With the United Kingdom, in partnership with Italy, due to host the UN Climate Change Conference of the Parties 2021 (COP26) shortly, global leaders, NGO’s, and your average joe are turning to digital solutions to combat climate challenges. This article discusses how artificial intelligence (AI) and digitalisation can help fight climate change and environmental issues while highlighting some drawbacks of the technology used to do so.
AI is a technological tool that is ‘taught’ using training datasets to perform tasks no longer requiring human input. It is a branch of computer science enabling computers to problem-solve using algorithms within set boundaries. For example, voice recognising virtual assistants e.g. Siri; self-driving cars e.g. Tesla; and learning algorithms enabling computers to champion chess. Digitalisation is the process of changing an analog system, for instance, paper-based systems, into a digital format.
The relationship between AI, digitalisation and sustainability is complex. On the one hand, AI and digitalisation are vital in accomplishing carbon neutrality, creating smart energy systems and helping make informed decisions. On the other hand, digitalisation is not inherently sustainable. There are hidden costs to producing technology hardware which may undermine digitalisations’ positive role in sustainable developments relating to COP26 goals.
While AI software and digitalisation can be positively deployed to secure global net-zero by 2050 and other COP26 goals, there are, however, some drawbacks. One drawback is the “largely unaccounted for environmental impact of the tech industry” such as the energy costs of data processing (Kate Rich, 2021). For example, the mining and processing of lithium has environmental consequences. Both the beginning and the end of a smartphone’s life-cycle have ramifications in that the production has hidden labour costs and electronic waste has the potential to release harmful chemicals if mis-handled during disposal.
Social inequality challenges
Combatting environmental issues may be hindered by problems with social inequality such as digital poverty. The Covid-19 pandemic has illuminated the problem of digital poverty and digital exclusion in the UK. Research by the University of Cambridge shows that “only 51% of households earning between £6000-10,000 had home internet access compared with 99% of households with an income of over £40,001”.
Nevertheless, there is a silver lining to every (smog) cloud. There are many potential applications of AI that can help contribute to mitigating climate change, achieving COP26 goals and SDGs. AI technologies present promising innovations for tackling deforestation. AI can increase the accuracy and efficiency of forest monitoring and analysing canopy health, help make forest datasets more reliable and help add a wider context to the reports produced by local communities. In Brazil, AI and remote sensing have assisted the Global Forest Watch, “an online platform that takes millions of satellite images with the help of crowd-sourcing”, in successfully identifying illegal mining activities and deforestation sites.
The Royal Society’s ‘digital technology and the planet’ report suggests innovation in AI and the transition to digital-based processes will help develop solutions that cut global emissions. By collecting and examining large quantities of data, “digital technologies offer opportunities to learn from, organise and optimise processes in ways that significantly reduce emissions” across multiple sectors, including agriculture, energy, and transport.
Despite digital exclusion, remote working demonstrates how digital technology can support a low-carbon economy. Virtual technology has allowed many to work from home during the pandemic, linking people, separated by thousands of miles, to constructively debate and problem-solve environmental issues. “Th[e] corresponding reduction in travel contributed to a sharp drop in carbon emissions during lockdowns, with daily global fossil carbon emissions down 17% in early April 2020 compared with the previous year” (The Royal Society, 2020).
AI opportunities in humanitarian issues
Knowing the number of people in ‘internationally displaced persons’ (IDP) camps in Afghanistan is a very positive example of AI being used in a humanitarian crisis. Alcis, is an organisation using geospatial information, to aid humanitarian projects in complex environments. Alcis use satellite imagery, global information systems and machine learning to count the number of tents, which is a proxy for population, allowing the correct aid and resources to be allocated. Regarding environment and climate change, this initiative can be broadened out based on the predicted rise in climate refugees following natural disasters and changing climates. Food issues for IDP camps are based on crop productivity which is also directly impacted by climate change.