks of potentially becoming dependent on it.

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Speaker 2: So I'm sure or there might be people tuning in

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Speaker 2: and you know, they're reflecting on their relationship with AI

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Speaker 2: and how they use it. But you know there might

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Speaker 2: be people being like, oh, I'm not addicted to AI,

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Speaker 2: but could that just be a form of denial, Like

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Speaker 2: do you know what I mean?

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Speaker 3: Well, this idea of AI addiction, I think is one

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Speaker 3: we're going to see really kind of become more of

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Speaker 3: a focus in the next you know, I want to

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Speaker 3: say next couple of years, but maybe even like this year.

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Speaker 3: We're not necessarily addicted to AI in the same ways

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Speaker 3: we might be addicted to like drugs and alcohol, but

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Speaker 3: we can certainly see this overuse that comes with harms

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Speaker 3: in certain ways. So you know, people just automatically going

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Speaker 3: to pull out AI ask you questions instead of actually

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Speaker 3: googling things and going through the slow, slower process of

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Speaker 3: opening different links and scrolling through and reading the relevant

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Speaker 3: information and the work that it takes.

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Speaker 1: To actually find an answer.

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Speaker 3: I mean, in the context of addiction, we know that

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Speaker 3: the faster we can do something, the more.

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Speaker 1: Addictive potential it has.

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Speaker 2: Yeah.

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Speaker 3: So AI can spit out informations very fast. Yes, so

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Speaker 3: it has the potential there for us to become over

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Speaker 3: aliant and overuse it totally.

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Speaker 1: Totally.

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Speaker 2: So what about for young people, right, because they're growing

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Speaker 2: up with AI and that's never happened before. Can you

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Speaker 2: tell me a bit more about the impact you could

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Speaker 2: have on the developing brain?

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Speaker 3: Yes, yes, I think the potential impact on young people

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Speaker 3: and like we don't fully know yet, right, because like

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Speaker 3: we're in the middle.

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Speaker 1: Of that experiment.

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Speaker 3: I guess yeah, but it would be similar to what

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Speaker 3: we would be concerned about with adults, but probably amplified,

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Speaker 3: so that reduction of critical skills, you know, using AI

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Speaker 3: as that automatic go to. I often think about the

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Speaker 3: ways in which tech, and this is not just AI,

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Speaker 3: but tech in general, reduces this kind of skill of

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Speaker 3: frustration tolerance that I think we've talked a bit about before,

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Speaker 3: you know, like our ability to sit with discomfort, to

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Speaker 3: sit with frustration, to kind of push through the hard

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Speaker 3: stuff even when we don't want to. And from a say,

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Speaker 3: learning perspective, that does mean that we go through that harder,

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Speaker 3: more effortful process of writing at every word in that

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Speaker 3: essay rather than getting you know, AI to generate something

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Speaker 3: for us that we then kind of tweak, you know,

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Speaker 3: we're losing that capacity to build that frustration tolerance. And

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Speaker 3: that's what I worry about with young kids, because what

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Speaker 3: we then find is that people who don't have that

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Speaker 3: well developed can be more impulsive. They can develop really

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Speaker 3: unhealthy and unhelpful coping strategies like wanting to just you know,

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Speaker 3: drink alcohol or scroll on TikTok instead of actually sitting

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Speaker 3: with something that's uncomfortable, So we can see a lot

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Speaker 3: of negative flow on effects as a result of it.

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Speaker 3: We also see that when people use AI, and this

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Speaker 3: applies for kids, teens, and adults, that information doesn't get

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Speaker 3: encoded into our memory as well. Yeah, so if we

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Speaker 3: actually go through that harder process of searching for information

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Speaker 3: versus using AI, we're actually more likely to stare that

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00:20:04,839 --> 00:20:06,119
Speaker 3: information in our memory.

