Plan B? Helping combat climate change with AI
Starting today until the 27th thousands of students and workers across Australia and 150 other countries will part in the global School Strike for Climate inspired by Swedish teenager Greta Thunberg.
The strike is about demanding an end to the age of fossil fuels and ensuring our political leaders take real and urgent action.
There is a ticking clock to all this as we know.
The science is undeniable.
But what is also starting to become clearer is the impact technologies like artificial intelligence (AI) can play in combating climate change through more efficient building design, maintenance and monitoring not to mention using data to achieve energy efficiency.
A recently published paper called “Tackling Climate Change with Machine Learning” has brought researchers together from a host of research bodies including Harvard University, University of Pennsylvania, University of Colorado, Boulder, Universite de Montreal , MIT, Stanford University, Deep Mind, Microsoft, Google and ETH Zurich.
The paper aims to provide an overview of where machine learning (ML – a branch of AI ) can be applied with high impact in the fight against climate change.
Our key takeaways reading the paper?
- Enhanced understanding of data: Many areas of transportation lack data, and decision-makers often plan transport infrastructure and policy based on uncertain information. ML can provide information about mobility patterns thereby improving operational efficiency of transport methods that emit significant CO2.
- Alternative to meetings: Leveraging newer more immersive technologies such as virtual reality (VR) we could potentially replace passenger trips with virtual meetings and help reduce transport per se.
- Designing for efficiency: ML can be applied to create more efficient vehicle engines, improved aerodynamics and reducing a vehicle’s weight or tire resistance. through failure detection or material design. [This same thinking can also be applied to built asset design ensuring the design of more sustainable buildings.].
- Optimising buildings: Applying technologies to reduce both the cost of build of and greenhouse gas emissions . [Snobal’s
XR reviewsprings to mind here which was created with the vision of reducing rework in the construction of complex built environments].
But our key takeaway is collaboration. And all of us taking responsibility to change our behaviour. As the paper highlights:
“…technology alone is not enough – technologies that would reduce climate change have been available for years, but have largely not been adopted at scale by society. While we hope that ML will be useful in reducing the costs associated with climate action, humanity also must decide to act…”
Read:. There is no plan B.
You can read the full research report here.
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