“AI is a super fascinating field. The whole world is literally open for you to find problems to solve.”

 

Tony Zhou 
Hello, listeners. Welcome to our final episode of The Longitudes of Imagination series. Throughout the series, we’ve shared conversations with the leadership team of the Mayflower Autonomous Ship 400 project. I am Tony Zhou, a Longitude fellow at Yale University.

Jade McAdams 
And I’m Jade McAdams, a Longitude fellow at Rice University. We hope you’ve enjoyed this series as much as we have. In this episode, Tony and I will discuss a few highlights and topics that stood out to us.

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Tony
We started off with a conversation with Brett Phaenuf, who’s the co-director of the Mayflower 400, such a brilliant guy. We spoke a lot about AI ethics and his vision for the Mayflower 400. I think it is really interesting how his vision goes so much more than what is currently the Mayflower 400, because he hopes one day that this ship will traverse the seas, and if it finds something that it is curious about, it will look at the sample and send it back to scientists who would be on land so that they can explore and do more research on whatever the ship finds.

Jade
Yeah, I think that’s really cool. Because something you just mentioned is like what the ship is curious about. I think that’s a really interesting way to put it, because this whole project was really driven by Brett and Don’s curiosity about researching the ocean. And then they came up with this crazy concept to really take something that didn’t exist and push it to the boundaries and create a full deliverable. And now their goal for the ship is actually to be curious in and of itself. And I think that’s a really interesting way that human creativity is sparking creativity in a machine. And I also think it’s interesting because Brett’s creativity sparked Don’s creativity when it came to this project. There was that quote that Don said, where him and Brett are standing at the edge of a cliff. And Brett asks Don if he wants to jump off and then kind of just shoves Don off with him. And then Don has to create a roadmap from nothing, and really just go from no idea at all to creating a final product. And I think that’s something that engineers are actually really good at. So personally, I thought that was really cool. And I liked how Brett really has a vision for where this is going to go.

Tony
Where do you think Don gets his creativity and imagination?

Jade
I think Don mentioned that he gets a lot of his creativity and imagination from learning from his dad when he was a little kid. His dad was a geologist who used to dive down to the bottom of the sea to collect samples. So Don’s had this fascination with the ocean and ocean engineering. And him and Brett have been working on projects in the ocean engineering field for 30 years. So it’s interesting how people can draw creativity from a lot of different sources.

Tony
When I asked Brett the same thing about who he draws creativity and imagination from, or who his influences are, he also spoke about his parents. The things he actually talked about were how they instilled values of working hard and education. And so to me, when I think about that, I would think of someone who’s very rigorous when it comes to academics. But when you speak with Brett, he’s like, so out there with his ideas. But at the same time I think he thinks very methodically, kind of like how Don as well talked about. They both think in like first principles.

You had mentioned that engineers are really purpose driven, and they’re independent thinkers. And I think that really aligned with also what Don was saying, right? But at the same time, what is it with the stereotype that engineers aren’t really that creative?

Jade
Yeah, I mean, I think it’s an interesting thing, because engineers can be incredibly creative. But it does require them to be motivated and engaged in what they’re working on. For example, I’ve noticed in my own work at school, that a lot of times professors, for example, will give you a problem and an equation tell you to solve it. And while an engineer absolutely can do that, we don’t necessarily want to. We’d rather be given, like Don, this blank piece of paper, and a blank map, and told to figure out how to do it for ourselves. And I think that’s kind of what Carrie is saying has happened on this project. The engineers haven’t been given something specific and said, You have to do it this way. Instead, they’ve been given this really big goal, and told to figure out how to reach it. And I think that’s where engineer creativity really shines. And I think Jonathan actually makes a point to engage people from the very beginning of the story. And that brings in how engineers need to be brought in at the very base levels, because they need to be part of the people coming up with that problem solving process and taking it from point A all the way to point Z. If you just bring people in towards halfway through a project, or you know, when the Mayflower is actually successful, and accomplishing its voyage across the ocean, people aren’t going to be as engaged and motivated.

Tony
Yeah, that’s really interesting that you pointed that out. Alright, so if you had to pick between being that engineering mind, like Don, or that creative visionary, like, Brett, what would you pick?

Jade
I think that where I am right now would probably put me more at the engineering, hands on, creating all the steps, like where Don is, but I think that I’d like to work in my career towards being a more visionary person like Brett. Because I think when you create a vision, you can make so much happen and really expand the future of technology, and really utilize the skill sets of the people around you. If you’re creating a vision, you can bring anyone in and say, Hey, what do you think about this project? And I think that’s really fascinating.

Tony
Jonathan does the opposite, right? Like Jonathan is, he’s the one that injects that storytelling or that narrative into a project. And then when he spoke with Molly, he was like, I wish I learned more about coding. I wish I learned more technical stuff. And if I had to go back, I would probably be studying oceanography right now. So I don’t know, maybe it’s just humans, we think the grass is always greener on the other side.

Jade
Yeah, I mean, I think it’s a combination of that. And also the fact that to really be successful at anything, I feel like you need to know about a lot of different things. You can be an expert in one field and know almost everything there is to know in that field. But if you can’t make cross sectional relationships to other fields, or tie it back to why it would matter, then nobody is going to go deep into your research and really dig into that one specific point because they won’t understand it as well as you. So you need to be able to really show why your research matters across a variety of fields, and why what you’re creating is important. And I think that ties in to what a lot of our interviewees spoke about when they talked about being interdisciplinary and having various- I think Brett talks about really loving to read and being an avid reader at one point. And Jonathan talks about how he was a humanities major, and really had this great grasp of history and philosophy, but he wishes he could code. It all ties back to wishing that you can tie your knowledge in to the knowledge of another field.

Tony
Yeah, definitely, I think all of them come from such unique backgrounds. Brett identified as an anthropologist, and yet he’s working on the forefront of AI. Carrie started off in journalism, I believe. You know, she ended up working in corporate and managing people. And even Don, I think he draws from, like, I remember in his interview, he was saying one of his mentors worked on medical imaging, and that’s where he also got a bit of his ideas from, and so everyone draws from places all over, and then they channel that towards their own projects. Would you want to be someone of like, a lot of breadth? And just learn broadly? Or would you want to be that person on a team who knew like one thing, very solid.

Jade
I think that for me, I would want to be someone who has a breadth of knowledge, because I think you can always find an expert in a field but I think it’s sometimes harder to find someone to make connections for you. So I think being able to be the person that makes those connections across the field would be really cool to do. It’s interesting that you bring up how all these people draw from different resources and have different backgrounds. Because if you look at what they all want for the future of this ship, it kind of ties into that. They don’t want this project to be something that’s like a one and done. They don’t want it to be something that only makes an impact in the specific field of fully autonomous ships, going from the UK to the US collecting ocean research. They want this to be something that really has an impact across various fields and paves the way for augmented intelligence in, yes, the ocean industry, but also in other industries, and really just opens people’s eyes to what augmented or artificial—Don  likes to call it augmented so it doesn’t scare people—but what augmented intelligence can really do for the world as a whole. So what are your thoughts on either what you think AI can do in the future, or just what the interviewees think about AI?

Tony
I think the last interview we had, Andy, he spoke a lot about transferable tech, or  transferable skills, how he would want to apply all of the things that are successful for the Mayflower 400 to new projects. Brett also talked about it in his vision for it, and how he would want it to be implemented into cargo ships like that. That’s a huge thing. I remember he mentioned how there’s bias in ocean data because so much of it is unexplored, that the data we do have about the ocean is only the little parts of the sea that we do have data on. So he would want to apply that to all the unknown parts of the ocean.

And where do I think AI is gonna go? I mean, I think AI is eventually just going to be something that is like our cell phones, it’s going to be built or modeled in a way that will help us, that will improve our lives. At the same time, I think there’s also sort of, well, how Brett talked about this like fear towards AI, and I think Don also talked about it, because people don’t really understand exactly what’s going on. So it’s interesting, and as someone who is studying and learning about data science, machine learning, it’s a super fascinating field. And the whole world is literally open for you to find problems to solve. And I think that’s really interesting. And this is just such a good example of use case for AI.

Jade
Yeah, absolutely. AI is, I think, one of the best examples of imagination, creativity and technology, because like you said, it can be used for almost everything, but people are scared of it. And I think one of the things about imagination and creativity and innovation is that the unknown is always going to cause a little bit of fear. And people are always going to be hesitant to trust something that they don’t understand or that they’ve never seen before. But I think what makes the Mayflower project so fascinating, and such a good example of how to get people invested in something completely foreign to them, is that it really has brought people together. And they’ve been able to watch the story from the beginning all the way through. And the team has just been so open, for example, letting us interview them and telling us all their stories and things that they’ve been motivated by or been scared of during the process. They’ve been able to share that with people. And I think that makes the project so much more human, and makes AI so much more human, but not in the way that people are scared of. So I really enjoyed hearing about that on the project. And I think the future of AI is a fascinating realm.

Tony
Definitely.

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Jade
This brings us to the end of our episode in the Longitudes of Imagination series. Tune in next for our series on Space Technology.

Tony
Follow Longitude on Facebook, Instagram, and LinkedIn to make sure you don’t miss the release of the next Longitude Sound Bytes series. You can also visit our website longitude dot site, s-i-t-e, for more information and content.

 

“It’s almost like you can talk about the future of the entire planet through the Mayflower Autonomous Ship project.”

 

Molly Turner
At the intersection of ideas and action, this is Longitude Sound Bytes, where we bring innovative insights from around the world directly to you.

I’m Molly Turner, a Longitude fellow from the Juilliard School. In today’s episode, we will be featuring highlights from a conversation I led with Jonathan Batty, Chief Communications Officer of the Mayflower autonomous ship project. This is a project to build a fully autonomous AI-powered vessel that can cross the Atlantic. We explored this project for our Imagination series to learn about the individuals involved and the experiences that brought the project to fruition.

As an orchestral conductor, I was interested in Jonathan’s experience in content creation and storytelling, and how he brought to life the incredible story of the Mayflower Autonomous Ship, aka MAS 400. His role in media relations is quite a bit like the content and engagement offices at a symphony orchestra, both of their jobs being to distill and focus the technical jargon of a project so as to connect the project to the general public and establish relevance. In my case, the project is performance, and in his case, it is a technological feat of many people to build the ship. We started our conversation with his description of the MAS 400. 

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Jonathan Batty
So this is a very exciting and bold project to build a fully autonomous and crewless vessel that’s capable of crossing oceans and gathering vast amounts of biological and environmental data as it goes.

Molly
And how long have you been a part of MAS?

Jonathan
So I’ve been working on it for about two and a half years. I’m not on the technical team: my role is really focused on the storytelling in relation to the Mayflower autonomous ship, the publicity, communicating the goals of the project, public awareness, also building the web portal. I’ve been working with a team of people from IBM to build a web portal for the project, so really publicity and public engagement, that kind of thing.

Molly
Great. And I have a question early on, I don’t have a science background. Well, I was pre-med for one year, but that definitely doesn’t count.

Jonathan
That counts for something.

Molly
I was wondering if you could explain AI to a layperson?

Jonathan
Yeah. So it’s essentially a set of technologies enabling tech to operate in a similar way to the human brain, so much more automated, autonomous, learns as it goes, it gets better all the time. And it’s essentially it’s a tool to augment human capabilities and to enable humans to be the best at what they can be.

Molly
Were you part of the video series in any way on the website?

Jonathan
Yes.

Molly
Okay. That’s fantastic.