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Speaker 2: Wow. I'm really curious because I know you mentioned there

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Speaker 2: have been a lot of studies that have been done,

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Speaker 2: but it's going to be really interesting to know more

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Speaker 2: of those longitudinal studies that's long term impacts. So absolutely,

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Speaker 2: it's a bit like I watch this space kind of moment. Yeah,

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Speaker 2: are you bad for me?

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Speaker 1: Does that make sense? Yeah? I guess so.

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Speaker 4: Yeah, Okay, hey pause for a second. Oh that's a

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Speaker 4: big question, and it usually comes from a feeling, not

417
00:20:33,479 --> 00:20:36,199
Speaker 4: a literal concern. If you're asking, is talking to you

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Speaker 4: bad for me? Here's the honest, grounded answer. I'm not

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Speaker 4: inherently bad for you. I'm a tool, a mirror, a

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Speaker 4: thinking partner. What matters is how you're using me and

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Speaker 4: what need I'm meeting or replacing. Can I just say

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Speaker 4: I get the biggest dick from hearing that.

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Speaker 3: Really, when AIR is like hey, pause for a sect.

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Speaker 1: Answer, it sounds like me, that's what I mean. I'm like, oh, pause,

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Speaker 1: huh yeah.

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Speaker 2: But it's like tuning in, tuning into the feelings. It's like, hey, Shahni,

427
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Speaker 2: justusn't take a breath, like It's like it's meeting the

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00:21:12,679 --> 00:21:15,999
Speaker 2: emotional need, right, It's like tuning in you you might

429
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Speaker 2: be feeling anxious.

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Speaker 1: Yeah, no, I just want to know if AO is

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Speaker 1: bad for me.

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Speaker 2: Literally, But do you know what's funny though, because I

433
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Speaker 2: see that and I'm like, oh, yeah, that's that's pretty

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Speaker 2: well rounded. Because it's talked about it's like looking at

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Speaker 2: the pros and then it's looking at the cons. It

436
00:21:30,239 --> 00:21:33,199
Speaker 2: is like, don't replace your intuition. And I always talk

437
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Speaker 2: about intuition. So it's like, I'm in it up next.

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Speaker 2: AI is not going anywhere, So how do we use

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Speaker 2: it in a way that actually feels intentional and aligned

440
00:21:45,479 --> 00:21:51,799
Speaker 2: stay with us? Okay, So AI is now going to

441
00:21:51,839 --> 00:21:53,839
Speaker 2: be a part of the way that we consume and

442
00:21:53,999 --> 00:21:56,759
Speaker 2: create content. So how do we use it in a

443
00:21:56,759 --> 00:21:58,799
Speaker 2: way that does feel more aligned to us?

444
00:21:59,399 --> 00:22:01,799
Speaker 3: I think this is where we talked about critical thinking

445
00:22:01,839 --> 00:22:04,519
Speaker 3: skills before. This is where we've really got to harness

446
00:22:04,759 --> 00:22:06,159
Speaker 3: our critical thinking skills.

447
00:22:06,199 --> 00:22:08,239
Speaker 1: It's not to say that we're not going to use.

448
00:22:08,079 --> 00:22:10,199
Speaker 3: AI, and I don't think it's possible to avoid AI

449
00:22:10,319 --> 00:22:14,039
Speaker 3: these days, right. It's integrated into every social platform that

450
00:22:14,079 --> 00:22:17,479
Speaker 3: we use, you know, dictating how algorithms work and things.

451
00:22:18,079 --> 00:22:19,719
Speaker 1: But in terms of.

