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AI in Climate Change · Artificial Intelligence Exposed

• 0:00
  Speaker 1: Welcome to the deep dive everybody. Today, we're well diving
• 0:03
  Speaker 1: deep right into AI and climate change. So how AI
• 0:08
  Speaker 1: is being used to you know, try to tackle this
• 0:10
  Speaker 1: global challenge. We've got some really interesting material for this
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  Speaker 1: one exploring how, you know, artificial intelligence can do things
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  Speaker 1: like predict those big environmental shifts that are happening to
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  Speaker 1: you know, optimizing how we use energy, and even help
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  Speaker 1: to create more sustainable materials. So by the end of
• 0:31
  Speaker 1: this deep dive, you are going to you know, hopefully
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  Speaker 1: have a really clear understanding of just how AI is
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  Speaker 1: being used and some of the benefits and challenges it
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  Speaker 1: brings to the table. I hear, yeah, you know. So
• 0:43
  Speaker 1: it's reading through the material and one of the things
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  Speaker 1: that really blew me away is like, did you know
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  Speaker 1: AI is now being used to figure out like the
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  Speaker 1: most stable places to store like carbon that we capture.
• 0:54
  Speaker 2: Oh yeah, like.
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  Speaker 1: We're talking potentially you know, locking that stuff away for centuries. Yeah.
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  Speaker 3: It's really quite pretty amazing, right, it really is. It
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  Speaker 3: is it It's like, weren't a whole new era of
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  Speaker 3: you know, of climate action where we can leverage AI
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  Speaker 3: to come up with solutions that you know, maybe we
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  Speaker 3: never even thought of before.
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  Speaker 1: Yeah, it's mind blowing. So let's let's start with AI's
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  Speaker 1: role in you know, climate modeling and prediction. You know,
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  Speaker 1: the traditional models, you know, they relied a lot on
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  Speaker 1: historical data and simulations. But AI, it's it's taking things
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  Speaker 1: to a whole.
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  Speaker 2: New level totally.
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  Speaker 3: Yeah. AI algorithms can analyze these huge, massive data sets
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  Speaker 3: from you know, satellites, sensors, and climate simulations, and that
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  Speaker 3: allows them to spot these these patterns and predict changes
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  Speaker 3: in the environment, you know, with unbelievable accuracy. I mean,
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  Speaker 3: imagine being able to like forecast you know, sea level rise,
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  Speaker 3: changes in temperature, and those extreme weather events like with
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  Speaker 3: that much precision. It's it's essential really for preparedness and
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  Speaker 3: could even you know, help save lives.
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  Speaker 1: It's almost like having like a crystal ball, right that
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  Speaker 1: can show us like what's coming down the road. But
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  Speaker 1: you know, I'm curious, isn't there a risk that if
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  Speaker 1: we rely too much on on AI for these predictions,
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  Speaker 1: that you know, we might become a little bit complacent,
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  Speaker 1: you know what I mean, like maybe less proactive in
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  Speaker 1: addressing the root causes of climate change.
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  Speaker 3: That's that's a really great point and it's crucial to
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  Speaker 3: remember that AI. It's it's a tool, yeah, right, the
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  Speaker 3: predictions that it's making, we should use them to inform
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  Speaker 3: our actions, right and motivate us to take those steps
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  Speaker 3: to mitigate climate change. It's not a reason to just
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  Speaker 3: sit back and wait for technology to solve it.
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  Speaker 1: Exactly exactly. So we've we've talked about predictions, but what
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  Speaker 1: about you know, energy consumption. I mean, energy is a huge,
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  Speaker 1: huge part of this whole, this whole climate change equation. Absolutely,
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  Speaker 1: and it seems like AI is really stepping in as
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  Speaker 1: this energy efficiency guru. Keep it.
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  Speaker 3: Yeah, I like that it is. And one of the
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  Speaker 3: most impactful areas is in these you know, energy grids,
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  Speaker 3: like optimizing energy grids. Okay, so think of it like
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  Speaker 3: you know, a smart grid. Think of it like a
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  Speaker 3: traffic control system, you know, but for energy, it's directing
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  Speaker 3: the flow of energy where it's needed most, and it's
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  Speaker 3: reducing waste. These AI algorithms they're analyzing you know, energy
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  Speaker 3: use patterns in real time. Wow, and they can adjust
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  Speaker 3: the distribution accordingly. And this is especially helpful for you know,
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  Speaker 3: for maximizing those renewable sources like solar and wind.
