October 13, 2024
How high performance sailing teams are using AI and machine learning to win the America's Cup
We've just seen the preliminary regatta for the Louis Vuitton Cup and a first glance of the America's Cup 75's (AC75) that have been designed, built and even race prepared using artificial intelligence (AI) and machine learning (ML). What can the banking fintech sector learn from sport?
If we look back to the highly successful America's Cup in Valencia (2007) the big noticeable shift to today is: Where have all the sailors gone? In just over 15 years we have seen a transformation from traditional sailing skills (navigator, strategist, trimmers, grinders, pit, mast bow) to just three key roles (cyclor, flight controller and pilot) and arguably if the rules allowed power to be stored via batteries, the cyclors would be made redundant.
Simulators in the America’s Cup have developed dramatically over the last decade with all teams using them. The rules dictate that the teams are only allowed to build one AC75 and there are also strict rules around the number of components they can build, such as foil wings. This is where the simulator can really help.
In the initial phase, the simulator can be used for exploring concepts and designs, but once the design is signed off, the “sim” can then be used for tactical and racing practice. In this era of the America's Cup it would be very hard to win without a simulator.
One of the big concerns for leaders is how AI will affect the productivity of their teams going forward and how best to develop the skills and capabilities of existing teams to meet those future demands. As AI and machine learning advance, it is clear that many automated jobs will go. The question facing us all is, How do we adapt?
In the last America’s Cup, the winning team, Emirates New Zealand switched from using Grinders (arms) to Cyclors (legs) to power their high speed catamaran. Their Cyclors not only produce more power to enable the manoeuvres, they also freed up their hands to do other jobs - and that was the key to their success. The onboard roles were better allocated which enabled the Pilot (Helm) and the Wing Trimmer to be much more efficient.
Leaders are grappling with how AI tools will shape their future workforce, balancing the need for increasing productivity whilst reducing costs. Regulation and control might be required to balance the skills shift that is inevitable to allow time for humans to adapt. But eventually, as we are seeing with climate change, if humans can’t adapt quickly they will be replaced by technologies that can.
Winning in turbulent times requires a leader to balance risk with good seamanship. In a storm, you might think it prudent to reduce sail early or navigate away from its path, but sometimes the storm might not be the real danger. It can be the aftermath of the storm where dangerous waves can capsize your yacht, or even the calm that follows the storm that can kill your performance and allow your competitors to make gains.
Empathy is a part of emotional intelligence and allows us to understand or feel what another person is experiencing or feeling within their frame of reference. Can you imagine an AI Teacher in front of a class full of neuro-divergent students being able to create an environment where everyone can learn at their own pace?
The interesting thing is if you ask Gemini or ChatGPT for some ways to support neuro-divergent learning, it will give you the toolkit. So why in the future, could we not programme it to learn and teach in this way?
Some of our biggest concerns with AI and machine learning are around so-called “bad actors” particularly in a world with so much trauma and conflict. Do the machines learn to do bad things? The “Hype” would have us believe that as “bad humans” we are incapable of preventing machines from learning to do bad things. What if the machines learn that we are the problem?
I’m an optimist and believe that most people deep down are decent. And if you need some historical evidence of this, read Humankind by Rutger Bregman. Rutger argues that if we look at science and our evolution, we are intrinsically kind natured and in a crisis we are often at our best.
So when we talk about human centric leadership, particularly in relation to sport, one element that is absent in machines is “gut feeling”. Simulators can enable us to rehearse different scenarios and outcomes over and over again, helping us to develop a play book. But there are certain human attributes that can help us over-ride the playbook and this is where gut feeling and intuition separate us from machines.
I describe sixth sense leadership as “a leader’s intuition to sense what is needed at the right time to ensure people thrive during uncertainty”
When you are building anything of human value at its core is “purpose” This is what we get “excited” about. It creates a sense of “belonging” and drives “performance”
If you are interested in learning more about Six Sense Leadership see the link
When leaders talk about the benefits of AI, they often refer to creating less friction in the system, or even frictionless. But friction is important. It creates heat, stickiness and perhaps most important, conversation. If we eliminate all friction, life becomes, well, easy, boring and simple.
We also might eliminate one vital learning tool, “feedback”
If there is no resistance, it’s hard to know how hard to pull
We won the BT Global Challenge because of Intelligent Data. It was the driver of our Human Performance.
On this 33,000 mile race around the world we logged our performance manually every 15 minutes and then using Excel, one of my crew who was a risk analyst from Rail Track built a simple performance model to show where the sail crossovers lay. We discovered that at 16 knots true wind, we were faster with our No2 genoa (sail) upwind - the original polars suggested that sail change should be at 18 knots true wind. The boat felt underpowered, but our VMG (speed towards our goal) was better. The numbers don’t lie. We used a data model to evaluate every aspect of our performance.
At the end of the race, I was asked what single thing I did that contributed to our crew success. After thinking for a minute, I reached into my pocket and pulled out my notebook. Inside, was a detailed account of every single crew member from the first day we met to the end of the race. I could recall how they performed during every training session, what they liked, what their kids' names were, who they most admired, who they least admired.
I knew what made them tick.
Performance sailing like every sport is data driven and that helps us make better decisions, but there will be times in the heat of the battle, when our human instincts will also serve us well.
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