The Emerging Water Crises

One in three people in the world, according to the latest figures by UNICEF, do not have access to clean drinking water, while two out of three people do not have access to a basic handwashing facility. Moreover, 40% of the global population is affected by some form of the scarcity of water.  On the other hand, safe and hygienic management of sewage has become a big problem for many cities and countries of the world.

Forms of AI-based Solutions to Water Scarcity

AI-based solutions to water scarcity take the following forms: –

• Optimization of water use: For example, irrigation and industrial use of water involve a lot of complex decision-making, which can be solved through the use of appropriate AI technologies.
• Monitoring and maintenance of distribution systems: Monitoring of pipes, faucets, and outlets are very difficult on a large scale and requires a lot of dedicated human resource to do it successfully. However, an AI-based system can troubleshoot many of these problems in real-time. This can reduce significant amounts of water wastage at a large scale.
• Reducing uncertainty: It helps in predicting uncertainties, like the disruption of supply due to environmental or man-made hazards. They can also help in creating ethical distribution models in times of scarcity.

Emphasizing Responsible AI

A growing concern of data scientists and philosophers of science is around how AI as a discipline can potentially normalize the marginalization of different individuals in the name of efficiency. And as AI starts being used for essential services like water supply, the need to address these ethical issues becomes pertinent.

Within AI-based water management systems, several issues are being addressed in many ways. For example, one of the ways of doing this is to ingrain principles of fair distribution within the algorithms like equal distribution or minimum water access per household.

Secondly, using a multiplicity of data sources like GIS, and census, AI systems can understand and create indices of access, which acknowledges a larger set of variables for decision-making going beyond economic efficiency, making it socially responsible.