Jonathan
Yeah, no, we’ve done all kinds of content in relation to the Mayflower autonomous ship project, because it’s such a rich story. There’s so much potential. And over the years, since I started getting involved, we’ve tried our hand at all kinds of content. We’ve even done a podcast series ourselves. Not sure whether you’ve heard that, but there’s so much opportunity with this Mayflower autonomous ship product you can talk about, you know, science and technology, the relationship between humans and machines, the future of the world, future of the ocean…

Molly
A lot of topics!

Jonathan
…Big data. Yeah, absolutely, Yeah. Plastic pollution, marine mammals, global warming, ocean acidification. It’s almost like you can talk about the future of the entire planet through the Mayflower Autonomous Ship project, which is super cool. So that’s why I like it, and also that’s why we’ve been able to do so many different things and try our hands at different types of content. So the video series I think that you’re referring to is the IBM docuseries called The Uncharted about the Mayflower. That was an IBM project. And I was a member of that team. I’m actually based in the UK, which is where the ship is based, so I also have an important role being the man on the ground and the guy who, you know, can go and hang out with the team and kind of force them into doing video recordings and interviews and get up at the crack of dawn to do recording work documenting the ship as it goes on expeditions and stuff. So I’ve been quite fortunate in that sense to have a good location. And that’s also given me an important role on the project.

Molly
And is there an approach to how you come up with ideas and solutions to certain things, and how you interact with the MAS crew?

Jonathan
Yeah, I mean, look, the most striking thing about the Mayflower Autonomous Ship project, and the way we’ve gone about storytelling, is its honesty. It’s an extremely honest project. This is a bunch of people who really just have this shared dream, this common goal. They want to do something amazing, and they’re mostly scientists or technologists. There’s not really any sense of a marketing spin to the story with this from an IBM perspective. We were excited by the goals of this project, we wanted to help this marine research nonprofit, to do this incredible thing, because IBM is not in the shipping business. We don’t build ships, we don’t build cars, you know, we don’t have this kind of opportunity every day. So the people on this project were really just wanting to do it because they believed in the vision, and also because they wanted to have some fun, and they wanted to help build an autonomous ship. There’s a great deal of honesty to the motivation of the people involved. And there’s also a great deal of honesty in the way that we’ve done the storytelling. It’s not been engineered, it’s really just been giving a voice to the team, giving them a chance to talk, recording what they’re doing, asking them honest questions, and helping people understand, you know, what is it? What is it about? How does it work? How does the tech work? What do we hope to achieve? And also, what is the current status, because it’s a real, living, breathing project. So we’ve had a lot of people all over the world, from media to schoolchildren, to university students, to members of the private sector, the public sector, everyone wants to know, what’s going on with the share, what’s the current status? So we’ve had a certain responsibility to keep people updated and tell them what’s going on and where the ship is, and on the recent attempt to cross the Atlantic, which unfortunately wasn’t successful, we just tried to be as honest as possible about what was going on, where was this ship, what was broken, when’s it going to be repaired? When’s it going to be back in port? What’s next? So we built this web portal called MAS400.com, that’s M A S 400 dot com. And that’s a great example of very honest storytelling, because on there, you’ve got a whole portal dedicated to telling people about the ship, but also showing people where the ship is, its current position, the views through the cameras of the ship, information on the research projects, lots of live data about the vessel. So there’s a great deal of honesty there. I think from an IBM perspective, even though a lot of the technologies used on MAS are available on a commercial basis, that wasn’t the motivation for getting involved. This was not some kind of marketing sponsorship. It really was the case that our own people, our own engineers, our own scientists, they voted for this project with their feet, right? So they decided that we were going to work on it. And then the marketing and PR teams like myself, we joined later and we basically gave them a voice. There are some projects in companies where the marketing or PR team come in and sign some major agreements and put lots of money on the table, and then the technologists kind of have to play catch up and deliver on what’s been promised in the sponsorship agreement. This one was not like that. This one was really the case of a bunch of scientists and technologists on the ground wanting to do this thing. They did it in their own time. They did it as volunteers. At the beginning no one was getting paid for this work. It was just purely done.

Molly
When you say like, they just wanted to build a ship, you know, to cross the ocean, which seems pretty ridiculous. And that..

Jonathan
Yeah, it is. It’s a crazy idea. I mean, as you know, it’s named after the Mayflower, a vessel which brought pilgrims and other settlers from Plymouth, England, to Plymouth, Massachusetts, in the 17th century. And so, this whole story is about the relationship between England and a modern America, or Europe and modern America. So it’s a nice one for IBM to get involved in. It has lots of lots of synergies in terms of what IBM is and does. The ship is being built in Plymouth, England, but it’s all about the relationship between the UK and modern America as I mentioned. It’s got lots of different angles.

Molly
And it’s great to hear how marketing came into this picture, because it reminded me of the symphony orchestra. As a conductor, we choose works that we want to do. And they might not be super popular, they might be new pieces that we’re discovering. And then we show up to the marketing meeting, and they’re like, we can’t sell tickets for this. This is absurd, we’re not going to play this, you know, never heard of piece. And so it’s great to hear that the technical team had a crazy idea, and then you guys jumped on it, too. And it kind of snowballs, which doesn’t always- sometimes you kind of run into each other. So that was great.

Jonathan
That’s exactly it. That’s a great analogy. It is exactly the same thing. In your case, it’s your musicians who are finding these crazy pieces of music or crazy projects to work on. And then it’s taking it back to the orchestra. And in our case, it’s the scientists and the technologists who dug up this project and wanted to take on the challenge, and then took it back to the corporation for them to agree to. But the fact is, they were already working on it. So I’m not entirely sure that the IBM Corporation had a lot of choice. But I think IBM is great at that. It does enable its people, it does empower its people. I think to be to be fair to IBM, it’s been an unusual project for IBM. I think it’s made one or two people nervous over the years because it’s a relatively risky project. And we, the team building this, haven’t known whether it was going to be successful or not. So even though there’s no one on it, and the chance of anyone getting injured or killed is low, there is some element of reputational risk involved. To be fair to IBM, I think they’ve been very brave, and I think it’s a credit to them that they’ve gotten behind it and enabled their team to do what they want to do.

Molly
Well that’s fantastic. If you were starting out college now, what additional skills, courses, or other things—partying, not going to class—what kind of things would you integrate into your college experience knowing what you know now?

Jonathan
You mean for myself?

Molly
Yes, for yourself, if you were to kind of go back?

Jonathan
That’s a great question. So a few things. As I mentioned, I studied literature, so I also come from a humanities background. So I spent my university reading and criticizing books. But it was also a great subject for me because it’s a pretty all-encompassing subject. It covers philosophy, it covers history, covers society, and the arts as well. There’s lots built into literature. So I think I came out of that with a fairly grounded view of the world. But obviously now working in tech, I feel like if I had the chance to dedicate some years of study again, it probably would be to further my IT skills. Even though I have been working for a technology company for the past 20 years and know a lot about it, my practical skills are pretty limited. I can’t code. I think I’d love to love to know how to code, you know, at least at the basic level. And then the other thing I thought, I’ll be honest with you, is I do have this love for the ocean. And I’ve always had that. But since I’ve been working on the Mayflower Autonomous Ship project, I’ve discovered this whole area of oceanography and these brave people who spend huge amounts of time collecting data about the ocean, either on ships or sometimes diving under the water, and coming up with all kinds of technologies to help people to collect more data about the ocean. I think that’s a fascinating area. And if I could notch up another degree, it probably would be an oceanography right now.

Molly
You know how to drive a boat? Do you have interest in it?

Jonathan
A little bit. Yeah, I’ve always had a strong connection with the ocean, through boats, or swimming in it, or diving in it. I’m a qualified diver. I also wind surf. I am a really keen swimmer. So I have lots of ocean-related skills, but to be an oceanographer, I think, would be super cool. I’d like to do that if I had another chance.

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Molly
It’s really beautiful to me that this was a volunteer-driven project in its inception. People wanted MAS 400 to happen from their honest curiosity about the ocean. Jonathan uses this core value of honesty in his storytelling by being honest about the status of the ship, even when the most recent attempt to cross the Atlantic was unsuccessful. He wants people to feel involved and stay updated on the progress of the vessel. He also extends honesty in his visionary tone about the project’s potential world-changing discoveries. Even more, at the end of the interview, he talks about his personal love and connection to the ocean, and how he’s actually a qualified diver himself.

Moving forward in my own work, I can see that honesty truly speaks more than any other trait in storytelling. In my own storytelling through music, I can take cues from the MAS 400 and from Jonathan.

We hope you enjoyed today’s segment. You can learn more about the Mayflower Autonomous Ship on MAS400.com. Please feel free to share your thoughts over social media and visit Longitude.site for the episode transcript. Join us next time for more unique insights on Longitude Sound Bytes.

 

“It’s been the pure passion of fantastic teams, all working together, because of a very common focus.”

Can Erdogan
At the intersection of ideas and action, this is Longitude Sound Bytes, where we bring innovative insights from around the world directly to you.

My name is Can Erdogan, and I’m a Longitude fellow from Rice University. In today’s episode, we will be featuring highlights from a conversation I led with Dr. Andy Stanford Clark, chief technology officer at IBM UK. He’s also the technical leader of IBM’s team working on the Mayflower Autonomous Ship, which we explored for our imagination series to learn about the roles of individuals and the experiences that brought it to fruition.

The ocean covers more than 70% of Earth. Today, more than 80% of it remains unexplored. As an engineering student working at the cross section of statistics and data science, I was interested to hear about the technical challenges of creating an intricate marine vessel that could gather and process data for ocean research, using only an artificial intelligence based computer brain and not a ship captain. We started our conversation with Dr. Stanford Clark’s description of the Mayflower Autonomous Ship.

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Andy Stanford Clark
The Mayflower Autonomous Ship is a small ship that is about 15 meters (45 feet) long, six meters wide (by 18 feet). And it’s made of aluminum as a trimaran design that’s got two wings coming out the side of the main hull. And the main thing is there are no people on board, so it’s going to sail around the oceans captained by an AI captain, so some software-based IBM products for machine vision, optimization, and rules-based decision processing, which together form the brain of the AI captain.

And the purpose of the ship is to explore the oceans and have experiments on board that will improve our understanding of the impact of climate change on the ocean, and also the effect of pollution of the ocean from humans. And from that we plan to spend a long time at sea, gathering large amounts of data, and use that to change our understanding of this not very well understood, massive resource that’s 70% of the Earth’s surface.

Can
How long have you been a part of it? And what led you to become the technical leader of this project?

Andy
IBM has been involved for about five years when we, accidentally, one of my colleagues attended a conference where the designer of the ship was speaking about the physical design of the ship. And he went up to the speaker and said, How are you going to build the AI captain? And they said, We don’t really know yet. And so my colleague said IBM will help you. That’s how IBM was involved.

I’ve been involved for about the last two and a half years. Mainly when IBM officially announced our partnership with ProMare, which is a company that’s sponsoring the ship, it is funding it. So we came on board as the official technology partner, and that started a whole whirlwind of promotional activity and media interviews, podcasts, conference presentations, and … as it was in the run up to the launch of the ship. A lot more focus on the day-to-day requirements of how the different teams in IBM interacted with MSubs, which is a company that’s building the Mayflower Autonomous Ship. So I took the role as the technical lead from IBM, coordinating all of the activity, but also the media front, the media persona of IBM’s involvement with the Mayflower project, which is really, really exciting.

