People love to utter phrases like “data is the new oil” or “data is the new gold.” When we hear these phrases, we immediately think of businesses and big data, not the simple aspects of our daily lives. However, this obsession with data seeps into every crevice of our existence, even when the data is worthless. The reality is that people find activities less valuable, or even pointless, unless they have data about them. This is like Nikola Tesla, who had a terrible meal if his portions weren’t divisible by three.
Many can’t just wake up well rested after a good night’s sleep. They need to confirm using data from a sleep tracker, ensuring that their sleep duration, O2 saturation, and heart rate variability fall within specific ranges. In many cases, reality is overridden by data, despite the fact that devices aren’t foolproof. When your device conflicts with your reality, the device wins because… data.
Modern readers are also data-obsessed. They hunger for a wealth of statistics and datapoints that they can poke, prod, and analyze. They seem more infatuated with data about their reading than the reading itself. As it so often does, our modern world, with its hyperfocus on optimization, shifts our attention away from what matters and leads us to optimize the wrong things. This result leaves us worse off while giving us the illusion of productivity.
Reading Data Obsession
In my previous post on reading, one thing I failed to mention was people’s obsession with data about their reading. As I mentioned in that post, I prefer physical copies of books, but I also have an eReader. In 2026, I switched from a Kindle to a Kobo as my primary eReader. As I poked around the Kobo community, I found that people were very excited about StoryGraph coming to Kobo.
For those unfamiliar, StoryGraph is an application that seems to suck the value and fun out of reading. StoryGraph has three main features: reading stats, personalized recommendations (including mood-based recommendations), and a read-with-friends feature. None of which enhances the reading experience. However, all of which are detrimental.
Read With Friends
The read-with-friends feature is a clear drawback. Yes, please interrupt the flow and focus of my reading so I can see what one of my dumb friends has to say about it. This provides the same type of distraction as social media, now available on your dedicated reading device.
Algorithmic Shoving Match
People will argue with me about algorithmic recommendations until the heat death of the universe. They tell me how AI is much better than other forms of recommendation. I’m sure some will swear by the value it provides. I mean, it’s not like I haven’t benefited from algorithmic recommendations myself, so fair enough. Despite this, mediating everything through algorithms isn’t the great idea it’s cracked up to be.
First of all, you take a social activity, getting recommendations from others, and turn it into an anti-social one, taking whatever recommendations the algorithm spits out. People may say, if the recommendations are good, who cares? Maybe. But other forms of discovery may provide even better value.
Ultimately, the algorithm removes any chance from the equation. There is never any room for happy accidents. Every decision is bent towards the mean, eliminating any chance of discovery as you are shoved towards the narrow selection of books that others “like you” have read. However, this article is about data, so let’s look at that.
The Data
The image below shows stats from StoryGraph. Not a single stat being tracked here is useful for your reading experience. In fact, I’d argue they are the opposite.
Describing the data from left to right and top to bottom, we have, who gives a shit, irrelevant, pointless, and stupid. What’s displayed is data for data’s sake and tells you nothing useful. Let’s start with Pace and end with the number of books and pages.
Pace
What does the Pace chart even tell you? Nothing. Not all books are created equal. Some are harder to read than others. Some authors even make up their own language, and still others contain dense technical content. There’s nothing to track and nothing to optimize. This data is irrelevant.
Despite its irrelevance, whenever data is shown, people tend to want to “optimize” that data. Taking actionable steps based on this pace data can mean you beat yourself up about nothing at all. Maybe you purposefully try to read faster to optimize your pace and, in doing so, degrade your comprehension. Maybe you chose different books that are easier to read. Regardless, this isn’t good for your reading experience.
Moods
What about Moods? It’s pointless to keep a historical record of this data. Just imagine what the chart would look like for someone who is goth. Like, what are they supposed to do? Balance their Poe with some comedy to provide levity for their tortured soul? Call me NightPain.
I guess Mood is intended to be a check yourself before you wreck yourself, but it’s just pointless. Read what you are in the mood for, and read what you want. Life is too short for anything else. Obsessing over balancing your reading mood can diminish the value of the reading experience, nudging you in different directions for absolutely no purpose.
