Front-loaded Quality: Not much back then, and nothing much has changed.

In Japanese-to-English translation, the need to cut costs and the long-held folk beliefs by some native Japanese speakers have often taken precedence over the value of front-loading quality into the translation process.

Back in the late 1970s, most Japanese-to-English translation was done by native Japanese speakers (NJSs), with varying degrees of ability to translate and to write in usable English. There is strong evidence that the demographic makeup of at least the humans still translating remains largely the same, particularly when you consider in-house translators in Japanese entities.

Those translations were often then subjected to what was then (and even now, apparently) called a “native check,” which very often, particularly back then, was characterized as a “brush up” performed by a native English speaker (NES) who would sometimes not be Japanese-capable, making referring to the source text impossible and meaningless. The salient characteristic of this workflow was that frontloading of quality was not part of the translation process. Quick and cheap, followed by repair was the norm.

Numerous hapless foreigners were employed in such work in Japan, some were English teachers, others were recruited from among in-house foreigners working in Japanese companies, but who were not necessarily hired as translators or editors. They just had the misfortune to be standing around when a translation needed a “native check.”

As they became more numerous, NES translators started receiving more JA-EN translation work. There was still, however, a lingering uneasiness among many Japanese clients that a non-Japanese person couldn’t actually understand all the nuances of something written in Japanese. And could they really read the characters? I have been asked as much at translation conferences, even after it was clear that I am a JA-EN translator. One such encounter happened when I attended a translation gathering of the Japan Translation Federation as the head of Japan Association of Translators.

Perhaps more importantly as a business reality, however, NES translators were considerably more expensive than their NJS counterparts, so the process of making a rough translation and having it repaired continued for years. Again, front-loading of quality took a back seat to other concerns.

Decades went by and the number of NES translators who could convince clients of their capabilities gradually grew.

Enter machine translation, years before the AI hype. This gradually turned many translation opportunities for freelancers into opportunities to repair not poor translations done by an NJS human, but rather the output of an MT system, resulting in their earnings tanking even further, as translation consumers demanded cost cutting.

What is happening is that professional humans are being replaced in the translation process by collections of software commands with insufficiencies that are supposed to be fixed by professionals humans, but at a fraction of the earnings that were possible when those humans were still being trusted to translate. Post-editing repair crews come to the rescue. Many translators are not eager to take on such work, but numerous translators have few other options, particularly ones in mid-career or later. And that is where freelance translation sits as I write this.

A business plan for people short on skills and ideas, and not willing to spend time writing.

Give a prompt to ChatGPTx as follows:

“Write 300 words about [insert name of a well-known person, a totally unknown person, or even a fictitious person, a movie, a historical event, or just about anything that has something to do with—or nothing to do with—you or the social media platform you’re on].”

Countless variations are possible and are recommended for best effect.

The requested “content” will be generated immediately, and you can copy-and-paste it into an anonymous or pseudonymous social media account to attract engagement, which could be hundreds of comments, or even thousands if the post includes politically controversial content. An important element to include in each of your posts is either a photo you steal (no need to ask permission for republishing—remember you’re anonymous and not going to be held accountable) or an AI-generated image.

This works on most social media platforms, which essentially guarantee that you can remain anonymous and unaccountable. These days, although truly anonymous accounts might seem difficult on LinkedIn, many people have overcome this problem, and even LinkedIn is demonstrating itself to be as good a place as any to drop your slop.

After a while, when the account has accumulated enough engagement on numerous such slop posts, you can sell the account for repurposing by someone else, but that won’t be obvious to subsequent visitors, because the account will remain anonymous or pseudonymous after the sale as well. I have seen ads for places willing to purchase or rent your LinkedIn account, provided it has a record of high engagement levels.

Alternatively, you can keep the account and hope that people will click on your other social media links. You can include a fake physical address without a problem, with confidence that nobody is going to show up there and find out it doesn’t exist. It doesn’t matter. In fact, nothing matters in this business model, which is precisely its charm.

And you can make as many of these anonymous accounts as you want, with each posting countless meaningless buckets of AI slop every day.

What the fuck wrong with people? And I’m also—particularly, in fact—including those people who, because of their stupidity and credulity, actually engage with this AI-generated garbage, often created by wretches who have nothing to offer other than endless demonstrations that, well, they have nothing to offer.

Again, what is wrong with people? Lots of things, it seems, and that’s on both sides of the ocean of AI slop that has flooded the online places some people think are real and have come to rely on, often as a replacement for real-world interaction with other members of their species. These people need to get out more.

LinkedIn is becoming just another social media cesspool.

In just a week or so, I have seen a rapid and disturbing increase in the number of posts thrown at me by Microsoft’s LinkedIn that are clearly Facebook-like engagement-harvesting slop.

A typical post describes at length some historical or current event that might have happened or a person, although some are clearly total fabrications. Sources are not cited, because there are none to cite.

Most of these posts are lengthy (as if someone told ChatGPT to write N hundred words about XYZ), and much of the writing has the undeniably cadence and style of AI.

Many of these posts are from non-anglophone places. Many of them are accompanied by AI-generated images, and sometimes by photographs that the poster is highly unlikely to have obtained permission to use. This turns a post that is merely annoying drivel into an unlawful act that is annoying drivel.

In any event, while Microsoft seems skilled at detecting when posts are in any way negative, particularly with regarding its platform or AI, and effectively shadow-bans such posts (as it did to this blog post today when it was uploaded to LinkedIn), it actively promotes the above-noted garbage, which is nothing more than AI-slop aimed at harvesting engagement for someone or something with nothing to say or offer.

This garbage needs to be kept on Facebook or other social media platforms, although an argument can be made that the social media platform called LinkedIn is rapidly coming to resemble the Facebook cesspool, and I’m making that argument.