Can
Do you think IBM is going to continue this project to an extent that goes beyond what we have today? And where do you think- where do you see IBM’s involvement in the MAS 400 project in the next 5 to 10 years?

Andy
We’re involved in MAS 400 for a number of reasons, not only the sustainability in marine research and helping further the science of climate change, but really, we see this being the beginning of a new era of the marine industry.

400 years ago, the original Mayflower set out from Plymouth, UK to sail across the Atlantic to the US. So we really see this as the beginning of the next 400 of the marine industry, and challenge and innovation and exploration at sea.

And so a big part of this is that the AI Captain technology is highly transferable to other ships, from research ships as we find the MAS 400, through Navy ships and for the military, a lot of interest from them on autonomous ships and autonomous submarines, and also for cargo ships. And we’re already talking to quite a lot of large container companies about what the future of shipping will look like. You can imagine that ships will have far fewer people on board, and the actual navigation will be done by computer systems. You might even imagine a future where there’s a human captain on board and there’s a second pair of eyes and an AI Captain looking over their shoulder, saying oh, look out for that iceberg over there to avoid any nasty accidents. And you might- I have talked to some of the marine insurers like Lloyd’s of London, and they say that in the future, they might require a ship to have that kind of technology on board, just as our cars have to have ABS brakes and seat belts and airbags before we can get insurance. Ships might have to have similar equipment on board, the AI Captain, sort of guardian angel looking over their shoulder before it can set to sea. That’ll make the shipping industry a lot safer and a lot less expensive, particularly for research because it costs a huge amount to have a crew of 20 people and researchers out at sea for months on end, then you get a tiny amount of time working on the experiment because it takes a long time to get to and from the research site. And they have to eat food and drink water and get paid and go on vacation and they get sick, all these things, which costs a huge amount and reduces the efficiency of the trip, whereas the autonomous ship can just go out in the ocean, just stay out there for months on end. That’s where we see the value of this.

Can
What kind of outputs have you gathered so far with regards to advancements in marine science and research?

Andy
The original plan was that she’d set sail on the 16th of September 2020, the exact 400th anniversary of the original Mayflower setting sail, to traverse from Plymouth, UK to Plymouth, Massachusetts, following the same route. But because of COVID, the development, the building of the ship got delayed. So we had the naming ceremony on that date, but she was still not fully ready. The AI Captain wasn’t fully functional at that stage. So we did some trials around the UK, and she finally set off to the US on the 15th of June, this summer just gone. She got about four days into the mission, just got past the west, no, three days. It just got past the west tip of Ireland. So she was really facing the open ocean and a component broke in the generator exhaust system. There’s a really trivial mechanical part of pipe fractured so the exhaust gases were going into the wrong place. And it was polluting the generator and we wouldn’t have had enough power. Although MAS 400 is solar powered, she has a a biodiesel generator as a backup. And we couldn’t rely on getting enough energy from the sun to keep her going all the time. So it would have taken a very long time, months and months to get to America. So we decided to turn back and the AI Captain technology and all the IT systems on board were working absolutely flawlessly. It really gave us great confidence in the technology. So we spent the rest of the summer redesigning and replacing the generator system. She’ll be going out in local missions in the UK for the next few months, so we can make sure everything’s working properly in particular science experiments.

Because one thing we learned, your second part of your question, was the experiments work great on the workbench in the laboratory, but they don’t work so well when you put them in a salty environment and shake them out relentlessly inside the ship. So we have a number of adjustments to make to some of the experiments. We gathered some good data from the video cameras on board. And we also gathered some good data from the hydrophone, which is the underwater microphone listening out for whale and dolphin songs. And we found a really nice clip of dolphins swimming along with Mayflower on the second day. And we’ve identified the hydrophone clip from that same time. So we’re currently analyzing that to see if we can actually catch the clicks from the dolphins. We’ve got some other data as well from the hazard detection experiment, which looks at the camera images and uses a very clever system on a chip, so basically, a neural network on a chip to look at those visual images and look for recognized objects. So boats, people. So we are very positive. The current plan is to defer the next US attempt until next April, because we’ll run into the winter storms about November time. So we don’t want to head off into a big storm because there’s some pretty big waves out there. So next spring, we’ll be heading off back to the US with the current plan.

Can
I’m very impressed by the subtle technological complexity behind the project. That is not easy to see when you look at a regular ship. I have several technical questions for you.

Andy
My favorites!

Can
How many people do you have inside the technical team and what kind of programming languages do you use? How do you utilize mathematics into the programming of different neural networks? And what were some of the technological challenges that you had to tackle? And how did you tackle that? So I think this is three questions packaged as one question.

Andy
Okay, great question. So we have more than 100 people inside IBM working on the Mayflower project, in different aspects.

Can
That’s impressive.

Andy
Yeah, so not all of those are full-time, but very few of them are full-time, most of them are doing it because we love the project. So we’re just doing evenings and weekends, grabbing a bit of time here and there just to squeeze it in alongside our day jobs. But it’s probably 20 people, I think, working full time, officially as their day job. Most of those are working on the machine vision part of it. And it’s a lot of technology going into that, which is using deep learning. Trained it on labels, images or captioned images, we’ve got more than 2 million captioned images of things you might see at sea, which are being used to… so we’re training the model in the IBM cloud. And then we’re downloading the trained model into the ship itself. It’s an edge computing solution.

The other part of it is the rules-based decision system, which actually encodes the collision regulations, which is the “colregs,” as we call them, it’s the rules of the road for when you’re at sea, so that’s the rules you have to obey. And that’s been written not in a neural network, but in a rules-based system. So the nice thing about that, we get full explainability. So we can tell from looking at the logs exactly what set of preconditions the AI captain was experiencing from its sensors from the cameras, the radar, the AIS, and weather systems, all the different sensors.

In terms of programming languages, it is quite a mix. We’ve got a lot of Python, Java, a lot of C, some Ruby, and some Go. I think that’s pretty much everything, everything on board, because different people have developed different systems.

What else did you ask? Oh, some of the problems? Well, some of the biggest problems, interestingly, is how you disambiguate images in the cameras. So they can go to a camera, and it’s moving left and right and up and down. And the ship you’re looking at is moving left and right, and up and down. You’ve got two things that are moving left and right and up and down, it’s really easy to convince the computer or convince yourself that the entire picture is full of ships. But to convince yourself to just one ship there requires some really careful, first of all, image segmentation, but also data fusion from things like radar and AIS, saying, Well, it looks like there’s 20 ships in front of us. But actually the radar saying there is one, the AIS is clearly saying there is one. So let’s go with one shall we, and base our decisions around that.

And the other problem is the multi-ship problem. So collision regulations are really easy, very well defined when there’s just one ship. It is you and somebody else, who goes in front of who, who gives way to who, who slows down, who speeds up, how much space you have to give, that sort of thing. If you’ve got multiple ships in the picture, that becomes like a game of chess. You say, well, if I move, if I move out of the way of this one, I am moving into the path of this one, I can’t do that. Okay, so maybe I slow down a bit. Oh, no, cuz that means I cut off this guy behind me. Hmm. Maybe I just stop. Then you become a floating hazard. So all these things become really complicated as soon as there’s multiple players involved. And that’s really where the optimizer component of the AI captain comes in. It basically takes all possible future outcomes and says, okay, given the constraints I have, which is the best outcome? And the best outcome is kind of like a Maslow hierarchy of needs. The first rule is don’t hit anything. Okay? So number one rule. So all other things like, how you get to America, how you run the experiments, how you preserve power, how you make best use of the solar panels, how you head up into and all of those are secondary to not hit anything. So after that, those other things kick in as well, which is basically completing the mission.

Can
Wow, all of the technical complexity behind it sounds extremely challenging, but also extremely interesting as well. What kind of sensors do you use in order to be able to gather data for a combination of so many different experiments that you can try to pursue?

Andy
Yeah, so there’s two classes of sensors. One is the ones for the situational awareness for the AI Captain itself. So those are cameras, radar, the AIS and a little local weather station. And then whether they are dissenting from the Weather Company, which is the weather forecasting company that IBM owns, we process that in all the 15 minute weather forecasts in the Cloud. So we can basically tell Mayflower what weather it needs to know about to factor into its assessment of where it’s going to go next. So that’s the navigational stuff. Then for the experiments, each different experiment has its own set of sensors. So there is the hydrophone. There’s a sonar thing, which kind of points at the waves to see what- kind of assess the angle of the waves. There’s a chemical sensor, which assesses pH and salinity, and conductivity and temperature and stuff like that. Then we’ve got a really cool experiment, which is called Hypertaste, which is an electronic tongue, which came from IBM Research in Zurich. And that uses different ion sensors, trained with a neural network, rather like our own tongue. So there’s one for sweet, one for sour, one for bitter. So there isn’t a sense of … we don’t have a sensor in our mouth, orange juice, we just know that the combination of the activation of those different sensory areas in our tongue, we recognize that as orange juice. So in the Hypertaste, the rate of saturation of the different ion sensors tells us against the trained neural network model that that’s something, one of the chemicals we are looking out for. So we take in a small sample of water, run it through the Hypertaste system, it goes past through different ion sensors. We wait for a few seconds for it to saturate over time. We compare that against the machine learning model. We say, right, we sense this particular chemical that we’re looking for, and then we flush it through, flush it with clean water, get ready for the next one.

We also use the same sample, we take a photo with a very special microscope, and it’s like a 3D microscope that’s from the University of Plymouth. So it almost takes- a bit like a hologram image of the water. And that’s looking for microplastics. We’ve all seen photos of the big rafts of plastic bottles that are floating in the ocean. Microplastics is much scarier. This is where the plastic from the landfill has washed down the rivers into the water. And these are pieces of plastic that are smaller than you can see with the eye but can see with a microscope. Plankton eat those and then they get into our food chain. So when you eat a fish, then you’re eating plastic from microplastics in the water. What we don’t know is how bad that is as you get into the deep ocean because no one has ever measured it in the far, like, in the middle of the ocean. They’ve only measured it near the edges. So one of the experiments is to assess this microplastic density.

Can
I’m really surprised that IBM has developed so many different sensors. They have the tasting sensor, they have like this weather forecasting, I think IBM is producing technical products in a very diverse range of fields, it looks like.

Andy
That is one of the many amazing things about IBM. We operate in so many different industries, so many different countries.

Can
What do you think propels ideation and implementation? What drives the team behind this project that works voluntarily sometimes and gives up from their weekends or from the nights that they can have with their families and friends?

Andy
So I guess there’s two parts to it. One is, there’s a long list of technical objectives that need to be met. So you know, we’ve had technical teams working dimensions for a number of years to develop the core technology that goes on board the ship, everything from machine vision, to edge computing, to Internet of Things, to the decision system that drives it. All that stuff’s got to work in a disconnected world. So you can’t assume that you’ve got a high bandwidth data connection to the cloud, because we simply haven’t. So everything has to work with partial connectivity. So the real motivation for those teams has been that this is a really unusual project for a really unusual customer. It makes a great reference, a great showcase for our technology. And we think, well, if we can make it work on board a ship that is barely connected to the internet, then it’ll work in all sorts of other better connected situations and more reliable environments. So that was part of it.

But all the other people working it, it’s really been the pure passion of a fantastic team, we’ve been really lucky to work with amazing people at Promare and MSubs and MarineAI, also the IBM team all working together, because you’ve got a very common focus. And the idea was to get the Mayflower out into the sea, heading off for America in June. And everything was focused on that date. And all the things that had to come together, all the list of things that to be ticked off before we could go. Getting all the experiments online, working and calibrated, rapidly running out of time, people lining up to receive the data when it came in. And this is a very unusual situation. We don’t often do these kinds of moonshot type events, projects. And when we do, it really galvanizes people around it.