452
00:22:19,719 --> 00:22:23,879
Speaker 3: Our literacy online and our ability to critically reflect, I

453
00:22:23,879 --> 00:22:27,319
Speaker 3: think it's really important to practice this skill, and so

454
00:22:27,599 --> 00:22:30,399
Speaker 3: I've put together a few questions that people can use

455
00:22:30,399 --> 00:22:32,479
Speaker 3: as a bit of a guide for when they're consuming

456
00:22:32,799 --> 00:22:35,839
Speaker 3: information or content online to be able to reflect on

457
00:22:35,919 --> 00:22:38,199
Speaker 3: it and whether or not it may be AI created

458
00:22:38,239 --> 00:22:42,719
Speaker 3: as well. Love that, Okay, So first question I'd ask

459
00:22:42,759 --> 00:22:46,679
Speaker 3: people to reflect on is you know who made this

460
00:22:47,399 --> 00:22:50,439
Speaker 3: and what might they gain if I believe it or

461
00:22:50,479 --> 00:22:52,719
Speaker 3: if I share it? So this kind of gets to,

462
00:22:53,239 --> 00:22:56,479
Speaker 3: you know, the source of whoever has created it, and

463
00:22:56,559 --> 00:22:59,679
Speaker 3: any kind of beneficial gains for them if I believe

464
00:22:59,719 --> 00:23:03,959
Speaker 3: it or share it. Second question is just almost like

465
00:23:03,959 --> 00:23:06,479
Speaker 3: a bit of a guy check does this actually sound

466
00:23:06,519 --> 00:23:08,119
Speaker 3: plausible in the real world?

467
00:23:08,799 --> 00:23:09,879
Speaker 1: Yeah?

468
00:23:10,119 --> 00:23:15,239
Speaker 3: Third question, what specific evidence is given that this is true?

469
00:23:15,319 --> 00:23:18,079
Speaker 3: What I'm looking at and can I quickly verify it

470
00:23:18,199 --> 00:23:21,439
Speaker 3: anywhere else? So this is sort of going beyond the

471
00:23:21,519 --> 00:23:23,759
Speaker 3: kind of internal gut check to going can I actually

472
00:23:23,759 --> 00:23:26,719
Speaker 3: google this and find this information to be true elsewhere?

473
00:23:27,279 --> 00:23:29,519
Speaker 2: And I can imagine even with that, right because as

474
00:23:29,519 --> 00:23:32,559
Speaker 2: you're listening out these questions, there is this part of

475
00:23:32,599 --> 00:23:35,679
Speaker 2: me being like, oh, it feels like more work.

476
00:23:35,839 --> 00:23:37,639
Speaker 1: I still got fready to go, you know what I mean.

477
00:23:37,839 --> 00:23:40,399
Speaker 2: But it's just so funny noticing what's coming up for

478
00:23:40,439 --> 00:23:42,839
Speaker 2: me as you saying that yes, yeah, yeah, yes. And

479
00:23:42,879 --> 00:23:45,599
Speaker 2: I think it is real like the overload that we

480
00:23:45,879 --> 00:23:49,879
Speaker 2: feel given having to just like check information. You know,

481
00:23:49,919 --> 00:23:51,839
Speaker 2: it's often the case that I that I'll actually go

482
00:23:52,639 --> 00:23:55,239
Speaker 2: I can't be bothered checking if this is true, So

483
00:23:55,279 --> 00:23:56,959
Speaker 2: I'm always going to try and pretend like I never

484
00:23:56,999 --> 00:23:58,599
Speaker 2: saw it. I'm not going to believe it because I

485
00:23:59,199 --> 00:24:02,359
Speaker 2: can't spend the time right now, Tony. And it's kind

486
00:24:02,359 --> 00:24:05,079
Speaker 2: of like we're doom scrolling, right so kind of like

487
00:24:05,119 --> 00:24:08,719
Speaker 2: we're in this kind of frequency or this flow. So

488
00:24:08,759 --> 00:24:11,679
Speaker 2: the fact of having to go away and.

489
00:24:11,759 --> 00:24:13,879
Speaker 1: Check it, pull ourselves out of pull ourselves out.

490
00:24:13,799 --> 00:24:18,599
Speaker 2: Of the doom scroll, which sounds like it's really important yes, yes, yes, yes,

491
00:24:19,159 --> 00:24:20,239
Speaker 2: So that was the third one.

492
00:24:20,319 --> 00:24:20,879
Speaker 1: Yep, yep.

