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  • So really we're on the brink, I think, of a transformation

  • in the way science is done.

  • Not only tackling the problem of climate change

  • and trying to find solutions,

  • but also actually trying to understand the system itself.

  • So some of the technological advances that we might be able to use

  • to combat climate change involve the ability

  • to generate energy in sustainable ways.

  • The question today is can we make solar panels or other materials

  • that are capable of generating energy in useful ways?

  • In the past, scientists and engineers have developed new materials,

  • but in rather a haphazard way.

  • Thomas Edison created the lightbulb

  • but he developed the original filament

  • by testing thousands of materials to find eventually the one that worked.

  • Today we can use machine learning and artificial intelligence

  • in our search for new materials.

  • The reason that we can do it better in the computer

  • is that the computer allows millions of potential solutions

  • to be searched in ways that you couldn't do in the lab.

  • The reason that AI is important in the development of our understanding

  • of the Earth's system is that we're getting more and more data

  • about the Earth as time goes on.

  • So today we collect satellite data,

  • remote sensing observations allow us now

  • to look at the patterns of landslides.

  • As climate is changing, as weather patterns change,

  • is the land being more destabilised by excess water?

  • Or are the erosion patterns in the mountains

  • changing as climate changes?

  • Extreme weather events as a result of climate change

  • do appear to be on the increase.

  • But there's another aspect of this - cities are getting bigger,

  • areas that have always been vulnerable to natural hazards.

  • With so many people potentially at risk,

  • it becomes important to understand the system very quickly.

  • Examples include understanding the ways in which

  • to respond to a situation.

  • Where to send the first responders.

  • Which hospital is put on high alert.

  • Where to send relief supplies, who needs tents.

  • So all of these sorts of disaster relief processes

  • depend upon information.

  • And we know, as we travel around congested cities,

  • that we spend a lot of time sitting in traffic,

  • burning energy, getting nowhere.

  • Autonomous vehicles provide routes

  • to making transport systems more effective, more efficient,

  • so that you don't have these waves of static traffic on a motorway.

  • That everything is moving at the right speed

  • and gets from one place to another in the most effective way,

  • the most efficient way.

  • That's not something that, as individuals,

  • we're very good at planning for ourselves.

  • So if we want to reduce, recycle, reuse, can AI help us?

  • Well maybe. But it depends upon our motivation.

  • AI is a tool, it's not a master, and so our responses ultimately

  • will depend upon our own personal motivations,

  • and those of the society that we're part of.

  • But AI and machine learning can help us move in the right direction.

So really we're on the brink, I think, of a transformation

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B1 ai climate climate change machine learning relief depend

Four ways AI can help tackle climate change | BBC Ideas

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    Summer posted on 2021/04/22
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