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  Speaker 1: Gotcha, so it's it's almost like AIS like the conductor
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  Speaker 1: like of an orchestra, making sure all of the instruments
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  Speaker 1: are playing, you know, in a harmony to create this
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  Speaker 1: like really efficient and sustainable energy system.
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  Speaker 2: I like that analogy a lot. Yeah.
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  Speaker 3: AI can even like anticipate those peak energy demand times
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  Speaker 3: and just automatically adjust that energy distribution and to avoid
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  Speaker 3: those those brownouts. And this lets us tap into those
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  Speaker 3: you know, cleaner sources more effectively, and ultimately it's it's
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  Speaker 3: reducing our reliance on on fossil fuels.
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  Speaker 1: This is this is fascinating. I really hadn't realized how
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  Speaker 1: much AI could like really fine tune the performance of
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  Speaker 1: renewable energy systems. Yeah, but you know, what are some
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  Speaker 1: of the limitations or challenges in this area, do you think?
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  Speaker 3: Well, one one challenge is security, really like ensuring that
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  Speaker 3: these AI powered grids are are secure and that they're resilient,
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  Speaker 3: because as they become more complex, you know, and more interconnected,
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  Speaker 3: they also become you know, more vulnerable to things like uh,
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  Speaker 3: cyber attacks or system failures. So we really have to
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  Speaker 3: invest in cybersecurity measures that are robust and and build
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  Speaker 3: you know, redundancy into these systems so we can prevent disruptions.
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  Speaker 1: That's that's a really important point. Okay, So we've we've
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  Speaker 1: talked about AI's role in making our energy grid smarter,
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  Speaker 1: but it sounds like it's not it's not stopping there, right,
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  Speaker 1: It's it's also like revolutionizing how we we generate this
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  Speaker 1: clean power in the first place.
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  Speaker 3: That's right, You're right, Yeah, AI is being used to optimize,
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  Speaker 3: you know, both the design and the performance of solar
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  Speaker 3: and wind energy systems.
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  Speaker 1: Oh wow.
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  Speaker 3: So for example, AI can can predict the ideal placement
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  Speaker 3: you know, for solar panels, yeah, based on on weather patterns, location.
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  Speaker 3: It can even it can adjust like wind turbine positions
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  Speaker 3: in real time to capture the most wind energy possible.
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  Speaker 1: So it's like it's like AI is giving these these
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  Speaker 1: renewable energy sources like a serious upgrade.
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  Speaker 2: Exactly what kind of.
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  Speaker 1: Impact is is that having on you know, the cost
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  Speaker 1: and the scalability of renewables.
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  Speaker 3: Well, these advancements you know, driven by AI are making
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  Speaker 3: renewable energy more cost effective okay, and more scalable, which means,
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  Speaker 3: you know, it's becoming becoming a much more attractive alternative
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  Speaker 3: to to fossil fuels.
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  Speaker 1: It sounds like AI is really helping to like pave
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  Speaker 1: the way it is, Yeah, for for a much cleaner
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  Speaker 1: energy future, I think.
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  Speaker 3: So.
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  Speaker 1: Okay, so we've we've covered prediction, energy efficiency, and renewable
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  Speaker 1: energy generation. What what other you know, climate related challenges
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  Speaker 1: is AI is AI tackling?
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  Speaker 3: Well, let's let's talk about agriculture, Okay, because it's it's
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  Speaker 3: a it's a major contributor to climate change, but it's
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  Speaker 3: also significantly impacted by it. Right, and AI is is
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  Speaker 3: making agriculture, you know, more sustainable in a few key ways.
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  Speaker 1: Okay, So AI is like stepping up to the plate,
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  Speaker 1: so to speak. It is it is how how exactly
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  Speaker 1: is AI being used to make agriculture more sustainable?
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  Speaker 3: Well, one example is is precision irrigation. Okay, so AI
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  Speaker 3: is analyzing the soil and weather data to guide farmers
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  Speaker 3: right on the optimal amount of water they should use, right,
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  Speaker 3: and that results in less waste and healthier crops.
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  Speaker 1: That makes a lot of sense. It's like having like
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  Speaker 1: a super smart, you know, farming assistant that's just constantly
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  Speaker 1: looking out for both the crops and the environment.