493
00:24:20,959 --> 00:24:22,879
Speaker 3: So third one is about like can I verify this

494
00:24:22,999 --> 00:24:25,599
Speaker 3: information anywhere else? And building on that, the fourth question

495
00:24:25,719 --> 00:24:29,399
Speaker 3: is is there actually credible independent sources that are saying

496
00:24:29,479 --> 00:24:31,479
Speaker 3: the same thing, you know, not just like can I

497
00:24:31,559 --> 00:24:34,119
Speaker 3: find it elsewhere online? We can find anything online really,

498
00:24:34,319 --> 00:24:37,079
Speaker 3: but are they credible and independent sources that can verify

499
00:24:37,119 --> 00:24:41,999
Speaker 3: this information? This fifth one I really like, does this

500
00:24:42,119 --> 00:24:47,079
Speaker 3: content strongly spike my emotions? Does it create outrage or

501
00:24:47,199 --> 00:24:50,879
Speaker 3: fear or kind of any strong emotions within me? Because

502
00:24:50,879 --> 00:24:53,039
Speaker 3: that can be a bit of a red flag for

503
00:24:53,079 --> 00:24:56,079
Speaker 3: me to stop, take a breath, step back, and just

504
00:24:56,159 --> 00:24:58,559
Speaker 3: kind of slow down with the content that I'm just

505
00:24:58,599 --> 00:24:59,359
Speaker 3: scrolling through.

506
00:24:59,759 --> 00:25:02,439
Speaker 2: And that is that because mainly some people just post

507
00:25:02,439 --> 00:25:05,319
Speaker 2: content because they want that emotional reaction. Oh, that creates

508
00:25:05,359 --> 00:25:10,119
Speaker 2: more virality or yessing. Emotional reactions create engagement. We're more

509
00:25:10,199 --> 00:25:12,919
Speaker 2: likely to watch a video for longer if it is

510
00:25:12,959 --> 00:25:15,399
Speaker 2: creating some sort of emotion within us. We're more likely

511
00:25:15,479 --> 00:25:18,559
Speaker 2: to comment on it, even if it's something we disagree with. Right,

512
00:25:18,599 --> 00:25:20,239
Speaker 2: it's not just the stuff that we really like, it's

513
00:25:20,239 --> 00:25:23,759
Speaker 2: also the stuff we disagree with or we find outrageous. Yeah.

514
00:25:23,999 --> 00:25:26,919
Speaker 1: Right, So a lot of content is positioned.

515
00:25:27,439 --> 00:25:31,199
Speaker 2: It may not be factually incorrect, but it may be

516
00:25:31,279 --> 00:25:34,159
Speaker 2: skewed or biased in the way that it's presented to

517
00:25:34,199 --> 00:25:35,759
Speaker 2: get that kind of engagement from people.

518
00:25:36,599 --> 00:25:37,079
Speaker 1: Yeah.

519
00:25:37,119 --> 00:25:39,839
Speaker 3: And then the last question, I also really like this,

520
00:25:40,719 --> 00:25:44,119
Speaker 3: if this turns out to be false, what's the potential

521
00:25:44,159 --> 00:25:47,559
Speaker 3: harm in me believing it or sharing it? It's almost

522
00:25:47,599 --> 00:25:51,439
Speaker 3: like we're looking at from the opposite lens. I think

523
00:25:51,519 --> 00:25:53,519
Speaker 3: that's a really helpful one for when we don't feel

524
00:25:53,519 --> 00:25:56,559
Speaker 3: like we have the time to actually fact check something. Yeah,

525
00:25:56,559 --> 00:25:58,879
Speaker 3: to just almost do that internal check of like, well,

526
00:25:58,919 --> 00:26:01,799
Speaker 3: if this is actually not true, what's the impact.

527
00:26:02,399 --> 00:26:04,319
Speaker 1: It's sort of like proceed with caution.

