AI in the Fight Against Climate Change
Introduction
Climate change has emerged as one of the most pressing and encompassing problems of our generation. Global temperatures continue to rise, bringing with them increasingly devastating effects.
The need for unified international action to lower emissions across all sectors to limit warming to 1.5ºC is well documented. However, many changes and innovative solutions are necessary to achieve this goal. Machine learning has gained significant popularity in the past decade and disrupted industries like automation and healthcare, but what solutions can it offer us in the fight against climate change?
AI to Mitigate
The fight against climate change can be divided into two distinct strategies: mitigate global temperature rise and adapt to the negative effects of a hotter climate. Concerning prevention, AI is being used in several ways. There are businesses tracking companies’ carbon output throughout their supply chain to allow for reduction and optimization. Researchers use Natural Language Processing (NLP) to create knowledge graphs summarizing climate literature to aid researchers and policy decisions. AI is also used to optimize processes with emission reduction in mind. Examples include energy grids, transportation systems, smart buildings, and more. However, it is essential to note that AI is only one facet of the strategy and often not even the most crucial part. For instance, when it comes to emission reduction, insulation is a lot more important than having smart buildings!
AI to Adapt
Adapting to the effects of climate change has broader and more impactful applications for AI. Climate prediction models have leveraged AI to predict the occurrence and intensity of extreme weather events (for example, check out this paper that predicts the location and time of lightning strikes using AI). Machine learning has also given us tools to predict localized long-term effects of climate change, including droughts and temperature forecasts. These tools provide information to make informed decisions about resource allocation and changes required to protect vulnerable populations.
Negative Effects of AI
It would be biased to ignore the fact that the carbon footprint of AI is contributing to climate change. Training and deploying models is an energy-intensive process, and considerable research has gone into tracking the energy costs of large-scale models. Entrenching AI into society also risks exacerbating the biases found in training sets, which have been reported in several instances as affecting minorities. It is worth considering and analyzing whether one’s use of AI is furthering the fight against climate change and not negatively affecting it.
Looking Forward
AI is not the silver bullet in the fight against climate change. All research shows that AI is one of the many innovations the world will require to mitigate and adapt to the effects of a hotter world. One issue limiting the impact of AI is that current AI solutions are disconnected and independently challenging to scale. In future years, look for emerging companies that leverage AI to offer complete climate-based risk assessment. Companies like Cloud to Street, One Concern, and Blue Sky Analytics have emerged as leaders in this space. We have an opportunity to build a stronger and more resilient future and learning about and supporting ethical AI use is a great way to assist in this effort.
This article was written as a collaboration by QMIND & The Queen’s Business Review (QBR).
