The use of AI in the future is only projected to increase, or at least develop beyond what it is being used for right now.
With that being the case, in this guide, we’ve outlined the impact AI might have on sustainability and the environment in the future
Is it a positive or a negative in this regard?
We’ve also looked at how AI might be used, or how in might help across both areas.
Summary – AI, & Sustainability & The Environment
The impact that AI might have on sustainability and the environment depends on several factors such as what sustainability indicator is being measured (and how it’s being measured), what type of AI technology is being used, what the AI is programmed for and how it’s being used (along with what abilities the AI is using), plus more
Across some measures or indicators, AI might help with sustainability, but across others it may inhibit sustainability (this is analysed in depth in the Nature.com resource listed)
As just one example, measuring carbon footprint and energy use is only one aspect of sustainability
Some studies indicate that AI will mean companies might use more energy and therefore have larger carbon footprints – largely as a result of processing data, needing server centres, and needing energy to cool data centers
This makes AI potentially similar to Blockchain as a technology for use in sustainability – with energy use being being a significant concern
Others claim AI has the potential to be trained to figure out how data and energy use can be saved or reduced, and therefore only using a minimal amount of energy and emitted a minimal amount of CO2, or even reducing energy and emissions
Others claims that we don’t know how much energy AI will use in the future, and more comprehensive and wider studies are needed to see their environmental and sustainability impact
Some of the industries or areas where AI might already be addressing sustainability issues are agriculture, energy, transport, water resource management, manufacturing, facilities management, and materials science
Some of the main areas AI might have the ability to help with environmental sustainability in the future are in:
1. Making processes more efficient, or cutting steps from a process (and saving energy and resources in those processes)
2. Reducing errors currently made by humans (that use energy and resources)
And, 3. Better monitoring and managing material and resource usage
What is clear is that companies and organisations will have to focus on tracking and studying the impact of AI on sustainability into the future – a specific focus is needed to obtain this data and these results
The impact of AI on sustainability may vary depending on the variables listed at the top of this summary, and also depending on how AI develops and is used in the future compared to now
What also needs to be examined in greater detail is the potential risks of AI in the future. The nature.com and greenbiz.com resources both discuss these potential risks
AI can help across environmental, social and economic areas, but it is not a ‘magic bullet’ solution. Like any technology, the costs and benefits of each type of AI technology has to be weighed up, along with any improvements or optimizations that can be made to the technology
AI, Energy Use & Carbon Emissions
AI based systems can be:
– compute intensive
– and, they must process data, in addition to needing servers, and also needing energy to cool data centers
With these things being the case, any organisation using AI will very likely increase their energy use.
There’s mixed claims on how much extra CO2 emissions this could lead to
One study indicates that: ‘[training one uncommonly used AI model to do NLP can produce the CO2 equivalent 5x the lifetime emission of the American car]’ (forbes.com)
But, other more commonly used AI doing more representative training tasks may produce much less CO2 emissions.
There’s also AI technology that helps reduce data center energy requirements, as is the case with Google’s DeepMind division (forbes.com)
It’s unclear how AI will continue to develop and function in the future.
More sustainability studies will likely need to be conducted in the future to get an idea of their true representative impact based on the most common uses and functions they carry out.
AI Being Used For Sustainability In Agriculture
[AI can be used in agriculture for] better monitoring and managing environmental conditions and crop yields [and can] help reduce both fertilizer and water [use] while improving crop yields (forbes.com)
AI Being Used For Sustainability In Energy
AI can use deep predictive capabilities and intelligent grid systems to manage the demand and supply of renewable energy.
By more accurately predicting weather patterns, AI can optimize efficiency, cutting costs, and unnecessary carbon pollution generation
AI Being Used For Sustainability In Transport
AI can help reduce traffic congestion, improve the transport of cargo (supply chain logistics), and enable more and more autonomous driving capability.
AI will eventually help with the “last mile” delivery problem and reduce the need for delivery vehicles.
AI can help businesses with demand forecasting, helping to reduce the amount of transport needed
AI Being Used For Sustainability In Water Resource Management
AI can help reduce or eliminate waste while lowering costs and lessening environmental impact.