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Can
Today we had a deep dive into the challenges of creating Mayflower Autonomous Ship and the technical collaboration behind it. Hearing the story of a team who worked so selflessly to protect the oceans by implementing machine vision and edge computing into a marine research vessel was an eye-opening example of using technology to help our planet. But we don’t have to be programmers or statisticians to protect our Hydrosphere: we can start somewhere with simple steps. Ocean Explorer and filmmaker Jacques Cousteau says people protect what they love. So we can start by going out and exploring our oceans and learning how the hydrosphere keeps the world, and us, together.

We hope you enjoyed today’s segment. Please feel free to share your thoughts over social media and visit Longitude.site for the episode transcript. Join us next time for more unique insights on Longitude Sound Bytes.

 

“The Mayflower project represents, I would say, the best of IBM…but not just the best technology, the best of our people.”

 

Jaena Kim
At the intersection of ideas and action, this is Longitude Sound Bytes, where we bring innovative insights from around the world directly to you.

I’m Jaena Kim, Longitude Fellow from the University of Ottawa. Today’s episode features highlights from a conversation I shared with Carrie Bendzsa, the US Markets and Regional Communications Leader for IBM Americas.

Carrie is also a shipmate of the Mayflower Autonomous Ship’s IBM Marketing and Communications crew, aka The Mayflower, which we explored for our Imagination series to learn about the roles of individuals and their experiences that brought it to fruition.

As a law student, I was especially interested to hear about the communications-related logistics and teamwork behind launching a project as innovative and unpredictable as the Mayflower. But first, we started our conversation with how Carrie discovered her interest in English and journalism.

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Carrie Bendzsa
I always liked telling stories growing up, and writing. I couldn’t get enough of reading and writing. I got interested in journalism as a career option back in high school, really. I thought that would be a lot of fun, writing stories, going around the world. So I went to Carleton for journalism, did a double major in journalism and English. And when I came out, I ended up getting a job in public relations and communications with Corel Corporation. The PR managers who worked at Corel at that time, no one wanted to write press releases, so I ended up writing all the press releases for a year for everybody in the department. And I really got to know the company and work with the executives and the communications team. And it was fun. That sort of started my corporate comms career.

Jaena
Yeah, I see, just doing a quick Google search of your name, you’re always affiliated with- when IBM needs a spokesperson, I find that you’re always on the press release. Or there’s always something that you say, and it’s always so incredibly worded. And I wonder if in part, it comes from your journalism degree.

Carrie
I think that journalism degree really helped in communications. At Carleton especially, I mean, fantastic journalism program. They gave us the skills, I think, initially, to synthesize content, and get the content prepared in a way that a publication would want to see it. And that has helped on the reverse side, being in communications, understanding what journalists are looking for and their needs, and in trying to kind of meet in the middle with the corporate statements we do provide or the corporate materials we do provide, because at the end they’re trying to do a job and create a story. And I maybe have an old fashioned view of communications, but part of my view about communications is it’s our job to help them shape that story.

Jaena
Would you mind telling us a bit about your role as manager of US external communication? What are some of the responsibilities and what do you do on a day-to-day basis?

Carrie
Some of the responsibilities on a day to day would include a lot of reading and observing what’s going on in the market. Seeing if something is becoming an issue in one area or another, whether we want to pitch something there, whether we don’t. Reaching out to journalists, having coffee chats with journalists, working with my team, putting plans in place, looking ahead at the next couple of months, what campaign work we’ve got. IBM communications focuses on five different communications campaigns. All of our activity falls under AI, hybrid cloud, business growth, good tech, which would include our skills development and education initiatives, and then quantum innovation. I take a look at the materials that come from the corporate teams, and then see what would apply into our area of the market, which is US markets and regional communications. So we take a slice of the US where our top clients are headquartered in, where the largest number of our employees live and work as well, and we focus on those areas. So we pitch journalists, we write op eds, the whole gamut of external communication.

Jaena
How do you approach challenges or conflicts that arise within your team, because I can’t imagine it’s easy leading a big group of people.

Carrie
It isn’t, you know, everybody thinks they want to become a manager. And then they realize once they become a manager that it actually is tough. It requires work and investment in people. And it requires someone to actually care about the people you work with and want to help them grow and achieve success in their careers as well.

I became a manager at a very early age back in my career, I think I was 26 when I managed my first team. I was younger than everybody on the team that I managed. And that was, you know, when you’re 26 that’s… I felt awkward. There was a little bit of imposter syndrome there. You know, how can I at 26 manage people who are older than me. And I think just by being myself and being authentic and really genuinely interested in the people that I work with has helped along the way.

In terms of challenges, I’m a fairly laid back person. I really focus with my team on empowerment, because that’s how I like to work, making sure they’re empowered, they have what they need to do their jobs, and they can easily do their jobs. And having a fun environment too, from a team perspective. That said, there’s always challenges, whether that’s on the personnel side or whether that’s on the business side. And I learned a long time ago not to make too much of a fuss about challenges. You just have to step back, put yourself in someone else’s shoes, be willing to learn and to listen and to find a common solution to the challenge, and sometimes challenges become opportunities along the way. You can usually twist them and lead to a positive outcome.

Jaena
So you’re also part of the ProMare Mayflower Autonomous Ship project. There would be no ship without the technical crew of scientists, engineers, programmers, but without marketing communications, the world certainly wouldn’t know about the Mayflower as well we do. Especially I think the Uncharted episodes, they were so cinematic, it was like watching a mini Netflix episode, but also so informative, and learning not only about the technology, but the struggles and the success. Would you mind telling us how you got involved with the Mayflower project and what your role is?

Carrie
Sure. This is interesting because about two years ago- and this ties into my regional role. A part of what I do on the regional side is I look into the region’s places, like Atlanta, or Austin, Raleigh, and look for local stories that we can tie into. I was doing that. And I was looking at some content that our systems university had put in place in Atlanta. So I was going through the agenda of this systems university and there was this session on Mayflower Autonomous Ship, and I stopped at that. Well, that’s neat. So I went into the section, pulled it out. And at the time, IBM had just started getting involved with the group from a very focused area of our business, our systems team and hardware team were involved. So I started talking with the project lead, who was in France, and we got to talking. We got connected to the ProMare team, and built out a narrative or overview in our content and corporate storytelling team because I thought this story had a lot of potential. And the corporate team picked it up. And then the UK team, we had a chief storyteller, Jonathan Batty, over with UK team, he picked up the project and started to frame it out as we went along. So the Mayflower project represents, I would say, the best of IBM, because along the way  it has grown from what was maybe perceived as a system story. Now it’s an AI story. It’s a weather company story. It’s an edge computing story, and it showcases the best of our technology. But not just the best technology, the best of our people. Because what started as something that that might have been maybe just UK-US actually has people working on it from Poland, from Canada, from all around the world. There’s this group of people we have come together with who are like minded and passionate about the project and have built it that way.

Jaena
Did you have any interest or prior knowledge about ocean research? Or were you just like, I see potential, and it was just the right time at the right place?

Carrie
The right time at the right place. I saw the potential for the story to be more than it was, and to tell the story early. At first when I brought it up, we were met with a bit of resistance, I have to say, because people said, Well, let’s just wait till the ship makes its voyage. And then we’ll talk about it when it’s successful. But luckily, my colleague Jonathan was very like-minded and saw the potential and started to build a story from what this could be, the steps along the way and whatnot. So we both had the same thinking that this could be much more than just that “oh yes, we made the voyage” story, and added in research projects and all the different connections. The research team has just been fantastic. I think there’s great potential to do some real good for the world through the research that’s going to come out of this ship.

Jaena
That’s very exciting. So I’m currently a first year law student at the University of Ottawa. And I come from a music background, so I’m not really knowledgeable on the law yet, but it is my aim to learn, and a passion of mine is environmental law. And so the Mayflower project really resonates with me in terms of what it can do. So it really sounds like you kind of took a chance. You heard about the Mayflower, you saw its potential. And if you were met with resistance, you know, you still believed in that potential. And I think that’s really remarkable to hear, because a lot of people, including myself, nowadays are very risk-averse. If we don’t see something definitive, we tend to hesitate away from it. So is that something you draw from your past personal experience? Is this some philosophy you have for yourself?

Carrie
I think one of our executives said along the way—and I believe this—you learn from failure, right?  Some of the best learnings along the way come from failure. And if I think back about my life, some of my best life learning has come from where I failed, and then gotten up. And that’s how you build resilience, right? You get back on your feet, and you learn, and you adjust, and you keep moving forward. And this project was kind of like that as well. It was worth taking the risk. And there’s an attitude at IBM, with the people who got involved in the project, that the risk was worthwhile, that we could always overcome the risk by learning from a failure or a setback each step of the way. So that kind of spirit of innovation, I think really helped move the project along.

Jaena
I love that you mentioned innovation because I know you were the two-time recipient of the IBM Marketing and Communications Forward-Thinker award. So I think it’s safe to assume you know a little something about innovative thinking and good leadership practices. What is your approach to effective management? I know we talked briefly about, you let things become learning opportunities. But do you have any leadership philosophies that you truly believe in, that you’d like to share with up and coming professionals?

Carrie
I’ve been working really hard, I think, on the management side, to become a more inclusive leader. I think along the way, I recognize myself, in my early years of management, I had this idea about management that it was hard for me to trust people. So I would just do it myself and take on more work. And then as you grow and progress, you learn that you have to be able to trust your team, and empower them. And part of that empowering comes from delegating, and giving them things so they can feel like everyone’s contributing to the whole. So that’s kind of grown, I think, from back in the very early days of management. And you learn along the way that success doesn’t come from individuals, it does come from teams. I played sports, a lot of team sports, in high school and then beyond high school. And I have a set of girlfriends that still get together now who I played volleyball with for 20 years. From all being that connective tissue on a team sport team, you can take that same philosophy into the business world. And that is what makes a successful team is everybody’s doing their part. And you pull on everybody’s strengths. And everybody has different strengths that can contribute to that equation, and then progress together. And if you can get that right on a team, then you can do wonderful things.

Jaena
Great storytelling is very crucial, obviously, to catching the attention of readers, especially nowadays, when everything is so readily available online. I guess in terms of creativity, do you believe it’s innate, or it can be learned? And my second follow up question to that is how important do you think creativity is for the modern professional and students of today?

Carrie
I think creativity is critically important. And we need to actually build it in our schedules, because everybody’s busy and things are coming at you 24/7, which doesn’t leave a lot of time just to step back and take the thinking time that’s required to be creative. So you’ve got to give yourself that right. And if you can’t give yourself that, then build it into your schedule. I’m a big fan of what they call deep thinking and deep work without distraction, so that each day you carve out a portion of your schedule where you can actually get into something without having text messages and social media or emails, and put that all aside and actually go deep on a project or an initiative, I think you get better work that way. And the same with creativity. You’ve got to just allow yourself the space and the time to let your mind go and bring new thoughts, and meet with different people, and bring in different ideas to projects as well.

Jaena
Do you do any specific exercises that help nurture that creativity? I know you mentioned meeting new people.