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  Speaker 3: Yeah, it's like having a consultant twenty four to seven.
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  Speaker 1: Yeah, exactly.
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  Speaker 3: AI is also being used to predict crop yields, which
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  Speaker 3: which helps farmers you know, plan more effectively, right and
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  Speaker 3: minimize their losses.
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  Speaker 1: Okay.
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  Speaker 3: And it can also help to minimize pesticide use by
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  Speaker 3: identifying those pests and diseases really early on, so that
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  Speaker 3: way you can have these really targeted interventions.
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  Speaker 1: It's it's incredible to see how AI can make such
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  Speaker 1: a like a tangible difference, you know, in an industry
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  Speaker 1: that's so so vital, like agriculture. But you know, with
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  Speaker 1: all this talk about AI's potential, I can't help. But like,
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  Speaker 1: you know, think, are there any concerns about the impact
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  Speaker 1: of of like widespread AI adoption in farming.
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  Speaker 3: Yeah, there are definitely some some valid concerns. For example,
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  Speaker 3: there are concerns about the potential displacement of farm workers.
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  Speaker 3: You know, if if these AI powered systems automate tasks
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  Speaker 3: that that humans traditionally do, so it's crucial that we consider,
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  Speaker 3: you know, the social and economic implications of of these
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  Speaker 3: technologies and make sure that the transition to these to
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  Speaker 3: these more automated farming practices, you know, it's just an
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  Speaker 3: equitable for everyone involved.
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  Speaker 1: That's an important important point to consider. Yeah, Yeah, we
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  Speaker 1: need to make sure that these technological advancements are benefiting everyone,
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  Speaker 1: not just you know, a select few exactly.
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  Speaker 3: Yeah, and there are also concerns about AI AI systems
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  Speaker 3: potentially you know, making existing inequalities worse. Right in the
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  Speaker 3: agricultural sector. You know, if if access to these these
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  Speaker 3: AI powered tools and resources is limited to you know, larger,
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  Speaker 3: wealthier farms, it could it could further disadvantage you know,
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  Speaker 3: smaller farmers and just just widen that gap between them.
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  Speaker 1: Yeah. So it's not just about you know, developing these
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  Speaker 1: these amazing technologies, it's about making sure there's there's equitable
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  Speaker 1: access to them. Okay, so we've we've covered a lot
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  Speaker 1: of ground already, but there's there's still so much more
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  Speaker 1: to explore, there is. Yeah, and in the next part
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  Speaker 1: of our deep dive, well, we'll explore how AI is
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  Speaker 1: transforming our cities, helping us create sustainable materials, and even
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  Speaker 1: tackling that big challenge of carbon capture.
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  Speaker 2: Yeah, that's going to be good. I'm excited to talk
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  Speaker 2: about that. B two and B two Welcome back to
• 9:42
  Speaker 2: the Deep Dive.
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  Speaker 3: So last time we were talking about you know, all these
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  Speaker 3: amazing ways that AI is being used to tackle climate change,
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  Speaker 3: you know, from predicting those environmental shifts to optimizing our
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  Speaker 3: energy use and even like revolutionizing agriculture.
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  Speaker 1: Yeah, it's been it's been really incredible learning about all
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  Speaker 1: the potential that AI has to address these you know,
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  Speaker 1: these huge challenges that we're facing. Yeah, you know, you
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  Speaker 1: mentioned before we took a break that there was there's
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  Speaker 1: even more to uncover. So what other like climate related
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  Speaker 1: challenges is is AI taking on.
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  Speaker 3: Well, let's shift gears a little bit, okay, and uh
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  Speaker 3: and talk about urban environments, because cities, you know, they're
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  Speaker 3: they're major contributors to greenhouse gas emissions, you know, from
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  Speaker 3: transportation and energy use and all that waste that they generate.
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  Speaker 2: But AI is now being.
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  Speaker 3: Used to you know, create more sustainable cities in some
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  Speaker 3: pretty amazing ways.
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  Speaker 1: You know, I've heard about, you know, this concept of
• 10:40
  Speaker 1: smart cities, but I'm curious to know how AI is
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  Speaker 1: actually playing a role in making them, you know, more sustainable.
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  Speaker 2: Well, you can kind.
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  Speaker 3: Of think of AI as like a smart city architect almost.
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  Speaker 3: It can analyze data from you know, traffic, camera sensors,
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  Speaker 3: all these different sources to optimize urban planning and help
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  Speaker 3: to create you know, these more efficient, more sustainable urban environments.
