AI and Environmental Law and Policy

April 14, 2020

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environment — Image Source: https://bit.ly/2Slsvug

This article has been written by Ishaan Banerjee, studying at Vivekananda Institute of Professional Studies, affiliated to Guru Gobind Singh Indraprastha University. This article explores the benefits of AI and its applications in environmental law and policy.

Table of Contents

Introduction

We all must have heard about artificial intelligence or AI. AI is the latest game-changer in the field of technology. It has a wide ambit of applications across different fields, ranging from daily household chores to performing quantum level calculations and gathering data that otherwise cannot be gathered easily by humans. In our world, where the environment is being damaged by the use of fossil fuels and ecosystems are being destroyed, one can certainly wonder whether AI would be able to prevent such large-scale destruction of the environment. So how would AI be applied in such instances? This article would provide an insight into such questions.

What are the benefits of using AI?

AI could basically be defined as a mimicry of a human being’s intelligence by a machine. A human’s cognitive functions such as learning or problem solving are copied by the machine. Therefore, one might also define AI as a machine that has the ability to think and solve problems on its own.

This ability of AI could be of various benefits to humans such as:

In general, AI would help people to perform better at their jobs and would increase human efficiency, while cutting down costs at the same time by eliminating unnecessary processes.
Menial and small tasks such as answering emails and data entry jobs would be taken over by AI. The tasks performed by the AI would be quick and precise and it would save the time. A few examples of AI from our daily lives include search engines, face recognition software and computer chess where your opponent is actually an AI. However, these forms of AI are known as narrow AI since they perform only select narrow tasks. The face recognition software can only recognize human faces and not cars or animals.
Although the AI being used now, is narrow, its applicability is still ever-expanding. It can be used in healthcare, the automotive industry, finance and economics, cybersecurity, law and many other fields. It can be used to collect various kinds of data that otherwise humans cannot normally collect, or find it extremely difficult to collect.

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How is the Legal Field using AI?

Before this article begins with the applicability of AI to environmental law, it shall explore the AI applications to the law in general:

AI has not yet deeply penetrated the legal field. However, it will be present in future legal jobs and the legal professionals who embrace AI would be benefited. That is why lawyers must keep up with the technology of their times.
Legal Research: Legal research would completely be changed through AI. The AI used in search engines, particularly in legal search engines like Westlaw, would become more advanced and capable of conducting legal research and getting precise results in a matter of seconds, and it has already begun doing so. This task if done by a lawyer would take longer. Therefore, AI in legal research has cut down the costs and resources used in legal research and would be devoid of any human errors. Nowadays, legal tech startups like NearLaw, CaseMine, etc are making Natural Language Processing (NLP) based applications to go beyond simple keyword-based research.
Client service: AI is making client service more economical, efficient and innovative. Legal solutions are provided to clients after carrying out predictions on judgments through case analysis run by AI software to increase the chances of success in a case. Firms can implement a performance-based remuneration for lawyers where they would be paid according to their performance and not according to the billable hours.
Brand value of firms: AI also helps to establish the brand value of a firm by providing smart legal solutions and better connectivity with clients and other stakeholders across the globe in a way that serves them better.
Contract drafting and review: AI has the ability to draft and review contracts and perform due diligence related tasks in the future. A program called ‘Contract Express’ uses a question-answer form to draft a contract through a given set of coded instructions. Contract review through AI is already being done quickly and correctly, where there are no errors involved. Thus, we can see that the firms using advanced technology would have an edge over others.
Prediction Technology: AI can be used to analyse arguments, past judgments and even the reasoning of a judge in deciding cases. The AI could even predict the outcome of a case by analysing past judgments and giving a probability. This would help a lawyer to understand how to exactly frame the arguments, and give him an insight into the judge’s mind.
Legal Analytics: AI helps to provide and point out important questions and issues of law in a case and can provide accurate case law and precedent for use.
Legal Documentation: AI can help lawyers to prepare legal documents within a matter of minutes.
Intellectual Property: Management of IP portfolios is much easier with AI. Registration of trademarks, copyrights, etc, is much easier and quicker, being performed by AI software which would not require the lawyer to go to the Registrar to get it registered.

AI might also have many more uses that will be seen in the near future. There is a general notion among people that AI may be a threat to jobs. From a legal perspective, AI probably will only completely replace data entry jobs. The main aim of AI would be to make lawyers’ work easier and more efficient.