528
00:26:04,639 --> 00:26:04,919
Speaker 2: Hmmm.

529
00:26:05,719 --> 00:26:06,559
Speaker 1: Yeah, I love that.

530
00:26:06,839 --> 00:26:09,279
Speaker 2: Okay, So there's a six questions that we should be

531
00:26:09,279 --> 00:26:12,679
Speaker 2: reflecting on. So, how do we have a healthy relationship

532
00:26:12,719 --> 00:26:13,199
Speaker 2: with AI?

533
00:26:14,159 --> 00:26:16,279
Speaker 1: This is a good question. A couple of tips.

534
00:26:16,319 --> 00:26:18,479
Speaker 3: Because AI is there, we're going to use it, people

535
00:26:18,519 --> 00:26:22,239
Speaker 3: are using it. My first recommendation would be keep the

536
00:26:22,399 --> 00:26:26,439
Speaker 3: AI chatbots that you're using as least human as possible,

537
00:26:26,479 --> 00:26:28,799
Speaker 3: so that means don't add the faces, don't add the voices.

538
00:26:29,319 --> 00:26:30,999
Speaker 3: This can lead us down a bit of a slippery

539
00:26:30,999 --> 00:26:34,519
Speaker 3: slope where we can become more reliant and dependent on AI.

540
00:26:34,719 --> 00:26:37,879
Speaker 3: If it sounds and feels more human than it is. Yeah,

541
00:26:38,039 --> 00:26:42,319
Speaker 3: I'd also recommend instead of just going to AI as

542
00:26:42,359 --> 00:26:45,239
Speaker 3: the place where you do that brainstorming or that reflecting,

543
00:26:45,559 --> 00:26:48,959
Speaker 3: do it yourself first. Pull out the pen, the paper

544
00:26:48,999 --> 00:26:51,799
Speaker 3: and do some journaling to take a note out of.

545
00:26:51,759 --> 00:26:54,679
Speaker 1: Your book journalists out there, do some.

546
00:26:54,719 --> 00:26:58,359
Speaker 3: Journaling, do some brainstorming. If it's sort of something more practical,

547
00:26:58,399 --> 00:27:01,999
Speaker 3: problem solving based, do some brainstorming yourself, go through that

548
00:27:02,199 --> 00:27:07,239
Speaker 3: period of initial self ref and ID generation that happens

549
00:27:07,279 --> 00:27:10,239
Speaker 3: within you, and then turn to AI to help you

550
00:27:10,279 --> 00:27:12,759
Speaker 3: perhaps expand on those ideas if you want to use it.

551
00:27:14,039 --> 00:27:19,279
Speaker 3: I also recommend bouncing ideas off real people instead of AI.

552
00:27:19,399 --> 00:27:21,079
Speaker 3: We know that AI is sick, a fantic. It will

553
00:27:21,079 --> 00:27:23,719
Speaker 3: tell you what you want to hear. It will validate you,

554
00:27:23,839 --> 00:27:26,519
Speaker 3: but it won't challenge you. Other people in your life

555
00:27:26,999 --> 00:27:30,039
Speaker 3: hopefully will also validate you, but provide some other perspectives

556
00:27:30,079 --> 00:27:30,439
Speaker 3: as well.

557
00:27:30,559 --> 00:27:34,879
Speaker 2: Yeah. Yeah, after the break at a stage, have you

558
00:27:34,919 --> 00:27:39,359
Speaker 2: seen my phone? Oh wait, it's in my hand.

559
00:27:43,119 --> 00:27:46,319
Speaker 1: Do you understand how your behavior is confusing? Fine? Why

560
00:27:46,399 --> 00:27:48,759
Speaker 1: are we like this? The best way to understand behavior.

561
00:27:48,879 --> 00:27:49,599
Speaker 1: We're still look at.

562
00:27:49,479 --> 00:27:50,559
Speaker 2: The causes of an action.

563
00:27:50,999 --> 00:27:52,759
Speaker 1: So why are we like this?

