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How we have been using artificial intelligence to protect whales’ natural habitat
Team members Hartvig Johannson, Pedram Sherafat, and Simen Norrheim Larsen share the essentials behind their approach to innovation.
Using AI to help the planet
Behind great scientific innovations are teams of experts whose names don’t always make headline news. Yet their skills help forge the transformations that come to benefit the world. Their job is to build on the work of others, harness the power of all the knowledge and tools at their disposal, and apply it to solve a specific problem.
In this way, data scientists at Capgemini are using technological innovations to understand climate change better and to help create a sustainable future for life on Earth. One initiative that brings them together to look at how they can help create a better future is the Capgemini Global Data Science Challenge.
The team that won the 2020 competition developed a cutting-edge data solution that is set to play a part in protecting the future of an endangered species – sperm whales. Their work will help biologists map whale migration patterns and monitor any changes in the species’ behavior that might have arisen from environmental factors, such as climate change and warming ocean temperatures.
For the 2020 challenge, the Norway-based Capgemini team used Amazon Web Services (AWS), artificial intelligence (AI), and machine-learning technology to develop a tool that can accurately identify sperm whales via photo image processing. In turn, this will help scientists track the whales’ migration routes, look at the social structure of the sp
Capgemini team members Hartvig Johannson, Pedram Sherafat, and Simen Norrheim Larsen created a winning project that can deliver real-world impact, by applying tried-and-tested principles of innovation.
“When we came together as a team we all had experience in the field of AI and analytics as part of the same insights and data department at Capgemini,” says Hartvig. “Challenges like this are great opportunities to learn and apply that experience to practical, real-world use-cases. I’m also personally interested in nature and the environment, so it was exciting to see how we could use our computer science knowledge in a completely different area.”
The foundations for the team’s success were built on understanding the available data. “That begins with a scoping exercise,” explains Pedram. “It also helps to have a specific challenge. With ours, it was to identify the individual ‘fingerprints’ of sperm whales through images of their flukes, or tail fins. A defined challenge like this is where machine learning really shines.”
According to the team, tools and technology can sometimes be seen as a fix-all – but that is rarely the case. Instead, it is better to tightly define what you want the tech to achieve. “You can’t simply sprinkle some AI on top of a problem to expect a good outcome,” says Simen. “Any good modeling is built on the foundations of knowing the domain and what the technology is capable of.”
Finally, the team agrees that innovations often build on the work of others. “People have been identifying whales manually for years,” says Hartvig. “A lot of ground was already prepared, so we could come in and add a technical solution to build on that. It has been a great way to make the most of machine learning and AI.”
The scientist Isaac Newton famously said, “If I have seen further it is by standing on the shoulders of giants.” It seems that principle still holds true in today’s world of AI and machine-learning – in this case, to safeguard the future of whales. When passionate people and smart technology combine in clever ways, it can help our clients succeed their sustainability challenges – and deliver a better future for the planet at large.
Sarah Gonçalves wasn’t always a data engineer. She began her career as an archaeologist, unearthing the secrets of the past in sites across France before retraining as a data engineer. She brings the same curiosity to her new vocation at Capgemini, using artificial intelligence (AI) to uncover what lies beneath the surface.
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