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Preservation and Loss

5/21/2026

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Those of you who have been running around in the same geeky circles that specialize in Thoroughbred history and breeding as I have can probably remember a number of cherished resources that are no more. Some were print periodicals; some were online. There are others that, while still available, are no longer updated and have uncertain futures; still others may still be out there but are increasingly difficult to find beneath layers of Web architecture.

Every form of recording past information has drawbacks. Books, which provide layers of knowledge and sometimes even wisdom atop the information they contain, are treasures when one has physical access but useless when one does not. They are also subject to physical deterioration and destruction, and many books in this field are rare and difficult to locate. Additionally, books are not readily updated (though that can be a strength in that a given book doesn't change according to the whims of later times). Printed magazines and newspapers provide snapshots of parts of the Thoroughbred world on a weekly, monthly, or quarterly basis, but their physical archives are space hogs and subject to the same perils that befall books; further, the lifespans of many periodicals are short and subject to both economic pressures and changing fashions in what owners and editors may decide to cover. CD-ROMs and DVDs can store multimedia information and have a reasonable level of durability with proper handling but require specialized equipment if their contents are to be accessed. And Internet sites, while highly adaptable so far as new and updated information goes, are subject to attack by bad actors, are often poorly edited, and sometimes ... just disappear.

At this time, AI seems more likely to complicate than solve the problem of preserving information, let alone that of preserving knowledge, which requires a certain level of value judgments and perspective to assess. (Wisdom is completely out of AI's sphere, implying a moral or transcendent dimension as it does). While AI can sift through tremendous amounts of information much more quickly than even the brightest and most capable human being, its ability to weigh and synthesize that information is much more questionable, not least because every large language model incorporates the biases and limited perspectives of its creators. When one considers that most of the major developers of the large language models on which AI systems are based are Millennial-generation males from the upper social classes and with a strong techie orientation---a group not exactly noted for strengths in relational skills, empathy, the humanities, a strong and reasonably unbiased grasp of human history, or humility regarding the limitations of humans and their technologies---the concern should not be what such individuals will design into their systems but what they will leave out. Whether the omissions are deliberate or (more likely) the result of the blind spots common to any relatively homogenous group scarcely matters in the long run.

How this will circle back to preserving information about our beloved horses, I don't know, but I don't think most of the techies are all that interested. Which, I suppose, leaves it up to geeks like me and you to write the books and articles and to create the blogs and websites before the things in which we are interested slip away into oblivion.



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    Author

    I'm Avalyn Hunter, an author with a passion for Thoroughbreds and a passion for writing and storytelling.

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