Ratings
Tracking your average rating of books is just plain stupid. I mean, all of your values are going to be right-skewed, heavily weighted toward the high end. Why wouldn’t they? Who spends time reading a book they’d give 1.5 stars? The reality is, nobody keeps reading a bad book unless it’s for some other purpose, such as a class or research.
Number of Books and Pages
Of all the data shown, the number of books and pages will be the most contentious. Let’s strip reading down to its core and focus on the benefits. What does the number of books you’ve read tell you about the benefits you received from reading? More specifically, what does the number of pages read tell you about the benefits you receive? Does reading fewer books mean that you’ve gotten less value? By now, it should be obvious that this data tells you nothing.
For those who still think this data is relevant, let’s consider that War and Peace, with its approximately 560k words, is one book. It’s easy for one large book to throw off your statistics.
Regardless of length, as I previously mentioned, some books are more difficult to read than others, but this doesn’t make them less valuable. However, given that long books will throw off your stats, you may be tempted to only read smaller books to keep your stats up. That doesn’t sound very valuable for your reading experience.
I have no idea how many books I read last year, or the year before that. Not having data doesn’t bother me because it has nothing to do with the value I gained from my reading.
Despite being an irrelevant metric, people love tracking how many books they read. Knowing their number means they can talk about it online. Reading becomes something to be performed, and that performance is an important part of reading for these people.
Still, some may claim that setting a target for reading a number of books gives people a goal to shoot for. First of all, you don’t need an app for that. Second, how does that number relate to the value from reading? Some may say that setting this goal forces them to set time aside for reading. Okay, but if the number of books is just a proxy for something else, then measure the proxy.
Ultimately, if people are looking for a way to optimize their reading, it’s not about the number of books, words, or pages. It’s about time.
Optimizing Reading
True optimization of reading requires manipulating factors that lie outside the pages of a book. It involves an investment of time, space, and attention.
If you are looking to truly optimize your reading, the most important thing you can do is dedicate time to it. Without dedicating time, there’s no way to build a habit. It’s the same when you are trying to start a workout routine. Find the time and schedule that work for you, and do your best to stick with them. The more you do it, the easier it will get.
You also need to create the space for reading. Trying to read surrounded by distractions isn’t a recipe for success. However, as a positive effect, the better you get at focused reading, the better you get at tuning out distractions. In the meantime, do your best to keep distractions to a minimum. Silence devices and notifications. Utilize do-not-disturb mode if necessary. Better yet, keep your devices in a different room.
Attention is required for reading. I know, attention is in short supply these days. Deep reading is an exercise with multiple benefits, including increased attention. However, you need to be comfortable with being uncomfortable. If you haven’t read in a while, you’ll experience some discomfort. You may get easily distracted, your mind may drift, and you have to reread passages. This is because your brain has been rewired. Don’t get frustrated or beat yourself up about it. Just stick with it, you’ll see the change.
Conclusion
Data has become a security blanket. Something we are happy to have, whether it provides value or not. It’s there if we need it. However, whenever we are shown data, we need to ask how it’s valuable to whatever we are trying to accomplish. This will differentiate between data that’s truly helpful and data as a distraction.
Accidents aren’t always bad. That’s why we have the phrase “happy accidents.” When algorithms are involved, we never leave room for chance or happy accidents. Some would call this a feature, but I call it a bug.
Talk to any tech bro, and they’ll be happy to tell you, scarcity is about to become a thing of the past. Abundance is coming and we are going to have so much awesomeness that we can’t even fathom how amazing it will be. Sam Altman recently said that society has been structured around managing scarcity, and now we need to get used to managing abundance. Hell yeah, bro! There’s just one problem. Well… there are many problems, but a big one that isn’t talked about is that nothing in abundance is worth anything. This fact alone can bring visions of utopian abundance crashing down like a house of cards in a tornado, and it’s a lesson we can learn from Napster. Yes, that Napster.
AI, Abundance, and the Future
We are told that scarcity is about to be in our rearview and the bright shiny utopia is out the windshield. With AI and robots doing all of the work, the cost of goods and services will crash to near zero. It’s yachts and Lambos for everyone! Oh, there’s just the small problem that nobody has a job. Damn, there goes my Lambo.
