Qualitative vs Quantitative Thinking
Thesis season is coming!
As a rising second year in the MIT Media Lab’s masters program, I’ve begun thinking about the exciting (and slightly surreal) concept of having a good sit to write and write and write and write….
I’m particularly psyched about opportunities to do a landscape assessment of the field before I dive into writing the thesis. Coming from a standard electrical engineering background, I’ve always thought
quantitative > qualitative thinking…mainly because, well, efficiency. I would whiz through problem sets in Linear Systems, but if I spent an extra 30m thinking about how the problem sets related to some bigger picture, it would’ve taken 3x as long to complete.
I was trained to efficiently arrive at the destination, but not to understand why I was on the journey in the first place.
Alas, I’m still in school trying to figure out how to go about understanding larger systems without deducing them into tiny buckets for the sake of efficiency, although that framework of thought certainly has its time and place. This thesis work will be a foray into ‘unlearning’ that “quantitative or nothing” mindset that I’ve been so fond of.
Exploring the Field
I’m a firm believer in technologists understanding the problem through the eyes of those who experience it, day in and day out. Luckily for me, my advisors think the same. Before I try to provide a solution (let’s call this ‘x’) to a problem I read about in academic papers and articles, its crucial for me to see whoever will use x, how they will use it, what the surfaces it will sit on (if x is a physical thing) smell/look/feel like and if there’s already some technology there that should be the basis of designing x.
To do a thorough swipe of information gathering in the Pacific Island Tuna fisheries sector, I’m going on a few field trips.
Oh the places you’ll go…
In Honolulu, I’ll be visiting vessel-level electronic monitoring systems aboard a couple of the Hawai’ian Longline Association fleet vessels, where a NOAA-funded pilot uses camera installations on select boats. I’ll visit the Hawai’i Conservation International office and chat with the team on their sustainable ocean projects. I’ll stop by an Auction on Pier 38 at 5AM (...oof) and then go visit the processing side of the fishery supply chain in the Norpac facility, where vertically integrated supply chain technology is being developed for better traceability.
Then I’m headed to Guayaquil to support the Conservation International team in a training on how to use a CI-developed social responsibility assessment tool. The week afterwards we’re headed to Manta in order to interview fishermen aboard purse-seiner fleets in collaboration with Verité.
On a Lindblad Expedition with National Geographic for drop cam deployment, I’m headed to the Galapagos Islands. The drop cam is a $15,000 untethered and waterproof camera that can safely descend 6000m. Eventually, ocean exploration is something I plan to do a deeper dive into.
In Majuro, I’ll watch over the shoulders of a few of the brilliant humans who work in the enforcement side of transshipment with satellite intelligence data.
Somewhere in there, I’m headed to the Cook Islands to discuss with the local governing bodies to identify if (and maybe how) I can be of help with a traceability technology solution for a Fishery Improvement program on their roadmap.
There are a plethora of stakeholders I could be building the core of this thesis (“the technology”) for, so I’ve not settled on a single idea yet. Instead, I’ll compile these ideas and their respective elevator pitches here…
What does sustainable seafood practices look like for the USD 42 billion tuna trade market? In this work, the opaque Pacific tuna supply chain is investigated as a network of nodes in an evolving organism. From bait to plate, the data collected along the journey of a wild-caught Pacific tuna is layered into a crowd-sourced network graph to better analyze fractures and vulnerability points throughout the supply chain.
For this thesis work, I propose an interactive network graph that visualizes the complex journey of seafood supply chains - “bait to plate” - of Bigeye and Yellowfin tuna.
This network graph will be made up of data points from existing sensors on vessels (e.g. Vessel Monitoring Systems, GPS, Electronic Monitoring etc) and people (e.g. crowdsourced information of living conditions/daily loigs at sea from a WhatsApp bot) to more accurately tell the story of where the tuna’s data trail begins: the vessel.
Blockchain-based Grassroot Tooling for Fishermen
After interviewing the crew of an industrial perse seiner vessel in Manta, Ecuador, one thing became evident: the hardships felt by the crew were rooted in a lack of understanding of their contracts. Why and what they were paid was not clear to them at all - especially when the quality grading and pricing of their catch was done outside of their purview. Access to grievance policies is unclear if not unaccessible, therefore not even considered by crew members who feel exploited/discriminated against, experience loss of family on-shore or are injured on the clock.
Contract data is stored in analog formats, often not even digitized. As far as I understand it today, there is no reason to actively keep these records from the active crew members.
For this thesis, I propose a WhatsApp interaction tool (WhatsApp being the most highly used messaging app in Ecuador) that stores contract data on a secure node which lives on-vessel (due to the uncertainty of having consistent internet access). These nodes will share the stored contract data and witness its existence to a local blockchain network, operated by the vessel owner(s).