AI in Environmental Law and Policy

Applications of AI in different fields of Environmental Law and Policy:

Climate Change

In India, climate change has wreaked havoc, by changing weather patterns that farmers had previously relied upon, to grow their crops. With the changed weather patterns, the farmers can no longer use traditional methods to grow their crops and need to innovate and devise new methods, timings, etc, of harvesting crops. With AI, weather forecasts have been made more accurate and this could help farmers grow crops in favourable conditions. In Andhra Pradesh, an AI has helped to get a 30% higher average yield per hectare.
The Intergovernmental Panel on Climate Change (IPCC) uses prediction models to forecast climate patterns. Each model is taken into account and the range of predictions is averaged out. This means that each model is given equal weight. AI takes those models which are predicting more accurately than the others and gives added weightage to them, therefore making better climate predictions. AI can predict weather patterns and extreme weather events because it takes into account real-world data and factors which are otherwise very difficult to collect such as atmospheric, oceanic dynamics and chemistry and many more.
Through accurate and timely predictions of weather and climate patterns, we might be able to prevent large scale destruction and loss of life due to natural disasters like cyclones and droughts, etc. Our disaster response and management systems may get strengthened and we would also be able to study why a particular cyclone behaved the way it did and what we can do to prevent dangerous future cyclones.
AI can also be used to reduce the amount of carbon emissions through smart energy usage and can make the use of renewable energy a matter of a future household’s daily life. AI aims to incorporate renewable energy into entire grids by which entire cities will be powered, thus reducing the need for fossil fuels. An example of smart energy usage is that wind companies have been generating more electricity per rotation from each turbine propeller by incorporation of real-time weather and atmospheric data. In Berlin, the WindNODE project uses AI to control a household’s heating. The house has sensors, which work by increasing the heating when there are residents in the house, and by decreasing it when there are none. Thus, smart energy management will help in reducing harmful emissions and pollutants.

Air Pollution

Air pollution is a widespread problem across the world. It is something which directly harms the health of humans. In China, which has some of the most polluted cities in the world, IBM set up its Green Horizon project which uses AI technology to track air pollution levels, forecast air pollution levels, and track the sources of such pollution and provide potential solutions to deal with it. It could deal with potential questions like whether to restrict the number of drivers on the road or whether to close particular power plants, something that would take humans a lot of research and time to answer. Many other such models are being developed which can reduce the emission of air pollutants through safe and smart energy use. Thus, the benefit of AI applications in environmental policy primarily lies in deep data collection and analysis.

Species and Habitat Protection

In China, the World Wide Fund for Nature (WWF) has used an AI to evaluate thousands of photos to sort out tiger photos that had been taken using automatic photo traps. This system of sorting out the tiger photos is way more efficient and time-saving than people going through the thousands of pictures. It also helps in tracking a particular tiger through image recognition and analysis of the stripes of the tiger, which cannot be done by people. This would help to keep track of the tiger’s movements and protect it from poachers. Furthermore, there will not be the need for tranquilising and attaching a radio collar on the tiger. This task of identification of species is very difficult since the jungle is usually thick and densely covered with vegetation. Further, in rainforests, the canopy is so thick that it is very difficult to spot an animal from above, let alone recognize a species. Here, AI is useful in obtaining high-resolution images and processing them to make them clear.
AI may also be used to provide habitats for animal and plant species. German researchers and scientists plan to develop ‘weather stations’ for biodiversity to provide better protection to plants, insects, birds and perhaps even large animals.
A project called Protection Assistant for Wildlife Security (PAWS), started by the University of Southern California has been using past crime records to predict where future poaching may take place. The algorithm analyses the past poaching records, taking into factors such as location, timing, ranger patrols at that particular time, and then accordingly notifies the rangers to patrol a particular area. With the provision of real-world data, the effectiveness of the machine would improve.
AI has the capacity to possibly manage and monitor ecosystems. For example: in Washington, Long Live the Kings, an environmental protection group, is trying to increase the salmon and steelhead population. Supported by Microsoft, they have implemented the use of an AI to monitor and manage marine ecosystems, track the movements of marine species, ensure availability of food for the species and observe and study the behaviour of these species. This will help improve hatchery, harvest and ecosystem management and also help to protect these ecosystems.

