This article has been written by Abhishek Ray pursuing an Executive Certificate Course in Corporate Governance for Directors and CXOs from Skill Arbitrage.
This article has been edited and published by Shashwat Kaushik.
Table of Contents
Introduction
Humans have been terrible with all the inventions they have made till now. Either we have created a monster out of it that threatens to eradicate the entire human race or we have exploited the invention to the extent that the ramifications are profound and wide reaching. Artificial intelligence, in my opinion, has the potential to be one of the similar mistakes that humans have been consistently committing. Unless we embrace a different path to unlock the positive possibilities and potential that can be harnessed out of this powerful tool we know as artificial intelligence.
For centuries, we have rapidly discovered new technologies, invented new products, modified them and proceeded with mass production to monetize them and bring ease into our lives. Short term self-interest has led to the exploitation of environmental resources. Picture this: In India during the 1980’s, black and white televisions were a luxury. One television would gather four to five neighbours to watch the epic Ramayana together. Today, most of those neighbours and their next generations might have more than a coloured, wide screen LED television. Needless to say, our attention is fractured across a sea of mobile screens and endless online content to watch. From then on, how much has changed, how much more we have of everything (barring the still underprivileged section) is just a resounding fact of what mass manufacturing and the ever-increasing marketing push have done. And at the extreme end of the receiving end has been our environment. Global warming, polluted rivers and extinct species are just the truths of our lives that we have conveniently accepted. And that brings me to being responsible and aware of the need to use artificial intelligence not to further this mountain of abundance and waste but to find and embrace environmentally sustainable ways of life and business.
Application of artificial intelligence in environmental sustainability
The world we live in today is in a critical state of climatic crisis. Most of the measures and laws, both local and global, have failed to restrict the situation and move ahead with a sustainable approach. However, artificial intelligence brings with it three unique qualities that can help the earth achieve environmental sustainability. First is its ability to perform repetitive tasks in a much faster manner compared to the same work done by its human counterpart. The other ability is to integrate multiple computers and machines to solve a complex problem. One more underlying quality of integration is adaptability. This entire integration of computers can be upgraded with one click of a button. The third unique ability is to make sense of the sea of unstructured data that is available, which is humanly impossible to do. Information asymmetry is one of the key challenges to environmental sustainability, which AI takes care of.
Biodiversity
Biodiversity is the variety of life on earth. It depicts the diverse species, flora and fauna that live on earth. Apart from its intrinsic and ecological role, it is responsible for our clean drinking water, our food source and the building materials that we use. Our short-term benefit aspirations have led to the depletion of this biodiversity. Artificial intelligence, with its unique qualities, helps to map and monitor with high precision. With techniques like acoustic monitoring, remote sensing, and satellite images, it can analyse huge amounts of data and predict specific threats to the components of the ecosystem. This helps us to direct our resources towards specific conservation efforts that will be winners in a cost to benefit ratio. Artificial intelligence can help detect poaching and wildlife trafficking, which are the chief reasons for the extinction of several species on the face of Mother Earth.
Energy
The twin challenge of energy and sustainability is like walking on a tightrope, with the tilt being extremely heavy towards energy. Application of artificial intelligence can be a game changer for the unfortunate super underdog in this game of balance. Artificial intelligence can have a fourfold effect on our energy management and the quest for sustainability. First is an effective and accurate forecasting of our energy requirements at the domestic and commercial levels. By analysing our past consumption data and the various parameters that affect the production of energy, AI can achieve this. The second is how it can help increase efficiency and decrease waste in our production and distribution ecosystems. Third is its contribution towards operations and maintenance. AI tools can significantly predict machine downtime and provide pre-emptive servicing to reduce such downtimes, which add to cost and reduce efficiency. Fourth, AI can be used to incorporate renewable energy by making companies prosumer from consumer. These four-fold strategies can significantly reduce our carbon footprints and make for an energy sustainable future.
