AI and the Blue Economy: Insights and Lessons from Jennifer LaPlante’s Making A Difference Speaker Series Talk
*Disclaimer: This article is AI-assisted. While AI has been used to fix the grammar and editing touches, the content is authentic and based on the ideas shared in the Brilliant Labs’ Making a Difference Speaker Series Talk
The deep and intricate connection between technology and the oceans is becoming increasingly important. Brilliant Labs’ Making a Difference Series recently featured a talk titled ‘Harnessing the Power of AI for a Sustainable Blue Economy’ that shared some exciting insights about how Artificial Intelligence (AI) is changing the game in the ocean sector. Speaker Jennifer LaPlante from Canada’s Ocean Supercluster introduced us to the awe-inspiring world of Artificial Intelligence (AI), further elaborating on the ocean’s crucial role in Canada and globally and the need for responsible AI use.
Before diving in, Jennifer began by asking everyone, “How do you feel today?” Just like we might be feeling happy, excited, tired, or even curious, every piece of information and emotion plays a role in the vast world of AI.
AI might sound complex, but we’ve already interacted with it in simple ways! Have you ever unlocked a phone with your face? That’s AI at work. However, AI’s abilities are limited to performing specific tasks. Unlike in the movies where AI seems to be portrayed as super AI taking over the world, in reality, we’re currently in the world of “narrow AI,” where machines can only perform specific tasks they’re designed for.
Just as you need ingredients to bake a cake, data is essential for creating AI. This data can take various forms, such as pictures, texts, numbers, or any type of information. For example, teaching AI to identify orcas (killer whales), requires a substantial amount of orca images for learning. However, authentic data must be used to effectively train AI in recognizing these images. Imagine being shown pictures of sharks and being told they’re dolphins; training AI resembles teaching a baby to recognize objects. We provide the AI with numerous examples (data) and assess its ability to recognize them independently. If it makes mistakes, we correct it until it improves. Additionally, AI requires a clear objective, similar to instructing your pet dog with “Fetch the ball” instead of just “Fetch.” In the case of our orca AI, the objective could be defined as “Identify orcas in the water.”
But AI can only be as good as the information it’s given. If the data is flawed or biased, the AI’s conclusions can be inaccurate or unfair. Imagine only showing AI pictures of cartoon Orcas and expecting them to recognize a real Orca! Every one of us is unique, as is the data fed to AI. For AI to be effective, it must understand and recognize the vast diversity in the data. It’s like appreciating that every snowflake is different. AI is fascinating, isn’t it?
But just like any tool, it’s neither good nor bad; it’s how we use it that matters. As we journey further, always think about the importance of accurate data, clear objectives, and the vast potential of AI.
Jennifer stressed the moral responsibility in using Artificial Intelligence. “The Big Nine” by Amy Webb spotlights the nine leading AI companies globally, with OpenAI, the creator of ChatGPT, being one of them. The G-mafia (mostly US-based) and China’s B.A.T. (Baidu, Alibaba, Tencent) are major players, controlling vast data from our emails, texts, and social media. While they develop powerful tools, they wield immense power. She pointed out the significant need for more diversity in these companies, with low representation from marginalized groups. The numbers tell the story: Google has only 4.1% Black employees, and Microsoft has 5.1%. Women make up just 26% of tech professionals. This lack of diversity risks embedding biases in AI systems that affect billions. Consider self-driving cars, for instance. Who gets to decide the value of a potential accident victim: a pedestrian or a passenger? This ethical dilemma represents just one of the numerous questions we confront.
Jennifer also emphasized the significance of the “blue economy.” The ocean’s economic value, especially in Canada, is immense. More than 80% of the products we use have travelled by sea. Notably, the ocean is the source of over 70% of oxygen, thanks to plankton’s vital role. Due to the planet’s warming climate, ocean patterns are shifting, affecting the migration and survival of marine species. Additionally, oceans absorb a substantial 50% of our carbon emissions, underlining the importance of preserving them.
Canada’s Ocean Supercluster initiative is dedicated to bolstering the country’s oceanic economy, focusing on various aspects, including ocean energy (such as wave buoys and tidal power), sustainable seafood, future transportation, and comprehensive climate solutions.
