Women Leading the AI Industry: “One of the first things that stands out is how much data we have at our fingertips”, with Caitlin Kontgis and Fotis Georgiadis
We’re in the midst of an AI revolution. One of the first things that stands out is how much data we have at our fingertips. For an AI engine to produce any meaningful results, there needs to be enough fuel. In this case, the fuel is data. From private and public satellites, to crowdsourcing and in situ sensors, the data is seemingly endless.
As part of my series about the women leading the Artificial Intelligence industry, I had the pleasure of interviewing Caitlin Kontgis. Caitlin is an applied scientist lead for Descartes Labs. In her role, Caitlin leads a team of data scientists who are leveraging AI to process satellite images and sensor data to create a digital twin of the earth. Caitlin joined Descartes Labs after completing her dissertation at the University of Wisconsin, which focused on remote sensing of urban and agricultural changes in southern Vietnam. Her work at Descartes applies the background in agronomy, remote sensing, and landscape change that she has been building since her undergraduate years at University of California, Santa Barbara. She is also an enthusiastic traveler, reader, and hiker.
Thank you so much for doing this with us, Caitlin! Can you share with us the ‘backstory” of how you decided to pursue this career path?
I first got interested in remote sensing as an undergraduate at UC Santa Barbara. Remember, this was before Google Earth, so looking at satellite imagery was really novel. My passion solidified when I traveled in my early 20’s after graduating. I went to Vietnam and was fascinated by its rice paddies and land cover change after economic reform.
As soon as I got home, I wrote a fellowship proposal to use machine learning and remote sensing to quantify urban growth and changes to rice paddy management. My thesis utilized satellite imagery, machine learning, and field-collected data to map and analyze trends in Vietnamese landscape change. While I was pursuing my PhD, I thought I would stay in academia post-grad, but stumbled upon Descartes Labs and was really impressed by the scale of what the company was doing.
Now, I lead the Applied Science team at Descartes Labs which leverages our geospatial analysis platform to create maps and models of the Earth using NASA, ESA, and commercial satellite data. We use machine-learning and computer vision to extract usable information to create actionable insights and images — basically, we’re creating a digital twin of the earth via cutting-edge technology
What lessons can others learn from your story?
I think the biggest takeaway is that inspiration can come from unexpected places. When I left for my trip in Vietnam, I certainly didn’t think it would evolve into a dissertation. But that trip was formative for my career.
In the same vein — be open to taking risks. I never imagined I’d be living in New Mexico (where Descartes Labs is headquartered). I never imagined I’d be working for a company with less than 15 people. But now New Mexico is home and our company has 115 people. The risks were well worth the pay off.
Lastly, continue to learn. You should always be challenged by your job!
Can you tell our readers about the most interesting projects you are working on now?
These days, I lead a team of about ten people, so I’m not in the weeds with as much technical work as I’d like to be. Not all of the projects I oversee leverage AI directly, but they’re all fascinating.
One project uses GOES-16 satellite imagery to detect wildfires. GOES-16 is a satellite that collects weather information, and we’ve engineered a way to detect wildfires and inform local agencies of any outbreaks. The information is collected and processed every five minutes, so we’re able to get near real-time responses.
Another project is focused on the density and spread of greenhouse gases. We’ve leveraged new data from Sentinel 5P, a satellite that monitors the atmosphere, to detect levels of methane across the globe. This could have a major impact on our understanding of climate change.
Recently, I was able to revisit my PhD work and traveled back to South East Asian to speak with farmers and gather data so I can map changes over the last 20 years. One of the best things about the technology that I’m working with is that there are so many different applications in countless fields.
What are the 5 things that most excite you about the AI industry? Why?
We’re in the midst of an AI revolution, so it’s hard to choose five. One of the first things that stands out is how much data we have at our fingertips. For an AI engine to produce any meaningful results, there needs to be enough fuel. In this case, the fuel is data. From private and public satellites, to crowdsourcing and in situ sensors, the data is seemingly endless.