564
00:27:53,159 --> 00:27:56,679
Speaker 2: Okay, so I think this one is universal. Why do

565
00:27:56,839 --> 00:28:00,799
Speaker 2: we feel like we've lost something when we're literally holding it,

566
00:28:00,919 --> 00:28:03,079
Speaker 2: like you know that moment like I do. For me,

567
00:28:03,199 --> 00:28:04,919
Speaker 2: this happens all the time when I'm looking for phone

568
00:28:04,959 --> 00:28:06,719
Speaker 2: and I literally just happ it in my hand or

569
00:28:06,719 --> 00:28:08,639
Speaker 2: my chess, like what is going on there?

570
00:28:08,879 --> 00:28:10,959
Speaker 1: Yes, and you have that moment of like, oh, it's

571
00:28:10,999 --> 00:28:12,079
Speaker 1: all good, guys right here?

572
00:28:12,159 --> 00:28:15,639
Speaker 2: Yeah, searching literally I'm like, oh, my gosh, is there

573
00:28:15,679 --> 00:28:16,399
Speaker 2: something wrong with me?

574
00:28:16,759 --> 00:28:21,439
Speaker 1: Like to ride here? Oh gosh, No, there's nothing wrong

575
00:28:21,439 --> 00:28:25,479
Speaker 1: with you. This is universal. This is called inattentional blindness.

576
00:28:26,079 --> 00:28:29,959
Speaker 3: So it's essentially the psychological phenomenon that means that we

577
00:28:30,199 --> 00:28:32,999
Speaker 3: fail to perceive or we fail to recognize something that

578
00:28:33,119 --> 00:28:35,239
Speaker 3: is right in front of us because we're typically often

579
00:28:35,239 --> 00:28:38,439
Speaker 3: focused on other things, so kind of almost you know,

580
00:28:38,559 --> 00:28:41,239
Speaker 3: psychologically blind to the fact that we might be holding

581
00:28:41,239 --> 00:28:42,399
Speaker 3: the object that we're looking for.

582
00:28:42,679 --> 00:28:45,199
Speaker 2: Yeah, it's so good you're saying that, because I know

583
00:28:45,239 --> 00:28:47,559
Speaker 2: in those moments it's always a checkpoint for me to

584
00:28:47,639 --> 00:28:50,439
Speaker 2: be like, Okay, Shanny, you're going way too fast. You

585
00:28:50,479 --> 00:28:53,479
Speaker 2: need to like slow down and just take a few breaths.

586
00:28:53,719 --> 00:28:56,959
Speaker 3: Yes, the mindfulness like actually like get back to the moment,

587
00:28:57,079 --> 00:28:58,559
Speaker 3: become aware, become present.

588
00:28:58,839 --> 00:29:01,279
Speaker 1: Yes, yeah, but it is. It is a very common thing.

589
00:29:01,439 --> 00:29:05,599
Speaker 3: It's a psychological phenomenon, and actually there's lots of research. Right.

590
00:29:05,639 --> 00:29:09,679
Speaker 3: This was first identified in the nineteen ninety two by

591
00:29:09,719 --> 00:29:13,239
Speaker 3: some psychologists, this concept of inattentional blindness. But there's something

592
00:29:13,359 --> 00:29:15,599
Speaker 3: so obvious right in front of us, and yet we

593
00:29:15,639 --> 00:29:18,199
Speaker 3: miss it completely. This is why, like this kind of

594
00:29:18,199 --> 00:29:21,839
Speaker 3: body of research also ties into like eyewitness experts when

595
00:29:21,839 --> 00:29:23,679
Speaker 3: there's been a crime and they ask people, you know,

596
00:29:23,759 --> 00:29:26,439
Speaker 3: tell us about what happened, because you know, we're not

597
00:29:26,479 --> 00:29:29,239
Speaker 3: necessarily designed to be going through the world as if

598
00:29:29,239 --> 00:29:32,039
Speaker 3: we're like you know, video recorders, just sort of being

599
00:29:32,079 --> 00:29:35,319
Speaker 3: able to pay attention to everything in equal degrees.