Transportation
Transportation has played a crucial role in economic growth and global connectivity. And this has been a major contributing factor to the global carbon footprint and there is much in this sector that can be done for environmental sustainability. Artificial intelligence can improve energy efficiency in this sector by better route planning, to put it simply. AI is proving to be a game changer in traffic management, which not only contributes to a significant reduction in accidents but also optimises trips there by positively impacting energy consumption. AI driven traffic management reduces congestion and thereby reduces emissions. A significant cost can be saved by preventive maintenance predicted by artificially intelligent systems, thereby reducing time and increasing efficiency.
Water
AI has the potential to participate in the entire water cycle management process. It will help analyse and monitor data such as water quality, consumption and availability. AI can help predict water demand, helping utilities supply water as per demand and thereby reducing waste. It can help identify idle water wastage and leakage up to a household level. Monitoring of weather systems by artificially intelligent systems can predict floods and droughts, largely enabling authorities to take necessary and timely precautionary measures. AI can be used to identify water depleting points there by focusing on further investigation and taking preventive action to refurbish the waterbody.
Artificial intelligence is a vast subject with multiple aspects that determine its level of application. The more aspects are incorporated, the better and more accurate the results can be. The most basic level is machine learning. To put it simply, it is how machines/computers learn from data to make accurate predictions. An e.g is your music playing application, which gradually, with your music listening trends, which for the application is data, learns to predict and suggest music to you. The next level is the artificial neural network, which is essentially inspired by the human neural network. An example would be how self-driven cars recognise road signs. The third level is a combination of cognitive behaviours. This domain is the very deep learning of complex mental processes like decision making, memory, etc. And, for example, there would be interactive robots. The fourth is natural language processing. In this way, the computer can understand, generate and manipulate human language. E.g., your own Siri. The last domain is using fuzzy logic rather than boolean logic. It means the application would use various degrees of truth rather than basing itself on yes or no logic. E.g., it would be home automation. Finally, there is an expert system, which means computers learn from an expert human being. E.g., Alpha Zero is a chess playing application. Simply by looking at the above cited examples, one can imagine the combined strength of artificial intelligence and how it can power up achieving environmental sustainability.
Marketing and saleability
Environmental sustainability through artificial intelligence is broadly divided into two parts: static and autonomous. Static means the decision made during the preproduction, production, and logistics of a product until it reaches consumers. Autonomous means the product’s capacity to learn from the environment and make better choices. An example of a robot cleaning a house and learning the family’s consumption and behavioural habits to make better choices. This is important to note as it has two fold effects on marketing and thereby the saleability of a product. A product that has been produced with a sustainable approach and can further improve its delivery based on a continuous enhancement of an environmentally sustainable approach has huge marketing potential. Take, for example, an IOT based home light that boasts of saving energy consumption significantly but has a huge carbon footprint at its production phase due to non-sustainable manufacturing. The product, while giving a lot to the environment in its post-sales life cycle, has caused significant damage to the environment during its manufacturing stage. On the contrary, a company that applies to reduce, recycle, and reuse principles in producing an IOT based home light has significantly higher marketability.
But the obvious question arises that will this marketing have the desired effect on the consumer’s mind that will finally translate into the product’s saleability. Regular products offer benefits to customers through their quality and features. Environmentally sustainable products offer benefits to the environment and nature. These benefits have traditionally been seen as of no use to the marketing guns in enhancing the sales of a particular product. However, in recent years, a behavioural shift has been observed. With increasing awareness about the environment, sustainable products are now positioned to increase profitability. Companies are now moving forward to reap marketing benefits for sustainable products. The sustainable product and thereby the manufacturing company are positioned in the customer’s mind as an ethically superior company, which leads to the desire of the customer to be associated with such a company and has a positive effect on its sales. While customers achieve a feel-good factor by doing their part for the environment, companies gain long-term goodwill. The trend is moving upward. A recent survey conducted in 2022 showed 69 percent of the respondent’s agreement to pay more for environmentally sustainable products. Consumers are becoming more and more aware of the harmful effects of nature, and that their individual well-being is also secured by an environmentally sustainable lifestyle.
