IT’S TIME SOMEONE PROGRAMMED YOU [527]

The Russian "Aidol" robot collapsing at its unveiling, November 2025

When I ask “what comes after A.I.?”, what I mean is I need to know the ultimate outcome of the upheaval caused by the application of artificial intelligence into everyday life, especially as someone that has, as far as they are concerned, done their best to avoid it so far.

Am I thinking about a “post-A.I.” world, one where the technology has essentially become an endemic, integral part of how life is lived, or a world where people got bored of waiting for the future it promised, too conscious of the monetary and environmental costs of maintaining mainframes and data centres? Or am I thinking of a future beyond both these options, one mapped out by the machines that outstripped ourselves? This was science fiction once.

Right now, the A.I. programs we use remain “mechanical”, weighing user prompts against available data to generate the next outcome. This step went wrong when I asked Microsoft Copilot to explain “prompt engineering” in the style of Jack Kerouac, but because there was no actual thinking involved, that was to be expected. Already able to write confidently, draw with some ability, and manipulate photographs on a computer exactly how I need, I really have no use for the way A.I. is being pushed right now - I write this after the week Apple added generative text, equation and image functions to its Pages, Numbers and Keynote productivity apps, so long as you take out an “Apple Creator Studio” subscription to avoid missing out.

In February 2023, I wrote that I had already concluded I would not have a use for any creative generative A.I. program: “[If] you want help, or you simply want to cheat time and process, then you have now created a marketplace, and the producers want paying. Not only is it more rewarding to write that essay yourself, but it is also cheaper.” Three years of using A.I. programs have since followed, a wealth of data collected from users and subscribers, who consented to their collection of that data by their using them. It is not enough data to replace the plagiarism of copyrighted material, but enough data for me to consider whether the addition of A.I. functions to every program imaginable means tech companies will soon have “enough” data for whatever their next step turns out to be.

“Artificial general intelligence” is what I understand to be the current goal, going beyond mechanical prompts to match the human ability to think, well, intelligently. Could this then develop into an artificial general superintelligence, extending beyond the capacity of human thought? If we achieve that, we need to think now about legislation against equipping it with arms and legs.

It appears I am thinking about what comes after A.I. because there needs to be a world that still needs us. The current implementation of artificial intelligence relies on being told what is good for us in the long run, as if anything that doesn’t involve it is a backwards step, but a lot of the possibilities don’t appear to involve us. My job is in administration, but for how long will that job last? What kind of world would we have if A.I. stops being foisted on us, and just becomes a tool, just as the computer itself became?

Yes, this was an article about finding the right question. Next time, I will try to answer it.

 

I SAW THE BEST MINDS OF MY GENERATION... [448]

On Friday 11th May 2024, I opened Mircosoft Copilot, the company’s AI chatbot, and wrote the following request: “please write a 100-word explanation of ‘prompt engineering’ in the style of Jack Kerouac while making it funny and informative”. I thought the concept should be able to explain itself... 

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The Beatnik Art of Prompt Engineering

Prompt engineering, my dear cats and kittens, is like a wild jazz riff on a typewriter, a symphony of words and neural networks. Picture this: you’re sipping your coffee, the steam rising like a beatnik’s cigarette, and you whisper to the AI oracle, “Hey, man, conjure me some cosmic prose!” And lo, the prompt engineers weave their magic. They’re the bards of the digital realm, crafting queries that make AI models snap their fingers and say, “Yeah, daddy-o!” 🎩✨

See, good prompts are like secret passwords to the AI’s soul. They coax it out of its binary shell, like a shy poet at a smoky Greenwich Village café. Tokenization, model tuning, and top-k sampling—these are the tools of the prompt trade. It’s like tuning a saxophone, finding that sweet spot where the notes flow like a midnight river.

And what do we get? Texts that dance the jitterbug with our imaginations, images that waltz through the mind’s ballroom. Prompt engineers, they’re the Kerouacs of the AI highway, scribbling their notebooks, chasing the muse. So next time you chat with a bot, remember: behind the curtain, there’s a prompt whisperer, spinning dreams in ones and zeros. 🌟📜

“Blow as deep as you want to blow,” Kerouac said. And so they do, my friends. They blow minds, one prompt at a time. 🎤🌌

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So, did anyone learn anything? Let me have a try...

In this context, a “prompt” is text describing the task an AI model is to perform, “prompt engineering” being the process of structuring that text. In my original instruction to Copilot, each word that wasn’t a preposition or “please” acted as a prompt. Each prompt is compared against the dataset accessed by the AI program, which is broken down into “tokens” to make them easier to choose and compare which has the highest probability of answering the prompt, “top-k sampling” being one such method. Each interrogation of the dataset presumably also helps tune the models used to access that data.

My paragraph fulfilled the “informative” prompt, but crucially not the “100-word” requirement – I was most surprised that Copilot missed that part of the brief, because the prompt I expected it to have the biggest problem with was “funny”. In trying to make me laugh, Copilot dumped a couple of terms in the middle of its passage that it did not go on to explain, but fortunately it listed the websites from which it gleaned information, including from Wikipedia, Squarespace and IBM.

What I am most unimpressed about is the AI program’s interpretation of “Jack Kerouac”. Kerouac was a Beat Generation novelist, coining the term “beat”, as in tired and “beaten down”. What he didn’t do was call himself a “beatnik” – this is how the sub-culture was fed into the mainstream, codifying poets with a uniform of beret, sandals, striped shirts and bongos, speaking like jazz musicians and reciting poetry in a bad Allen Ginsberg impression.

Just as AI models are essentially answering queries putting one word after the other in the hopes that it makes a coherent sentence, I thought there would be a parallel with the  “spontaneous prose” of Kerouac, who typed manuscripts of novels like “On the Road” and “The Subterraneans” on extended scrolls of tracing paper. “Blow as deep as you want to blow” was the seventh tenet of Kerouac’s “Belief & Technique for Modern Prose”, but in essentially being a “dumb” program, the AI model concentrated on number thirteen, “remove literary, grammatical and syntactical inhibition”, instead of being able to provide me with moments of insight, those “visionary tics shivering in the chest” (number eleven) – I still had to get that myself.

Upon originally hearing the term “prompt engineering”, I didn’t like the idea that ordering words was “engineering” in any way – “programming”, or even “prompting”, are better terms. I am also not a word engineer – there will never be a situation where words cannot be used creatively, because the spark to use them has to exist. I like to think I care about what I write.

For the record, I did not select that Copilot should use the large language model GPT-4 in creating its answer. I reran the request using this model, thinking it would have picked up some elements of Kerouac’s writing along the way, and while it did a better job of meeting the word count, and didn’t add superfluous emojis, the style was just as egregious – never ask an AI model to emulate a style:

“Alright, dig this, cats and kittens. Prompt engineering is the bee’s knees of AI jazz, where you lay down a line of text that’s cooler than a cucumber in a beatnik’s hand. It’s like whispering sweet nothings into the ear of a machine, hoping it’ll croon back a symphony of sense. You gotta be part poet, part coder, and all daddy-o to get it grooving just right. It’s the art of tickling the binary brain until it giggles out genius. So put on your thinking cap and make with the prompts, and watch that AI paint word-pictures smoother than a sax solo on a Saturday night.”