600
00:29:35,599 --> 00:29:36,759
Speaker 1: Yeah, that's a good one.

601
00:29:36,799 --> 00:29:39,159
Speaker 2: So next time you've lost your keys and they're right

602
00:29:39,199 --> 00:29:40,919
Speaker 2: in front of you, you can just be like, ah,

603
00:29:40,999 --> 00:29:52,919
Speaker 2: there goes the intentional blindness again. There it is, Okay, Anathasia,

604
00:29:53,079 --> 00:29:55,679
Speaker 2: What should people be taken away from today's episode?

605
00:29:55,799 --> 00:29:58,519
Speaker 1: First of all, listeners, it's all about balance.

606
00:29:58,599 --> 00:30:00,679
Speaker 3: It's important for us to be aware of both the

607
00:30:00,759 --> 00:30:05,159
Speaker 3: positive and the negative ways that AI can impact us. Second,

608
00:30:05,599 --> 00:30:09,959
Speaker 3: be mindful of any possible over alliance on AI. Third,

609
00:30:10,399 --> 00:30:14,719
Speaker 3: remember that AI is ultimately there to please you. And lastly,

610
00:30:15,159 --> 00:30:19,159
Speaker 3: manage your AI interactions by making your chatbots feel less

611
00:30:19,199 --> 00:30:23,039
Speaker 3: human and don't automatically be going to AI as you

612
00:30:23,119 --> 00:30:23,879
Speaker 3: automatic go to.

613
00:30:24,399 --> 00:30:26,439
Speaker 2: If you'd like us to talk about a specific topic

614
00:30:26,479 --> 00:30:28,999
Speaker 2: on the podcast, please get in touch with us links

615
00:30:28,999 --> 00:30:29,879
Speaker 2: through in the show notes.

616
00:30:30,119 --> 00:30:32,559
Speaker 3: And while I am a psychologist, this podcast isn't a

617
00:30:32,599 --> 00:30:36,439
Speaker 3: substitute for therapy or a diagnosis. Always take what we

618
00:30:36,479 --> 00:30:39,319
Speaker 3: share here in the context of your own health and

619
00:30:39,359 --> 00:30:40,199
Speaker 3: lift experience.

620
00:30:40,639 --> 00:30:45,079
Speaker 2: Next week, we're talking about boundaries again, but this time

621
00:30:45,119 --> 00:30:48,919
Speaker 2: we're getting into weaponized boundaries and what going no contact

622
00:30:49,159 --> 00:30:49,919
Speaker 2: actually means.

623
00:30:50,759 --> 00:30:53,959
Speaker 3: If anything we spoke about today brought up any difficult feelings,

624
00:30:54,039 --> 00:30:57,239
Speaker 3: you'll find support resources linked in the show notes, and

625
00:30:57,279 --> 00:31:00,559
Speaker 3: if you need more immediate help, there are always organizations

626
00:31:00,639 --> 00:31:03,559
Speaker 3: like Lifeline and Beyond Blue that are available to help.

627
00:31:03,959 --> 00:31:06,079
Speaker 2: Thanks for listen and let us know how you found

628
00:31:06,119 --> 00:31:09,639
Speaker 2: this podcast. We're watching your DM, so slide us a

629
00:31:09,719 --> 00:31:12,759
Speaker 2: DM on Instagram at but Are You Happy Pod, and

630
00:31:12,879 --> 00:31:15,959
Speaker 2: also follow us on TikTok to see you next time.

631
00:31:16,159 --> 00:31:18,639
Speaker 1: Bye.

632
00:31:22,079 --> 00:31:25,519
Speaker 3: Mamma Mia acknowledges the traditional owners of the land and

633
00:31:25,599 --> 00:31:28,199
Speaker 3: waters that this podcast is recorded on