The term Artificial Intelligence conjures quite vivid and colorful images in our minds. Think of aliens in Star Trek or the assistant in Interstellar. Pop culture, in fact, is abundant with such characterizations of AI.
One might think such characterizations are ill-informed and aggrandized. Granted, most are. However, the birth of so-called true AI is possible just, not today. As of now, it is a distant possibility. But to make that possibility real as soon as possible, the world’s largest companies are pouring decades and billions into improving the technology.
And the rationale is quite simple.
Already, investing in business intelligence solutions such as RPA — a simpler form of AI — has propelled businesses to new heights. Businesses that have leveraged the technology, compared to those who have not, have made staggering gains in productivity, efficiency, cost-effectiveness, risk management, scalability, and other parameters that drive revenue.
Imagine what a full-fledged AI could achieve.
This is a technology that combines human creativity with computation far beyond human capacity to make more accurate deductions, generalizations, and solve problems impossibly complex for us. It could revolutionize everything we could think of.
The list of problems AI could solve is extensive. Though, on the whole, two stand out. Identifying opportunities for profit. And identifying opportunities for preservation.
Only one of the two is urgent.
Why is sustainable investing important?
Consider climate change, for instance.
Climate change has been long identified as a threat to the planet, and hence, us. However, the impact of climate change has only recently been more evident. Innovations like the internet have democratized information. The result is a new generation of stakeholders — investors, customers, employees, shareholders — that is hyper-aware of the impact its decisions have on others, and the generations to come.
And the impact is not limited to the environment, but extends to the social, political, and cultural aspects of a community. Modern stakeholders want a system-wide change — not just the use of renewable energy and higher quality of air, but also more equality, diversity, and conscientiousness. Not just less deforestation and water pollution. But also, less hunger, poverty, toxic workplace culture, data mismanagement, and improper marketing.
They want a change. They want it now. And, therefore, change is what companies are delivering.
Already, more than 200 of the world’s biggest companies are heavily investing in ESG consulting, seeking to make strategic decisions that mitigate Environmental, Social, and Governance risk, and drive sustainable growth.
The rapid rise in materiality assessment and sustainable investing saw the value of global ESG funds increase by 42%, reaching a record-high of $17 trillion.
And what was responsible for that meteoric growth? Artificial intelligence.
How AI enables sustainability
A fascinating study by Nature found that AI has the capacity to, both, drive sustainability as well as inhibit it. However, by their estimates, AI is more likely to drive change than inhibit it.
The UN has identified what it calls its Sustainable Development Goals (SDGs). These are 17 objectives in total, checkpoints of an ambitious plan, which the UN hopes to fulfill by 2030 in collaboration with private and public institutions worldwide.
Nature’s study grouped the 17 objectives into 3 categories, termed — Environment, Economy, and Social. Then, the researchers determined the percentage of sustainable targets AI could enable us to reach and the targets AI could inhibit, in each category.
The results, overall, were positive. The study found that AI could enable 93% of the targets under Environment; 72% of the targets under Economy; and 82% of the targets under Society. The rest are likely to be rather inhibited. (Why? We shall get to that later.)
As to what will fundamentally drive sustainability, what will enable us to reach the targets above, is believed to be AI’s extraordinary capacity for making extraordinarily accurate data-driven decisions.
In other words, optimal business solutions will lead to optimal use of resources.
Google, for example, uses AI-based mathematical models to track their resource usage. A Google unit that burns through massive amounts of energy is its multiple-acre wide data center, many of which are distributed across the globe.
And data centers quite literally burn. They produce a lot of heat energy. And so, Google uses the AI-based models to optimize the space and usage of their data centers, reducing the cost of cooling by more than 35%.
Of course, Google is not alone. Many companies are now relying on AI to design systems that are optimized for energy production and use. Xcel Energy is another private entity, a coal-reliant one at that, which relies on AI to monitor and optimize fuel consumption. And as the tracking and prediction capabilities of AI get more advanced, they become better at monitoring, analyzing, and optimizing resources, further increasing the efficiency of operating systems.
A self-driving vehicle is a great example. Not only will one run on renewable energy, but one will also optimize its routes, minimizing not only pollution but also congestion and hence, wastage of fuel.
Conservation of resources
Nearly half of the earth’s forests have been cut down for human use. While the best time to make change was 20 years ago, the second-best time is today. And AI is what will help us do so.
Carbon Tracker, for example, an ardent climate change advocate, collects volumes of diverse data with multiple satellites and processes and analyzes it with AI tools to optimize land use.
And, again, Carbon Tracker is not alone. Several companies are analyzing satellite data in real-time to monitor changes in land use and vegetation. An identical AI-based model has been used to track the population of different species. This knowledge can be used to identify poaching routes and inform policies that promote the welfare and conservation of animals.
And why just limit conservation efforts to land animals? AI could collect data from places we find hard to access. It could monitor deep ocean data to better understand the impact of water pollution on its animals and their habitat. The same technology could also yield actionable insights that guide efforts to undo those adverse effects.
Sustainability is for all.
Fighting air pollution
Everything is a source of meaningful data if you know what you are looking for. Even the air.
Not only has the adoption of AI made IBM’s weather forecasting 30% more accurate, but the AI also monitors and analyzes millions of data points in real-time to gain a systematic understanding of how carbon emissions pollute the air. AI-based models like these can be used by companies to design solutions that minimize carbon emissions. They help companies manage their plants more efficiently and responsibly.
Further, real-time air quality data could power simulations that could predict the consequences of dangerous changes in air pollution with incredible accuracy. Such an AI-based model could inform better city planning and regulations regarding greenhouse emissions. It could lead to the emergence of transportation that is green and responsible.
Improved disaster management
AI’s potent combination of creativity and computation goes well beyond predicting the weather. It could also offer insights into disaster management.
AI’s accurate weather forecasting could enable us to predict natural hazards as well. However, not only could AI enable us to make more accurate predictions of tremors, droughts, floods, and storms, but, as we have learned, it could also allow disaster management teams to deploy rescue resources more efficiently.
In such high-risk situations, AI could be of tremendous help to policymakers, who can reliably use AI to identify decisions that are optimized for minimum risk. But more crucially, this can be done with unprecedented speed.
The groundbreaking insights could also inform engineering decisions that shape architecture and infrastructure.
Challenges to AI-based sustainability
AI can save lives by reducing emissions and deforestation, developing green transportation, and predicting natural disasters. But it can also ruin lives by promoting authoritarianism, unethical surveillance, and optimizing resource allocation for profit instead of preservation.
What here ultimately separates democracy from autocracy, and equality from discrimination is the intent behind using artificial intelligence. While it is impossible to police thoughts, it is possible to regulate the use of AI. Yes, AI could ensure responsible growth, but before we ensure that we must first ensure that AI itself is used responsibly.
This is what inhibits AI from fulfilling Sustainable Development Goals. And to minimize these inhibitions, independent regulations must be established to govern the use of AI.
Pop culture, of course, is abundant with characterizations of misused power as well. As Ben Parker remarked, with great power comes great responsibility.