Author:
A couple of years ago, Google AI for Social Good’s Bioacoustics team created a ML model that helps the scientific community detect the presence of humpback whale sounds using acoustic recordings. This tool, developed in partnership with the National Oceanic and Atmospheric Association, helps biologists study whale behaviors, patterns, population and potential human interactions.
We realized other researchers could use this model for their work, too — it could help them better understand the oceans and protect key biodiversity areas. We wanted to freely share this model, but struggled with a big dilemma: On one hand, it could help ocean scientists. On the other, though, we worried about whale poachers or other bad actors. What if they used our shared knowledge in a way we didn’t intend?
We decided to consult with experts in the field in order to help us responsibly open source this machine learning model. We worked with Google’s Responsible Innovation team to use our AI Principles — a guide to responsibly developing technology — to make a decision.
The team gave us the guidance we needed to open source a machine learning model that could be socially beneficial and was built and tested for safety, while also upholding high standards of scientific excellence for the marine biologists and researchers worldwide.
On Earth Day — and every day — putting the AI Principles into practice is important to the communities we serve, on land and in the sea.
Curious about diving deeper? You can use AI to explore thousands of hours of humpback whale songs and make your own discoveries with our Pattern Radio and see our collaboration with the National Oceanic and Atmospheric Association of the United States as well as our work with Fisheries and Oceans Canada (DFO) to apply machine learning to protect killer whales in the Salish Sea.