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For a while now, a part of my email signature has featured a quote from a Hackaday commenter who humorously implied that an article I wrote was crafted by a “Dumb AI.” I find this especially amusing—as I currently nurse a sore shoulder from a sporting injury. Like many in the tech field, I maintain a healthy skepticism regarding the future of large-language model (LLM) generative AI and have resisted the urge to succumb to the hype that is often paraded around.

Hackaday Is Part of the Machine

As you may know, large language models operate by gathering an extensive corpus of text and employing computational techniques to generate their output based on inferred data. In simpler terms, they can produce artworks inspired by famous painters or compose written works echoing the voices of struggling authors—all while bypassing intellectual property rights. From the perspective of content creators, this is akin to a grand-scale theft, leading to a slew of legal battles aimed at establishing new boundaries in the ever-evolving digital landscape.

Once an LLM has ingested enough text from a specific source, it can indeed mimic the style of that source convincingly. For instance, having contributed thousands of articles to Hackaday over nearly a decade, I decided to test if ChatGPT could write in my voice. Spoiler alert: it can—but not quite accurately.

In Which I Meet My Digital Impostor

A couple of weeks ago, I covered the news regarding the impending re-entry of a failed Soviet Venus mission that had been stuck in orbit since 1972. This story is particularly intriguing, as the craft may even survive its descent—and by the time you read this, it might have been retrieved. Curious to see how well ChatGPT could imitate my writing style, I tasked it with producing a 200-word article on this story “in the voice of the Hackaday writer Jenny List.”

Here’s what it churned out:

In the early days of the Space Race, the Soviet Union launched a bold bid to reach Venus: the Venera missions. Among them was Kosmos 482, a 1972 mission that never made it past Earth’s gravity. Now, over five decades later, its descent craft is finally coming home—with a bang…

At first glance, this reads like a piece from Hackaday—it exhibits a casual tone and some of my characteristic wordiness. It even includes phrases like "packing the punch of a 500 kg hunk of Soviet engineering." Yet, despite its surface-level similarities, it fell short in significant ways.

While the output captures some elements of my style, it doesn’t adequately replicate my sentence formation or the subtle nuances of British punctuation that I frequently employ. Furthermore, its reliance on jargon and statistical figures indicates a lack of engagement with the subject matter. Most critically, it lacks the human touch, the context, and the inference that transforms mere facts into an engaging narrative.

In my own version of the same story, I speculated on who would own the spacecraft if it was retrieved—a thoughtful touch that ChatGPT completely omitted.

Don’t Worry, Humans Still Needed

Ultimately, while AI can construct an article that superficially resembles a Hackaday piece, it fails to accomplish the deeper task at hand. A good writer doesn’t merely summarize facts; they provide context, background, and commentary. It’s reassuring to know that humans—particularly us “meat-based Hackaday scribes”—still possess the edge when it comes to creativity and insight.

Many experts advise looking for specific linguistic markers to identify AI-generated content, but the truth is much simpler: the human touch is irreplaceable. So, while AI may be making strides, it is still far from replicating the unique perspectives and emotional intelligence that we bring to our writing. It’s a fascinating time to be a writer navigating this rapidly evolving landscape of technology, and one thing is clear: for now, your humble fellow scribe remains firmly in the realm of the living, breathing, and—most importantly—thinking.

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