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  Speaker 1: So it's almost like like AI is helping to to choreograph,
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  Speaker 1: you know, the flow of a city, making sure that
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  Speaker 1: everything runs you know, smoothly and.
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  Speaker 3: Sustainably exactly exactly. So for example, by you know, reducing
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  Speaker 3: traffic congestion, right, we not only make you know, those
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  Speaker 3: commutes shorter and less stressful, but we also significantly decrease pollution.
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  Speaker 3: You know, AI can be used to to create these
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  Speaker 3: these smart buildings. Okay, you know that can that can
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  Speaker 3: adjust the heating, the lighting, even the cooling based on
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  Speaker 3: you know, real time occupancy and the weather.
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  Speaker 1: So the building like knows when I'm in the room
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  Speaker 1: and adjust the temperature accordingly. I mean that sounds incredibly futuristic.
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  Speaker 1: It is, but I can definitely see like the energy
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  Speaker 1: saving potential there. Yeah, but are there any you know,
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  Speaker 1: any concerns about about relying you know so heavily on
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  Speaker 1: AI to like manage these these complex systems.
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  Speaker 2: Well, you know, you bring up a really good point.
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  Speaker 3: One concern is is the potential for these systems to
• 12:12
  Speaker 3: be vulnerable to things like cyber attacks or malfunctions.
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  Speaker 2: Okay, I imagine.
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  Speaker 3: A city's entire traffic system or energy grid being disrupted
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  Speaker 3: because of some kind of technical glitch or malicious hacking.
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  Speaker 3: I mean that could have some really serious consequences. Yeah,
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  Speaker 3: so it's essential to have you know, really strong cybersecurity
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  Speaker 3: measures and backup systems in place just to mitigate those risks.
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  Speaker 1: Yeah, that makes that makes a lot of sense. Yeah,
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  Speaker 1: we need to make sure that these systems are are
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  Speaker 1: reliable and secure if we're going to entrust them with
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  Speaker 1: managing you know, our cities. M hmm. Okay. So AI
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  Speaker 1: is like, you know, transforming our cities into these these
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  Speaker 1: eco friendly havens. It sounds like what else? What else
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  Speaker 1: is on the horizon?
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  Speaker 3: All right, Well, let's talk about something equally fascinating. Sustainable materials.
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  Speaker 3: AI is actually being used to design new materials that
• 13:02
  Speaker 3: are both functional and environmentally friendly.
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  Speaker 1: Hold on, AI can design new materials. Yes, I have
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  Speaker 1: to admit I'm a little skeptical, like, how does does
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  Speaker 1: that even work?
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  Speaker 3: It's it's actually pretty remarkable. AI can analyze, you know,
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  Speaker 3: molecular structures and run simulations to help scientists discover materials
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  Speaker 3: that are stronger, lighter, and more importantly, more sustainable.
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  Speaker 1: Okay, So now that you now that you explain it,
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  Speaker 1: it's it's starting to make a little more sense to me.
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  Speaker 1: Can you give me like an example, sure?
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  Speaker 2: Sure. One.
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  Speaker 3: One really exciting area is biodegradable plastics. Okay, So AI
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  Speaker 3: is being used to develop plastics that break down much
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  Speaker 3: faster in the environment, which you know could have a
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  Speaker 3: massive impact on reducing plastic pollution.
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  Speaker 1: Yeah. So so no more plastic bottles like you know,
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  Speaker 1: hanging around for for hundreds of years.
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  Speaker 2: Well that's the that's the hope.
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  Speaker 1: Yeah.
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  Speaker 2: Yeah, what what a applications are there?
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  Speaker 1: Yeah? What about what about other applications?
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  Speaker 3: Well, AI is also helping to create you know, more
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  Speaker 3: efficient solar panels, batteries using materials that are not only
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  Speaker 3: you know, more effective, but also eco friendly.
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  Speaker 1: It sounds like AI is like really pushing the boundaries
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  Speaker 1: of sustainable manufacturing. It is, you know, helping us create
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  Speaker 1: a future where like the products that we use have
• 14:26
  Speaker 1: a minimal impact you know, on the environment. But are
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  Speaker 1: there are there any you know, challenges or potential drawbacks
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  Speaker 1: to using AI in material science?