These takes are common, and you see them every day. For example, here’s a random one I saw this morning.
But this isn’t the only claim. They also claim it will cure all diseases and won’t just end poverty, but make everyone rich.
The “things will be free” argument is typically packed among heaps of bullshit, as seen in these examples. It’s intended to overwhelm your critical thinking skills. Let’s just acknowledge that none of this makes sense.
They state that people are going to lose their jobs, but don’t worry, because AI is going to make everything super awesome! They also claim that in this new environment, people are going to become obscenely rich by giving you free shit. Admittedly, I don’t have an MBA, but that doesn’t seem to be how business works.
I’ve covered this topic before in Techno-Communism and the Things Will Cost Nothing Fallacy. In that article, I attacked some of the core premises of this fallacy. I even covered the fact that, despite the premise, things will still cost something, and that nobody is investing in companies to produce zero-dollar goods and services. I may only lightly recover some of that ground, so please refer to the previous article for the core arguments.
This is an important topic to consider now because we will see better AI technologies. We will eventually get to AGI. Many of the nonsense claims people make about today’s LLMs will be true of this new technology, and the impacts will be far-reaching. We need to consider how this environment affects us as humans and our culture.
In this article, I focus on value and frame the lesson of Napster as it relates to abundance and the future.
Napster
I have to do some work here. Let me explain Napster to young millennials and Gen Z, who’ve always had reliable internet connections and never had to wait for anything. Napster was a peer-to-peer file-sharing application that mostly focused on music. If there was a song or album you wanted, you’d search for it and download the MP3s. The songs were encoded at varying quality levels, and depending on how many people had the files and their internet connection speeds, you may have to wait a day or two for the songs or album to download. Oh, and surprise! Sometimes the files you downloaded weren’t what they claimed to be at all.
A look back on the UI of Napster is enough to haunt your dreams.
I use the term “was” in reference to Napster, but apparently, they are still around and drumroll… They’ve pivoted into AI slop. Imagine that! Although you might think this is the lesson of this article, it’s not. It’s just a fun byproduct in the AI era. Enjoy.
Back in 2000, Metallica sued Napster. For clarification, Metallica was a band of aging gentlemen who sounded like Avenged Sevenfold. Sad but true.
At the time, I remembered thinking how backward Metallica looked, like they were just some aging rock band that didn’t understand technology. Most of all, they just looked greedy. People just wanted the freedom to use their music as they wished. Many downloaded MP3s of albums they already owned. For example, maybe you already had Metallica’s black album on tape or found downloading MP3s easier than ripping them from the CD you owned. CDs were also cumbersome, and taking a bunch with you on a road trip was a pain. Sure, people pirated music, but that was a minority. My perspective solidified as the space for digital music grew.
As digital music grew, it came with heavy-handed DRM (Digital Rights Management), which meant that, despite purchasing the music legally, you couldn’t use the music the way you wanted to or play it on devices you chose. Hell, Sony even went so far as to install malware on your computer in an attempt to stop piracy.
Then came streaming, and music essentially became free. The lesson that started with Napster now came full circle with services like Spotify and Apple Music. However, inheriting a gigantic problem.
Music Is Now Free and Worth Nothing
In the ignorance of my youth, I fell victim to a condition most young people do. I failed to see the big picture. When something is free, it is essentially worth nothing. Nobody values music today, and why should they? There was no friction to access it. Nobody had to go to a store and choose between one album and another. Nobody had to wait in line for a midnight release from their favorite artist. Nobody had to choose which albums to take with them on a road trip. Although this sounds like a major inconvenience, it enhanced the value of music for both the listener and the artist. These activities created loyalty and forged a bond.
Musicians were well aware that listeners had a choice when buying music and felt responsible for creating art to the best of their ability. Or at least, this concept was in the back of their mind. Artists also made money selling music, which gave them the freedom to spend more time on their craft, further enhancing their art/product. This environment didn’t require an artist to be as big as Taylor Swift to do so, either.
