By Annie Button
It’s no secret that artificial intelligence (AI) has emerged as a game-changing tool in addressing various technological challenges in sectors worldwide. With AI programs now able to solve problems in a fraction of the time that it might take a human being, many – including those in the sustainability sector – are beginning to harness this technology in innovative ways.
Furthermore, as pollution, climate change, and rising global temperatures have dominated discourse in recent years, and with our society so tech-enabled, many are wondering how AI can be leveraged to preserve the planet’s future.
On the surface, many may question how AI and sustainability complement one another, yet the intersection of AI and sustainability has emerged as a focal point in recent years. Digital sustainability is especially significant as institutions and leaders continue to tackle environmental challenges.
But with AI integrations taking numerous forms and working with such varied data sets, not only are there pertinent concerns to address, but determining how effective this technology can be in digital sustainability efforts and environmental initiatives must be confirmed. This article looks to explore those multifaceted ways in which AI can be a powerful asset in our journey towards a more sustainable future.
What Do We Mean By Digital Sustainability?
Credit: Stefan Kühn – Own work
Digital sustainability refers to the process of applying social, economic, and environmental stewardship principles to digital data, services and products. It harnesses the Internet of Things (IoT) and other technologies to support sustainable business operations and reduce their negative impact on the environment.
A further interpretation of the term encompasses the collective effort to deliver specific (and more eco-friendly) digital products. However, it can refer to existing technology which can advance incumbent sustainability efforts. It is therefore a fairly broad term encompassing many of the same types of goals.
As the average Internet user accounts for 3-4% of greenhouse gas emissions (GHGs) per capita (229 kg of carbon dioxide per year), this can be viewed as a double-edged sword. AI, with its ability to process and aggregate large amounts of data, identify complex patterns, automate tasks, and improve productivity within teams, can therefore be positioned as the focal point of digital sustainability. AI can, in no uncertain terms, revolutionize how environmental challenges are addressed, tackled, reviewed, and optimized.
Key Areas Where AI Drives Digital Sustainability
Artificial intelligence is undoubtedly reshaping the energy and technology sectors. AI is altering how power is generated, consumed, and distributed, making accurate, data-driven forecasts, analyzing patterns, augmenting cyber threat detection and response teams, improving collective digital safety, and much more.
As far as enhancing digital sustainability goes, AI has several convenient and impactful applications.
- Energy Efficiency and Smart Grids
AI plays a pivotal role in improving energy efficiency both in terms of optimizing resource usage and reducing waste. This proves particularly useful when trying to consolidate usage from, for example, data centers, which house millions of servers and utilize large amounts of electricity. A recent IEA report indicated that data center electricity usage is set to double by 2026, citing AI workloads as contributory to this growing demand.
AI-powered systems can predict energy demand patterns, optimize distribution, and identify inefficiencies. Intelligent energy management systems – powered by AI – can also monitor and control energy consumption in a broad range of buildings, not just those confined to the tech space.
AI can also be integrated into the process of developing smart grids which can facilitate efficient energy based on optimized and balanced supply and demand. Using advanced analytics, energy consumption patterns and load management can be predicted.
- Sustainable Transportation and Logistics
The transportation sector is also a significant contributor to global carbon emissions (8 billion metric tons of carbon dioxide equivalent in 2022), with the United States being the biggest contributing country. AI presents numerous opportunities to make transportation systems more sustainable and energy efficient.
- Traffic management: AI algorithms can be used to predict traffic patterns, allowing for the optimization of routes to reduce congestion, maximize fuel efficiency, and minimize import/export bottlenecks. This is particularly useful for logistics companies.
- AI-powered cars: Self-driving cars are gaining traction, with underlying research and development suggesting they will be able to improve fuel efficiency and reduce accidents.
- Integration with EVs: In line with advancements in AI-powered car manufacturing, the greater influence of electric vehicles will prove crucial in the global fight towards net zero.
- Environmental Monitoring and Conservation
Given that AI can process and analyze large quantities of data, this can make it an invaluable tool for environmental condition monitoring and broader conservation tasks.