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  Speaker 3: There are one one challenges is the cost okay, and
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  Speaker 3: the complexity of developing these new materials, right, you know,
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  Speaker 3: while AI can you know, help to speed up accelerate
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  Speaker 3: that discovery process, it's still you know, really expensive and
• 14:54
  Speaker 3: time consuming to bring them to market. And you know,
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  Speaker 3: there's also those concerns about the the potential uh, you know,
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  Speaker 3: environmental impact of producing these new materials. Right, we need
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  Speaker 3: to make sure that the processes that are used you
• 15:09
  Speaker 3: know to create them are also sustainable and don't just
• 15:13
  Speaker 3: you know, create create new environmental problems.
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  Speaker 1: Yeah, it's a good reminder that we need to consider,
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  Speaker 1: like the the entire life cycle of a product exactly,
• 15:21
  Speaker 1: from from the design and the manufacturing to the use
• 15:24
  Speaker 1: in disposal. Where we're really evaluating it's it's sustainability. Okay,
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  Speaker 1: so we've we've covered a lot of ground, but I
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  Speaker 1: know there's there's at least one one major piece of
• 15:34
  Speaker 1: this this climate change puzzle that that we haven't talked
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  Speaker 1: about yet, and that's that's carbon.
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  Speaker 3: Capture, you're right, And and it's an area where AIS
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  Speaker 3: is playing a really increasingly important role. Okay, you know,
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  Speaker 3: carbon capture and storage or CCS. It's all about you know,
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  Speaker 3: capturing that carbon dioxide from these various sources and storing
• 15:54
  Speaker 3: it safely so it doesn't enter the atmosphere.
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  Speaker 1: You know, I've I've heard about this technology, but it
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  Speaker 1: always seemed like very complex and kind of futuristic to me.
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  Speaker 1: It is, how how is AI, you know, being used
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  Speaker 1: to make it a reality?
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  Speaker 3: Well, AI is being used to enhance you know, the
• 16:15
  Speaker 3: development and the deployment of these carbon capture technologies. For example,
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  Speaker 3: AI can analyze geological data to pinpoint the most stable
• 16:23
  Speaker 3: formations for storing that captured carbon, potentially you know, locking
• 16:28
  Speaker 3: it away for centuries.
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  Speaker 2: Yeah.
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  Speaker 3: And you know those those machine learning algorithms, they can
• 16:33
  Speaker 3: analyze tons of data from from carbon capture sites, allowing
• 16:38
  Speaker 3: for you know, those real time adjustments and predictions of
• 16:43
  Speaker 3: the best strategies for storing that carbon safely and efficiently.
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  Speaker 1: So it's like AI is helping us to not only
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  Speaker 1: capture the carbon, but also find like the best and
• 16:52
  Speaker 1: the safest places exec store it.
• 16:54
  Speaker 2: Long term exactly.
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  Speaker 3: And and this is this is crucial because AI could
• 16:59
  Speaker 3: hold the key to you know, creating these scalable solutions
• 17:03
  Speaker 3: for reducing those industrial emissions, especially in in sectors that
• 17:08
  Speaker 3: are that are really difficult to to decarbonize, like like
• 17:11
  Speaker 3: cement and steel and chemicals.
• 17:13
  Speaker 1: Yeah, that's huge. We're talking about like tackling some of
• 17:16
  Speaker 1: the biggest emitters out there.
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  Speaker 2: They are.
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  Speaker 1: Yeah, but are there are there any concerns about you know,
• 17:20
  Speaker 1: the safety and the effectiveness of carbon capture technology, even
• 17:24
  Speaker 1: with even with AI's.
• 17:26
  Speaker 3: Help, there there are One concern is is the potential
• 17:31
  Speaker 3: for leaks from those storage sites.
• 17:34
  Speaker 1: Right, you know, if that if that captured carbon escapes
• 17:36
  Speaker 1: back into the atmosphere, it really defeats the purpose of
• 17:40
  Speaker 1: the whole process, right, And some critics even argue that,
• 17:43
  Speaker 1: you know, focusing on on carbon capture kind of distracts
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  Speaker 1: from the more urgent need to just reduce emissions in
• 17:50
  Speaker 1: the first place.
• 17:51
  Speaker 2: Yeah. Yeah, it's it's a it's a complex issue.