AI-driven localized weather forecasting will help reduce water usage
AI Being Used For Sustainability In Manufacturing
AI can help reduce waste and energy use in production facilities. Robotics can enable better precision.
AI can design more efficient systems
AI Being Used For Sustainability In Facilities Management
AI can help recycle heat within buildings and maximize the efficiency of heating and cooling.
AI can help optimize energy use in buildings by tracking the number of people in a room or predicting the availability of renewable energy sources
AI Being Used For Sustainability In Materials Science
AI can help researchers find new materials for solar panels, for turning heat back into useful electricity and to help find absorbent materials as components of CO2 scrubbers (taking CO2 out of the atmosphere.)
Other Industries Or Areas Where AI Might Help With Sustainability
AI can be used in conjunction with other technology (with just one example being the Internet Of Things) to address sustainability in (according to forbes.com):
– Species protection
– Maximizing renewable energy technologies (such as solar and wind)
According to pwc.co.uk:
– Some examples of AI application include AI-infused clean distributed energy grids, precision agriculture, sustainable supply chains, environmental monitoring and enforcement, and enhanced weather and disaster prediction and response
– [AI could impact the environment across] agriculture, water, energy and transport
– … using AI for environmental applications could contribute up to $5.2 trillion USD to the global economy in 2030, a 4.4% increase relative to business as usual
– At the same time as productivity improvements, AI could create 38.2 million net new jobs across the global economy offering more skilled occupations as part of this transition
– [The main benefit of AI is that it allows our systems to be more productive in an economic and environmental sense]
The raconteur.net, recode.net, and weforum.org resources go into further detail on the different ways AI might help with sustainability in the future.
How AI May Have An Impact On Environmental Sustainability In The Future
Apart from what is outlined above, the areas of impact may include (paraphrased from forbes.com):
– Reducing errors
That are currently being made by humans in certain processes, and saving energy and resources in the process
– Increasing efficiency of different processes
This can lead to the same or more being produced with the same amount of resources, or less resources (such as less energy). AI can also cut out certain human steps from an existing process
– Better management of raw materials
Related to the point above – AI can manage the use of raw materials, to either use them more efficiently, or use less of them, or use more sustainable alternative materials
Additionally, when 200 business decision makers in environmental sustainability were polled in 2018, 74% of them ‘agreed that AI would help solve environmental problems’ (forbes.com)
AI Can Both Help & Inhibit Sustainability Goals
One study found that AI might help but also inhibit sustainability across environmental, social and economic goals:
– AI can enable the accomplishment of 134 targets across all the goals, but it may also inhibit 59 targets (nature.com)
Refer to the nature.com link below in the sources list for more information on this study
They look at factors such as:
– What sustainability goals are being measured
– What AI software and capabilities are being used (perception, decision making, prediction, automatic knowledge extraction and pattern recognition from data, interactive communication, and logical reasoning
– How AI might be a benefit or how it might inhibit things across specific goals and targets (mainly environmental, social and economic)
Note that there might be some limitations to this study such as the analysis mainly representing to perspective of the authors, and mainly the SDGs being analysed (and not independent sustainable indicators or goals)
The deloitte.com resource outlines that AI is ‘not a silver bullet … and must be used responsibly’. There should be a focus on ‘green AI’.
Potential Risks Of AI Use In The Future
The nature.com study goes through some of the risks of using AI in the future (such as specific governments and companies using technology to further their own agenda, instead of the majority of people)
Greenbiz.com also provides some feedback on the potential risk of AI use in the future:
Companies already are making use of AI to achieve step changes in, for example, efficiency and emissions reductions, and to innovate new products and services.
These AI applications for sustainability are not widespread, and they are early stage, but the data suggests that AI can bring significant benefits for sustainability in the medium term.
What we don’t see, however, is much evidence that companies are understanding the numerous and serious risks that AI presents.
[Some risks may include automated bias, claimed benefits may turn out not to be as significant or as effective and the initial claims and could ne a net negative, and the erosion of some jobs]
2. Vinuesa, R., Azizpour, H., Leite, I. et al. The role of artificial intelligence in achieving the Sustainable Development Goals. Nat Commun 11, 233 (2020). https://doi.org/10.1038/s41467-019-14108-y [accessed at https://www.nature.com/articles/s41467-019-14108-y#citeas)