Carrie
Meeting new people is a big part of it. Learning from people with different points of views is huge, right? Because you know, I’ve got my set of experiences, but if you can bring three or four other people together with a whole different set of experiences, it’s even better. You get to a better outcome. I like doing design thinking and going through the design thinking process and using that as kind of a backstop for a new project initiation or whatnot. I use sometimes tools like Mural, where you can do a whole bunch of sticky notes and just do mind mapping, and kind of think visually how things could come together. But usually the best creativity is when you can get a larger number of people contributing, and getting those thoughts together. It’s important to realize that I’m an introvert at heart, so I’m not the best in brainstorming sessions, yet everyone immediately goes to brainstorming, I think when you think, oh, let’s creatively brainstorm on something, that doesn’t always work for me. And as a manager, I have to be conscious, too, that the people on my team may be introverts, their best ideas may not come out in a brainstorming session like that. So we have to give everybody opportunity to contribute in whatever way they’re most comfortable with. And sometimes that means allowing for more time, so that those ideas can surface and people can bring them forward.

Jaena
That’s very surprising that you identify as an introvert at heart because, well, one, I would not be able to tell, but two, I feel like even my own personal experiences with the best managers were the ones that self identified as introverts. And so was there anything that you worked on conscientiously to break out of that shy shell and be able to partake and speak up?

Carrie
For me, I have to schedule time to give myself breaks, thinking breaks if you will. I have some days where I have back-to-back meetings, 14 meetings a day. I can’t have too many days like that. Consciously, I have to fix my schedule to address that and to make sure I always have enough energy to bring. Early on in my career, I used to get the constructive feedback that I was too quiet, because my voice is rather quiet. I won’t be the most aggressive person at the table in any room. I much prefer the kind of the smaller conversation, smaller group interaction. So I have had to work on that, and come to the table and make sure I actively participate and let my voice be heard. So that’s something I’ve worked on throughout, just to say something when you’ve got something to say and don’t hold back.

Jaena
Is there anything else that you would like to share with us or anything that you deem would be helpful?

Carrie
I think from my perspective, the key to success has always been being collaborative, being curious, and loving learning. Learning about new things, new people, new projects, new initiatives. I think if younger professionals can embrace that sense of continuous learning that they will be really successful in the workplace, in any workplace. It’s just that,  never lose the sense of curiosity. That’s critical for success.

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Jaena
Are you a young professional or postsecondary student that can relate to my worries of being the most perfect version of myself at all times? I’ve been tempted to invent time travel to jump forward into the future and bypass the journey getting there. That’s why I’m grateful Carrie highlighted for us today the importance of learning from failure. Getting back up when you fall down is more important than focusing on never falling down in the first place. The more we get back up, we’ll build resilience, grit—and both are invaluable tools to have on the pathways to one’s personal definition of success. Don’t forget to draw inspiration and learn from the people around you as Carrie reminds us too, and the power of collaboration. You can look to the Mayflower Autonomous Ship for exemplary teamwork.

I’ll definitely be taking Carrie’s sage advice with me into the hallways of law school.

We hope you enjoyed today’s segment. Please feel free to share your thoughts with us on our social media and visit Longitude.site for the episode transcript. Join us next time for more unique insights on Longitude Sound Bytes.

 

“Creating a physical representation of what used to be an idea.”

 

Jade McAdams
At the intersection of ideas and action, this is Longitude Sound Bytes, where we bring innovative insights from around the world directly to you.

​​I’m Jade McAdams, Longitude fellow from Rice University. In today’s episode we will be featuring highlights from a conversation I had with Don Scott, Chief Technology Officer of MarineAI and the Director of Engineering at Submergence Group LLC. He is also part of the Mayflower Autonomous Ship project, which we explored for our Imagination series to learn about the individuals involved and the experiences that turned an idea into reality.

As a mechanical engineer, I was interested to hear about Don’s experiences with the design aspects of the project and delve into the engineering mindset behind this AI ship. Being able to take an idea from the brainstorming phase all the way to a concrete product can be a difficult process, and I wanted to learn more about the hurdles that can arise and how they can be overcome.  We started our conversation with his description of the Mayflower Autonomous Ship project, otherwise known as MAS400.

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Don Scott
Basically, it’s a vehicle of exploration and discovery. The goal is to design and develop a completely autonomous vehicle—in other words, so nobody’s on board—to head out and explore the world’s oceans, collect scientific data about the ocean to increase our knowledge and understanding of this incredible resource that we have.

Jade
So can you talk a little bit about what your role as CTO entails?

Don
Sure, well, this particular project, a lot of the work that’s involved has been managing the teams and focusing our energies on how to develop these new and innovative capabilities. And the key for us is not just developing the ideas, but developing them so that they’ll work in the real world. So deployment. In a development cycle, you have conceptualization, R&D (research and development), and then finally deployment. We follow sort of an applied research and development approach where- we call it full contact engineering, where you’re not just sitting around doing thought experiments on how you would do something, you’re actually building something and putting it out into the environment, and seeing how it works and then improving on that. That’s mainly my job. My job is basically managing all of those different projects and keeping them focused on the direction we want to move in.

Jade
So following off of that, how do you come to know everything that you need to account for when you’re designing this brand new technology, essentially? And then make it happen? Can you go a little bit more in depth on the problem-solving process?

Don
Sure. Just to step back just a little bit first, though, I mean, we’re not just a couple of guys who were sitting around our living room and said, hey, let’s build an autonomous ship, right. My partner and I, we’ve been working together for about 30 years in ocean engineering, and for the last 15 building manned and unmanned submarines for various navies. We have a lot of experience in building these kinds of things. What we’re doing for Mayflower is really just sort of a natural extension of that. So I lost your original question, but it’s just sort of giving you background about how we got into this.

Jade
Yeah, no, you’re totally fine. That’s definitely important. I was just asking a little bit more about the problem-solving process, like ideating, for this?

Don
Yeah. It’s a tough question because we have a pretty clear understanding of where we want to go. What’s missing is the roadmap on how to how to get there. And I think that’s a big stumbling block for a lot of this type of development, like new innovative capability. You have this vague, sort of nebulous idea of what you think things should be and how it should act, but you really don’t know how to get there, right? And I think that stops a lot of people, and they don’t just make that first step. Okay, let’s really try to break this down into these little steps that we can accomplish. You know, there’s a saying, basically, if you’re trying to describe a project, if you can’t break it down into steps that take four or five hours, you don’t really understand what you’re doing. It’s the same on these larger scale projects, you know, the timeline’s not four or five hours, it’s like one or two weeks, right, or a month. So I think that’s what we do. And we have this expression, Done is better than perfect, right? That idea of actually getting something out on the water that works well enough and then building on that. And that actually also creates an energy too. I’m a big fan of not just creating a story of what you’re developing, but actually building the object itself, because it creates this growing energy amongst the people that are working on it to say, Oh, look, it’s out of the water. It’s doing something, it’s not working all that great, but it’s actually out there doing something, and now I really can have a tangible understanding of what I’m doing and when I’m working.

Jade
Yeah, that was an awesome answer. You said that sometimes done is better than perfect and that sometimes it’s better to just get something out there. So what would you say has been the biggest hurdle that you’ve had to overcome to get this ship on the water? Or a second part to this question, and you can answer both, would be something that you guys have had to sacrifice in the engineering of this project that you originally would have loved to have, but at some point, it just became impractical.

Don
When I say done is better than perfect, like, you do have to meet a threshold of goodness. So we’re there. The idea of things that we had to sacrifice, I guess, in the grand scheme, especially of defense-oriented ships, we’re a small company. Like the MarineAI side, we’re only about 10 people. And the MSubs side, which is our parent company, is about 70 people. We’re no Lockheed Martin or Electric Boat, right? So for us, budget is always a concern that we have to be sort of- an expectation that it’s going to take a little more time, because a lot of the people that are working on it are also working on other projects, right. So when we started doing this, there weren’t a lot of people doing it. There’s a lot more people doing it now. And so we have had to sacrifice- speed, let’s say, we’ve been able to be fairly quick and innovative, I know we can act quicker than some of the larger companies but what we can’t do is throw massive amounts of money and resources on a problem.

Jade
Right. I mean, budgets, open schedule, always go hand in hand. Trimmed down budget. The other two also have to be sacrificed a little bit.

Don
Yeah. Our engineers have been given a fair bit of agency in order to pursue their problems, not a lot of handholding. There are extra high expectations of performance, and some people are great with that, some people aren’t. You’re asking, like, things we’ve had to sacrifice and what were the biggest hurdles? To be honest, I think some of the biggest hurdles were regulatory. This is pretty disruptive technology in a fairly conservative environment. Like, the marine domain is not really known for its acceptance of change, right. But the issue you have is you have an established set of operators, master mariners, ship captains always operate a certain way, then you have the regulatory agencies, which are overseeing. I’m not trying to dismiss them at all, because their conservatism and resistance to change is well warranted, right, because an accident at sea means loss of life and major damages. So they’re naturally reticent for this type of technology to be introduced. They have these very significant safety concerns. That said, it creates a very difficult environment in order to introduce new technology. So the onus is on us to develop trust in the systems. So we do everything we can to develop trust, and it’s a difficult relationship to navigate for sure.

Jade
You know, you’re working to build trust with these regulatory agencies, and obviously you’re putting in place a project that is very innovative and new. So how do you navigate that field? What are the things you do to share your vision with someone who may not originally appreciate what you’re trying to do?

Don
Yeah, this is a kind of a classic “you’re afraid of what you don’t understand” type of scenario. So we’re very open about what we’re doing, very transparent. You know, these are sort of keywords when you’re talking about AI-based systems: transparency, explainability, trust, all these sort of things. And also approaching it as, how does it assist the industry. Where a lot of companies make the mistake, maybe they’ve done it with autonomous cars, when they first talked about it, like, we’re gonna have completely autonomous cars, you’re gonna be able to hop into this taxi and it’s going to, without a person, gonna drive you to the airport, right? They’re not saying that anymore. Now they’re saying, we’re not gonna have driverless cars, what we’re gonna have are- we’re not calling it artificial intelligence anymore. We’re calling it augmented intelligence, right. We’re gonna do all these things that are going to enhance your ability to operate safely. So that’s sort of where we are. The purpose of Mayflower is to develop the- it’s sort of like a forcing function, to develop the technology that can be introduced and used in the maritime industry to augment their capability. We call it sharing the cognitive burden, the computer vision and the collision avoidance, we call it collision regulations, recommendations, have all of that stuff working in the background because machines are very good at doing that and providing advice to the human who is now freed up to actually do what they’re better at, which is strategic navigation, things like that.

Jade
Just to paraphrase to make sure that I understand everything you’re saying, when it comes to getting people on board for something like this, a lot of it has to do with showing how it can benefit either them or other people further down the line. Where do you see the future of this project going? And how do you see, as people become more open to the idea of artificial or augmented intelligence, how far along do you see a project like the Mayflower going? And then how do you see it leading into new initiatives?

Don
Basically, creating a platform for ocean science and research, right, having an autonomous ship that could sail around the world’s oceans and collect data, creating this autonomous capability for ships. I think Mayflower is really in an interesting position. Because I think a lot of people are,  “scared of AI,” right? Like everyone watched the Terminator, and all that sort of stuff, and it’s never good when the machines “take over.” But I think you see Mayflower and it’s sort of like, Okay, this is an AI-based system, and look, it’s actually doing something good, right? It’s actually enhancing our lives, or we hope that it does, in this way. It’s essentially- we think of it as tech for good, right? It’s providing a platform for not only actually learning about the ocean, and the need for preservation, but it’s also engaging the public as well. It’s a platform. And so I think, in terms of the future, where Mayflower is positioned, it can be used almost as a demonstration that, like, it’s not all bad. AI can be used for good things.

