Using AI for environmental applications has the potential to boost global GDP by more than 4%, while also reducing global greenhouse gas emissions by the same margin (4.0%) by 2030.
As of March 2019, 195 UNFCCC members have signed the Paris Agreement, and 185 have become party to it. The agreement's long-term goal is to keep the increase in global average temperature to well below 2°C above pre-industrial levels, and to limit the increase to 1.5°C, since this would substantially reduce the risks and effects of climate change.
In order to achieve these goals, one of the methods named in the accord is the reduction of greenhouse gas (GHG) emissions by 20%, while making finance flows consistent with a pathway towards low greenhouse gas emissions and climate-resilient development. While it would still leave the world a substantial way off from that target, new research by PwC, commissioned by Microsoft and released today, has found that using artificial intelligence for environmental purposes in just four sectors could have significant economic and emissions impact around the world.
According to the study, harnessing AI in agriculture, water, energy and transport to support better management of the environment could yield productivity benefits, higher GDP, reduced carbon emissions and up to 38 million jobs globally by 2030. AI applications in energy and transport will have the largest impact on emissions reduction, with the automation of repetitive tasks possibly lowering energy emissions per unit of GDP 6%-8% by 2030, relative to business as usual. Meanwhile, AI could help health systems save an estimated $2.4 billion globally in reduced healthcare costs and health impacts.
Regionally, AI shows the greatest potential to reduce GHGs in North America (-6.1%) and Europe (-4.9%) and the largest economic gains (by GDP) in Europe (+5.4%) in 2030. While Latin America and Sub Saharan Africa stand to gain the least in the analysis, their gains could be higher if more digital transformation can be realised through infrastructure investment, enabling them to leap-frog developed countries through mitigation of greenhouse gas emissions.
However, the report warns that for all the potential that AI for environmental systems have, its application and uses could also exacerbate existing threats or create new risks. Broader AI risks linked to bias, security and control are all potential risks to the environment. In addition, there are substantial and wide-reaching barriers relating to these sectors that need to be overcome to realise the full potential of AI for environmental applications.
Celine Herweijer, Global Innovation & Sustainability Leader, PwC UK commented, “Put simply, AI can enable our future systems to be more productive for the economy and for nature… [However,] technology firms and industry alike will need to champion responsible technology practices, considering social, environmental impact and long term value creation. What is clear is that the companies and countries that fare best will be those that embrace the simultaneous changes and reinforcing opportunities of the AI era and the transition to sustainable economies.”