The Dock to Dish model has expanded across North and Central America. Above, artisanal fishermen on the Pacific coast of Costa Rica head out to sea seeking schools of abundant forage fish to supply the program.
In 2012, entrepreneur Sean Barrett founded Dock to Dish in Montauk, New York. It connected local fishermen and women with local chefs, enabling the chefs to serve hyper-fresh seafood – with the caveat that they didn't know what would be on their menus until it arrived in their kitchens the night before.
"Since we're not a seafood-centric culture, people don't know what's what, where fish are from, and when they're in season, making them easy to dupe."
In June of 2017, The United Nations Foundation designated Dock to Dish as one of the top breakthrough innovations that can scale to solve the ocean's grand challenges. His company has since expanded across the Americas and has just opened up shop in Fiji. Leapsmag recently chatted with Barrett about his inspirations and ideas for how to overcome the hurdles of farming wild seafood. This interview has been edited and condensed for clarity.
What inspired you to start Dock to Dish?
The short story is "A Tale of Two Hills."
The first is Quail Hill Farm in Amagansett. I grew up in the commercial fishing port of Chinicock in the 1980's and 90's, working on my family's dock from an early age and in the restaurant industry in my teens. By my thirties, I had accrued my 10,000 hours of experience in both dock and dish. I watched the food system shift from local to global, especially in seafood. By the early 2000's, over 90 percent of seafood in the U.S. was imported. It was bad.
Quail Hill was the first CSA [Community Supported Agriculture, in which customers pay up front for a share in whatever crops grow (or don't) on the farm that season] in the U.S., founded in 1990. So people in the area were accustomed to getting their produce that way. Scott Chaskey, the poet farmer at Quail Hill, really helped crystallize the philosophy for me and inspired me to apply it to seafood. Fishermen had always been bringing a share of their day's catch to their neighbors; now we were just doing it in a more formalized way.
The second is Blue Hill at Stone Barns. [Executive chef and co-owner] Dan Barber literally trademarked the phrase "Know Thy Farmer"; we just expanded it to Know Thy Fisherman and it took off like a rocket ship. His connections in the restaurant world were also indispensable.
17th generation Montauk fisherman Captain Bruce Beckwith (above left) with crew Charlie Etzel (Center) and Jeremy Gould (right).
Do you have any issues that are unique to seafood that a CSA or meat co-op wouldn't face?
This food is WILD. People are totally disconnected from what that word means, and it makes seafood different from everything else. Everything changes when viewed through the prism of that word.
This is the last wild food we eat. It is unpredictable, and subject to variables ranging from currents and tides to which way the wind is blowing. But it is what makes our model so much more impactful and beneficial than the industrialized, demand-driven marketplace that surrounds us. The ocean and its ecosystem are the boss, not chefs and consumers.
There has a been a lot of press about seafood being mislabeled. How and why does that happen? Can Dock to Dish fix it?
Imported, farmed seafood is cheap. Wild, sustainable seafood is not. People are buying low and selling high to make a buck; and while fisheries are extraordinarily regulated, the marketplace isn't. There is no punishment for mislabeling, and no means to correct it. Since we're not a seafood-centric culture, people don't know what's what, where fish are from, and when they're in season, making them easy to dupe. But technology is poised to fix that; DNA testing can test what a fish sample is and where it's from, and SciO handheld spectrometers – soon to be incorporated into smartphones – can analyze the molecular makeup of anything on your plate.
We've created the first ever live tracking system and database for wild fisheries. It is similar to the electronic system used to monitor commercial fisheries, thanks to which the resurgence of wild seafood in U.S. waters is a model for the rest of the world. We have vessel tracking devices on our fishing boats and delivery vans, so the path of each fish is publicly available in real time.
In 2017, Dock to Dish launched the world's first live "end-to-end" tracking system for wild seafood, which provides full chain transparency and next-generation traceability for members.
People are increasingly looking to seafood as a healthier, possibly more sustainable protein option than meat. Can Dock to Dish scale up to accommodate this potentially growing market?
Nope. We can't scale; the supply is finite. That's why the price keeps going up. To avoid becoming "fish for the rich" we are working closely with Greenwave.org to create a network of 3D restorative ocean farms growing kelp and shellfish, which sequester carbon and nitrogen out of the air and soil. Restorative, because sustainable is no longer an option. In fifty years, a plate of seafood will be mostly ocean vegetables with a small amount of finfish as a garnish.
