Understanding Sustainable AI beyond Green Washing
In the times when “being sustainable” and “AI expert” have become a trend, what is the real meaning of sustainable AI?
Sustainability and artificial intelligence (AI) have become popular phrases, with individuals embracing them as tags of modernity without fully understanding their significant ramifications. Today, sustainability is sometimes synonymous with eco-friendly lifestyle choices like using wooden toothbrushes, while an AI expert is perceived merely as someone proficient in generative AI technologies, however, the real significance of these concepts is overshadowed.
These crucial concepts, which hold far more significance than this, are reduced to catchphrases. This nullifies the true essence of these critical terms. This article aims to understand Artificial Intelligence, sustainability, and the emerging idea of Sustainable AI.
To remain current and appealing, brands are plastering the label 'sustainable' on everything from bags to clothing, procedures to lifestyles. However, the fact remains that the complexities of sustainability are missed and misinterpreted in a trend-driven approach.
Parallelly, the domain of artificial intelligence is not immune to this trendiness. Many people rush through AI training classes, not to fully understand the complexities of this vast area, but to use it as a tool for making PowerPoint presentations and efficient Excel sheets. The temptation of being viewed as an AI expert while avoiding the complexity of AI has become a recurrent subject.
AI, in its purest form, is large and diverse that is sometimes oversimplified by generalizations. AI spans a wide range of applications, including machine learning and natural language processing.
Sustainable AI is not just about using artificial intelligence to develop sustainable technologies, and developing and using artificial intelligence (AI) in an environmentally responsible and socially beneficial manner; but it is also about developing sustainable AI systems, systems which have sustainability imbibed in them. Sustainable AI is also called Green AI.
Sustainable AI is a rapidly growing field.
As per the research findings of PwC, a member of the Big Four and one of the biggest accounting firms in the world, AI would add $5.2 trillion to the global economy by the end of this decade.
In addition to this, scientists are leveraging AI to meet carbon neutrality goals by mid-millennia. In this domain, the research conducted by DeepMind, a British-American artificial intelligence research laboratory, is showing a bright future. According to their findings, if AI is effectively implemented across various sectors, it could lead to a substantial 4% reduction in global CO2 emissions by the end of 2030. This reduction is equivalent to the emissions caused by Australia, Canada, and Japan combined. This opens the doors of significant AI potential in meeting climatic goals and negating already-caused damage.
Understanding the Working of Sustainable AI:
Sustainable AI works through a combination of algorithms, data, and optimization. These can be imagined as the brains, fuel, and the goal of AI.
Smarts: Smarts are AI algorithms, which can analyze massive data sets in one go. This helps in data prediction and data optimization.
Data: sustainable AI relies on data sets to make informed decisions. If the data set is large and accurate, the resultant data would be unbiased and fairly accurate.
Optimization: Providing optimization is the real goal of sustainable AI.
Overall, AI's analytical prowess lies in its ability to process mountains of environmental data. It can predict natural disasters and model climate change impacts. This deep understanding of the data and climatic patterns empowers us to make informed decisions. This helps in preventing environmental damage before it has even started.
Applications of Sustainable AI:
More than ever, sustainable AI is finding applications in every domain, but the majority of its applications are in the development of trial phases only.
Google's Nest Renewables project is one such example. This uses AI technology to analyze electrical equipment in homes to estimate household energy demand. Then as per the load requirement of the home, the energy is harvested from a nearby solar/ wind power grid.
The smart power management tool is helpful in the smart management of homes and their electrical supply.
Similarly, Tesla's Autopilot for Energy storage systems, called Mega packs and power walls, is also a similar technology that uses AI-powered software to optimize energy distribution but differs in application. Google Nest project analyses the energy demand and loading patterns of the homes, while this uses AI in charging batteries for cars. It uses weather pattern data to store and release energy from mega packs. This technology avoids power blackouts and uses energy more efficiently.
Apart from applications in electrical management systems, Sustainable AI also finds applications in a variety of domains, such as agriculture.
On the one side, IBM's Food Trust platform uses blockchain technology and artificial intelligence (AI) to track the provenance of food items. This enhances the agricultural supply chain's transparency. This encourages sustainable farming methods along with also minimizing food waste.
On the other side, Microsoft's FarmBeats utilizes a data-centric strategy to enhance agricultural operations like fertilization, pest management, and watering by combining data from sensors and even satellites. The project demonstrates how artificial intelligence (AI) can completely transform sustainable farming operations by increasing crop yields and resource efficiency.
Furthermore, the Plantix Disease Detection App, which enables farmers to recognize pests and plant diseases using smartphone photos, is also another example of AI's use in agriculture.
In summary, thinking about sustainability only in terms of making a few lifestyle alterations and AI expertise limited to models like Chat GPT and Bard is too narrow. There is more to both. Sustainability goes beyond small changes, and AI isn't just about a few chat programs. They both have much deeper meanings. It's crucial to consider their larger impact and how they can work together to make a positive difference on a bigger scale. By looking at the bigger picture, we can unlock their true potential and create a world that's both sustainable and technologically advanced.