Purchasing music connected listeners to artists in a way that streaming doesn’t. When people bought an album, they listened to the album the way the artist intended. They could evoke emotion through ebbs and flows, taking people on a musical journey. With streaming, people just add things to playlists and hit shuffle. An artistic vision of an album is completely dismantled, chucked into the chaos of a musical vortex, spinning alongside Snoop Dogg and Conway Twitty.
Now, artists blast out music as fast as they can to increase their breadth because more music means more potential streams. Not releasing music at a steady cadence creates the impression that you’ll be forgotten in the vast sea of content.
Of course, artists now have to make money in other ways, spending less time on their music. They used to agonize over albums and songs, pouring their hearts and souls into them and taking the time to get things right. They also took creative chances. Now, music is collapsing into a formulaic structure where all music sounds the same, and artists bash the formula like the preprogrammed buttons in Mortal Kombat.
Music has become less something to be listened to and more something that provides background noise in daily life. It doesn’t take pride of place as an activity. It’s wallpaper.
Musical Abundance and Lost Value
What we have today is essentially musical abundance. There’s literally so much music on streaming platforms that people can’t find it. In 2024, it was reported that Spotify had over 100 million songs with over 60,000 new songs added per day. Want to guess just how much of that is good music? Certainly less than 1%, there is no way you can convince me that there are 1 million good songs on the platform. In this world of abundance, most things are shit.
As an artist, you basically have to give your music away. As a listener, music is nothing to you. If one song isn’t available, you just listen to something else without emotion. Music, possibly humanity’s very first art form and something that has meant so much to so many humans throughout history, is now stripped of its value and devoid of connection and meaning. In reality, musical abundance hasn’t led to positive outcomes for either the artist or the listener, and this is our lesson here.
In reality, musical abundance hasn’t led to positive outcomes for either the artist or the listener.
The healing effects, the satisfaction, the connection, the memories, and most of the factors that made music valuable and essential to humanity are now gone. Industrialized, homogenized, and mass-produced music has stripped the art of its value. For the far fewer than 1% of songs that aren’t terrible, we are left with momentary blips of completely forgettable, average sounds labeled as music that just happen to hit our ears. No wonder kids are rediscovering the classics.
There’s no going back. Once a technology is implemented, even if it makes things worse, there is no going back. We are stuck with it, which is why it’s so important to understand the trade-offs and implement mitigations before adopting a technology. We just can’t seem to do that.
Now, the music industry also has its share of blame here. It got greedy. A CD never should have cost anywhere near 20 dollars, unless it was a double album or some other special edition. $9.99 was a fair price and should have been the cost for an album. But that time has passed.
Abundance Math Doesn’t Make Sense
Let’s set a couple of foundations for abundance. The premise behind abundance is that companies will employ AI and robots instead of human workers. So, first and foremost, no jobs for most people on the planet.
We are told by futurists and AI bros that abundance will bring a utopia. That everything will be democratized. The cost of everything will be near zero, compute, goods, intelligence, development, and on and on. With so many things driven to essentially zero, not only does the math behind abundance not make sense, but its value as well, as we’ve seen with music.
With so many things driven to essentially zero, not only does the math behind abundance not make sense, but its value as well, as we’ve seen with music.
Let’s start off by addressing the use of the term democratize. Whenever an AI bro uses the term democratize, they actually mean something else: either devalue, degrade, or destroy. I call these the 3 D’s, and I’ve covered this before. But let’s get back to cost and value.
It doesn’t matter if the cost of things is driven to near zero. If they cost something and you have nothing, you still can’t afford it. If a brand new car costs a dollar and you don’t have a dollar, its inexpensiveness doesn’t change the fact that you have to walk. Assistance programs like UBI will hardly have us living lives of luxury.
When people have little to no money, they tend to focus on pure necessities. Pretty much the entire global economy is focused on selling us stuff that we want, not necessarily things we need. That means in this situation of supposed abundance, most companies on the planet disappear.
This shift will rewire our values. I’ve discussed how this may happen in retail through the implementation of agentic shopping. This rewiring isn’t lost on people who are thinking about these issues. The CEO of Walmart resigned because of AI’s potential to upend retail. If successful, more rewiring is on the way and will upend the entire fabric of the modern world. Just imagine, instead of lusting after material things, the dominant belief in the world was meditation and inner peace. Not great for business.