AI has the potential to revolutionize our understanding of oceans. For instance, companies like Cyan employ AI to study different kelp species, using abundant footage and labeled data to track changes in kelp biodiversity and health, thereby contributing to a broader comprehension of marine ecosystems. In the shipping industry, AI effectively streamlines processes, particularly in managing extensive shipping logs through the use of Natural Language Processing, enhancing efficiency for shipping companies and border security. Additionally, AI aids in predictive maintenance by sifting through extensive records for many marine vessels, preventing potential malfunctions. Moreover, AI plays a pivotal role in shipping and port management, with sensor-equipped buoys collecting critical data that AI algorithms can analyze to provide valuable insights benefiting various industries, from fisheries to shipping.
Jennifer delved into the complexities of our ocean systems, stressing the importance of accurate pattern predictions. Like other scientific fields, oceanic predictions rely on ample, robust data. Halifax, renowned for its sporadic hurricanes, serves as an ideal example. The unpredictability of these storms necessitates a wealth of multi-year data for precise forecasts. A comprehensive history of similar events is essential for understanding their patterns.
In the Bay of Fundy, tidal shifts occur dramatically, making it a hub for tidal energy research. One innovative method involves using an echo sounder towed behind a boat to ping the ocean floor and detect entities in the water column, primarily fish. However, challenges arise from interference caused by surface waves and air bubbles, complicating the task of extracting valuable data from the noise. Traditionally, this was a manual, tedious, and subjective process. Enter neural networks. By training these networks on historical data, the process of automating and streamlining data separation becomes more consistent and efficient.
Such technological advances aren’t limited to data filtering. A project in Dartmouth at the Center for Ocean Ventures (COVE) uses computer vision to observe mussels. These aquatic creatures, with their environmentally-responsive behaviors, potentially act as early indicators of water toxicity. By monitoring their opening and closing patterns, AI can detect anomalies faster than traditional sensors, aiding in quicker responses to potential hazards. Another integration of AI can be seen around hydrodams. While they represent a renewable energy source, they pose risks to migrating fish. In collaboration with Nova Scotia Power, Innovasea has developed a system using sonar and video data to detect, categorize, and count the fish, reducing the potential harm while maximizing the energy output.
However, it’s paramount to understand that AI, as powerful as it is, doesn’t operate in isolation. The way we use AI in oceanic research mirrors its application elsewhere: it’s about optimization, efficiency, and reducing human error. It’s crucial, though, to understand its scope and limitations. We currently exist in an era of narrow AI, where AI excels at specific tasks based on human-fed data. It’s about mimicking, not innovating. As we look towards the future, especially in the realm of ocean sciences, we must consider the ethical implications of AI. It is a tool that holds great potential but equally great risks if not employed responsibly. Transparency in its creation, application, and decision-making processes is key. This responsibility falls not just on developers, but on users and stakeholders too.
To ensure the oceans remain a vital, thriving and sustainable ecosystem, our strategies for exploration, research, and conservation need to be as dynamic and interconnected as the waters themselves. The fusion of artificial intelligence and oceanography provides a promising avenue, but like all tools, it requires wisdom in its use.
The talk illuminated many facets of AI’s role in marine sectors, from its vast potential to the ethical dilemmas it presents. The challenge, as always, is to harness this potential responsibly. The hope is that Canada, with its rich maritime heritage, can lead the charge in this endeavor. Expressing gratitude for such an enlightening discussion, the audience left with a renewed curiosity about the oceans, AI’s role in preserving them, and Canada’s unique position in this global narrative. The discussion concluded with thanks and the promise of further engagement.
Join us for the inaugural #BrilliantBlueChallenge and follow 39 youth teams from Atlantic Canada and around the world as they design and prototype sustainable tools or products for the Blue Economy. Don’t miss out — like and subscribe to stay updated on the #BrilliantBlueGeneration journey on Facebook. Stay tuned for details on how you can secure an invitation to this one-of-a-kind virtual ocean competition on December 16th.
Thank you to Brilliant Blue Challenge funders CanCode & The National Research Council Of Canada; Sponsors: Cooke Aquaculture, and InnovaSea ; Official Partners & Supporters Canadian Integrated Ocean Observing System (CIOOS), Marine Environmental Observation Prediction & Response Network (MEOPAR), Cloud & More; Endorsed by UN Ocean Decade; Media and Public Relations Partner amPR inc.
