Why are so many important journalists, educators, and artists too eager to complain about Artificial Intelligence?
Generative AI is an easy target for three reasons:
✅ ONE: Every sensible person hates the concept of “Techbros,” which has become a meme that amalgamates every misogynistic alpha-male stereotype stitched together into zip-up vests that seemingly get paid far too much for what they don’t seem to be doing.
✅ TWO: Large Language Model Platforms stole the Internet and put paywalls around the next phase of information technology, likely breaking the spirit (if not the language) of every copyright law in history. And they’re likely going to get away with breaking those laws because the digital landscape of the Internet remains largely unregulated, like an Old West bank with swinging half doors on the vault.
✅ THREE: Because every form of commercial art is being disrupted while tech companies suck up IP and the ownership of movies, films, and novels, which is all going back into those large language models regurgitating artistic assets into what many mindlessly call “AI Slop,” patting themselves on the back for being so clever as to repeat a meme that seems to matter to everyone and no one at the same time.
But Let’s Take a Beat From What Feels Right To Consider What May Be Right, In Spite of How We Feel.
Generative AI, along with its developers, product managers, marketers, lawyers, lobbyists, and sales professionals, is easily vilified in journalistic attack pieces from companies that openly sue Large Language Model Platforms, demanding access to their users’ activities. I question the integrity of such obviously biased journalism. I want to see more data, because I know where Enterprise is going with Generative AI.
There are companies out there, some born in the Cloud (meaning their applications, digital services, and data storage all run over the internet), who are synthesizing their entire data architectures into digital services empowering AI Agents to engage with any human in plain language and get shit done faster and, in some cases, much better with fewer resources used and less time wasted. That is happening across all industries right now.
The world has been using machine learning AI effectively for a long time, but some companies have been faster than others to adapt and adopt Generative AI. There are massive companies right now that will be demoted in earnings because smaller competitors are willing to experiment with and deploy Generative Artificial Intelligence integrated with all their first- and second-party data. While these big companies shuffle their feet and waste time in useless committees, the smaller competitors who adopt emerging AI technology are going to eat their market share.
How is Hollywood doing these days compared to Netflix? The answer is Netflix is buying Hollywood for a song.
Another factor to know is that not every Large Language Model is based on stolen IP from the Internet. Information fuels LLMs, and Enterprise information is highly protected. In industries like government, healthcare, and financial services, some information is highly regulated and mandated by law to be preserved and protected. Human beings are always the weakest link in the chain of protecting information. Time and again, it’s because a human being clicked a link they shouldn’t have behind their corporate firewall that the hack occurs. It’s not the technology at fault, but rather the buffoon who misused it.
The myth that Generative AI has no value is a memetic emotional manipulation tactic by those I’ll refer to as “TECHSPERTS.” Like a priest lecturing on the immoral danger of oral sex before marriage, these Techsperts can tell you all about why they hate AI, but they would never dirty their dirty bits by using it earnestly to produce value.
Like so many complex issues with human social interactions at scale, there is nuance that the AI haters refuse to acknowledge, or maybe they don’t know about it. My purpose here is to educate them with knowledge, offering a broader perspective while still acknowledging the serious risks and disruptions already occurring across all industries of commerce due to Generative AI. And there will likely be much more disruption to come from this technology.
Reader, beware of those who only complain about AI, writing and speaking in tones of great moral certainty while remaining conveniently vague about causes, mechanisms, and personal responsibility regarding the use of generative artificial intelligence in our personal and professional lives.
So instead of declaring what AI is, it’s worth exploring what the complaints about it reveal. So, let’s start there with The Seven Sins of Complaining about AI.
1. Nostalgia
When a learned expert says, “AI is ruining art, work, and writing,” which paradigm are they defending? The one where only certain people (read: “professional experts”) are allowed to command commercial entertainment, educational, and journalistic resources? Are they heralding a world in which the publishing and distribution of scholarship and art exist as gated communities?
Is the world these sleighted experts are constantly moaning about protecting from AI, the one where opportunities are meted out through back channels, political favors, and outright racist and classist nepotism? Is it the world where labor was slow, expensive, and largely invisible to those who funded it, with a thick layer of unnecessary middlemen following archaic processes that produced lesser value but still required unionized resources whose sole modern purpose is to retard progress in order to ensure the distribution of less-productive profit?
Are these so-called experts really protecting the same apparatus that gave us Donald Trump as the Reality TV Potentate of the Earth? Yes, it’s probably this world the moral technology experts are nostalgic for, but no modern artist with common sense guiding their thoughts would seek to build or work in that busted old world ruled by the morally vacant Hollywood and New York City illiterati.
Generative AI is disrupting our world, and a new order is emerging, one where artists and entrepreneurs can now own the entire supply chain of bringing ideas to markets of all sizes and demographics. And the illiterati are worried about their empty palms being put back in their pockets when the cold wind blows through an annoying crowd they are suddenly stuck standing in.
