When you think about artificial intelligence (AI), your mind probably jumps to self-driving cars, smart home assistants or even robots straight out of a sci-fi movie. But AI is quietly making a difference in places you might not expect, like the water you drink every day. Yes, AI is diving headfirst into the clean water game, and it’s making some serious waves. This timely and interesting topic came to us from EurekAlert! in their article, “Artificial intelligence helps produce clean water.”

Clean water is something a lot of us take for granted. Turn on the tap, fill up a glass and that’s it. But for millions of people worldwide, access to safe, clean water is still a huge challenge. Pollution, climate change and population growth are putting major pressure on water sources. So, how does AI fit into all this? Think of it like a super-smart lifeguard that’s always watching, analyzing and ready to act before things get out of hand.

AI can monitor water quality in real-time. Traditionally, testing water for pollutants or harmful bacteria involved physically collecting samples and sending them to a lab. Not exactly fast or efficient. But now, AI-powered sensors can be deployed in lakes, rivers and treatment plants to constantly track water quality. These sensors analyze tons of data—temperature, pH levels, contamination—flagging any signs of trouble before it becomes a full-blown crisis.

In parts of the world facing extreme drought, AI is stepping up to the plate, as well. Researchers are using machine learning algorithms to predict droughts and help farmers manage irrigation more effectively. AI can determine the exact amount of water crops need, reducing waste and conserving water in dry regions. This helps keep agriculture sustainable and communities hydrated.

AI’s impact on clean water is only just beginning. As technology improves and more data becomes available, AI could help us get even better at safeguarding this vital resource. The combination of AI’s processing power with smart water management might be the key to solving one of the world’s most pressing problems.

The biggest challenge is that most organizations have little knowledge on how AI systems make decisions and how to interpret AI and machine learning results. Explainable AI allows users to comprehend and trust the results and output created by machine learning algorithms. Explainable AI is used to describe an AI model, its expected impact and it potential biases.

Melody K. Smith

Data Harmony is an award-winning semantic suite that leverages explainable AI.

Sponsored by Access Innovations, uniquely positioned to help you in your AI journey.