We can’t manage what we don’t measure, goes the old business adage. This rings true more than ever today as the world faces a triple planetary crisis of climate change, nature and biodiversity loss, pollution, and waste.
More climate data is available than ever before, but how that data is accessed, interpreted and acted on is crucial to managing these crises. One technology that is central to this is Artificial Intelligence (AI).
So, what exactly does AI mean?
“AI refers to systems or machines that perform tasks that typically require human intelligence, and can iteratively improve themselves over time, based on the information they collect,” says David Jensen, coordinator of the United Nations Environment Program’s (UNEP’s) Digital Transformation sub-programme.
Jensen highlights several areas where AI can play a role in tackling environmental challenges, from designing more energy-efficient buildings to monitoring deforestation to optimizing renewable energy deployment.
“This can be on a large scale – such as satellite monitoring of global emissions, or a more granular scale – such as a smart house automatically turning off lights or heat after a certain time,” he adds.
UNEP’s World Environment Situation Room (WESR), launched in 2022, is one digital platform that is leveraging AI’s capabilities to analyze complex, multifaceted datasets.
History
It’s a historic moment for Artificial Intelligence (AI). All the pieces are coming together: big data, advances in hardware, emerging powerful AI algorithms, and an open source community for tools that reduces barriers to entry for industry and start-ups alike. The result: AI is being propelled out of research labs and into our everyday lives, from navigating cities, ride shares, our energy networks, to the online world.
In 2018 everyone is started to see the business value of AI. It is getting smarter and smarter – accelerating human innovation. But as AI becomes more powerful, more autonomous and broader in its use and impact, the unsolved issue of AI safety is paramount. Risks include: bias, poor decision making, low transparency, job losses and malevolent use of AI, such as autonomous weaponry.
The challenge, however, goes beyond guiding “human friendly AI” to ensuring “Earth friendly AI”. As the scale and urgency of the economic and human health impacts from our deteriorating natural environment grows, we have an opportunity to look at how AI can help transform traditional sectors and systems to address climate change, deliver food and water security, build sustainable cities, and protect biodiversity and human wellbeing.
Informing real-time analysis
Supported by a consortium of partners, WESR curates, aggregates and visualizes the best available earth observation and sensor data to inform near real-time analysis and future predictions on multiple factors, including CO2 atmospheric concentration, changes in glacier mass and sea level rise.
“WESR is being developed to become a user-friendly, demand-driven platform that leverages data into government offices, classrooms, Mayor’s offices, and boardrooms,” says Jensen. “We need credible, trustworthy and independent data to inform decisions and drive transparency – WESR provides this,” he adds.
“Over time, the goal is for WESR to become like a mission control centre for planet earth, where all of our vital environmental indicators can be seamlessly monitored to drive actions.”
Monitoring methane emissions
One of the UNEP-led initiatives inside the WESR digital ecosystem is the International Methane Emissions Observatory (IMEO), which leverages AI to revolutionize the approach to monitoring and mitigating methane emissions.
The platform operates as a global public database of empirically verified methane emissions. It leverages AI to strategically interconnect this data with action on science, transparency, and policy to inform data-driven decisions.
“IMEO’s technology allows us to collect and integrate diverse methane emissions data streams to establish a global public record of empirically verified methane emissions at an unprecedented level of accuracy and granularity,” Jensen says.
“Reducing the energy sector’s methane emissions is one of the quickest, most feasible, and cost-effective ways to limit the impacts of climate warming, and reliable data-driven action will play a big role in achieving these reductions,” he adds.
Other areas where AI can make a difference is calculating the environmental and climate footprints of product. “AI will be fundamental in this area,” Jensen says.
Measuring environmental footprints
“It can help calculate the footprint of products across their full lifecycles and supply chains and enable businesses and consumers to make the most informed and effective decisions. This kind of data is essential for sustainable digital nudging on e-commerce platforms such as Amazon.com. Shopify or Alibaba.”
Reducing ICT emissions
While data and AI are necessary for enhanced environmental monitoring, there is an environmental cost to processing this data that we must also take into account, says Jensen.
“The ICT sector generates about 3-4 per cent of emissions and data centres use large volumes of water for cooling. Efforts are underway to reduce this footprint –including through the CODES Action Plan for a Sustainable Planet in the Digital Age – one of the spin-off initiatives from the UN Secretary General’s Roadmap for Digital Cooperation.
But e-waste is a major concern as only 17.4 per cent currently recycled and disposed of in an environmentally sound manner. According to the UN Global E-waste Monitor report, E-waste will grow to almost 75 million metric tonnes by 2030.
UNEP research shows that to target this waste, consumers should reduce consumption, recycle electronic goods and repair those that can be fixed.
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