In a world of abundance, many large companies probably won’t exist. Diversification and competition will eat them alive. The abundance of tools and techniques will allow for quick imitation. Sure, some will remain, kind of like the company store in a mining town, but the economic landscape will look vastly different.
We are told that, despite things being so cheap, companies will make money from volume. But once again, with distribution spread across many small companies, it’s hard to see how that amounts to anything more than table scraps. This begs the question, then, where will the money for UBI come from? Even worse, instead of UBI, we may end up with company vouchers, forcing us to buy from a single company or to obtain vouchers for things we don’t need.
Abundance Equals Sameness
Henry Ford is quoted as saying of the Model T that a customer can have any color they want, as long as it’s black. There’s a lesson here for technological abundance. Many are laboring under the delusion that a world of abundance looks like the world of today, just with more. But the reality is this world will look totally different.
The world of technological abundance laid out before us isn’t a world of diverse beauty with green grass and open skies where people spend their days writing poetry and contemplating their existence in the universe. It’s a homogenized world of sameness where everything collapses into uniformity because this uniformity is predictable and can be mass-produced at scale. Individuality and one-offs are unpredictable and costly, and thus must be crushed. It’s a world where humans become little more than a burden.
Sure, people will try to control for this uniformity in the ways that they can. For example, if a family has a 3D printer at home, they have some control over what they print. However, they still need the resources to buy the printer and printing materials, and most would rely on the available designs. This concept of a utopia is starting to smell pretty rank.
New Business? Maybe.
I’m sure it will be said that I’m not envisioning the new businesses that will sprout up and how humans will change their behavior. Sure, the world is a complex place that defies prediction. I acknowledge that adaptation is possible, and surely, humans will change their behavior. They won’t have a choice. But it isn’t going to turn out the way people think.
Just shooting from the hip here, but a world in which people don’t have money and things are essentially free doesn’t seem like a robust environment for business. You won’t see a plethora of new startups all angling for that gigantic pot of nonexistent money.
You won’t see a plethora of new startups all angling for that pot of nonexistent money.
People invest in companies on the hopes of a big return. They take chances and are willing to take losses, but the gambler loses big in this new environment. Because even an investor with money and a successful business bet basically converts that investment into less money. In this environment, there are no incentives to improve, and everything will plateau at mediocrity to preserve existing margins.
Another thing to consider is that this environment is inherently fragile. Any problem, no matter how small, could cause a company to lose money since the margins would be so tight. Any amount of downtime, errors, or integrity issues, whether accidental or intentional, could be catastrophic. The predictable answer from the AI bro is: “But the AI won’t make mistakes.” To which I say, good luck with that.
Now, is it possible for us to evolve beyond money or capital toward a society that aligns its value with other meaningful activities and goals? Sure, it’s possible. But, once again, this wouldn’t be good for the business bros who are pushing this fallacy the hardest. In a world where abundance is truly successful and is beneficial to humanity, it’s bad for business.
Complexities and Negative Impacts
A full conversation on the negative impacts is outside the scope of this article. However, I have covered some of these before.
I’d argue that these people vastly underestimate the world’s complexities and the sheer number of negative impacts this change brings, not just on the economics but on humanity as a whole. There are basically only one or two ways this can kind of go right, and an incalculable number of ways it can go wrong. For example, this is an environment tailor-made for surveillance and totalitarianism. How can it not when your existence is completely dependent on external factors like the state or the generosity of a benefactor?
If you think that people will tolerate a few trillionaires while the world suffers mass unemployment, you are dead wrong. This is so obvious it shouldn’t need to be stated. I can completely envision a group calling themselves The Children of Ludd wreaking havoc. Only their anger won’t be isolated to the machines in data centers and their embodiments out in the world. They’ll direct their anger at the people they see exploiting the situation as well. It won’t be pretty.
I can completely envision a group calling themselves The Children of Ludd wreaking havoc.
In many cases, this new environment will make people far more tribal and extreme and willing to believe just about anything, but this is a topic for another day.
