Have you been using Alexa, Siri, or Google Assistant to ask what’s the weather for today? Or use any of them to switch on a device, increase the brightness of a screen, or dim the lights of your room? Or ask them to schedule meetings and reminders?
If so, you are actually interacting with AI or artificial intelligence. What was once considered science fiction a few decades ago is now a reality. AI, the ability of a computer to learn, is now a buzzword.
Virtual AI assistants such as those mentioned above are just the beginning. As technology expands, we’ll have even more powerful, more analytical, and more intelligent AI that will assist us in all aspects of life.
But can AI aid in the preservation of the environment? Will it enhance recycling processes? Will it increase the latest recycling statistics? Will it improve sustainability? Does it present opportunities for us to become more efficient in managing our planet’s dwindling resources?
Strong AI vs. Narrow AI
When you hear the word AI, what comes into your mind? Most likely, you will think of computers, machines, and devices that imitate human decision-making and consciousness, even emotions. That is referred to as “strong AI.” Strong AI is often thought of as being developed in the hopes of creating smarter computers, conceptual consciousness, or human-like robots that are capable of expressing emotions. “Strong AI” is the kind of AI that is truly as smart as a person in any situation and can do anything a human can do mentally. (See AGILaboratory.com for details)
For more practical industrial and commercial applications, however, “narrow AI” is used. Narrow AI involves using a set of existing analytical technologies that help businesses, industries, and people to make use of resources more efficiently.
To understand the value and function of narrow AI, let’s see the industrial and commercial sectors in their broadest sense. In the real world, nothing is really absolute, known, or fixed. Material compositions vary from one product to another. External conditions differ, and fluctuations happen regularly in commercial and industrial processes. Each operation has limitations, margins of error, permitted ranges, and inaccuracies. In other words, nothing is certain.
This uncertainty can result in a lot of inefficiencies that are bad for a business’s bottom line and the environment. For example, by operating in uncertainty, a company may use an excessive amount of raw material. Or it may be using too much energy for a given operation. Perhaps its flawed logistics causes a waste of time, energy, and money.
Narrow AI helps bridge the uncertainty gap by using machine-learning technologies. These technologies learn from the company’s standard processes, create predictions, and track down resources and output. From what it learns, the AI then recommends specific actions to improve the process. For instance, an AI may accurately estimate the projected output of a certain process, allowing the company to adjust its acquisition of raw materials. Or it can suggest the most optimal operating parameters so a company can reduce energy and lessen pollution without compromising its output.
Present AI Models That are Helping the Environment
Combining AI and sustainability seems to be an odd move. However, many governments and companies are either actively using or advocating their use for environmental preservation and sustainability. Let’s check out some examples:
Established by the Rainforest Alliance and Grameen Foundation, the FarmGrow application aims to support cocoa farmers in many places in the world. The AI teaches them ways to optimize their harvests minus the negative environmental impact. In addition, FarmGrow utilizes Satelligence to blend satellite imagery and AI. This combination equips FarmGrow with remote-sensing technologies that allow farmers to track production, view the latest recycling statistics, and receive notifications about sustainability risks.
Karma is a food-waste AI app that was endorsed by none other than former US President Barack Obama. Karma allows supermarkets, groceries, and restaurants to enumerate foodstuffs that would be thrown away. Food items in this list are sold to the public at discounted prices.
Presently, Karma has collected 900 million tons of food, prepared 2 million meals, and reduced 1,300 tons of carbon dioxide. Talk about food recycling!
This London-based tech company introduces AI that specializes in deep learning for more efficient and sustainable video delivery. The iSize Technologies AI precoder software is designed to learn so that it significantly lessens a bit rate without sacrificing video quality. The lesser bitrate results in a considerable energy reduction, which makes it perfect for businesses that offer data-intensive streaming services.
The company that operates the biggest search engine in the world is a forerunner of AI. The engineers at Google used a machine-learning model—originally developed for another application—to maximize the efficiency of its data centers. Through various inputs, the model learned certain processes that were done in the data centers.
Using the data gathered by the machine-learning model, Google’s algorithms pointed out viable options that would potentially result in additional savings. This ultimately allowed Google to significantly reduce the energy they use to cool their data centers by 40%.
Xcel Energy is a Texas-based utility company that burns coal to generate electricity. While the burning of coal is necessary, the power plant also generates nitrous oxide, a suspected greenhouse gas that damages the ozone layer.
To solve this, Xcel installed neural networks in their smokestacks to rapidly analyze data from coal combustion. From this data, the system can then provide accurate recommendations on adjusting the plant’s controls, operations, output, and other functions to reduce nitrous oxide emissions while operating at maximum efficiency.
Using this AI, Xcel reduced their nitrous oxide emissions by 20%.
Future Applications for AI on Human Development and Environmental Protection
While there are many doomsayers saying that the introduction of AI can spell doom for humanity, a lot of scientists see the potential of AI to catapult humanity into a state of epochal positivity.
Pretty soon, we will see our latest recycling statistics improve vastly as the AI in our mobile devices tell us which items in our homes need recycling. AI-equipped self-driving cars will be more efficient in driving or using fuel than humans. In the logistics industry, AI apps will help exporters and bulk shippers to identify the best times, routes, and conditions to ship their products, maximizing their efficiency while reducing marine pollution. With AI, the future’s looking bright indeed.