A custom data platform and AI tools help UNEP plumb the depths of global water pollution
By Jennifer C. Clemente
With his furrowed brow and direct gaze, Sam pauses thoughtfully before answering a seemingly innocent question: “Why do you care about marine litter?”
“Good question. I care because the people who created me, the men and women of UNEP, IBM, Soul Machines and our member and state partners care about the oceans and our future. Solving the issue of marine litter is vital to the oceans and our planet.
“The real question to ask is: Do you care?”
It’s a provocative question—and all the more so because it’s coming from a virtual human.
Indeed, Sam is provocative by design, explains his creator, Richard Darden, a distinguished engineer and digital human evangelist at IBM. Sam’s sole purpose, when peering out from behind a computer or smartphone screen, is to help humans solve a problem they helped create.
With 8.8 million tons of plastic washing into the oceans annually, the United Nations Environmental Programme has been rallying marine experts, environmentalists, academics and citizen scientists worldwide to significantly reduce marine pollution by 2025.
Sam now joins their ranks.
Yet putting a responsive virtual human to work on behalf of the world’s oceans is just one way UNEP is looking to technology to stem the damage of plastic waste and marine litter on beaches and marine ecosystems.
“You cannot simply measure the plastic by going through the entire oceans of the world, nor can you have a camera capture every cleanup taking place on every single beach,” said IBM principal data scientist Kunal Sawarkar, who is working with UNEP. “This is where artificial intelligence comes to the rescue.”
Data, data everywhere, too much to sync
While it’s been observed that half the world’s plastics produced in the last 13 years can now be found in its waterways, only recent technological breakthroughs have given scientists the precise ability to trace and understand these and other aquatic maladies. Whether measuring coastal eutrophication—when mineral levels rise, causing excessive algal blooms—floating plastic debris density or the impact of a plastic bag ban in South Africa, data and AI are helping turn the tide of oceanic pollution.
UNEP began working with The Wilson Center, a Washington, D.C. think tank, to consolidate water pollution data as part of Earth Challenge 2020. But a critical metric for UNEP’s Sustainable Development Goal 14 reporting still needed to be extracted: The number of pieces of plastic per square kilometre.
One important source of such data comes from volunteers—UNEP calls them “citizen scientists”—who gather observations during beach cleanups and visits. But the quality, consistency and variety of such crowdsourced information can be more challenging than it is useful at times.
During the summer of 2020 Sawarkar and his team of IBM data scientists were selected to partner with UNEP to overcome the challenges inherent in citizen data and create a unified, global baseline dataset for measuring plastic pollution in line with Goal 14.
The IBM team deployed a suite of Watson data and AI tools, plus sophisticated model building, to conquer conditional datasets and other inconsistencies. This enabled new levels of analysis, and a pure baseline emerged.
“Data and technology, citizen science, local communities and the complementary value of global platforms can bring everything together to fill the gaps,” Dr. Anne Bowser, director of innovation at the Wilson Center and project lead, told Industrious.
Virtual humans, real-world problems
With an end-to-end AI lifecycle in place, scientists and policymakers could extract even more value from the Wilson Center’s datasets, whether to choreograph cleanups or predict a timeline for getting to zero pollution. IBM also created a custom digital dashboard to make the work easily accessible and sharable even for those without technical expertise.
These tools empower a UNEP stakeholder like Costa Rica to track its progress toward the nation’s aim of ridding itself of plastics entirely.
Yet UNEP leadership wanted to go even deeper into the data, to create a bond between the public and the issue of marine litter. To achieve this connection, the organization envisioned a digital avatar as the information go-to. And so Sam was born.
“Sam can emotionally connect with the users because he’s actually responsive,” explains Darden, the IBM digital human evangelist—who knows a thing or two about the sea, having earlier served as chief engineer on a US Navy nuclear submarine.
Sam’s emotive responses derive from Watson Assistant and Watson Speech to Text. These programs can interpret the intent of a user and then elaborate Sam’s reply by diving into UNEP’s vast repository and other sources.
That information is then filtered through a lifelike avatar built by Soul Machines, headquartered in San Francisco with R&D base in New Zealand, that makes what it calls “digital people.”
AI aids citizen science
Having discovered that AI can be a vital tool for measuring progress and influencing policy on marine plastics, UNEP is turning its attention to making data collection easier and more impactful.
Bowser and Sawarkar are exploring ways to use citizen science in UNEP’s reporting beyond beach cleanups, including with more sophisticated mobile apps featuring object detection and classification.
Based on the early success of her collaboration with IBM, Bowser thinks even more UNEP goals beyond No. 14 could also benefit from empowering citizen scientists with AI, such as goals No. 11 (sustainable communities), No. 12 (responsible production and consumption) and No. 13 (climate action).
“AI is a powerful ally for citizen science that can help local to global communities,” Bowser said. “We are just taking the first steps towards realizing this potential.”
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