When browsing the media, it’s easy to find articles describing how no niche is safe from the next wave of automation. Our experiences match these reports; distinguishing artificially generated content from human-created content has become nearly impossible. Yet something often feels subtly “off.” Initially, it just tugs at your instincts, but uncovering the clues—the minor imperfections that reveal an AI creator—can require significant effort.
In his book Shape, Jordan Ellenberg reflects on the mid-nineties and provides insight into what feels off, particularly in discussing Garry Kasparov’s historic chess loss to IBM’s Deep Blue:
Perfect play isn’t play at all, not in the plain English sense of that word. To the extent that we’re personally present in our game playing, it’s by virtue of our imperfectness. We feel something when our own imperfections scrape up against the imperfections of another.
Computers are frequently billed as ‘perfect’ and ‘flawless’—and indeed, for simple computations like 1 + 1 = 2, they are. But complex algorithms still make mistakes. However, these mistakes aren’t human-like; our biases and psychological constructs add a structured texture to our flaws, something machines still lack.
During a critical move in the chess match between Deep Blue and Kasparov, IBM’s machine encountered a bug and entered an infinite loop[1]. To recover, it randomly selected a valid move. Kasparov didn’t interpret this randomness as a flaw—he attributed it to “superior intelligence.” The machine had unintentionally concealed its imperfection.
[1] Deep Blue (chess computer) - Wikipedia. https://en.m.wikipedia.org/wiki/Deep_Blue_(chess_computer)
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