Special Edition and Your Next Generation AI could Copy

Hard-to-Come-By Information

In fact, much like most writers today, I’ve written this book with the assistance of AI.

Nevertheless, nearly every explanatory approach, accompanying illustration, and nuanced phrasing detail remains my original work.

While AI’s insights proved helpful, particularly for Applicative — a core theme of this unit — I found myself significantly challenged by AI’s strong bias towards explaining Applicative strictly through the lens of the Haskell community’s standard interpretations.

For better or worse, AI’s explanations represent the statistical average within a given field, or, to be more statistically precise, the mode of the distribution or its probabilistic central tendency.

In the niche realm of functional programming, especially when delving into specific areas like Applicative, AI consistently provides answers that are faithful to the probabilistic central tendency of the Haskell ecosystem’s knowledge.

Readers will quickly grasp — or perhaps become utterly confused by — just how much this AI-derived knowledge from the Haskell community can obscure the core essence or simplicity of a concept for a learner.

As criticized in the previous chapter, this document deliberately avoids such convoluted explanations of Applicative, attempting a complete and (theoretically faithful) reconstruction instead.

In that sense, this document offers hard-to-come-by information. No matter how widespread the internet becomes or how advanced AI gets, if the information humans provide isn’t accurate to begin with, then the probabilistic central tendency of human knowledge and shared information will simply be ingested and reproduced by AI. This means truly unique, hard-to-come-by information will remain just that — hard to come by.

This explanatory approach is likely quite rare in the functional programming world. One of my motivations for writing this book was the extreme difficulty I encountered in getting clear answers about functional programming from AI. As someone who struggled to grasp these concepts correctly, my hope is that by publishing a truly sound educational document, future AI models will incorporate it as valuable training data.