David Jaw and his dog Hank, an Alaskan Malamute. (Photo courtesy of David Jaw)
Many people have a project for which they are attracted or consider themselves particularly good. As head of the data science department at Trupanion in Seattle, David Jaw’s projects are actually about pets.
Jaw, the latest Geek of the week from., Uses artificial intelligence and machine learning to automate pet insurance claims, streamlining the process and eliminating the worry of what is covered or no.
Born and raised in a suburb near Toronto, Jaw’s family moved to Albuquerque, N.M., at the age of 13. He stayed there at university, where he studied mechanical engineering, pursuing a childhood dream of designing planes and spacecraft.
« Two or three years after the undergraduate, I realized that my peers could take aerospace courses in less than half the time, with better quality than me, » said Jaw. « This relationship has been reversed for math and numerical calculation classes. I decided to focus on a path that came more naturally to me. «
Current artificial intelligence applications generally accomplish their task of formulating a recommendation. Imagine a time when we will have enough confidence in our models to allow physical action.
Jaw moved for a year or two after college, living on poker winnings.
« Poker started as a solution to a short-term problem, » said Jaw. « I worked 30 to 35 hours a week in a call center for the first half of my undergraduate years. My grades were zero and my social life was nonexistent. When one of my friends won $ 15,000 in an online poker tournament, I asked him for advice, read a few books, and quickly turned online poker into a constant source of income. «
Jaw made twice as much playing poker as he did at this call center, and he stayed with him during his 20 years. He even spent a year playing poker full time as an experience.
« The earnings were higher than a typical engineering job, but not by a margin large enough to compensate for the disadvantages of an irregular work schedule and lack of job satisfaction, » he said. declared. “No regrets, however. I came out of the experience with greater mental resilience and a group of lifelong friends. «
Graduating and beating people at a card game no longer did it for Jaw and he wanted something new when he moved to Seattle with his wife now. He turned his attention to data science and a job at Trupanion.
« It didn’t take long to notice the opportunity of machine learning to have a significant impact at Trupanion, » he said. « We have a strong culture around high fidelity information gathering and a great data warehouse team that runs on our principles every day. The barriers we face as a data science team are interesting and satisfying. We answer questions like “How do we replicate the thinking processes of our people?” Rather than “How do I access the data to get started?” ”
Learn more about this week’s Geek of the Week, David Jaw:
What are you doing and why are you doing it? I started and currently head the data science department at Trupanion.
Pet medical insurance has a relatively low adoption in our country (1%) compared to Europe and Australia (20% +). We believe this is due in part to the awkward claims process. Even if the pet owner has insurance, veterinary bills are paid in advance and bills are submitted for reimbursement. The average processing time is measured in weeks.
In April 2018, we rolled out a series of machine learning models that fully emulate the role of a claims adjuster. Each independent thought process that goes into human decision-making gets its own code repository and its own model endpoint. These modular models then feed an « aggregator » which merges all the relevant information into a final result.
Today, we automate 40% of claims submitted through our software at 99% accuracy and an average end-to-end execution time of 6 seconds. Pet owners can now settle complaints before leaving the reception desk. We have removed the need for policyholders to pay out of pocket, and we have removed the uncertainty of not knowing what is covered and what is not. Our claims team can now spend their time investigating complex and interesting situations that use their medical knowledge. Easy decisions are automated. No one has lost their job as a result of this change.
We believe that all animals should receive the best veterinary care. No pet owner should have to make treatment decisions taking into account the financial burden.
What is the most important thing people should know about your field? Most of us seem to overestimate the long term effects of machine learning (deadly sensitive AI) and underestimate the short and medium term benefits.
Current artificial intelligence applications generally accomplish their task of formulating a recommendation. Imagine a time when we will have enough confidence in our models to allow physical action. Rather than seeing a suggested link to a dinner recipe, you can go home to do the grocery shopping and have a meal cooked just to your liking. Rather than going to a clinic every year for a flu shot, it could be delivered by a flying needle robot just before an outbreak. Mental resources will be released to pursue areas of interest with deeper attention and dedication. Large-scale machine learning should be a force multiplier for our civilization.
Where do you find your inspiration? I come up with a lot of ideas about flights. I have trouble reading or watching movies without motion sickness and my brain starts to overdrive due to a false positive signal of being in danger. Unable to sleep or consume the media, all that remains is to take stock of my current position and consider the paths to follow.
What is the only technology without which you could not live and why? Not the sexiest technology, but my choice should be glasses. Life would be much less productive or enjoyable if I couldn’t read a book or screen more than a few inches away.