If the impacts of Generative AI feel like a loss to that ancient, corrupted industry that brought ideas to market for over a century, is it because something inherently valuable disappeared, or because something exclusive suddenly became accessible to those they consider commoners?
And how confident are these moral techsperts that the past they hold up so dearly ever really existed for any but a few privileged people?
Nostalgia is a weak argument against the ethical and moral use of modern computing in bringing ideas to the commercial market for the equally important purposes of entertainment and education.
2. Category Error
When the techspert says, “AI is stealing, lying, and cheating,” who or what exactly do they think is doing the stealing? Does technology make choices independently from humans? Or does technology execute instructions, like all complex computer code?
See, Generative AI doesn’t actually think as human beings think. It doesn’t do anything close to our level of thinking. In its current state, Generative AI technology is an effective probabilistic word calculator that performs a single function: find the next best word in a series based on the words presented and the information the model is grounded in. That’s it. Simple.
Generative AI, despite its cultural saturation as a topic of anxious conversation, is still just computer code, executing instructions.
If a human deploys AI carelessly, who is responsible for the outcome? The tool? The developer? The government? Or is assigning blame to the technology simply more comfortable than confronting human incentives that cause bent people to do horrible things to others with the tools at their disposal? Many of us remember what box cutters did on September 11th, 2001. Box cutters were a fearful image for several years after that day. But what we should have been focused on were the people holding them, and what didn’t prevent them from committing mass murder that day.
What problem do the techsperts solve by turning tools into straw man villains? Is there any difference in categorical error between the politician who vilifies the immigrant as the main problem and the moral technology journalist who thoughtlessly blames the tool and its creator instead of the wielder?
Change can be overwhelming, but change also brings opportunities to reset the balance according to natural law, meaning the way things naturally work when left to their own expressions of behavior. Ideally, human technology is the application of tools to the way nature works with the goal of producing an expected result that is (again, ideally) aligned to the common good.
Some technology builds (farming). Some destroys (fire). And some rebuild into a new cycle (atomic-nuclear fission). Generative AI is all three at once.
3. Status Panic
If AI didn’t threaten their position as techsperts, would they object as vociferously? I wonder whether they would be as concerned if Generative AI only replaced work they didn’t want to do? If the technology only empowered people whom they already respected, starting with themselves. They’re so proud of their big brains, aren’t they, these Techsperts?
Or are they gatekeeping the moral application of AI because the technology could make life easier for those they perceive as below them, rather than just doing that for them, their peers, and self-acknowledged superiors?
Is this petty character flaw of ego and pride really the reason they scold and scoff at the rest of us, looking down their noses before removing their glasses, rubbing their eyes, and solemnly shaking their heads at how ignorant we all are for moving the way the market of ideas wants to go?
When access expands and gatekeeping collapses, is it a marker of cultural decay or a necessary redistribution of power that opens up opportunities that didn’t exist a year ago?
And how do you tell the difference between ethical concern and wounded pride? The answer is you poke these experts somewhere else and watch how they react. Poke them in their pride because it always screams first and loudest.
4. Labor Romanticism
Which jobs are techsperts actually trying to protect?
I’ve successfully sold Enterprise software for many years across nearly every industry it’s possible to sell to (Energy, Transportation, Insurance, Banking, IT, Government, Retail, Consulting, etc.). I’ve almost seen it all, and I’ve nearly sold it all.
Now, I sell the future of AI for profit to large companies, and I’m effective at this job. I’m a global expert in my field, and I have the results to prove it. Writing and publishing are hobbies I’ve turned into a side business, but mostly just for funsies right now.
One of the consistent conversations I’m having today goes like this:
Customer (after seeing a relevant, value-laden technology demo, and being given commercial numbers for the cost to buy and implement it, weighed against the likely ROI):
“Oh, you know Jim is our top producer, and he will never use this technology. In fact, he doesn’t use any technology except for occasional emails. Old Jim likes to write things down on a paper and then hand it to his assistant, and she uses the technology to get the job done for Jim. And because he is our top producer, if Jimmy won’t use this technology, then it’s not worth it to us investing in it right now."
It turned out Jimmy was 56.
I’ve had this conversation four times in the past two months with different customers. And I’ve given the same response that I’ll tell you:
We CANNOT make major technology decisions based on people and roles who will be exiting the workforce in five years.
I’m talking about stubborn Boomers and pig-headed GenXers who refuse to change and expect to still be paid for doing last decade’s job last year.
If your job can be automated, it will. Accept it and start preparing for change or ejection from corporate work. If a task was repetitive, underpaid, and exhausting before AI touched it, why does its automation suddenly become immoral? Working efficiently is exactly what nature does. And working like nature works is a very intelligent thing for humans to do. Was the suffering of these inefficiencies more acceptable when humans absorbed it quietly because they got paid? Are we preserving inefficient work, or cheap dignity? And what happens when those goals conflict? And why preserve either when there may be a better option?