Sustainable Development

One of the most important issues in our world is sustainable development. Sustainable development has been defined as development in such a way that the needs of the present generations are fulfilled, while not compromising on the needs of the future generations, while at the same time sustaining the environment. Energy wastage is certainly an important aspect of sustainable development, which this article has already explored. The Sustainable Development Goals are a set of 17 goals, ranging from zero poverty to climate action. AI is already helping in setting up sustainable transport systems in Pittsburgh, where sensors have been deployed under an AI system which adjusts traffic lights according to the flow of traffic. This not only helps prevent traffic jams but also helps to limit vehicular pollution by reducing idling by 40%. In the future, autonomous AI-driven vehicles using renewable energy sources like electricity may completely replace the cars of today.
AI may also revolutionize agriculture. Sensors placed in the field help the AI to monitor the soil composition, fertility, moisture and temperature so that the correct crop can be grown with the correct type of soil. Accordingly, the AI can also help the farmer by giving instructions regarding the best time to water and harvest crops. This will immensely benefit farmers, as they will be unlikely to run into heavy losses. In a country like India, where agriculture takes up a huge part of the people’s livelihood and the GDP, this AI could literally help transform the economy and the lives of these farmers. This may indirectly lead to bumper crops and AI may also help in the efficient allocation of food crops and resources among the people so that the second Sustainable Development Goal (Zero Hunger) is achieved.
AI can also reduce food wastage, where the aim is to bring all stakeholders in the food product production, distribution and marketing process together to prevent large scale wastage of food. The REIF project (Resource efficient, Economic and Intelligent Food Chain) aims to achieve exactly this by working on strict product safety requirements, low agriculture predictability, product specific conditions for food processing, etc.
AI can help in building entire smart cities where households and industries use smart energy consumption methods and real time data. They can help create a city which can effectively manage disasters through simulations, building ordinances and floodplains using real world data. An urban dashboard might be created for compiling all the available information on energy and water use, topography, demographics, etc. For example: IBM plans to develop a system for smart cities to deal with heat waves, where the AI would run simulations of heat waves in urban areas and find out which areas are impacted severely and accordingly, devise strategies.
If AI can help in preventing air pollution, it can help in cleaning the oceans as well. It can monitor and manage marine ecosystems, shipping routes, ocean mining activities, and fishing. AI can follow the spread of invasive species, track large quantities of waste discharged in the oceans, monitor ocean currents and measure pollution levels. It can be used to conduct analytical studies on marine based industries like fishing and oil rigs and can be used to research as to how it affects the marine ecosystem and how the sustainability of both the ecosystems and the industries can take place.
In the near future, where the demand for sustainable and environment friendly goods could be high, the businesses which produce these kinds of goods would be able to survive. Blockchain technology, consists of data records that is managed by many computers, could help to compile data on which goods are sustainable or not. Using these emerging technologies, sustainable, cost-effective products could be widely bought and sold.

Environmental Compliance

In many countries, companies and industrial plants may get away with committing breaches of environmental law, probably because environmental compliance authorities cannot adequately and efficiently allocate resources for checking these plants and corporations.
In the US, there is a specific problem on the proliferation of the large-scale, concentrated animal feeding operations (CAFOs) which are believed to cause a substantial amount of air pollution. This proliferation has occurred primarily because environmental authorities need to give permission for operations that actually cause pollution, but not for those operations which have the potential to cause pollution. Furthermore, these operations are difficult to spot and no authority has any official count of the number of such operations across the country. Stanford researchers have been using AI to conduct analysis of images captured by drones and satellites to recognise these CAFOs using image analysis of the barn size and shape and dry manure storages. The researchers have stated that this technology could recognise 95 percent of the CAFOs using fewer than 10 percent of the resources employed to identify them manually. Therefore, AI can allow for efficient resource allocation.

Risks of Artificial Technology

Although AI might have many applications in environmental law According to the World Economic Forum, there are six risks related to AI use in environmental law and policy:

Performance: AI might give inaccurate or undesirable conclusions as its conclusions might not be understandable to humans. This could be risky for applications which deal with disaster prediction and management where more certainty is needed.
Security: There are possibilities of AI systems being hacked, which can cause interference with energy, natural disaster and other systems.
Control risks: Since AI systems communicate autonomously, this can lead to unpredictable results. For example: two AI systems were communicating in a language that researchers did not understand.
Economical risks: The economy will become more digitized and technologically dependent in the future. Businesses slow to adapt to technological evolution will be left behind.
Social risks: AI will probably replace a lot of jobs and make them automated. AI enabled weapon systems will also have the potential to cause large scale destruction which could also impact the environment.
Ethical risks: AI uses assumptions in its analysis, therefore it can lead to biases in data.

Conclusion

AI has the potential to change human lives and the environment. It has a large number of applications and this number will increase in the future and has immense benefits. However,there would be some flaws in AI; there might be data biasness issues, and the data might not always be accurate, but that would not undermine the immense benefits offered by it. This is exactly why AI would not fully replace the jobs of environmental lawyers and policy makers since the analysis of data would always require human judgment since it applies to society as a whole and one needs to measure the impact such technology will have on the society.