Can We Use AI to Communicate With Animals?
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Can We Use AI to Communicate With Animals?
These tools may not look like what some people imagine, but AI-powered human-animal communication could be possible. Research is already underway.
Language is complicated. There’s a lot of complexity and nuance to how people string words and sentences together, but AI systems have gained a fairly impressive grasp on it. Natural language processing (NLP) is everywhere today, from autocorrect to smart assistants like Siri to voice-to-text features, and some individuals wonder if similar technology could let them communicate with animals.
That task may seem impossible at first, but so did robot-human communication at one point. The world’s first chatbot emerged in 1966, and IBM’s Watson won “Jeopardy!” less than 50 years later. Technology grows exponentially, so it’s not outlandish to think that AI systems could eventually help people talk with animals.
These tools may not look like what some people imagine, but AI-powered human-animal communication could be possible. Research is already underway.
Why Is Understanding Animal Languages Important?
First things first, why would researchers want to communicate with animals? While the idea of talking to pets is a fun concept, most AI-powered creature communication projects serve a deeper purpose.
For instance, AI-based animal communication tools could help scientists learn how various species interact. That understanding could inform more effective practices to breed animals or conserve endangered species. Considering that roughly 65 species exist only in captivity or protected areas, any improvements in this field are important.
Similarly, declining communication skills is a pressing issue for some species. The regent honeyeater, a rare songbird in Australia, is starting to lose its song due to a lack of interaction with other honeyeaters in the wild. Scientists with the right tools could help ensure they don’t lose their natural communication signals, effectively teaching them their own language.
Understanding animal communication could also help gauge animals’ well-being. Farms could keep better track of how their livestock feel, and researchers could see if species in some areas are growing more stressed.
If farms notice cows experience more stress as the weather gets colder, it could suggest their barns need more insulation or heating. Researchers noticing rising tension levels in animals near growing cities could show how urban expansion affects them, prompting leaders to adjust policies as necessary. In all these cases, understanding animal communication provides helpful insight to better care for them in the wild and in captivity.
How AI Could Help Animals and Humans Communicate
Communicating with animals is an understandably complicated process. As a result, it could take complex technology to tackle this issue. The blossoming AI market, poised to be worth $320 billion by 2026, offers the technology needed for the job.
Up to this point, most of what’s known about how different species interact comes through observation. Researchers watch animals and observe repeated behavioral patterns and their surrounding actions and reactions. In a sense, this process mimics how machine learning processes work.
Understanding how animal “languages” work requires analyzing many interactions to recognize patterns. That happens to be the sort of task AI systems are skilled at. Consequently, machine learning could be better at picking up on subtle differences between signals that wouldn’t make a difference in human language but are critical to animal communication.
AI models could look at signals like calls and other physical signs to see if they often correspond with different moods and feelings. This communication could suggest meaning, like how a dog’s wagging tail can show excitement. It’s important to remember that correlation doesn’t always imply causation, but enough of it could suggest a relationship, prompting further research.
These models could also help determine how context changes this meaning. Consider how tail-wagging, though often considered a signal of happiness, can sometimes suggest aggression, as not all excitement is positive.
Early Examples of Animal Communication AI
Despite this field being relatively new, AI systems have already shown some success in analyzing animal communication. In 2017, one algorithm identified marmoset calls with 90% accuracy when matching one group’s sounds to known marmoset call types. The model achieved this by classifying the shape of their frequencies to distinguish between different sounds.
That same year, a different study used machine vision to estimate pain levels in sheep by analyzing their facial expressions. The model accurately identified these visual signals 67% of the time, which, although not perfect, rivals humans’ accuracy. The team behind the study also suggested that further research to refine the training procedure could boost its accuracy and allow its application to different animals’ expressions.
Some AI animal communication tools are already publicly available. The app MeowTalk claims to help people translate their cats’ meows. However, the algorithm relies on owners labeling recordings of their pets, so it requires a baseline understanding of each meow’s meaning.
Limits to AI Animal Communication
These early examples show promise, but AI-powered animal-human communication still faces several obstacles. One of the biggest is the lack of a measurable standard. People can’t be certain they understand how animal communication works, so it’s hard to judge whether AI is correct or not in this area.
Similarly, interspecies communication may be limited because animal communication likely looks different from human languages. NLP models today generally look at five language factors to determine meaning, but these categories may not even exist with animals.
Animals could also lack vocabulary entirely. Human language is sequential — sounds are combined in different ways to create practically limitless words with agreed-upon definitions, providing an expansive vocabulary that allows for varied and complex communication. Animal communication may lack that, with only a handful of base sounds that cannot be combined or adapted to create more complex meaning.
Even human translation and voice-to-text apps don’t actually understand language itself. That could pose translation problems between modes of communication that work entirely differently, stopping humans from talking with animals.
There’s also the issue of data availability. NLP models for human languages often require millions of words for basic language functions. Some species may not have that many communication signals. That aside, observing animal communication in context enough to make meaningful connections can be difficult, especially with endangered species.
Promising Advances
These issues are significant, but research shows potential for this field. Most notably, some algorithms have successfully resurrected dead languages like Ugaritic, a Semitic language that’s been extinct for thousands of years. Deciphering a communication system with limited current parallels also shows promise for human-animal communication.
These models work by taking a different approach to translation. The system looks for patterns of how words appear next to others and maps them in a complex web of relations. Looking at language in this multidimensional space helps overcome barriers where direct, word-to-word translations may not be applicable.
A similar approach could help understand animal communication, which likely doesn’t have a one-to-one translation to human language. Animal “languages” might be so different from ours that it’s impossible to divide sounds and signs into specific meanings, so AI tools must look at them outside of words’ scope.
Rethinking how AI models view communication could help these technologies overcome the human tendency to see things through unique contexts. The models likely must move away from translation tools as we know them. Direct translation is probably impossible, but these changes can get us closer to understanding animals.
AI Gets People Closer to Understanding Animals
Humans may never be able to have direct conversations with animals, thanks to stark differences in how humans and animals communicate. However, AI systems could help people understand animals better than we currently do.
If current research trends continue, AI tools in the future could help people get a better idea of what animals are saying and how they communicate. Researchers could use insights from these tools to protect endangered species and take better care of animals in captivity. There’s still much uncertainty in this field, but early signs look promising.
About the Author:
Zachary Amos is the features editor at Rehack Magazine. Zac writes on a plethora of topics including AI, cybersecurity, and smart homes. His work has been features in Hacker Noon, Unite.AI, and CyberTalk.