Original article was published on Artificial Intelligence on Medium
When Rachel Carson published Silent Spring in 1962, her expose of the devastating environmental impacts of certain pesticides became an instant best-seller. Carson spent over six years analyzing the data on chemical pesticides, and her conclusions told a powerful story about the destruction caused by pesticides: children falling sick, food chains poisoned, springtime without songbirds. Traditionally, scientists have tended to prefer to stick to facts and data, but Carson’s powerful storytelling led to Silent Spring’s enormous success — one that reached JFK and led to sweeping policy changes across the nation. For the first time, readers could easily understand the impact of the chemicals found in their food — and many were shocked at the destruction the chemical industry was causing. She’s now credited as one of the first leaders of the modern environmental movement, who popularized modern ecology.
I thought of Rachel Carson when I read “A.I. Is Helping Scientists Understand an Ocean’s Worth of Data” on how artificial intelligence is helping scientists understand the ocean better than ever before. Despite how important the ocean is to the earth’s ecosystem, we know more about the surface of the moon. But there are so many barriers to our understanding. It’s huge. It’s dark and deep. Scientists have spent decades collecting enormous amounts of ocean data, more than any one person could ever understand — and because marine animals move habitats, temperatures rise, and currents shift, much of the data we do have is incorrect. This is compounded by climate change, which is making urgent action more necessary than ever — while also changing the environment around us, making data inaccurate and even more difficult to act on. I’m reminded of an analogy from one of my Stanford professors, that managing fisheries is like “managing a forest, except all the trees are invisible and move.” Twenty percent of fishing is illegal, unreported or unregulated. Imagine if we didn’t know where 20% of our forests were — how could we protect them at all, let alone as fast as we need to?
This is where machine learning applications and A.I. can help. Without A.I., it would take far too long for us to parse through the literal ocean of data we have. But with better tools, we can draw insights that can be used to slow the damaging impacts of climate change on our oceans in time. We can follow endangered North Atlantic right whales, whose population has fallen to about 400. We can track fishing vessels’ positions and make their activities public. We can assess the levels of microplastics in our oceans. We can follow the lives of zooplankton to see how much carbon dioxide they can sequester. Along with scientists and engineers around the world, my team Tidal at X, the moonshot factory (formerly Google[x]) is using tools like A.I. to help us understand more about the ocean than ever before. We can use these insights to help protect the ocean and preserve its ability to support life and help feed humanity, sustainably. And we can use them to tell stories that inspire others — from world leaders to citizens — to act.
Environmental issues like climate change and ocean acidification seem so vast and complex. Each part of our ecosystem is interconnected in ways often mysterious to us. It’s hard to know where we can make a difference. I have hope — “hope, with a sense of urgency”, as a colleague put it — that A.I. can be a tool for powerful storytelling. And I hope that this new understanding will reignite a feeling of urgency, and push us towards drastically needed action. The ocean can’t speak to us, but thanks to A.I. we can follow Rachel Carson’s lead and tell its story. As we look to the future, I hope that we can use new tools to build a better planet, and protect our oceans.