Researchers at Harvard University and Stevens Institute of Technology developed an AI model to identify toxicity levels of byproducts that come from the process of disinfecting drinking water. The idea is that AI-enabled chemical detection can help enhance global safety standards, according to a new paper published Thursday.
Chemicals commonly used to disinfect water, including chlorine and chloramine, react with organic matter naturally found in water to create harmful byproducts, which have been linked to cancer and fetal development issues. Many are regulated by the US Environmental Protection Agency, but not all, according to the researchers, who trained a predictive machine learning model on the toxicity data of more than 200 chemicals. Using that data, the AI model predicted the dangers of more than 1,100 other byproducts, some of which had higher toxicity levels than chemicals which the EPA has set standards for.
The findings don’t mean that your average glass of tap water is unsafe, but additional research can help scientists and regulators gain a deeper understanding of potential dangers.