AI could help match you with your perfect dog
Many researchers have tried to develop reliable personality assessment tools for dogs.
Every person and every dog have a unique personality and were raised differently, so looking for a canine pet that suits you can be a tricky procedure. Knowing the general behavior of specific dog breeds is often misleading.
Can a scientific technique based on artificial intelligence (AI) serve as a helpful and accurate matchmaker?
Canine personality and behavioral characteristics have a significant influence on relationships between domestic dogs and humans as well as determining the suitability of dogs for specific working roles. As a result, many researchers have tried to develop reliable personality assessment tools for dogs. Most previous work has analyzed dogs’ behavioral patterns collected via questionnaires using traditional statistical analytic approaches. Artificial Intelligence has been widely and successfully used for predicting human personality types – but similar approaches have not been applied to data on canine personality.
A multi-disciplinary research team specializing in canine behavior and AI has developed an algorithm that automates the high-stakes process of evaluating the personalities of potential adopted dogs, including those that work for the police, the military, or to service dogs for the disabled/
The scientists, from the University of East London and University of Pennsylvania, conducted the research on behalf of their sponsor, a Miami, Florida-based canine-technology startup. They announced the dog-personality testing algorithm results in their paper, “An Artificial Intelligence Approach to Predicting Personality Types In Dogs,” just published in the prestigious journal Scientific Reports.
Canine personality/temperament plays a critical role in establishing and maintaining positive, functional relationships between humans and domestic dogs. Those canines that present undesirable temperament traits are at greatly increased risk of being euthanized during their lifetimes, the team wrote. Almost half of Americans who return dogs to animal shelters blame behavioral problems as a contributory factor, and a quarter cite them as the primary reason for giving their dog up.
In addition, many dogs suffer from chronic fears and anxiety states that may not necessarily result in relinquishment or euthanasia, but which undoubtedly impair the overall welfare of these animals. Important public health concerns also arise from canine personality traits.
The team members hope to help dog-training agencies more quickly and accurately assess which animals are likely to succeed long term in careers such as aiding law enforcement and assisting persons with disabilities. The personality test could also be used for dog-human matchmaking, helping shelters with proper placement, thus reducing the number of animals returned for not being a good fit with their adoptive families.
The AI algorithm draws on data from nearly 8,000 responses to the widely used Canine Behavioral Assessment & Research Questionnaire (C-BARQ) to train itself. For over 20 years, the 100-question C-BARQ survey has been the gold standard for evaluating potential working dogs.
“C-BARQ is highly effective, but many of its questions are also subjective,” said co-principal investigator (emerotis) Prof. James Serpell, an expert on ethics and animal welfare emeritus at the UPenn School of Veterinary Medicine. “By clustering data from thousands of surveys, we can adjust for outlying responses inherent to subjective survey questions in categories such as dog rivalry and stranger-directed fear.”
The research team’s experimental AI algorithm works in part by clustering the responses to C-BARQ questions into five main categories that ultimately shape the digital personality thumbprint a given dog receives. These personality types have been identified and described based on analysis of the most influential attributes in each one of the five categories and they include: “excitable/attached,” “anxious/fearful,” “aloof/predatory,” “reactive/assertive,” and “calm/agreeable.” The data points that feed into those ultimate clusters include behavioral attributes such as “excitable when the doorbell rings,” “aggression toward unfamiliar dogs visiting your home,” and “chases or would chase birds given the opportunity.”
Each attribute is given a “feature importance” value, which is essentially how much weight the attribute receives as the AI algorithm calculates a dog’s personality score. “It’s rather remarkable; these clusters are very meaningful and coherent,” Serpell said.
Dogvatar and its collaborating researchers intend to conduct further research into potential applications for their dog personality testing algorithm. “This has been a really exciting breakthrough for us,” said Dogvatar CEO “Alpha Pack Leader” Piya Pettigrew. “This algorithm could greatly improve efficiency in the working dog training and placement process, and could help reduce the number of companion dogs brought back to shelters for not being compatible. It’s a win for both dogs and the people they serve.”
According to the US Centers for Disease Control and Prevention and the US Humane Society, there are about 4.7 million dog bites every year in that country, and these bites result in an annual average of 16 fatalities.
According to the US Centers for Disease Control and Prevention and the US Humane Society, there are about 4.7 million dog bites every year in that country, and these bites result in an annual average of 16 fatalities.
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