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  Speaker 3: There's there's no easy answers, right, and it's it's clear
• 17:58
  Speaker 3: that you know, more, more research and development is needed
• 18:02
  Speaker 3: to really make sure that this carbon capture technology is safe,
• 18:07
  Speaker 3: it's effective, and truly beneficial in.
• 18:10
  Speaker 1: The long run. Yeah, for sure.
• 18:12
  Speaker 3: You know, it's it's incredible to see how how AI
• 18:15
  Speaker 3: is being applied to such a wide range of climate
• 18:18
  Speaker 3: challenges there really is, you know, from from optimizing our
• 18:21
  Speaker 3: cities to to revolutionizing waste management and even capturing those
• 18:26
  Speaker 3: carbon emissions, Like it's it's really mind blowing, it.
• 18:30
  Speaker 1: Is, and and the possibilities they seem endless.
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  Speaker 3: But you know, as we continue to explore, you know,
• 18:36
  Speaker 3: the potential of AI in this in this space, it's
• 18:39
  Speaker 3: also crucial to remember, you know, the importance of responsible
• 18:44
  Speaker 3: implementation and and those ethical considerations.
• 18:47
  Speaker 1: Yeah, you're you're right. We need to make sure that
• 18:49
  Speaker 1: we're using AI in a way that that benefits all
• 18:52
  Speaker 1: of humanity and doesn't create these new problems or make
• 18:56
  Speaker 1: those existing inequalities, you know, even worse.
• 19:00
  Speaker 3: Exactly exactly, and in the final part of our deep dive,
• 19:03
  Speaker 3: we're going to delve into those those crucial ethical considerations
• 19:07
  Speaker 3: and explore, you know, the potential challenges and those societal
• 19:10
  Speaker 3: implications of using AI for climate change solutions.
• 19:15
  Speaker 1: Okay, welcome back to the deep dive. So in the
• 19:18
  Speaker 1: last couple of parts, we've been exploring, you know, how
• 19:21
  Speaker 1: AI is being used to really try to tackle all
• 19:24
  Speaker 1: these different aspects of climate change, you know, from predicting
• 19:27
  Speaker 1: environmental changes to you know, completely transforming our cities to
• 19:31
  Speaker 1: even capturing carbon emissions. But like we've kind of hinted at,
• 19:35
  Speaker 1: you know, this this powerful technology, it brings up some
• 19:38
  Speaker 1: really important questions it does, yeah, about you know, how
• 19:42
  Speaker 1: we implement it responsibly and what impact it's going to
• 19:45
  Speaker 1: have on society.
• 19:46
  Speaker 3: Yeah, I mean, as we continue to develop and deploy
• 19:49
  Speaker 3: these you know, AI powered solutions for climate change, it's
• 19:53
  Speaker 3: just it's crucial to consider, you know, what, what those
• 19:57
  Speaker 3: implications might be and and make sure that these type
• 20:00
  Speaker 3: tchnologies are are really benefiting everyone, not just you know,
• 20:04
  Speaker 3: a select few.
• 20:05
  Speaker 1: So in this this final part of our deep dive,
• 20:08
  Speaker 1: let's let's really dig into some of those potential challenges
• 20:11
  Speaker 1: and explore you know, those ethical considerations surrounding AI and
• 20:15
  Speaker 1: climate change.
• 20:15
  Speaker 2: Yeah, for sure.
• 20:17
  Speaker 1: One one concern that comes to mind, you know, immediately
• 20:19
  Speaker 1: for me is is access. You know, we've talked about
• 20:22
  Speaker 1: all this incredible potential of these technologies, but what happens
• 20:26
  Speaker 1: if if they're not accessible to everyone.
• 20:29
  Speaker 3: That's a that's a really crucial point. Yeah, I mean,
• 20:31
  Speaker 3: imagine imagine a scenario where where you have these advanced
• 20:36
  Speaker 3: you know, AI powered farming tools or or these sophisticated
• 20:40
  Speaker 3: carbon capture systems that are that are really only available
• 20:43
  Speaker 3: you know, to wealthy nations or corporations, while developing countries
• 20:49
  Speaker 3: or marginalized communities, they're they're left behind. I mean that
• 20:53
  Speaker 3: would just exacerbate you know, those existing inequalities and create
• 20:58
  Speaker 3: this this divide in our ability to actually address right,
• 21:02
  Speaker 3: you know, climate change effectively.
