By Sarah Currie-Halpern, Co-Founder and Partner
Seemingly overnight, artificial intelligence has leapt from a tech world bauble to a real-world phenomenon. AI’s biggest advocates claim that it is a technological turning point about to catapult us into a new future, while its detractors say it’s a waste of human and environmental resources. As with most things, the truth is probably somewhere in the middle. AI is an undeniably and exceptionally powerful tool, and it has a number of waste management use cases worth exploring. The question is not only how AI-assisted waste management might work, but whether AI’s benefits to waste management outweigh its larger environmental drawbacks.
A number of AI-assisted waste management systems already exist. The San Francisco-based tech company Glacier has created an AI-powered robot for recycling plants that can recognize and sort 30-plus materials. Sorting is one of the most cumbersome aspects of the recycling process, and many plants remain entirely dependent on manual labor to manage it. The longtime lack of innovation related to the sorting process has actually kept recycling centers from being able to capture the maximum amount of material to recycle. An AI-powered machine that can close that gap and keep more recyclable materials out of landfills is a positive development by any metric.
AI is not only a promising new tool for keeping valuable materials out of landfills but also for monitoring and maintaining these landfills. Combined with satellite imagery, AI systems can analyze patterns and predict potential methane hotspots, which means landfill operation teams can plug leaks and prevent contamination before it’s a problem. Landfill methane can be captured and converted into renewable gas, and continuous AI-powered monitoring systems can optimize the process. The Massachusetts-based firm LoCi Controls, which creates one such AI waste monitoring system, found that waste management companies were able to capture 28% more methane from landfills following implementation.
Methane emissions, however, aren’t the only problem landfills create. Contamination of groundwater and soil is a constant threat around landfills, typically referred to as leachate pollution. AI sensors can assist with the detection of leachate pollution, then identify trends and anomalies, thus accelerating response time among monitoring teams. It can even predict leachate movement to better test the effectiveness of newly implemented containment strategies.
Solid waste management often feels like a game of catch-up, which is why the predictive analysis and monitoring AI can provide has the potential to be such a game-changer. Then again, it’s important not to treat AI as a magic bullet for everything related to solid waste management. AI’s carbon footprint is enormous, and more AI means more energy-gobbling data centers. Freshwater evaporation related to AI energy needs is a rapidly growing problem, and last year researchers found that “global AI demand may be accountable for 4.2-6.6 billion cubic meters of water withdrawal in 2027.”
Utilizing AI for good in and beyond waste management must go hand-in-hand with addressing the energy consumption elephant in the room. We need a cross-industry conversation about how and where we use AI. AI’s potential benefits to waste management are undeniable and the companies addressing the innovation gap head-on are doing important work, but those benefits don’t exist in a vacuum. A climate-minded way forward with AI is possible, but not without sacrifices in other areas and certainly not without further energy innovation.
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