Marcellus’ Three Longs and Three Shorts newsletter was born out of an informal habit of sharing amongst ourselves what we found as good reads on the internet. In recent years, the likelihood of finding a good one has paradoxically reduced significantly despite or rather because the volume of articles online at the likes of Substack have shot up. Thanks to AI. We featured an interview with the founder of AI detection site Pangram recently. This one builds on that by showing why we should care about AI generated content. The author begins with what writing actually implies:
“For 3000 years, a piece of writing was evidence of human thought, and the fluency of that writing was a loose proxy for the quality (or at least degree) of thought that went into it. For the most part, good writing meant there was a mind behind the scenes that had done a lot of work.
AI broke writing as proof-of-thought.
When you read something that easily flows through your synapses, the ease with which you process those words is taken as a signal that the work itself is true — that you can trust the person who wrote it knew what they were talking about.2
We implicitly grant fluency a higher degree of trust.
Which isn’t a problem, as long as the bulk of fluent writing out there on the internet is true.
And up until about six years ago, this was the case — for the most part, when you came across a fluent piece of writing, it suggested that a mind behind it understood the subject.
Before AI, fluent writing was difficult to create. Someone, somewhere in the chain had to sit down and concoct a coherent and flowing piece of writing using their very own thoughts. It took immense time and effort. If you wanted to spread false information, you had to be a good writer to do it. Or you had to be a person with the means to pay for a good writer.
…After all, to truly understand something, you need to be able to explain it. And to explain it, you need to have assimilated extensive knowledge and the ability to synthesise it — to recognise where and how to build bridges over that dense knowledge so that they can be walked by the reader. Before AI, fluent writing signalled that someone had laboured for hours trying to collapse three-dimensional thought into a two-dimensional stream of words that could convey that understanding to another person. Good writing meant good thinking. Or it used to.
AI broke this. Fluency can now be manufactured, at scale. At the heart of the mind virus lies a broken signal: fluency is no longer a measure of thought.
A fluent piece of writing can still mean that many hours of thought went into it. It can also mean a one-line prompt did.”
Why does this matter? Good content is good content whether a human wrote it or an AI with a human prompt?
The problem the author says is in how we understand things. She builds on Richard Feynman’s concept that to truly learn a subject you need to explain it in simple language. It is in that process of producing or creating that the concepts get clear in our heads and neural pathways get built. In AI generated content, whilst the human is giving the prompt, the absence of ‘producing’ limits the understanding of the producer and worse, they don’t realise the limits of their understanding:
“So they open Claude and start pitching ideas for an essay. Their sycophantic thought partner encourages them, regurgitating their own ideas with fluent ease, and pulling existing knowledge to support them. The person feels understood — “Yes, that’s exactly what I mean!” This miraculous tool has finally allowed them to express what they truly think. What magic indeed!
After a few more iterations of this, the person instructs Claude to craft an essay that coherently lays these points out for a reader, and then, after a little more back-and-forth (and a lot of copy and paste) publishes that essay as their own words.
The scariest part isn’t that people are using these tools to manufacture fluency — to forge their understanding. It’s that they truly believe they do understand what they publish.”
The author makes a very important point here and shares her ideas on how best to use AI and writing is not one of her recommended use cases: “You can use AI to help you think. You can even use it to help you understand. But you will never know if you truly did either until you write.
And neither will your readers.
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Note: The above material is neither investment research, nor financial advice. Marcellus does not seek payment for or business from this publication in any shape or form. The information provided is intended for educational purposes only. Marcellus Investment Managers is regulated by the Securities and Exchange Board of India (SEBI) and is also an FME (Non-Retail) with the International Financial Services Centres Authority (IFSCA) as a provider of Portfolio Management Services. Additionally, Marcellus is also registered with US Securities and Exchange Commission (“US SEC”) as an Investment Advisor.