Jade
Yeah. Going along with that, actually, what do you think people’s general biggest fears regarding AI are? And what would you say as an engineer, someone who’s actually making this happen, to rebut that?

Don
I think a lot of people’s concept of AI is informed by hyperbole, this idea of generalized AI. Do you know what I mean when I say general AI?

Jade
No, actually.

Don
Okay, so general AI is that idea of innate intelligence, the idea of which I think of as really human capability, which is making conceptual leaps, having one set of information and being able to transfer that to another situation. But it’s about the idea that, you know, if you have an AI system used to build pencils, that AI system isn’t going to take over the world. All it’s going to do is build a really good pencil, right? Like, it’s not going to be able to take all its knowledge about building pencils and all of a sudden take over the world. That is generalized AI, right, what we have is very limited. And AI is such a difficult term too. Like, it’s basically statistics. And we’re using neural networks and things like that to do things really quickly that we couldn’t do before. Technology probably did itself a disservice by adopting this word AI. And we tend to use the term “deep learning” and “machine learning.” It seems to not have the same reaction in the general public when we use those terms because it’s like, oh, okay, it’s not this AI system that’s going to take over, you’re just using machine learning and deep learning to perform tasks that are otherwise kind of mundane.

Jade
When did you first develop your interest in this field? And how have you taken that interest and ended up on this project in the first place?

Don
So my dad was a geology professor. He was diving down to the bottom of the ocean in deep sea submersibles. That really piqued my interest in this environment, in the ocean environment and working in that space. So I pretty much worked towards forging a career in the ocean environment. I worked down at Woods Hole, at the Woods Hole Oceanographic Institute, with the deep submergence lab guys, for a year between my second and third year university. And that pretty much solidified my interest in working in this space. I’ve always been focused on the R&D side of things, working on new things. I know myself well enough that I like working on new things all the time. I get kind of bogged down and bored if we sort of spend- I’m not a production guy, right. I don’t need to see the end of a project, much to the chagrin of some of my business partners. I like white paper design where you’re gonna have a blank piece of paper or a blank whiteboard behind you, and you have a concept, you have this idea of where we want to be. I find a lot of satisfaction in making that roadmap and carving away through all the clutter and actually realizing those concepts and making them happen and creating a physical representation of what used to be an idea and seeing that come to fruition.

Jade
How has your role changed from the beginning of the project in this conception, making that first roadmap, till now?

Don
So Brett, who is my partner in this, the guy that I’ve been working with for like 30 years, he was in the city of Plymouth at a meeting about Mayflower. And they were talking about how are they going to commemorate the anniversary. And someone suggested that they make a replica ship. And he said, well, that’s not a great idea. There are tons of replica ships, right? And he said, Well, we’ll build an autonomous ship. He got out of that meeting. And his first call was to me, and he said, Don,  can we build an autonomous ship that will sail across the Atlantic? I said, sure. So that was the concept. To actually make it happen, we went through- I went through a lot of fits and starts. Back to your question of how did it happen? Or how does it happen? I think it takes a really diverse group of people. So that’s why I think Brett and I are actually a really good partnership. He’s definitely the idea person. And then I’m the one who likes to take those ideas and pursue them and make them happen. Like, basically where we’re both sort of standing on the edge of the cliff. And he says, oh, wouldn’t it be a great idea to jump? I’ll say, yeah, sure, maybe. And then he basically pushes me off the cliff and then jumps right after me. I do see, that’s how our partnership works. And Mayflower is a really prime example of that. He had this idea, you know, this concept. It was in his head, and he was able to express it quite clearly but also motivate others to do that. It’s great to have an idea, but you need to build a team to actually make it happen. You need mechanical engineers, you need electrical engineers, you need software people and stuff like that. So we were lucky in that we already had the mechanical, electrical, software people, right? We just needed to focus them on a different project.

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Jade
To me, the most fascinating aspect of Don’s experience with the Mayflower Autonomous Ship project is that success at every phase seemed to tie back to developing a strong understanding of the end goal, in this case, creating an autonomous vehicle of exploration and discovery.

Whether he was breaking down this vast idea into feasible steps, focusing team members on a new vision, iterating on a less than perfect design attempt, or convincing others of the future benefits of augmented intelligence, taking the time to understand the unknown and share this understanding with those around him opened the doors for innovation.

As Don says, people fear what they don’t understand, and so taking a risk like that of the MAS400 requires being willing to work to discover what you don’t know, and then help educate others on the value of your ideas. As I graduate with my mechanical engineering degree, I plan to take these insights from my conversation with Don and use them to drive my own engineering design process.

We hope you enjoyed today’s segment. Please feel free to share your thoughts over social media and visit Longitude.site for the episode transcript.  Join us next time for more unique insights on Longitude Sound Bytes.

 

Tony Zhou
At the intersection of ideas and action, this is Longitude Sound Bytes, where we bring innovative insights from around the world directly to you.

Hello listeners! I’m Tony Zhou, a Longitude Fellow from Yale University. Today’s episode features part-2 of a conversation I shared with Brett Phaneuf.

Brett is the Co-Director of the Mayflower Autonomous Ship 400 project, and the founder and chief executive of Submergence Group LLC (in the US), and M Subs Ltd (in the UK). In addition, he is 1 of 3 founding board members of ProMare, a non-profit (501c3) organization that advocates for marine exploration around the globe.

In our second episode of this series, Brett and I discuss his vision for the Mayflower 400, his role models, and qualities students should develop as they enter the workforce. We start our conversation with Brett sharing unexpected surprises throughout the project, and his vision for the Mayflower 400.

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Tony
Where do you see this project going in terms of your vision for it, but then at the same time, the part B of that question is, along your journey right now, what’s one thing from this project that your team has accomplished that you didn’t expect to happen?

Brett Phaneuf
Where do I see it going? I’d like it not to break anymore, that will be good. But the ocean will see to it. So I’m not worried about that. It’s definitely going to be broken many, many times. And that’s okay. You know, I like the idea that it doesn’t have a goal. So yeah, we wanted to cross the Atlantic. And we will. But sometimes the goal is just to explore. So it doesn’t have to go some place specifically, maybe it follows a trend in the ocean, and maybe it just goes out and detects something unique, right? I’d like to get to the point in some years where we could deploy an AI on the Mayflower or something like it, where it could detect something unusual. Maybe it’s on a mission to go survey, to do what they call an Atlantic meridional transect. So right down the middle, the Atlantic, north to south. And it finds something unusual, and without needing to be told, maybe in concert with satellite support within distributed space-based AI systems—which is happening, right, with instantaneous access to the global corpus of knowledge about the item—the system itself could decide that that was really unique. Or say, what would my humans really like to know about this, and know that it should, within the context of the boundaries of its mission, make a judgment to deviate, to chase that data. Because it was discovering something new, truly unique. That would be my vision for it. I think it’s gonna take a long time. But I think it’s really an applied research project. And so that’s why we’re doing it the way we’re doing it.

And then what have I discovered within the context of this project, what has been the most unexpected thing?

Tony
Yeah.

Brett
Wow, well, it won’t be a technological thing. I guess if I had to pick one, it’s really- even though I understand how fast it moves, the speed at which computing power is advancing is staggering. Things we didn’t think we could do five years ago, we can do now, you know, in the palm of my hand. So that’s cool, but it’s not unexpected. I think the most unexpected thing about it has been how interested so many people have been. And I often say that it’s because nobody did anything last year and we just had happened to do something. I don’t know. But I guess the most unexpected thing out of it was that IBM has been brilliant. They’ve been fantastic to work with. They have really blown me away with their generosity, and we’ve had the great pleasure to work with a broad slice of that company and never meet a person that we didn’t like, that didn’t have a genuine and profound interest in what we were doing and what they did. And they said something really funny, they said that it’s quite odd that it took an unmanned vessel that has nobody on it, an AI based ship, to humanize AI. That’s the most unexpected thing, that this autonomous vessel, this sort of spaceship-looking boat is very humanizing. I got up in the middle of the night once, when it was going out to sea, you know, we’re like 400 miles offshore in the first attempt to cross, and I logged into the portal and there’s, like, 30,000 people logged in looking at the camera feed from the vessel. That’s been really unexpected. I’m really appreciative at the level of interest, but I’m still baffled by it.

Tony
What you just said, it really ties in how you said that even though you’re interested in tech, you value people. You value connecting with people, and to see this project and so many people become invested in it, I can only imagine that it’s super overwhelming.

Brett
It’s awesome. And they’re all fun and interesting and brilliant, you know, asking about the vessel. It does literally get overwhelming, so we have to post more to answer questions. But now we’ve built this chat bot that’s really super- hyper-sophisticated that can synthesize data across all the instrumentation on the ship, that can actually mine the data entries and synthesize a response. That’s awesome. That’s IBM. That’ll help us talk to people more. Yeah. And the whole thing that has really shocked me about this unmanned, autonomous AI project is the level of interest and the number of people, and then the fantastic people we have the pleasure to work with.

Tony
Oh, that’s a very unique response. I thought you were going to tell me one specific aspect of this project.

Brett
No, it is the people, that’s the best part. That’s why I’m more and more encouraged every day and less… I’m discouraged about a lot of things in the world, but this is one of these things, AI and this drive to augmented intelligence, I am more and more encouraged about the possibility that we’re not completely doomed every day that I work in this particular area.

Tony
Yeah.

Brett
I mean, it sounds crazy, but it’s true. And even people panicking about climate change, this is one of the fundamental things we could actually do to- not Mayflower per se, but this type of thing. This technology can actually help us get our arms around, you know, maybe it’s okay. Maybe there’s a lot we don’t know, maybe it’s not as bad as we think. Or maybe it is, but maybe we’ll also discover answers that we can’t even contemplate or formulate questions for right now that will help us.  So I’m on the side of science, and if these are the people I get to work with in this field, then I’m actually more hopeful.

Tony
Right. Again, relating to people along your path, who’s someone who’s been very influential in your life, where they’ve impacted you and how they’ve shaped how you think about the world.

Brett
That’s super easy. I can give you three people right off, I can give you four. Absolutely. That is super easy. So first and foremost, my mom and my dad, who worked hard every day of their life, who—I was the first person in my family to go to college, go to university—who believed profoundly in education, and really had strong moral centers and had extremely deep work ethics. We didn’t grow up with very much, we were quite poor, but there wasn’t a day that they didn’t put us first and work hard to improve our lives, and always valued education above all things, and always supported, for the most part, the choices I made and wanted the best for me. I can’t say enough about them. They were the absolute number one and two, the joint number one place.

And then in university, an absolutely brilliant and wonderful woman, Elizabeth Will, who was a scholar par excellence in Roman history and archaeology. And then later in life working in the Marine Sonic Technology company, when I left grad school to do some work in industry in underwater sonar imaging technology work with Marty Wilcox, who is probably the smartest person I’ve ever had the great pleasure to meet, and taught me more in the few years I worked for him than the entirety of my education to that point. And most importantly, beyond all other things, gave me the best example, beyond my parents, of putting your ego aside, and that being right and wrong were factual matters, not emotional matters.

Tony
That’s very profound. Very humble, I think. For people like myself, or young emerging professionals, what is the most important trait someone would need to embody to work at the intersection of AI?

