What’s it about?
In this whitepaper, we discuss the current state of AI in the global effort toward achieving environmental sustainability and present four aspects of environmental challenges.
The rise of machine learning has coincided with an increased consciousness of the environmental risks and problems of both the present and the near future. The pressures of environmental concerns and the search for their solutions have spurred the exploration of the role of technology in compounding and mitigating environmental risks.
This whitepaper aims to give an outline of both the potential as well as the risks that are associated with machine learning for sustainability and discusses various use cases related to the following four aspects of the environmental challenges we are faced with in the near future:
- Electricity
- Agriculture
- Forest Management
- Climate Modeling