In the offices of Trupanion in Seattle. (Photo by David Jaw)
What does your workspace look like and why does it work for you? Our office in south Seattle hosts hundreds of dogs and cats at work every day. It is difficult to stay in a negative frame of mind when there is always a happy puppy or an animal-hungry kitten within walking distance.
Your best advice or tip for managing work and everyday life. (Help us, we need it.) I end up thinking about work all the time. I should be the one asking for advice here, not give it. Hah!
That said, I would be even worse if I did not make a considerable effort to lead a « balanced » life. My approach is to think about how time and energy are spent. I quantify the discretionary time and its distribution. I then evaluate the effect of the time spent in each category / effort with its first derivative. Using this model as a guide, I seek to align the time / energy allocation with my personal goals and values.
Mac, Windows or Linux? All! Windows for games, Mac for general purpose laptop. Linux for deploying ML models.
Kirk, Picard or Janeway? Can we extend it to any leader in a science fiction series? If so, I would choose Chrisjen Avasarala in “The Expanse”. Total badass. I love his willingness to sacrifice personal relationships for the sake of the greater good. “Earth must come first.”
Carrier, Time Machine or Invisibility Cloak? The invisibility cloak would be too sneaky for me. The time machine looks great, but I would be worried about accidentally causing something horrible, like the extinction of our species. I can’t think of a benefit that could balance this. The transporter wins through a disposal process. The downside is getting stuck or dying.
If someone gave me $ 1 million to start a startup, I … I would open a noodle shop. I love to make food and I would never get tired of iterating towards the perfect bowl.
I once stood in line for … Franklin Barbecue in Austin, Texas. Is it worth it.
Your models: My grandmother is the person I admire the most by a large margin. She went through incredibly difficult times, but never lost her temper. She knew she had to stay strong for those around her. Even though she didn’t have much herself, she went out of her way to help anyone who needed it. I’m not exaggerating when I say I’ve never seen her do anything selfish or immoral. It is a paragon of what we should all strive to be. It should also be noted that it is impossible to beat it in mahjong, unless it lets you win out of pity.
She was born and raised in the Chinese province of Sichuan. As the eldest daughter, it was her responsibility to take care of her younger siblings. As such, it did not have the luxury of a formal education. She left school at the age of 9 to help with the family farm and prepare meals. When the Communist Party came to power, she was in her early 20s with two baby girls. She correctly predicted that things would change dramatically if she stayed, so she uprooted her whole life and made the difficult journey to start over in Taiwan. Her sacrifice allowed her two daughters and her son to lead a happy and fulfilling life. She repeated this whole process when her children started having their own children. She again uprooted her life in Taiwan to move to Toronto where she helped raise all of her grandchildren. We all lead happy and fulfilling lives because of it.
She has been gone for nine years now, but she will always remain a strong motivation for my decision-making. “How can I be better to live in memory of my grandmother?” Is a question I often ask myself.
The biggest game in history Poker is my favorite game. Evidence-based decision making is rewarded and cognitive bias is punished.
Best gadget of all time: I wear a ring that measures sleep cycles. It should be helpful in composing an ideal sleep routine and improving overall health.
First computer: I convinced my parents to buy me a computer for homework in high school. I ended up playing « Starcraft » all day without remorse. I was a terrible son.
Current phone: Pixel 3.
Preferred application: Audible. Listening to audio books makes my long journey enjoyable.
Preferred cause:I love the concept of fairness and I support any cause that promotes it.
Most important technology of 2020: The proliferation of machine learning in recent years is due to open source tools (tensorflow, pandas, sklearn) and distributed computing as a service (AWS). Without these technologies, it would have been impossible for a small team like mine to do anything with impact.
Most important technology of 2022: The barrier to entry into AI usage is too high. It’s okay to know a lot of math or programming languages, but these hard-to-learn skills shouldn’t be a prerequisite for building good predictive models. Doctors, lawyers or any professional should be able to improve their decision making with machine learning. I hope our current position in AI is analogous to the early days of the adoption of personal computers, where users had to be familiar with command line execution. Once we reach the GUI operating system phase of analogy and the general population has access to these tools, we will start to see some really interesting applications.
Final advice for your fellow geekers: Approach your work with uncompromising integrity. Negative examples like dishonesty and acknowledgment of others’ work may seem beneficial in the short term, but I’m pretty sure it’s a trap. Humans are exceptional at passively detecting patterns; they will learn to avoid collaboration with bad actors even if they do not consciously know why. At best, the bad actor successfully removes the value from the system. More likely, the result will be a lower expected value for the actor and the system. Doing the right thing has the potential to inspire others to do the same, creating a positive feedback loop with unlimited benefits.
LinkedIn: David Jaw