You never stop learning, that why in my spare time I enjoy scouring the web in search of topics, courses, articles concerning the maritime sector. When I saw the online course, the title immediately caught my attention, because it’s a very special title in the eyes of a seaman.
In addition to having a technical-scientific definition, navigation is also defined as "The art of not getting lost". So the title immediately intrigued. I followed the course with great interest, at the end I had some reflections. Actually the course doesn't talk about how we are lost without longitude, the course talks about how problems related to longitude were solved, how it was discovered.
The course is well done, it shows with photos and descriptions many ancient instruments used in navigation, to determine the position and find the correct direction to follow (the route). Gives much space to the studies and work done by John Harrison and his clocks.
Making a course on any subject in the maritime sector is not very easy. Many things are connected to each other, and each would need its own course. Navigation is closely linked to nature, to ships and their evolution over the centuries, to crews and their knowledge increased. It is almost as old as Humanity, its origins are lost in history, and despite everything some things have not been fully resolved and many things have not been fully discovered. For example, Humanity reached the Moon, but has not yet fully explored the ocean's seabed, or completed the explorations, there are some areas still under exploration, especially in Antarctica.
Staying focused on the course, it's clear from the contents themselves that, longitude having been discovered 300 years ago, we have more history of navigation without longitude, than with longitude. To today's seaman, it would seem very difficult imagine to sail without today's knowledge and technology. But a careful analysis would show how navigation hasn't changed that much over time.
In fact, between the ancient seamen and those of today, there are still many things in common, such as: They navigate the seas for trade, military purposes, explorations. They face the same uncertainties and risks related to sea conditions, storms and unexpected events. They depend on the knowledge of navigation, and on the equipment and strumentations used to reach their destinations safely and efficiently, not always with a clear sky that allows you to see the stars for orientation, but also with any kind of weather conditions. We tend to underestimate the skills and knowledge of ancient sailors, but there are historical traces that show that they were able to navigate even reaching destinations very distant from their departure's points. Some examples are the invasions of the Sea Peoples in Egypt in the 12th century BC, the Hellenic colonization in the Mediterranean area, the Phoenician civilization, etc. In the world many ancient civilizations have developed remarkable skills in navigation, although much of this occurred as coastal navigation, it was not uncommon to navigate on the open sea (out of sight of the coast). Obviously they didn't have much knowledge that we have today, on geography, astronomy, meteorology, oceanography, etc. But it's clear that they had sufficient notions, knowledge and instruments to be able to navigate and reach even distant destinations. The main factor is that the ancient instrumentation, however rudimentary it was elaborated, but being built with raw materials that are difficult to resist over the centuries, today there are almost none left, and when we refer to ancient instrumentation, really it is the instrumentation used in the Middle Ages, or until a few centuries ago. Rarely some ancient instrumentation have been found, such as the Machine of Antikythera, built in metal and dating back to 100 BC. which is an ancient astrolabe, used for navigation with astronomy, found in the wreck of an ancient roman sunken ship (post’s picture), or historical traces such as the one left by Hipparchus of Nicaea, who in his writings tells us about the astrolabe in the II century BC.
Navigation has contributed a lot in the history of humanity, nautical explorations have revolutionized the conception of the world, above all they have colored the maps from the earliest times to today. The historical traces report some important ancient explorations, such as that of Annone the Phoenician, who in the V century B.C. he explored the African continental coasts going far south in the Atlantic Ocean. The explorations of the Greek navigator Pytheas, carried out in 300 BC, describing the British Isles and Iceland in his travels. Until the great medieval explorations with the famous "official" discovery of the American continent in 1492, even if there are historical traces of European civilizations that reached the American continental coasts in more ancient times, such as the Vikings for example.
This is why a title like "Lost without Longitude" is very intriguing, being strongly in contrast with the history of navigation, and with the romantic definition of navigation itself. Beyond all, the team of professors has written a very well done course, and I hope they will do others, I will certainly follow them with interest.
Thanking you for the time you dedicated to me, I take this opportunity to extend a cordial greeting.
I was interested in Prof. Gilbert’s discussion of how people internalize uncertainty and accuracy estimations. In his interview, he notes that individuals are typically unmotivated by statistics such as “a certain accuracy estimation improved by x%,” and are instead more impacted by behavior changes in others. He uses the example of recycling to argue that even people who were viscerally opposed to the notion of climate change now find themselves using blue bins simply because they observe others doing the same. The discussion reminded me of a common problem in modern natural language processing systems, where researchers still have trouble finding ways to convey uncertainty estimations to users of their programs. For example, if a chatbot on an online shopping platform could distinguish between requests to return and to exchange a product with 70% certainty, how would the company determine whether it is worth integrating into their site? Though it is not high, there is still a chance the bot could mess up the NLU and lead to angry customers, who were expecting a refund but instead got an exchange. I wonder if, instead, there might be a better way to convey uncertainty making use of the “herd behavior” mentality that Gilbert discusses. What if, say, there were a score generated that conveyed the number of companies who actually trust this chatbot (to use the same example) and have had a good experience? If the chatbot company were transparent about other users’ interaction with its platform, I wonder if new users would have a better time understanding the uncertainty involved?
This week I watched Professor Goodman's interview of Ned Hall. What I found most interesting about the talk was Professor Goodman and Ned's conversation about rules and theories. From what I gleaned rules are more tailored to specific situations and do not involve concepts that can't be directly observed or ones that need separate explanation. Theories on the other hand can often have exceptions since they are more general. In addition, Ned and Professor Goodman highlighted that theories can invoke concepts that can't be directly observed or explained in closed manner. I never really put much thought into the distinction between the two concepts and it was interesting to see Alyssa and Ned demonstrate the difficulty with defining rules, as they couldn't even provide a succinct rule that could be used to delineate between rules and theories.
One question I wish Alyssa asked Ned was if he knew of any situations where making the distinction between rule and theory was especially important. I somewhat get the distinctions at a high level but I am unclear about their utility. For that reason I'd love to hear more examples of how the distinction provided greater clarity or insight. In addition, I would love to know Ned's thoughts on AI potentially becoming more accurate without necessarily becoming any more transparent.