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How AI Is Enabling Smarter, Scalable, Sustainable Water Solutions

What if artificial intelligence could be help solve some of the world’s most pressing social and environmental challenges, such as water access? That is what DataRobot is trying to enable through its AI For Good program.

When we hear about artificial intelligence (AI), many people often think of complex programs that process and analyze massive amounts of data and information for surveillance, financial engineering or defense. But what if AI could be used to solve some of the world’s most pressing social and environmental challenges, such as water access?

That is what DataRobot, an enterprise AI technology provider that works across several major global industries, is trying to enable through its AI for Good program, launched in July 2019.

“The program was designed to address many of the challenges that often arise with other data-for-good initiatives,” Chandler McCann, Head of AI for Good at DataRobot, told Sustainable Brands™. “We wanted to offer nonprofits more than a one-time event like a hackathon or a difficult to maintain custom-code solution.”

DataRobot’s program takes a unique approach, going beyond providing nonprofits access to their platform — providing six months of hands-on engagement and support to ensure organizations can best utilize these tools in their important program work, including helping develop nonprofit-specific platforms.

“Implementing an AI solution can be difficult,” McCann says. “We want to make sure that an organization that applies for this program has the capacity and support from leadership to make the project successful.”

The program aims to make the same AI technology used by large global corporations available to nonprofits. Current and previous partners include Kiva, DonorsChoose and Anacostia Rivershed. One of the early pilot partners of this program was Global Water Challenge — a global nonprofit that aims to provide safe drinking water, sanitation and hygiene education worldwide. It had previously participated in other data-for-good programs, but found the resources lacking.

As Katy Sill, Water Point Data Exchange Program Director at Global Water Challenge, told SB: “Some of the findings were quite interesting, but none really had the impact we were hoping for; and in most cases – since we did not have a team of data scientists – we couldn’t easily work with the code-based products that were developed.”

This wasn’t due to lack of need, but capacity. Water access and water quality are two major developmental challenges, and key components of the UN Sustainable Development Goals. Global Water Challenge knew that one of the main issues was the breakdown of water access points — hand pumps and taps that nearly one billion people around the world depend on for their daily water needs. They had data, but did not know how to use that data to better utilize limited resources and understand what’s driving these breakdowns.

For Global Water Challenge, DataRobot’s hands-on, collaborative approach provided nearly instant returns.

“With DataRobot ... we were able to upload the data from Water Point Data Exchange and build a model which provides key insights on the important questions we had been looking for,” Sill said.

The initial pilot, in Sierra Leone, has proved successful so far — and also enabled Global Water Challenge to better engage with the government.

“After these initial successful deployments, Sierra Leone’s Ministry of Water Resources worked with the Ministry of Finance to pass a national directive that requires the use of data in decisions about water services,” Sill explained. “The government is using the output from the platform to inform the planning process for repairs, maintenance and new construction of water points, impacting nearly two million citizens across the country.”

Sill hopes to take what they’ve developed for Sierra Leone and utilize it in other countries with water access challenges.

“There is a huge opportunity to improve water access around the world using this data and the models we built with DataRobot,” she says.

Meanwhile, DataRobot sees opportunities beyond water — including in health and access to finance. The potential is limitless; though it’ll be key to continue expanding the capabilities of nonprofits to utilize and integrate AI into their work.

“The focus of the AI for Good program extends to any major societal issue or global challenge,” McCann said. “It’s incredibly rewarding to work with nonprofits ... to deliver success with AI.”

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