Furthermore, we have more computing resources than we have historically so the opportunity to mine all these data is huge. In fact, our company just created the first-ever cloud-based supercomputer to make the TOP500’s fastest supercomputer list, a major breakthrough for democratizing access to supercomputers broadly.
I’m excited to see how AI will continue to evolve our understanding of the world around us. AI-based methods of analysis are new to so many different fields, like ecology, astronomy and meteorology, just to name a few. And we’re still in the early stages. New methods, data sources and computing power may unlock new insights that wouldn’t have been possible even ten years ago.
Specifically, there are several use cases I’m most excited about, like cancer detection, self-driving cars, monitoring crop health, mitigating climate change and helping environmental watchdog organizations by alerting when things like deforestation occur. My team is directly working on several of these use cases, so it’s thrilling to see the innovation as it occurs.
What are the 5 things that concern you about the AI industry? Why?
Whenever there’s uncharted territory, there’s cause for pause. The first concern I have is around defining and understanding what AI is. Because AI has become such a hot topic, many companies are doing what we call AI-washing — saying their tools leverage AI when in reality they don’t. It’s important that we all understand what AI is and what it does so we can effectively use it to solve the world’s problems.
Furthermore, AI often isn’t the right tool for a problem. But because it’s such a hot topic, many are trying to apply it to everything, instead of appropriate use cases. This could cause AI fatigue, or create negative perceptions about its efficacy.
Thirdly, AI is almost too easy to use today. An AI professional still needs a strong foundation in statistics to interpret results, understand inference and design a study. Without following the proper methodology for building and interpreting results, we risk working off of faulty insights which could have major consequences.
Right now AI is a black box for most. We know the data we use and we can see the results, but the mechanisms to get those results are often obscured. This can lead to inaccurate data or bias in algorithms that cause problems down the line.
Lastly, I’m concerned about the lack of diversity in the field. Women and people of color make up an exceptionally small percentage of the field. Without addressing these problems head on, we stand to build the same structural inequities that we’ve seen play out over history in our AI.
Can you advise what is needed to engage more women into the AI industry?
The first thing we need to do is encourage girls to pursue math and science starting at an early age. My parents encouraged me to pursue math and science classes and worked tirelessly to make sure I was set up for success. There are several programs and organizations tackling the issue, but it needs to be top of mind for everyone, especially parents and teachers.
Beyond encouraging women to join the field, there needs to be more role models for women. Ultimately, it’s our job to show women the path to success so they can fulfill their potential.
None of us are able to achieve success without some help along the way. Is there a particular person who you are grateful towards who helped get you to where you are? Can you share a story about that?
I’m grateful to my parents, who have supported me throughout my life, and, in particular, encouraged me to stick with my math and sciences classes after seeing I had a talent for it. When I was in elementary school, my dad would check over my math homework after I went to bed, then wake me up in the morning to go over any problems I got wrong with me. An earlier wake up call meant I did particularly poorly on that assignment, and a later wake up call meant I’d done pretty well. He’d sit with me, often while it was still dark out, and help me work through each problem until I understood it at a foundational level and could solve it myself. Obviously I’m biased, but I’m not sure most parents would have such a commitment to their kid’s education in math.
As you know, there are not that many women in your industry. Can you share 3 things that you would you advise to other women in the AI space to thrive?
This isn’t necessarily limited to women, nor to AI space, but I think to thrive anywhere, you need perseverance, humility, and a good sense of humor. Time and again, I have battled imposter syndrome or thought about dropping out of this field, but a stubbornness and perseverance has kept me on course. And though humility might not often be a trait associated with tech or the AI industry, I think it’s necessary to be open about what you don’t know if you’re going to keep learning and evolving in this space. Finally, AI is like weird science fiction come to life in some instances; it’s the stuff of Hollywood storylines, including C-3P0 and the Terminator. I think it’s good to have some fun with it.
How can our readers follow you on social media?
This was very inspiring. Thank you so much for joining us!
Women Leading the AI Industry: “One of the first things that stands out is how much data we have… was originally published in Authority Magazine on Medium, where people are continuing the conversation by highlighting and responding to this story.