Challenges
There are many foreseen and unseen obstacles that lie in the path to implementing artificial intelligence. From technical to cultural issues, embracing artificial intelligence to achieve environmental sustainability is easier said than done. I’m sure all of us in our work lives have faced the difficulty of implementing new processes or applications. Changing the old way of doing things, with which there is already a comfort level achieved, is an uphill task. In the late 1990s and early 2000s, when laptops and computers were replacing the traditional fax machines and paperwork, it was very difficult for the majority of the workforce to adapt, especially in sectors that were not very tech-savvy. And this was nothing compared to the sea of changes that stared at us with the integration of artificial intelligence. Let’s look at some foreseen challenges.
Reliance on historical data
Artificial intelligence is all about historical data. The more data available, the greater the accuracy of the desired result. Data helps in predicting future events and taking necessary actions. However, what about a scenario where enough historical data is not available? Also, predicting future events with only historical data will lack innovation and adaptability in the event of a new situation. Past data may be compromised due to human error, biases and prejudice that will corrupt the desired outcome.
Uncertainty of human response
Every human being is unique. Their response to any scenario will vastly vary based on multiple factors pertaining to that particular individual. Responses to artificial intelligence-based interventions can be distorted and may lead to evoking strong emotions, leading to a totally new outcome.
Cybersecurity risk
One of the risks being witnessed currently and is a trending topic is the issue of deep fakes. AI can be used to create highly realistic duplicates of someone, not only in an image but on a video too. Artificial intelligence can be used to hack highly complex and encrypted networks, unleashing a major cybersecurity risk. Just imagine a scenario where biological warfare can be done on a country by tampering with its water quality data, which may guide the department to take necessary action, eventually leading to health hazards for its population.
Perception of job loss
Whether artificial intelligence will replace humans and to what extent is debatable. However, perception itself is a very big challenge for the application of artificial intelligence in the field of environmental sustainability. This will lead to resistance to adopting AI technology and the issue needs to be addressed as a priority by authorities to shift the perception towards a more positive thought process.
Cultural and social impact
Artificial intelligence-based solutions offered for environmental sustainability might not be accepted by society or from a cultural point of view. Especially for a country like India with such vast diversity in cultural and religious habits, it becomes all the more complex. Take for example, the immersion of ritual leftovers into rivers, which is in itself a ritual. Rivers in India are considered holy but this immersion ritual has a deep impact on the biodiversity and the quality of the water in the river. Now, an AI driven solution may be to prohibit this and collect all the leftovers in an organised manner, later to be recycled or disposed of in an environmentally friendly manner. This solution may well spark resistance.
Conclusion
Rome was not built in a day and no great initiative or change has happened without resistance. It has always come with its own baggage of nuances. But humans have thrived for centuries and will thrive in the future too. With an increase in education and awareness, along with access to so much information, we shall collectively move forward for an environmentally sustainable and green future. While it’s a cliché to finally put the onus on the government, authorities and corporations, I believe that big changes happen with small but collective and continuous steps taken. Each one of us has a role to play, starting with making our individual households environmentally sustainable and developing a sustainable culture in our family. Greenify your home and make everyday choices based on reduce, reuse, and recycle. Let’s make the world a better place.
References
- https://www.unep.org/news-and-stories/story/how-artificial-intelligence-helping-tackle-environmental-challenges
- https://www.sciencedirect.com/science/article/pii/S2666188822000053
- https://hbr.org/sponsored/2023/09/how-ai-can-help-cut-energy-costs-while-meeting-ambitious-esg-goals?utm_medium=paidsearch&utm_source=google&utm_campaign=intlcontent_bussoc&utm_term=Non-Brand&tpcc=intlcontent_bussoc&gad_source=1&gclid=CjwKCAiAs6-sBhBmEiwA1Nl8s1QPUN_0FHUWDvRrk6ZN0096IXjRUKgYQfQf_JYZi66WuSDBMh1f_BoCKIUQAvD_BwE
- https://www.europarl.europa.eu/RegData/etudes/BRIE/2019/635609/EPRS_BRI(2019)635609_EN.pdf
- https://www.ibm.com/topics/machine-learning
- https://www.freethink.com/robots-ai/ai-uncertainty
