The fear-mongering around Generative AI and ChatGPT taking jobs from hard-working, knowledge-economy humans has reached a fever pitch. 

Without naming names and linking links (I'd rather keep you here, more on that later), a simple web search returns hundreds of articles, listicles and correlation thought pieces, all written to harvest the click of the average bread-winner by instilling a panic image of the machines rising up and doing for free what you get paid for.

I've been working with Natural Language Generation (NLG) and the roots of Generative AI since 2010, which, on the technology timeline, is the Mesozoic Era.

And I've got some good news for you. And you might get an ironic chuckle when I tell you which jobs are immediately in danger of being erased.

How Technology Impacts the Bottom-Feeders

My journey into NLG began with a company called Automated Insights, which pioneered NLG tech to create narrative stories out of data in walled data gardens like sports, finance, marketing and so on. 

My job was to create the algorithms which analyzed the data and turned it into words. We sold to a private equity firm in 2015 and our tech, prehistoric as its origins may be, is still being utilized by Yahoo Fantasy Football, the Associated Press and dozens of other organizations. 

Anyway, as we made our meteoric rise from two engineers and a handful of young developers to a VC-backed, 75-person company, journalists took interest.

I did a lot of interviews with major media outlets and almost every single interview ended with the journalist turning off their recording device and asking, off the record:

"You're coming for my job, aren't you?"

My response was to get them back on the record and tell them firmly and flatly, no. Not you. While there were plenty of technological shifts plaguing journalism and media at the time, we weren't part of the problem. 

You know who we were coming for? Data scientists. And only the lazy ones at that.

In the mid-2010s, data science existed in two camps. In one camp were true data scientists who could take billions of rows of data and generate valuable, useful insights from it.

We could do that too and we realized we could automate a lot of it. Thus our name, Automated Insights.

The jobs that our NLG/Generative AI technology "took," were in the other data science camp. In the 2010s, with the influx of massive sets of data being released online, thanks to increases in processing power and innovations like Amazon's AWS infrastructure, there was too much data for data scientists to handle.

A new class of data scientists sprung up, basically anyone who knew SQL or Python and could game the system and generate $100,000-plus salaries for doing simple things that machines could automate. 

What I learned and what I've carried with me since those days is that technology has a way of calling out the bottom feeders in any industry and AI does it almost instantaneously. That's where the fear gets mongered.

However, ChatGPT is not coming for the bottom-feeding knowledge workers. Not yet. Because this slice of AI is niche and all Generative AI does is automate the creation of content.

So if your job is in the creator economy and if you're not very good at it, I've got some bad news for you. 

The World Doesn't Need More Content

It needs more targeted content. That's where Generative AI and ChatGPT hold the most promise. And they're coming for a camp within the creator economy.

The creator economy has two classes – not camps, I'll get to the camps later. 

In one class, you've got folks who are creating original content at the individual level (hello), in the form of words, music, film, art and even food and crafts. They're running businesses that are more creativity-based than product-based.

They target an audience as opposed to customers and they generate revenue from the attention of that audience.

This class is not in danger, yet. But they sense it. Generative AI is one of the concerns that brought about the entertainment industry's writer's strike.

In the other creator economy class, you've got people who discuss and critique content. They define and opine. It's a legit way to make a living and you probably have a favorite.

I'll point to Dan Olson and Lindsay Ellis, who do a great job of blending critique and knowledge, using creative elements to deliver their product to their audience and generate revenue. 

This is the class of the industry that's most in danger, but there are two camps within that class. 

The first camp is the legit creator, the Olsons and the Ellises. Then you've got the bottom-feeder camp, people who create low-quality and easily-replicable content, revolving around or even "stealing" copyrighted first-class original content, to game the creator-economy infrastructure and algorithms, flooding the market for a piece of that creator revenue. 

You folks are done.

Replace Entrepreneurs With Creators

Outside of my day job as head of product for a high-tech, high-growth startup, I create content that portends to make more and better entrepreneurs by writing pieces like this and more targeted Q&A content at Teaching Startup. 

So I know both the entrepreneurial ecosystem and the creator ecosystem intimately.

In the startup ecosystem, there have always been and always will be bottom-feeding "gamers" who sell a "business" based on manipulating some existing system that has a low barrier-to-entry to transact real cash money. 

A lot of creator-economy platforms are targets for these gamers. In my "word" world, it's Medium and Substack, but it's also Patreon, YouTube, podcasts, even Amazon with its affiliate links and Google with its pay-per-click ads.

These gamers plague Kickstarter and crowdfunding. They're rampant in sectors like crypto and NFTs, which is basically the unholy marriage of the creator economy and money.

Now, my point is, in the startup ecosystem, there are organizations and platforms that support and educate entrepreneurs (hello).

The organizations that promote that type of "gaming" business are, of course, not considered legitimate. However, the organizations that even tolerate that type of business are often held just as culpable and risk their reputations as legitimate entrepreneurship economy platforms. 

Replace "entrepreneurs" with "creators" and I do think, with the proliferation of a massive influx of automated, machine-generated, low-quality content, creator platforms like Medium and Substack are at a crossroads and will soon have a choice to make. 

Do they tolerate this low-quality content on a massive scale, and keep the attention-economy gravy train of algorithms and clicks and views going, or do they proactively challenge the low-quality content?

The latter will require an investment in both technology and the human element to raise the quality bar before low-quality content destroys their reputation as a legitimate platform.

And eventually, Generative AI tech will bring the same crossroads moment to digital art platforms, podcast platforms, video platforms and so on. 

Then it will hit the knowledge economy, at which point, knowledge workers can start worrying about their jobs. But going back to the 2010s, I already saw this happen.

Not just with lazy data scientists, but with almost every white-collar, butt-in-a-chair, pixel-pushing, spreadsheet-spelunking job that the influx of data wrought on the workforce. Those jobs are long gone or are only being used as stepping stones to turn "knowledge workers" into "knowledgeable workers."

Those are two distinct camps that are very easy to identify. You're probably in the latter and if you're not, well, you've likely still got five to ten years to get there before you become obsolete.

Inc