• 21:04
  Speaker 1: Yeah. It's like having this this powerful lifeboat, right, but
• 21:07
  Speaker 1: only allowing like certain people on board.
• 21:10
  Speaker 2: Yeah, that's a good way to put it.
• 21:12
  Speaker 1: We need to make sure that the benefits of these
• 21:16
  Speaker 1: these AI driven climate solutions, right, they're distributed fairly and
• 21:21
  Speaker 1: that everyone has has a chance, you know, to to
• 21:24
  Speaker 1: participate in this in this technological revolution.
• 21:27
  Speaker 3: Absolutely, and it's not you know, it's not just about access.
• 21:30
  Speaker 2: To you know, the technology itself.
• 21:32
  Speaker 3: Yeah, it's also about you know, access to the data,
• 21:36
  Speaker 3: the resources, the education that's needed to develop and really
• 21:41
  Speaker 3: utilize these tools effectively. I mean we need we need
• 21:45
  Speaker 3: like a global effort here to bridge that digital divide
• 21:48
  Speaker 3: and make sure everyone has a chance to benefit from
• 21:51
  Speaker 3: AI advancements in in climate action.
• 21:55
  Speaker 1: Yeah, that's that's a great point. You know, we can't
• 21:57
  Speaker 1: we can't just assume that these technologies or are just
• 22:01
  Speaker 1: automatically going to trickle down to everyone, right. We need
• 22:04
  Speaker 1: to be proactive and have you know, measures in place
• 22:08
  Speaker 1: to to promote inclusivity and make sure that no one
• 22:11
  Speaker 1: is left behind. Another concern that I have, you know,
• 22:14
  Speaker 1: is about data privacy. Yeah. You know, AI relies heavily
• 22:18
  Speaker 1: on data collection and analysis. So so how do we
• 22:22
  Speaker 1: how do we kind of balance the need you know,
• 22:25
  Speaker 1: for all this data with with the right to privacy,
• 22:28
  Speaker 1: especially when it comes to to sensitive you know, environmental information.
• 22:32
  Speaker 3: That's a that's a really valid concern. As we as
• 22:35
  Speaker 3: we deploy more and more of these AI powered systems,
• 22:39
  Speaker 3: you know, to monitor environmental changes and track emissions and
• 22:42
  Speaker 3: manage resources. We're collecting massive, massive amounts of data and
• 22:47
  Speaker 3: you know, some of it could be could be personally
• 22:50
  Speaker 3: identifiable or or sensitive in nature. I mean think about
• 22:55
  Speaker 3: you know, AI systems that are that are tracking like
• 22:59
  Speaker 3: individual and energy consumption patterns, Yeah, or maybe monitoring deforestation
• 23:04
  Speaker 3: in areas where where indigenous communities live.
• 23:08
  Speaker 1: Yeah. It sounds like we need to you know, really
• 23:11
  Speaker 1: establish like clear guidelines and regulations too, Yeah, for data collections, storage,
• 23:17
  Speaker 1: and use in in these in these AI powered climate solutions, right, Yeah.
• 23:22
  Speaker 3: We need to make sure that that the data is
• 23:24
  Speaker 3: being collected and used you know, transparently with people's consent
• 23:29
  Speaker 3: and only for that intended purpose, right, and and we
• 23:32
  Speaker 3: need you know, really really strong security measures in place
• 23:36
  Speaker 3: to to prevent data breaches and and protect that sensitive
• 23:40
  Speaker 3: information from from falling into the wrong hands.
• 23:42
  Speaker 1: Yeah, data privacy is definitely a crucial issue we need
• 23:46
  Speaker 1: to address. What about what about accountability? Yeah, you know
• 23:51
  Speaker 1: AI systems they're becoming increasingly complex, right, and they're they're
• 23:55
  Speaker 1: making these decisions based on these massive data sets and
• 23:59
  Speaker 1: these these intricate algorithms. How do we how do we
• 24:03
  Speaker 1: make sure that these systems are are making you know,
• 24:06
  Speaker 1: responsible decisions and that that there's accountability you know, for
• 24:11
  Speaker 1: for their actions. Yeah.
• 24:13
  Speaker 3: Accountability is just so important when it comes to AI
• 24:17
  Speaker 3: because these systems they're often opaque. You know, it makes
• 24:20
  Speaker 3: it difficult to really understand how they how they get
• 24:23
  Speaker 3: to those decisions, right, and you know, if if something
• 24:27
  Speaker 3: goes wrong, it can be really hard to pinpoint, you know,
• 24:31
  Speaker 3: who's responsible or or even to fix the situation.
