In the 1990’s, IBM developed “Deep Blue,” a software program that could play chess. It could look at the pieces on a chessboard and make predictions about winning moves. In fact, the program beat the champion, Garry Kasparov, by analyzing possible moves and choosing the most strategic one. “Deep Blue” had no memory and could not use past chess games to learn patterns and use them to play future games. This is a type of artificial intelligence that is known as “reactive.”
We’ve come a long way since then. Artificial intelligence, also called machine learning, now involves far more than learning to play chess. It now involves simulating human intelligence – learning, reasoning (using programmed “rules” to analyze and generate conclusions and/or predictions), and even self-correction.
The value of artificial intelligence, combined with new technologies of gathering big data have been known and used by businesses for several years now. For example, a bank can gather big data about loan products of all types from all financial institutions, and the demographics of the people who find hose loans popular. It can feed that data to a machine with specific queries. That “intelligence” can organize the historical patterns of borrowing, and use those patterns to predict the types of loans that future borrowers will want. Other uses include transportation and logistics, healthcare and research organizations, manufacturing, sales, and marketing. Taco Bell’s new “TacoBot” holds a conversation with customers, with patterns it has learned in speech recognition, in order to generate that conversation.
The promise of AI for Planet Sustainability
Now that business uses are proven, what more can AI do that will have more impact on humankind? What can AI do to save a planet that is in serious trouble?
Here are 8 ways that AI might be harnessed for Earth health.
Consider all of the current and potential uses of AI:
One of the big challenges we face is an efficient use of power. The inefficiencies result is a lot of waste, and waste results in use of energy resources beyond what is really needed. All additional energy use is stressful for our climate.
AI is now beginning to be used to learn patterns of energy use, by geography, by times of day and night, by seasons. With this information, predictions can be made that result in the right distribution, amounts of storage needed, load management, etc.
Big data collection surrounding climate can now be gathered from unlimited sources, organized, and churned out to present scientists with a huge amount of information about climate conditions all over the planet. Over time, changes can be charted to provide an accurate picture of the damage being done. This accuracy gives scientists start points as they identify risk zones and vulnerabilities.
And AI is used to study these patterns and the results (hurricanes, temperature increases, rising ocean levels) and provide predictions of future vulnerability and potential damage.
AI can also assist climate scientists and researchers test theories and potential solutions regarding reduction in air pollution. One such example is the Green Horizon Project of IBM – it analyzes data, formulates predictions about pollution, and actually tests scenarios for pollution reduction that scientists hypothesize.
Google recently was able to cut its energy use (and thus pollution) by 15%, using AI and machine learning. Other companies can certainly take a lesson here and do the same.
We’ve done a lot already in encouraging individuals to become more environmentally conscious. We have recycling efforts all over the planet. We have major educational initiatives to speak to human ocean pollution and the dangers it presents to almost every species of marine life. Scientists are even creating machines to vacuum up trash.
Still, much more must be done. We have love affairs with our cars; we continue to eat beef from cows that contribute 1/3 of the methane gas that goes into our atmosphere, because of the way they are raised and fed.
We leave home for the day with our thermostats unchanged, heating and cooling an empty house; We water our lawns, often forgetting to change sprinkler positions or that the sprinkler is still running. AI and machine learning can help design and develop products that can reduce this waste. Further AI-monitored devices will learn patterns of human use, and automatically alter things such as temperature and security systems, based upon those patterns. Humans can forget to alter their devices remotely, but an AI-controlled machine will never forget. It is projected that as much as 15% of heating and cooling energy could be saved through these devices, and over 8,000 gallons of water could be saved per average household. That’s a lot of “green.”
Every year, lives are lost and property lost and damaged due to weather events. If people and governments could have earlier warning signs that conditions are “right” for a major event, proactive precautions could be taken. AI, through its ability to learn weather patterns, and common results from those patterns can provide alerts before the human can. AI can also predict how long a weather event may last and its severity, based on it understanding of conditions.
Again, based upon its learning, AI can help detect the early stages of crop disease and other issues; it can take care of automated feeding of animals and can analyze and predict supply and demand. Those in the agriculture industry can thus better plan for production, so as to meet demand more efficiently. All of this information can ultimately lower water usage and the use of chemicals which damage the environment.
The use of AI to predict weather patterns will also come in handy, as farmers decide which crops to produce in any given year. As well, the agriculture industry as a whole can know what types of crops will be in high demand in various regions of the world and develop supply plans to move products where they will be in highest demand.
Of all the potential of AI for planet sustainability, nothing is more exciting than the concept of entire cities being able to utilize its learning and recommendations. Already, small amounts of AI use are in place in cities around the world. Here are some of the innovations that have come about because of AI:
In a more utopian world, it is predicted that ultimately, we may have a digital geospatial dashboard for the entire planet. This would be an open API, infused with AI, to enable the monitoring of all types of environmental conditions in real time, and the AI would specifically be designed to provide alerts for various conditions – illegal deforestation, hunting, and fishing, floods, air pollution conditions, ocean levels, impending natural disasters, etc.
These are exciting times, and AI holds the promise of tackling some of our biggest environmental issues. But, for all of its potential, there are risks.
If these security, control, and ethical issues can be resolved, however, AI can literally create a revolution in environmental sustainability.
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