Brett
Oh, that’s easy. And it is universal. We suffer broadly from a decision-making disorder in our society. We keep seeking consensus, we keep looking for somebody else to be in charge, and somebody else to be responsible. Innovation is not a consensus sport. I don’t mean that you don’t work with people, obviously, I’ve worked with hundreds of people that I respect. But all of those people that are successful have a common trait, which is that they’ll make a choice. And they’ll accept the responsibility that comes with that authority. And then they accept their failures and their successes with grace. So I think you need to bear in mind that the consequence of an incorrect decision is trivial universally, in almost all things. Because there were many, many billions of years when you didn’t exist, and there will be many, many billions of years when you don’t exist again. The part in the middle is extremely short. And if the choice you’re making will not lead to your death or somebody else’s, then I would submit to you that the consequence of not acting is significantly more dire than the consequence of making a choice that might be incorrect. Because in the end, you have that tiny amount of time. And while time isn’t the most important thing, because your life is finite, it absolutely is one of the primary qualities. So my advice to you is to make decisions and take chances and try things. It’s a trite answer, but so what if you make a mistake, everybody does. So what your business fails, fine, start another one. Take a job. Work with people you trust. But be the guy who will make the call. Be the guy who won’t be looking around like, well, whose responsibility is this? Yours! I strongly encourage people to be the guy in the room who puts his hand up and says, I’ll do it. Take a shot. You might get it wrong. Fine.

Tony
Yeah.

Brett
Don’t be the guy who didn’t do anything except think about doing something in the time you have.

Tony
That helps a lot. Someone could have just said, time, value time, or value discipline. It’s very nice to hear all of it enveloped.

Tony
So I read one of the articles that was published on you and you had a quote where you said, I want kids to be fearless and to have the determination to achieve. It’s about science and adventure and rekindling, a sense of wonder.

Brett
Yep, totally. Isn’t it a sad place if you think everything has already been discovered? Doesn’t it make the world sort of sad? Because it’s also not true.

Tony
Yeah, I think in the news maybe a week or two ago, it was saying how they found some planet, or something like that, that’s even closer to the sun. But then what we’ve been taught-

Brett
Yeah, what’s really weird is like, even our own planet, I mean, not a day goes by that we don’t find a new species of virus, bacteria, plankton, or bizarre new- what I guess they call extremophiles, organisms in the sea, right? Living in impossible places, living in impossible pressure, impossible depth, in things that are unimaginable. And someone might have the audacity to say that there’s no life on other planets in our solar system. Nonsense. We just haven’t figured out how to look. And we’re going to look more and more, and that’s really important. But we also need to look here more. There’s so much we don’t understand about the deep ocean, about those processes in the deep sea, we’re barely scratching the surface. You know, you go out in the ocean with a bucket, you pick up a bucket of water, you take it back to a laboratory, I guarantee you each and every bucket that everyone takes out, there’s something in there that no one has ever seen before. 

Tony
The Longitude of Imagination series provides its listeners an opportunity to learn how professionals in different sectors approach imagination, and how ideas turn into action for the good of humanity.

The Mayflower 400 would be the first fully autonomous vessel to sail across the Atlantic. A feat that would allow us to explore uncharted waters. Yet, it’s quite remarkable that Brett still feels overwhelmed by the huge following this project has attracted. From our interview, I see not only a deep thinker, but also someone who was raised to value hard-work and creative thinking by a supportive network of family and mentors. Pursuing big ideas requires courage — the courage to take risks and accountability for the decisions we make. Most importantly, the courage to fail gracefully and carry on the next day.

We hope you enjoyed today’s segment. Please feel free to share your thoughts over social media and in the comments, or write to us at podcast@longitude.site. We would love to hear from you.

Join us next time for more unique insights on Longitude Sound Bytes.

 

 

Tony Zhou
At the intersection of ideas and action, this is Longitude Sound Bytes, where we bring innovative insights from around the world directly to you.

Hello listeners! I’m Tony Zhou, a Longitude Fellow from Yale University. Today’s episode features highlights from a conversation I shared with Brett Phaneuf.

A serial entrepreneur who wears multiple hats, Brett is the Co-Director of the Mayflower Autonomous Ship 400 project, and the founder and chief executive of the Submergence Group LLC (in the US), and M Subs Ltd (in the UK). In addition, he is 1 of 3 founding board members of ProMare, a non-profit (501c3) organization that advocates for marine exploration around the globe.

In our first episode of the Imagination series, Brett and I discuss the inspiration for the Mayflower 400, his career path, and the ethical dilemma in data and AI governance. We start our conversation with Brett sharing the inception of the Mayflower 400.

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Brett Phaneuf
So Mayflower 400, what we call Mayflower Autonomous Ship or Mayflower 400, depending on who you are, or the MAS 400. My role in that is that I was sort of the chief instigator of nonsense and stupidity. I had the idea. I was in a meeting with folks here in Plymouth, UK, the city government, in 2016. And one of the things we were chit-chatting in the margins about was the coming 400th anniversary in 2020 how the city wanted to do something big, and then there was a proposal kicking around about building a replica. And I wasn’t particularly enthused, because first of all, there is a replica of the original Mayflower, the Mayflower 2, and that’s in Plymouth, Massachusetts. It was built in the UK, and sailed across in like ‘57 and was given to the people of the United States, so I said look, that’s been done. And also, you know, what do you get out of that? You get a 17th century ship. We shouldn’t be thinking about that. What we really should focus on is what the next 400 years of the maritime enterprise look like, right? And why is it important, and how do we speak to it? And maybe put ourselves in the mindset of, you know, it’s impossible to do but you could try at least, is over four hundred years from now when people look back at this moment, what is the thing we would do now that those people in the future would find inspirational? For me, that’s an autonomous vessel.

And it’s sort of an outgrowth of other work I do in the defense sector, building manned underwater vehicles and unmanned underwater vehicles for 25 years, and oceanographic and climatological research in grad school. It’s that, and also I grew up not far from Plymouth, Massachusetts, though now I live in Plymouth, England. I’ve got technological and oceanographic and historical facets to my personality, and I was already deeply interested in autonomy and AI. Even more from a philosophical perspective, how do we know what we know? Why are we alive, not epistemology, but more ontology? It’s sort of the roots of consciousness and how organic consciousness differs from so profoundly machine-based systems to analytical systems, whether that kind of general AI is possible. And those are kind of interesting philosophical arguments. In my business life, I’m more of an applied research guy. I had already gone down the path of practical applications, let’s build things that live out in the world that are autonomous and learn from them in a very practical way through meaningful interaction over time. So we decided to build the Mayflower Autonomous Ship in 2016. And we really focused the first four or five years of our work on building infrastructure to collect data.

So we said, you know, the AI is the hard part. We’ve got to start thinking about that. We have to have lots of data that we have to make into models. So we started setting up infrastructure, all around Plymouth Sound, at sea, on offshore structures, on small boats, vessels, collecting copious amounts of data, tagging data, and then being able to auto-label data, building engines to auto-label data based on our initial model structures. And we did that over… Well, it’s ongoing now, we are in year six of it.

At the same time we started talking about this vision of an autonomous ship, and how it would be useful, and that it’s sort of an end to end all-encompassing, multifaceted research program. So there’s the AI side of it, the machine learning side of it, the edge computing side of it. There’s the space side of it, where we have the space tech and communications and distribution of data through space-based assets, and tracking of the vehicle through space-based assets, and cooperative research with space-based assets looking at ocean health, meteorology, climatology. And then there’s the sort of oceanographic and meteorological component of the vessel. What’s in the water? What’s under the water? What’s the temperature? What’s the conductivity? What’s the fluorometry, the chlorophyll, the planktonic content, are there micro plastics? What’s the chemical composition? Where are their cetaceans and pinnipeds, and marine mammals, all these kinds of things that you want to find out, and then some meteorological data with two weather stations on it.

It took many years of talking to people and giving presentations about it, and through my nonprofit that was set up about 20 years ago, to get some base funding. And we did some crowd funding. And then IBM saw it and thought, hey, that’s super cool. So we stand on their technology platform, but they’ve helped us build our tools and systems right away, so we could practically deploy it.

And now just in the past three months, when we had our initial attempt to cross and it failed, and we brought it back, we’ve done refits now. We took the opportunity to change out the edge compute devices, and we’ve quadrupled the compute power on the edge in three months. Right. That kind of stuff is mind boggling.

Tony
Right. Right, right.

Brett
And so now we have lots of capability. And it’s all about how you apply that effectively to do a task. So it’s really kind of multifaceted. It’s interesting, then there are societal and philosophical questions about, what are people doing? Do we want robotic systems? And how do people interact with them? How do they interact with manned vessels? Do we need more of these? Do we need more man vessels? Is the AI that we’re building to navigate, is it something we want to put on man vessels to help people be safer? What does port infrastructure look like? What does international regulation look like for this kind of thing? Because it’s new.

Tony
All these questions that you’re still completing.

Brett
Yeah, we’ve got to figure it out. And so my answer was, while you want to push on all the soft spots, build something, right? Build a thumbtack that people step on and they’ll do something about it. And so we built a really lovely thumbtack. And it’s forcing people to engage, you know, the US Coast Guard, unbelievably forward, meaning being helpful. They said, well, we don’t have any regulations on this, so we’re going to take this opportunity to help figure out what they should be. The UK Coast Guard took a… there are no regulations on this, so you can’t do it and we’re gonna punish you if you try. But they are learning. They are coming along.

Tony
There’s a lot of ethical talk now and regulations for innovation with AI, and this is one of the prime examples. It’s really fascinating to just see it.

Brett
But what is ethical AI though? You know, I think about this a lot. I mean, it depends on what your perspective on AI is. I look at it this way, which is, it’s not artificial intelligence, because it’s not truly intelligent. It’s augmented intelligence. And so instead of thinking about it in terms of how it displaces people, you should think about it in terms of how it helps us be better people, right? It helps us be better people. And there’s myriad ways where this is true. So just as you would not want traffic in a major city managed by a person standing on a podium in the middle of an intersection waving their arms or manually changing colored placards. Traffic management’s a great example of incredibly sophisticated, ubiquitous automation and engineering that we live with all the time. Don’t even think about it, doesn’t bother you, you’re not thinking about any of that when you’re driving around the city. You look at the evolution of smart sensors in cars that do emergency braking, and lane keeping, and driver warning, and driver assistance. That’s a great example of an emerging technology that will become more ubiquitous and sophisticated, that helps us be better at all these things we want to do every day.

And we should use machine learning and AI systems to help us take those almost impenetrable masses of data that are beyond human comprehension temporarily, right, and reduce them to actionable information that can be integrated into the total corpus of knowledge about how our planet works. It’s using these technologies that helps us liberate a part of our intellect, which is so much more important than the ability to hold in your mind volumes of data. And that’s the insight, which is something computers don’t do. These are augmented intelligence.

So what are the jobs that people should be training for?

People are graduating university, I deal with this every day, trying to hire people graduating university every day, who their entire life were taught how to plug things into a program that will output an answer, but they don’t understand why the thing is as it is. All those formulas have been derived before, and so they get an answer. You know, one of my 60-year old engineers worked in the machine shop and worked in a foundry, and will look at the answer that comes up and goes, wait a minute that can’t be right, because I know that type of steel shouldn’t yield there, for example.

But we get a lot of people who come out with engineering degrees, advanced degrees, and they’re like, well, the answer is this. It is like, yes, but it’s clearly wrong. You have to go back and look at… because there’s no real understanding of even basic first principles.

Tony
This is super interesting.

Brett
It’s a real problem in society. And that’s actually the ethical dilemma with AI. That is the actual ethical dilemma that no one wants to talk about. It obviates the need for people to actually know things.