• 24:35
  Speaker 1: Right. It's almost like we're giving these these AI systems, like,
• 24:39
  Speaker 1: you know, a certain level of autonomy without without fully
• 24:44
  Speaker 1: understanding like how they operate or who's ultimately responsible for
• 24:48
  Speaker 1: their actions.
• 24:49
  Speaker 2: Yeah, that's a that's a good point.
• 24:51
  Speaker 3: And it's and it's especially concerning when you know, we're
• 24:54
  Speaker 3: talking about systems that are that are controlling you know,
• 24:57
  Speaker 3: critical infrastructure like our energy grid or managing sensitive environmental data.
• 25:03
  Speaker 3: So we need to you know, develop those mechanisms for
• 25:08
  Speaker 3: for auditing AI systems. We need to to ensure transparency
• 25:12
  Speaker 3: in in how they're making those decisions and establish those
• 25:16
  Speaker 3: clear lines of accountability.
• 25:18
  Speaker 1: Yeah, it sounds like we need to tread carefully here. Yeah,
• 25:22
  Speaker 1: I think so, you know, and and approach you know,
• 25:25
  Speaker 1: this whole integration of AI into into climate solutions with
• 25:28
  Speaker 1: with a with a healthy dose of caution and foresight.
• 25:32
  Speaker 1: We need to make sure that we're not just creating
• 25:34
  Speaker 1: you know, solutions that that sound good, you know in theory,
• 25:37
  Speaker 1: but are actually you know, beneficial and ethical in practice.
• 25:40
  Speaker 3: Yeah. I completely agree, And and it's important to remember
• 25:43
  Speaker 3: that AI it's a tool. It's not you know, some
• 25:47
  Speaker 3: kind of magic solution that's going to solve all our
• 25:50
  Speaker 3: climate problems. You know, it's up to us right to
• 25:54
  Speaker 3: use this tool wisely and responsibly.
• 25:57
  Speaker 1: Well said, Well, we've we've covered a lot of ground
• 25:59
  Speaker 1: in this in this deep dive we have We've we've
• 26:02
  Speaker 1: seen the the incredible potential of AI too to address
• 26:08
  Speaker 1: climate change. But we've also you know, highlighted some of
• 26:11
  Speaker 1: those ethical challenges and potential you know downsides.
• 26:15
  Speaker 3: Yeah, it's been a it's been a fascinating exploration, and
• 26:17
  Speaker 3: it just underscores the importance of having these kinds of
• 26:21
  Speaker 3: conversations and approaching the development and the deployment of AI,
• 26:26
  Speaker 3: you know, in a thoughtful and deliberate way.
• 26:30
  Speaker 1: Absolutely, as we move forward, you know, it's it's crucial
• 26:33
  Speaker 1: that we we keep these these ethical considerations at the forefront.
• 26:37
  Speaker 3: You know, of our minds and work towards you know,
• 26:41
  Speaker 3: creating these AI powered climate solutions that are that are
• 26:44
  Speaker 3: not only effective, you know, but but just an equitable.
• 26:47
  Speaker 2: For for everyone, right for all.
• 26:50
  Speaker 3: So as we as we kind of wrap up this
• 26:52
  Speaker 3: this deep dive into AI and climate change, you know,
• 26:56
  Speaker 3: we hope you've gained a deeper understanding of both, you know,
• 27:01
  Speaker 3: the opportunities and the challenges that lie ahead.
• 27:04
  Speaker 1: Yeah, we really encourage you to keep learning, you know,
• 27:07
  Speaker 1: about this this field that's changing so rapidly, and to
• 27:11
  Speaker 1: to engaging conversations you know, about how we can best
• 27:15
  Speaker 1: you know, utilize this powerful technology right to to create
• 27:19
  Speaker 1: that more sustainable future for everyone.
• 27:21
  Speaker 2: Well, thanks for thanks for joining us on this deep dive.
• 27:24
  Speaker 1: Yeah, thanks for having me, and remember.
• 27:26
  Speaker 2: You know that the conversation doesn't end here.
• 27:28
  Speaker 1: Keep questioning, keep exploring, keep pushing for a better tomorrow.
• 27:33
  Speaker 3: Yeah, and we'll see you next time on the deep dive.