WEBVTT

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- Southeast Asia and the Global South

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are some of the regions that face

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the highest impacts of climate change,

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impacting communities,
impacting the economy.

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And these are multiple hazards
that impact these countries,

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from sea-level rise to
storms to extreme heat.

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Now these are extremely complex systems,

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and these systems, we
are getting into a phase

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where these impacts are
increasing in frequency,

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they're increasing in severity,

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and they're becoming more unpredictable.

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So this is where the
power of analytics, data,

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become very helpful to
help narrow that range

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of uncertainty that decision makers face.

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And AI plays a critical part in this.

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It's an extremely helpful
tool in a wide variety

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of toolkits that we need to
apply to help these countries,

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these communities build resilience.

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Let's take an example
of coastal communities.

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In Southeast Asia, there are
numerous coastal communities

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that the economies and people
just live near the coast,

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and they're all exposed
to extreme climate events.

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There's impact to vulnerable populations,

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to the economy, to lives, livelihoods.

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And governments in this part of the world

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have limited resources
to build resilience--

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whether that's in technical
capacity and funding--

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and they'll need to make some big choices.

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With AI and advanced analytics,

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and applying that with
the latest climate science

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and with local context,

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you can start to unpack
the cost of inaction.

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If you did nothing,
what will be the impact

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on vulnerable communities?

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With that better understanding

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through this analysis and these scenarios,

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decision makers in
government, for example,

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can then decide what are
the optimal responses.

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Now do you move certain communities?

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Do you build protection
around parts of the economy?

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Do you make choices between

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green nature-based
solutions for resilience

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or do you invest in hard infrastructure?

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There are multiple choices,

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and having a good understanding

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of what is the cost of inaction,

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what are the different scenarios

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when you mix these responses,
allows decision makers

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to deploy those limited
resources in the optimal way.

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Now there are multiple benefits to use AI

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as part of the toolkit
to build resilience.

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Now that said, there are
some practical constraints.

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So for example, in a survey of public

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and private sector leaders,

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78% of them said that they don't have

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the technical capacity to use these tools.

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67% said that they don't have confidence

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in being able to get the data
and hence have confidence

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on the analysis that
comes out from this data.

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So these are some examples
of the type of roadblocks.

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There's capacity constraints,

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there's access to data constraints,

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there's constraints associated

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with access to the available
solutions--and these are
developing and moving fast

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- -and having them deployed in the places

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where they're most needed.

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These are all constraints,

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but they're addressable constraints.