Tony
Yeah. I think that the need right now because, you know, in curriculums there are a lot of, let’s say like online things, boot camps or even national institutions that are popping up these degrees. You leave with people trained as data scientists, or machine learning engineers, and they learn how to plug and chug models in but they don’t understand the inner workings of the model so that they can question and understand.

Brett
Well, I’ll give you a great example. We built a submarine for a client, but for a military client. A very large defense corporation that considers itself beyond reproach was involved in analyzing the hypothetical performance of the vehicle. They had done a computational fluid dynamic and hydrodynamic analysis based on a model of the vehicle they created from our drawings, and told us that the turning radius was almost a mile, like 1.6 kilometers at flank speed. And they’re presenting this to the government and to us and how this was problematic. And, you know, obviously, we’re going to have to go back and do redesign. And I said, but it’s wrong. They said no, we’ve run this several times now and this is the best we could come up with. And I said, yeah, but I drive the submarine. The turning radius is like 100 meters.  I think you I think you have an extra zero, I think you’re off by an order of magnitude. And they said, no, that can’t be right. The model says this. I said, yeah, but are we really going to debate whether your model is more right than reality? Because reality wins every time. And what you should be saying is, that’s weird. We need to go back and figure out why there’s a flaw in the assumption that underpins this model. Because clearly, reality is right. They couldn’t say they were wrong. Because they probably spent half a million dollars making this model. And so this is a problem, not just from the education system, but all the way through industry now. I think that the real ethical dilemma in AI is not, is it going to displace people from work?

I think what displaces people from work is the fact that they don’t bother to educate themselves. And generally, we don’t bother to properly educate them in the things that truly matter. And we are wildly distracted as human beings. So the ethical dilemma will be; Is AI exacerbating that problem because it does too much for us? Or does AI actually help us be more insightful and creative by eliminating certain elements of our existence that we don’t need to devote as much thought to? And is probably the answer is probably both.

And I would say that that is no different than the emergence of any major technology over the past couple of centuries.

Tony
One of the questions that I had immediately as you were speaking is that your career, the way that you’ve spoken about it, the trajectory, it didn’t involve AI at first, right? It was just things that you were thinking about, you were doing things that you were also interested in. Yet at the same time, in speaking with you, you speak with such depth, and sort of philosophically about AI. Would you mind sharing how you put all your interests and curiosities and passions into one, to focus it?

Brett
I wouldn’t say I’m focused, I’d say that I’m like my own. So the really bizarre thing about all this is, I’m actually an anthropologist by training. I started off in physics. I ended up leaving university, going into the military, came out, studied classics and classical history, archaeology and anthropology. And that’s what my degree is in. I went back for a master’s in nautical and marine archaeology, and then moved to geophysics in oceanography and worked towards a PhD there, but never finished it, and ended up starting a research company, and kind of went out into various bizarre trajectories in the nonprofit world. And then in the defense contracting, and offshore oil and gas, and subsea research, and all sorts of things that afforded me the opportunity to do things that are profoundly expensive, that I could never afford to do, but try to learn new things about my environment. And along the way, having a background in anthropology was really, really useful in dealing with the culture of the military and business, and oil and gas and different kinds of places and things and people and little subcultures that have their own dynamic. I’m an anthropologist, so probably why I talk about things in a philosophical way is because I’m interested in people. I love technology, I’m really interested in that. So more and more of my interest in AI is around these really strange, almost slightly off, sort arguments about whether or not something is ethical, and they all feel like they missed the point. Like they’re striking a target slightly off center of the actual ethical argument, right?

Tony
Like you connect the dots, but the your conclusion ends up…

Brett
Yeah, you’re kind of hitting the second ring out, right? You’re not in the bull’s eye. And so I think I’m in the bullseye. Maybe that’s narcissistic, but I sort of see it that way. But it’s- I read a lot. And I’ve had the pleasure and the privilege in my life to be able to read as part of my education and my job, sort of a really broad range of historical and philosophical and archaeological and technological and political and fiction, you know what I mean? I still do, and lately, all that reading, along with the work I do to put food on the table, and the Mayflower project, just had dredged up this interest in all the little disparate parts of my life that sort of- now I say, oh, well, I can see how I got here now, because I’m looking back.

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Tony
The Longitudes of Imagination series serves as an opportunity for its listeners to learn how professionals in different sectors approach imagination, and how ideas turn into action for the good of humanity.

As the Mayflower 400 project continues to grow, Brett and the teams at Promare and IBM will need to continually address both technical and social concerns of artificial intelligence and its use cases. From building efficient data pipelines to an autonomous ship that can survive whatever it may encounter at sea. Brett and the Mayflower 400 team will not only be involved in improving the ship’s capabilities, but also have active voices in shaping new regulations and policies in autonomous AI and ocean research.

When Brett credited his imagination and thoughts on AI towards its non-traditional and diverse education, it really resonated with me as I often find many parallels between learning data science and classical music. It is inspiring to see how Brett, who is an anthropologist by training draw from his studies in physics, classical history, archeology and oceanography for the Mayflower 400. After our conversation, I agree that the domain knowledge is perhaps the most important skill needed to contribute towards a project of this size and scope.

We hope you enjoyed today’s segment. Please feel free to share your thoughts over social media and in the comments, or write to us at podcast@longitude.site. We would love to hear from you.

Join us next time for more unique insights on Longitude Sound Bytes.

 

Jaena Kim
Welcome back to Longitude Sound Bytes, bringing innovative insights from around the world directly to you. This time we’re embarking on a voyage of imagination. I’m Jaena Kim, Longitude fellow and a law student at the University of Ottawa.

Jade McAdams
I’m Longitude fellow Jade McAdams, a mechanical engineering student at Rice University. Join us throughout November as we set sail behind the scenes with the shipmates of the Mayflower Autonomous Ship.

Tony Zhou
The Mayflower Autonomous Ship or MAS 400 is an ongoing story of collaboration and unpredictability, bringing together the best hands of IBM and ProMare on deck. I am Tony Zhou, a Longitude fellow and data scientist at Yale University.

Can Erdogan
But you won’t find anyone aboard the fully autonomous, AI powered marine research vessel. Find out how available imagination ripples into unchartered waters of innovative ocean research every Monday and Wednesday of this month. I’m Longitude fellow Can Erdogan, also an engineering student at Rice University.

Molly Turner
And this is Molly Turner, Longitude fellow and conducting fellow at the Colburn school in Los Angeles. Keep listening for a sneak preview of the upcoming Sound Bytes series: Longitudes of Imagination. Featuring Brett Phaneuf, Don Scott, Carrie Bendzsa, Andy Stanford Clark and Jonathan Batty.

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Jaena
Did you know the United Nations has declared a decade of ocean science for sustainable development from 2021 to 2030? IBM’s Chief Technology Officer for the UK and Ireland, Andy Stanford Clark, wrote that we know more about the surface of Mars than we do about many parts of the ocean.

Andy Stanford Clark (CTO at IBM UK and Ireland)
The purpose of the ship is to explore the oceans and have experiments on board that will improve our understanding of the impact of climate change on the ocean, and also the effect of pollution of the ocean from humans. From that we plan to spend a long time at sea, gathering large amounts of data and use that to change our understanding of this not very well understood, massive resource. Half of our oxygen comes from the oceans. So as my colleague says, if you take two breaths, one of those breaths was generated by the ocean. We really do rely on the health of the ocean to continue to occupy this planet.

Can
Dr. Stanford Clark talks about harvesting literally an ocean of data impossible for a single person, but not a team. The interesting thing was that the project was initiated by volunteers. So everybody who was working on the project had a tremendous passion for ocean science and innovation.

Molly
Oceans regulate the world’s climate systems, and we rely on them for food, transportation and natural resources. But oceans are formidable places, with waves that can reach heights over 60 feet during storms and make research explorations at sea dangerous.

Fortunately, autonomous technologies hold promise for innovative new ways to increase safety in ocean traffic but also for collecting critical ocean data. Brett Phaneuf saw this potential.

Brett Phaneuf (Co-director of MAS400)
So we decided to build the Mayflower autonomous ship in 2016. And we really focused the first four or five years of our work on building infrastructure to collect data, as we know how to build boats. And so then the question is, what’s the hard part? The hard part, aside from the fact that boats break, and the ocean is probably the most challenging environment on the planet and it’s the preponderance of the planet, nonetheless, and also, arguably the most important part of the planet in terms of maintaining a living ecosystem and climate in general. It’s a really challenging place to be. So we said, you know, the AI is the hard part. So we got to start thinking about that. We have to have lots of data that we have to make into models.

Jade
The unpredictability of oceans requires meticulous engineering. Marine AI Chief Technology Officer Don Scott also believes in the value of a passionate team when pursuing a vision. Don personally feels most at home taking a blank piece of paper and creating a roadmap to reach a final product. But he emphasizes that projects need cross-disciplinary team members focused on a single goal to actually become a reality. He claims that Brett’s conception of the Mayflower is a prime example of that.

Don Scott (CTO at MarineAI)
He [Brett] had this idea, you know, this concept. It was in his head, and he was able to express it quite clearly but also motivate others to do that. It’s great to have an idea, but you actually need to build a team to actually make it happen. You need mechanical engineers, you need electrical engineers, you need software people and stuff like that.

Tony
The Mayflower 400, a commemoration to the 400th anniversary of the 1620 Mayflower ship, has developed into a compelling story in partnership between ProMare, an idea on how to advance ocean research and autonomous AI. In speaking with Brett, co-director of the Mayflower 400, this project has made him increasingly encouraged for humanity, and he hopes this project could be an example of how artificial intelligence can be harnessed for good.

Molly
Funnily enough, Brett was most surprised by how interested people have been in the project.

Brett Phaneuf (Co-director of MAS400)
The most unexpected thing was that this sort of autonomous vessel, this sort of spaceship looking boat, is very humanizing. And, you know, I got up in the middle of the night, once, when it was going out to sea, we’re like 400 miles offshore in the first attempt to cross, and I logged into the portal and this, like, 30,000 people logged in looking at the camera feed from the vessel. That’s been really unexpected. I’m really appreciative at the level of interest, but I’m still baffled by it.

Jaena 
30,000 people! That’s 10,000 more people than can fit into Madison Square Garden. Can you believe the sharing of such a successful project was met with initial resistance for its potential for unpredictability at the beginning? IBM America’s US markets and regional communications leader Carrie Bendzsa gives us a bit of insight.

Carrie Bendzsa (U.S. Markets and Regional Communications leader at IBM)
At first, when I first brought it up, we were met with a bit of resistance I have to say, because people said, Well, let’s just wait till the ship makes its voyage. And then we’ll talk about it when it’s successful. But luckily, my colleague Jonathan was very like-minded and saw the potential and started to build a story from what this could be, the steps along the way and whatnot.

Molly
PR and technical teams sometimes come together in just the right way to share scientific endeavors with the world. I don’t think any project can embody that better than the MAS 400.

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Jaena
This brings us to the end of our introductory episode.

Can
Luckily, this is not the end. It’s just the beginning of the new Sound Bytes series.

Jade
We can’t wait for you to tune into the first episode of Longitudes of Imagination.

Tony
Join me and Brett this coming Monday where we’ll chat about his vision for the MAS 400, ocean research, AI ethics and edge computing.

Jaena
Follow longitude on Facebook, Instagram and LinkedIn to make sure you don’t miss the release of the first Longitude of Imagination episode in collaboration with the Mayflower Autonomous Ship project and IBM. You can also visit our website Longitude dot Site, s i t e, for more information and content.