Skip to Content
Artificial intelligence

The way whales communicate is closer to human language than we realized

A wave of new projects are taking us closer to understanding what whales are communicating to each other

sperm whales
Amanda Cotton/Project CETI

Sperm whales are fascinating creatures. They possess the biggest brain of any species, six times larger than a human’s, which scientists believe may have evolved to support intelligent, rational behavior. They’re highly social, capable of making decisions as a group, and they exhibit complex foraging behavior.  

But there’s also a lot we don’t know about them, including what they may be trying to say to one another when they communicate using a system of short bursts of clicks, known as codas. Now, new research published in Nature Communications today suggests that sperm whales’ communication is actually much more expressive and complicated than was previously thought. 

A team of researchers led by Pratyusha Sharma at MIT’s Computer Science and Artificial Intelligence Lab (CSAIL) working with Project CETI, a nonprofit focused on using AI to understand whales, used statistical models to analyze whale codas and managed to identify a structure to their language that’s similar to features of the complex vocalizations humans use. Their findings represent a tool future research could use to decipher not just the structure but the actual meaning of whale sounds.

The team analyzed recordings of 8,719 codas from around 60 whales collected by the Dominica Sperm Whale Project between 2005 and 2018, using a mix of algorithms for pattern recognition and classification. They found that the way the whales communicate was not random or simplistic, but structured depending on the context of their conversations. This allowed them to identify distinct vocalizations that hadn’t been previously picked up on.

Instead of relying on more complicated machine-learning techniques, the researchers chose to use classical analysis to approach an existing database with fresh eyes.

“We wanted to go with a simpler model that would already give us a basis for our hypothesis,” says Sharma.

“The nice thing about a statistics approach is that you do not have to train a model and it’s not a black box, and [the analyses are] easier to perform,”  says Felix Effenberger, a senior AI research advisor to the Earth Species Project, a nonprofit that’s researching how to decode non-human communication using AI. But he points out that machine learning is a great way to speed up the process of discovering patterns in a data set, so adopting such a method could be useful in the future.

a diver with the whale recording unit
DAN TCHERNOV/PROJECT CETI

The algorithms turned the clicks within the coda data into a new kind of data visualization the researchers call an exchange plot, revealing that some codas featured extra clicks. These extra clicks, combined with variations in the duration of their calls, appeared in interactions between multiple whales, which the researchers say suggests that codas can carry more information and possess a more complicated internal structure than we’d previously believed.

“One way to think about what we found is that people have previously been analyzing the sperm whale communication system as being like Egyptian hieroglyphics, but it’s actually like letters,” says Jacob Andreas, an associate professor at CSAIL who was involved with the project.

Although the team isn’t sure whether what it uncovered can be interpreted as the equivalent of the letters, tongue position, or sentences that go into human language, they are confident that there was a lot of internal similarity between the codas they analyzed, he says.

“This in turn allowed us to recognize that there were more kinds of codas, or more kinds of distinctions between codas, that whales are clearly capable of perceiving—[and] that people just hadn’t picked up on at all in this data.”

The team’s next step is to build language models of whale calls and to examine how those calls relate to different behaviors. They also plan to work on a more general system that could be used across species, says Sharma. Taking a communication system we know nothing about, working out how it encodes and transmits information, and slowly beginning to understand what’s being communicated could have many purposes beyond whales. “I think we’re just starting to understand some of these things,” she says. “We’re very much at the beginning, but we are slowly making our way through.”

Gaining an understanding of what animals are saying to each other is the primary motivation behind projects such as these. But if we ever hope to understand what whales are communicating, there’s a large obstacle in the way: the need for experiments to prove that such an attempt can actually work, says Caroline Casey, a researcher at UC Santa Cruz who has been studying elephant seals’ vocal communication for over a decade.

“There’s been a renewed interest since the advent of AI in decoding animal signals,” Casey says. “It’s very hard to demonstrate that a signal actually means to animals what humans think it means. This paper has described the subtle nuances of their acoustic structure very well, but taking that extra step to get to the meaning of a signal is very difficult to do.”

Deep Dive

Artificial intelligence

Sam Altman says helpful agents are poised to become AI’s killer function

Open AI’s CEO says we won’t need new hardware or lots more training data to get there.

Is robotics about to have its own ChatGPT moment?

Researchers are using generative AI and other techniques to teach robots new skills—including tasks they could perform in homes.

What’s next for generative video

OpenAI's Sora has raised the bar for AI moviemaking. Here are four things to bear in mind as we wrap our heads around what's coming.

An AI startup made a hyperrealistic deepfake of me that’s so good it’s scary

Synthesia's new technology is impressive but raises big questions about a world where we increasingly can’t tell what’s real.

Stay connected

Illustration by Rose Wong

Get the latest updates from
MIT Technology Review

Discover special offers, top stories, upcoming events, and more.

Thank you for submitting your email!

Explore more newsletters

It looks like something went wrong.

We’re having trouble saving your preferences. Try refreshing this page and updating them one more time. If you continue to get this message, reach out to us at customer-service@technologyreview.com with a list of newsletters you’d like to receive.