Technology CEOs are never going to beg for your handout, but we’re all going to beg for theirs if you don’t wake up and learn to use and shape the application of this technology. This is the world we live in, and this is your duty. Complaining about it will only make you feel better every time your post gets liked, and for most of us, that’s not enough.1
The choice to adopt Generative AI is yours, but make it fast before it’s made for you by those who aren’t as concerned with your welfare as you.
5. False Zero-Sum Thinking
Why do we assume AI gains must equal human losses?
I’m old enough to remember when bringing a graphing calculator to any test in high school was considered cheating. The thinking at the time of that decision was that they were teaching reasoning functions to the human mind using outdated, if still effective, methodologies. Those methods are now too slow and produce terrible results compared with students armed with calculators who were taught how to use them effectively to solve specific problems. It turns out my math teachers in the early 1990s should have taught me how to use a graphing calculator and tested me on its application. Eventually, math teachers started doing exactly that, teaching and testing the use of the graphing calculator as an informational reference and a tool for executing specialized algorithms to solve specific problems.
We are each challenged by the cultural and historical limitations of the educational institutions we attended and the commercial institutions that feed, house, clothe, and entertain us. And again, we are going through the same struggle with the calculator, only now it’s Generative AI. Shouldn’t we get it right this time and start testing with the calculator?
When calculators appeared, did mathematicians disappear? When video cameras and editing software in our pockets became ubiquitous, did making movies end? Or did the nature of participation with the functional purposes of these tools change and let us do more and better human work with greater ease? The jury is still out on the last one, so the wise aren’t clicking subscribe on the AI Slop meme just yet. Smart people are taking a wait-and-see, long-term view of this technology while tactically jumping in to experiment with its applications.
If Generative AI amplifies capability, who decides how that leverage is used? And what responsibility comes with refusing to engage while others do?
Is the danger really replacement, or should we instead be wary of those who threaten disengagement and the fracturing of modern digital labor methods in order to preserve a system that wasn’t working all that well to begin with?
6. Moral Outsourcing
Who do techsperts expect to fix this problem? Governments? Corporations? Committees yet to be formed (no doubt staffed by the best techsperts from all the prestigious pillars of old media)?
While waiting for perfect regulation, followed by pristine judicial review, and honest broker police enforcing the law through threat of bankruptcy or the gun, how is one to justify our daily choices when a compelling option is so morally vilified on one side?
What is morally acceptable to automate? Is it only what techsperts verify, publish, and ignore?
Is demanding ethical clarity from institutions a sincere request or a way to delay personal accountability for getting in line with what might work best for all instead of the privileged few?
At what point does complaining become avoidance, impasse, and stagnation? Not even being open to applying Generative AI technology is a fool’s game that only the already successful Techspert can play. But you and I can’t play that moral game of “Earning Without Learning” successfully.
7. Refusal to Learn
How well do these people understand the systems they condemn? Have they applied them deeply and earnestly, or just enough to confirm their worst fears? Are their critiques grounded in firsthand experience or in YouTube outrage videos, sympathetic screenshots, and polemical summaries hot-dipped in the wax of oversimplification?
If you refuse to learn how something works, on what basis do you claim authority over its use and impact? Is your resistance informed skepticism, or is it simply discomfort with being a beginner again? There’s that pesky ego pride showing its behind.
The Problem Behind The Problem
Anyone who has worked a day in professional consulting knows that the problem the client comes to you with is never the actual problem. You have to dig a little. So, let’s dig. What if AI isn’t the problem? What if it’s a stress test? What if Generative AI exposes those who relied on unfair and ineffective industries, revealing the motives of those seeking to protect a system of assumed scarcity that Generative AI technology has shown to be potentially abundant?
Unnecessary complexity is not a virtue, and doing work we don’t have to do for less value than we’d get by applying emerging technology is like eating stupid sandwiches every day and expecting to get smart. So, let’s be smart instead.
After the fall of kings, humans outsourced our thinking to institutions that grew more complex and more corrupt over centuries. By any moral measure, every institution concocted by the limited minds of human beings has failed to deliver a consistent experience of human fulfillment worldwide. There is no hope left in any institution.
But there is hope in human beings working efficiently together with natural law to deliver a more consistent experience of living that is calmer, wiser, and kinder. This alignment problem is one we can solve with technology, and I argue it’s the only problem that matters, with everything else being either a supporting argument or a convenient distraction.
Hating AI is a convenient distraction being used to manipulate your emotions and steer you away from opportunity. We don’t have time to listen to biased Techsperts with axes to grind because they once played well in a rigged game and are suddenly upset that they now have to compete against the rest of us in the open with technology they don’t like and probably don’t understand.
When they complain about AI, are they protecting humanity or protecting themselves? Let’s each be an honest broker and admit which one gives you more anxiety, the AI or the people who might use it to do better than you can alone without it.
*no humans were harmed in the writing of this essay.
After all, we can’t all be Techsperts who converted paper book readers gathered over decades into instantly commoditized digital subscribers. But that’s a good gig if you can get it.







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