AI can aggregate important data and statistics from satellite imagery, sensors, and other integrated hardware to track environmental conditions and also monitor how they have changed over time.
If conditions in certain wildlife habitats have changed to the point where they present dangers to biodiversity and endangered species (such as population loss, ecosystem changes, air and water quality drops, etc.) AI can act autonomously to rectify those issues. AI can also be used to predict future data and patterns and process complex data to aid in climate change mitigation strategies.
- Waste Management and the Circular Economy
AI is drastically improving waste management practices and supporting the transition to a circular economy, a priority for many global institutions including the European Union and the U.S. Environmental Protection Agency.
AI and machine learning (ML) technologies can be leveraged to improve the accuracy and efficiency of recycling, detecting materials autonomously to prevent contamination and reduce excess waste ending up in landfill.
Using AI, consumers and manufacturers can decisively predict when maintenance is needed, thus reducing waste from premature and unnecessary disposal. The technology can also be used to optimize the flow of materials in supply chains, optimizing their routes and identifying opportunities for recycling or reuse.
AI itself can also be used to aid in designing products that are inherently easier to repurpose or recycle once at the ‘end’ of their expected lifespan. All of these AI-enabled processes contribute significantly towards the broader goals of achieving a circular economy and moving away from standard linear models.
Challenges and Considerations
While it is clear that the potential of AI driving digital sustainability is incredible, there are several challenges and considerations that must be addressed quickly.
First of all, AI algorithms – particularly deep learning models – require energy and resources to run. Not only that, but they will require extensive testing and supervision, which all come at an environmental cost. Therefore, seeing improvements will need to account for these vital testing and refinement stages. Over time, having studied the effectiveness of AI architecture, further ways to optimize energy usage will need to be identified.
There is growing uncertainty about AI’s propensity for biases and perpetuating misinformation, and there have been cases where falsified or skewed data – generated by AI – has influenced business decisions. Alongside this, AI models can be trained to analyze, store, and process more data sets, which can, if not adequately monitored and supervised, raise concerns about data security and privacy. Users must remain vigilant and stay abreast of emerging AI security risks while safeguarding their data in situ.
AI-powered sustainability solutions must be accessible to all regions, not just those that have access to reliable, advanced infrastructure. In developing economies, AI and similarly innovative technology could prove useful, but efforts must be made to bridge the pervasive digital divide if we are to witness tangible and equitable benefits.
Ensuring AI systems are developed and deployed ethically is not just vital for long-term sustainability, it’s also crucial to prevent job displacement fears from compounding. Many fear that AI is – or could be – a solution to replace human workers in various fields, whereas users need to ensure that AI is positioned as a tool, not a direct replacement.
Recognize and highlight AI’s ability to automate certain tasks that make human teams’ jobs easier, and both re-skill and upskill where necessary to ensure that they are supported in a healthy and meaningful way.
The Road Ahead: Integrating AI into Sustainability Strategies
It’s clear that AI presents powerful and diverse opportunities in our quest for digital sustainability. Leveraging AI is an inevitability at this point, meaning that organizations everywhere will need to eventually get to grips with the concept and workings of AI. However, it would be naive to ignore the underlying concerns and challenges of AI as a technology, and instead give preference to hard-working human teams to supervise and manage its deployment and usage.
As we move forward, the integration of AI into sustainability efforts will become more apparent. Therefore, it’s prudent that organizations intent on improving sustainability take advantage of AI where possible now. While the improvements may not be apparent straight away with integrations, and while the technology itself is still evolving, deploying AI now will position organizations for future changes afoot and give them greater confidence in this technology.
The journey towards a sustainable future is complex, but using AI will give organizations everywhere the chance to make promising and meaningful changes to protect the planet and all who live on it.
About the Author
Annie is a freelance writer based in the UK, who has written for a variety of prestigious online and print publications.
She specialises in lifestyle, business, branding, digital marketing and HR.