AI and the environment: its application in improving environmental performance and use in environmental regulation

AI offers innovative solutions and insights that can help businesses operate more sustainably. As corporations face increasing pressure from stakeholders to improve their environmental performance, it has emerged as a powerful tool to help address these challenges.
AI and the environment: its application in improving environmental performance and use in environmental regulation
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AI has the potential to revolutionise environmental performance, offering innovative solutions and insights that can help businesses operate more sustainably. As corporations face increasing pressure from stakeholders to improve their environmental performance, AI has emerged as a powerful tool to help address these challenges.

In this article we highlight how AI can improve environmental practices and help make regulation more efficient and effective. We also give insight into important implications that regulated businesses need to consider when using AI and the role of the courts when it comes to accountability and liability. 

How can AI improve environmental practices?

The breadth of these applications highlights the significant role AI has to advance better environmental practices and offer innovative solutions to complex challenges. For example:

  • Detailed energy consumption analysis: AI goes beyond surface-level insights, delving into granular energy consumption data for each business process, identifying specific inefficiencies, and suggesting energy-saving measures and tailored sustainable alternatives.
  • Optimised resource allocation: AI-driven algorithms can manage resources dynamically, adapting to changes in demand to minimise environmental impact. AI’s advanced algorithms can not only reduce waste, but also contribute to sustainable resource management by predicting future resource needs and optimising their allocation.
  • Advanced predictive maintenance: by forecasting machine failures, AI reduces unexpected downtimes, conserves resources, and minimises pollutant emissions, reducing the environmental footprint of machinery malfunctions.
  • Smart building management: AI can adapt energy use in real-time, accounting for occupancy and weather conditions, leading to significant reductions in the carbon footprint of commercial and industrial buildings.
  • Waste management optimisation: AI can improve waste sorting accuracy, enhance recycling processes, and identify opportunities to repurpose waste materials leading to a reduction in overall environmental impact.

AI and environmental regulation

Environmental regulation is complex, time-consuming and expensive. AI can help in making regulation more efficient and effective. Some reported uses of AI in this area include:

  • Predicting environmental risks - for example, predicting oils spills or natural disasters. This can help enforcement bodies prepare for potential incidents and respond more quickly and effectively.
  • Informing policy decisions - for example, in evaluating the impact of proposed policies and laws by simulating different scenarios and predicting outcomes. AI can help identify areas for improvement.
  • Monitoring compliance with environmental law - for example, by analysing data from drone footage, satellite imagery and social media posts. AI can also identify resource optimisation by selecting where manual inspection would be most beneficial. One of the key advantages of AI in monitoring compliance with environmental law is its ability to facilitate real-time monitoring and enforcement. AI systems can be used to maintain air and water quality and detect illegal waste dumping. By providing real-time data, AI can help enforcement bodies quickly identify areas that require intervention, leading to more effective and efficient enforcement efforts.Clearly, this raises challenges for enforcement bodies in terms of prioritising performance objectives, allocating resources on the ground and reputation management.

Important implications for regulated businesses

As a result of AI technology being able to deliver or predict potential breaches of environmental law, there’s a higher risk of breaches being detected and environmental sanctions resulting. Regulated businesses could be subject to greater scrutiny and regulatory action, in particular where AI technology provides a low-cost method for detecting potential breaches of environmental law.

However, decisions made by AI technology are open to challenge. For example, drone image footage or satellite data could easily be processed wrongly by AI technology, predicting a breach of environmental law where none exists. Similarly, a business that invests in AI technology would need to be alive to the fact that whilst the technology may be relatively inexpensive, compared to an environmental fine, the technology is not infallible, and errors could result in a business being wrongly accused of a breach. 

For businesses that wish to invest in AI technology, it’s important to be aware of the regulatory environment and the potential impact of AI on the business. In-house teams should include regular testing of AI models and systems for handling errors. Businesses should design and implement procedures for the use of AI in environmental compliance, including how data is to be collected, stored and shared, reflecting new legislation and guidance from the environmental regulators.

Accountability and liability and the role of courts

The many challenges that AI technology raise requires innovative and responsive systems to ensure that AI systems are held accountable and used appropriately in environmental law enforcement and decision-making.

AI systems should be required to provide explanations for their decisions, similar to the requirement for human decision-making under the law. This can help ensure that AI systems are accountable and transparent. Policies and legislation should be developed to provide responsible use of AI in environmental law enforcement and decision-making. This can involve measures such as requiring AI systems to be tested for their environmental and socio-economic impact.

Litigation and courts can play a role in addressing the challenges and opportunities of AI in environmental law enforcement and decision-making. For example, court cases can be used to challenge the use of AI systems in environmental decision-making or to hold organisations to account for environmental damage by the use of AI.

Courts could shape the regulatory framework for AI in environmental law, by interpreting existing law and requirements in light of new technological developments.

The potential for AI to improve the effectiveness of environmental regulation must be considered alongside ethical principles and implemented in a responsible way. This requires close working between policy makers, environmental regulators, business and academics to ensure that AI is used in a way that is transparent, fair and delivers effective environmental protection.

For more information, please contact Ashford's energy and resource management team.

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