AI was integral to creating Moderna's mRNA vaccine against COVID.
But the truth is that before ChatGPT nabbed the public’s attention, AI was already here, and it was doing more important things than writing essays for lazy college students. Case in point: It was key to saving the lives of tens of millions of people.
AI-designed mRNA vaccines
As Dave Johnson, chief data and AI officer at Moderna, told MIT Technology Review‘s In Machines We Trust podcast in 2022, AI was integral to creating the company’s highly effective mRNA vaccine against COVID. Moderna and Pfizer/BioNTech’s mRNA vaccines collectively saved between 15 and 20 million lives, according to one estimate from 2022.
Johnson described how AI was hard at work at Moderna, well before COVID arose to infect billions. The pharmaceutical company focuses on finding mRNA therapies to fight off infectious disease, treat cancer, or thwart genetic illness, among other medical applications. Messenger RNA molecules are essentially molecular instructions for cells that tell them how to create specific proteins, which do everything from fighting infection, to catalyzing reactions, to relaying cellular messages.
Johnson and his team put AI and automated robots to work making lots of different mRNAs for scientists to experiment with. Moderna quickly went from making about 30 per month to more than one thousand. They then created AI algorithms to optimize mRNA to maximize protein production in the body — more bang for the biological buck.
For Johnson and his team’s next trick, they used AI to automate science, itself. Once Moderna’s scientists have an mRNA to experiment with, they do pre-clinical tests in the lab. They then pore over reams of data to see which mRNAs could progress to the next stage: animal trials. This process is long, repetitive, and soul-sucking — ill-suited to a creative scientist but great for a mindless AI algorithm. With scientists’ input, models were made to automate this tedious process.
“We don’t think about AI in the context of replacing humans,” says Dave Johnson, chief data and AI officer at Moderna. “We always think about it in terms of this human-machine collaboration, because they’re good at different things. Humans are really good at creativity and flexibility and insight, whereas machines are really good at precision and giving the exact same result every single time and doing it at scale and speed.”
All these AI systems were in put in place over the past decade. Then COVID showed up. So when the genome sequence of the coronavirus was made public in January 2020, Moderna was off to the races pumping out and testing mRNAs that would tell cells how to manufacture the coronavirus’s spike protein so that the body’s immune system would recognize and destroy it. Within 42 days, the company had an mRNA vaccine ready to be tested in humans. It eventually went into hundreds of millions of arms.
Biotech harnesses the power of AI
Moderna is now turning its attention to other ailments that could be solved with mRNA, and the company is continuing to lean on AI. Scientists are still coming to Johnson with automation requests, which he happily obliges.
“We don’t think about AI in the context of replacing humans,” he told the Me, Myself, and AI podcast. “We always think about it in terms of this human-machine collaboration, because they’re good at different things. Humans are really good at creativity and flexibility and insight, whereas machines are really good at precision and giving the exact same result every single time and doing it at scale and speed.”
Moderna, which was founded as a “digital biotech,” is undoubtedly the poster child of AI use in mRNA vaccines. Moderna recently signed a deal with IBM to use the company’s quantum computers as well as its proprietary generative AI, MoLFormer.
Moderna’s success is encouraging other companies to follow its example. In January, BioNTech, which partnered with Pfizer to make the other highly effective mRNA vaccine against COVID, acquired the company InstaDeep for $440 million to implement its machine learning AI across its mRNA medicine platform. And in May, Chinese technology giant Baidu announced an AI tool that designs super-optimized mRNA sequences in minutes. A nearly countless number of mRNA molecules can code for the same protein, but some are more stable and result in the production of more proteins. Baidu’s AI, called “LinearDesign,” finds these mRNAs. The company licensed the tool to French pharmaceutical company Sanofi.
Writing in the journal Accounts of Chemical Research in late 2021, Sebastian M. Castillo-Hair and Georg Seelig, computer engineers who focus on synthetic biology at the University of Washington, forecast that AI machine learning models will further accelerate the biotechnology research process, putting mRNA medicine into overdrive to the benefit of all.
This article originally appeared on Big Think, home of the brightest minds and biggest ideas of all time.