Conclusion
The vision of abundance defined by the tech bros is an absolute fallacy. It’s a world in which AI is talked about more like magic and less like an actual technology. From this tap spouts outlandish claims with no foundation in reality. As we’ve seen, even when abundance works, it has a degradation effect.
A world of successful abundance appears to be bad for business, which raises the question: Why are so many business leaders pushing this concept? If I had to guess, it’s that they hope to make their money before this big crash and leave humanity to pick up the pieces.
Here’s a secret: turning books into statistics won’t bring AGI, cures for cancer, utopia, or any number of useful inventions that we are told are merely 12 to 18 months away. This activity also won’t bring their users wisdom. As a society, we are told that if we don’t let companies freely pillage the intellectual work of our past and present, we won’t get the life of leisure we are promised. But turning War and Peace into statistics won’t lead to significant breakthroughs. It won’t even bring knowledge… for you.
I believe that many of the people who work at the big AI companies know that training on a large corpus of non-domain-related works won’t lead to AGI or significant breakthroughs in areas such as cancer research, but they do know it may lead to breakthroughs in manipulation, and that has them interested.
Project Panama: Books Into Statistics
Recently, the Washington Post had an article about Anthropic’s Project Panama, a secret project to destructively scan every book on the planet. The image is shocking, and the whole situation feels dirty, which is probably why Anthropic tried to keep it a secret. Although it was found that they didn’t break any laws, they tried to keep it secret because they knew this would have a negative public perception. Mission accomplished.
In one sense, this is an attempt to obtain untainted training data. The internet is submerged in AI slop after the launch of ChatGPT. AI slop is good enough for the internet, but not so good for AI training. AI models tend to degrade when trained on their own outputs, a condition known as model collapse. So, instead of a model getting better, it gets worse. Seems models know what’s better for them than we do.
But the quest for untainted training data isn’t the whole story. If you are trying to scan every book on the planet, then you’ve made a decision to ingest and train AI on books of all kinds, inaccurate books, dated books, and even “bad” books. In short, accuracy isn’t the goal here.
Okay, so what’s a “bad” book? I mean books with universally accepted bad ideas, poor stories, poor writing, and many other issues. Trying to train on all books means you’ve made a conscious decision to also train on material such as Mein Kampf and The Turner Diaries. That’s right, you’ve “trained” on it, not assigned it to an AI model as homework for a classroom discussion. There are a few things I can say with 100% certainty, although I can say this: there is nothing in the works of books like Mein Kampf that will cure cancer.
Bad books shouldn’t be eliminated, although bad for AI, they can be beneficial for humans. You can always stop reading a poor novel or other books you feel aren’t providing proper value for your effort. As for books with bad ideas, when a human reads one, they can do so from a given perspective, trying to formulate a certain understanding. They can even be read with the intent of identifying and avoiding certain conditions in the future. Only a fool would think reading a book with bad ideas is always bad.
It’s basically just nom nomming the data, creating statistical grenades.
When an AI trains on a bad book, it incorporates the ideas and even the poor sense of style. It isn’t providing any perspective. It’s basically just nom nomming the data, creating statistical grenades. I’m certainly not claiming that training on Mein Kampf creates an AI Hitler, there are other ways that can happen. What I am saying is that the ideas and concepts contained in these books are kicking around in there somewhere, even if they are shoved way down in the statistical distribution. What this ultimately means is unclear.
I don’t mean to be disingenuous here. The definition of a “bad” book is highly subjective. This quickly devolves into a who decides scenario, which could lead to unintended consequences of its own. My point is that there should be more purpose to the activity.
There were also plenty of idiotic takes on Project Panama. Never underestimate the true cluelessness of the e/acc community. One thing they effectively accelerate their own idiocy.
One of my favorite arguments from the e/acc community was that they weren’t destroying the books, they were preserving them. To which I joked that it was preservation through destruction. Preservation through destruction sounds like a quote that could be ripped from Orwell, just like the pages of his books for Project Panama. Turning books into statistics to monetize them doesn’t preserve them in any sense of the word. This is a silly argument that can be destroyed by one simple question. If they are preserved through this process, then where are they?
Preservation through destruction sounds like a quote that could be ripped from Orwell, just like the pages of his books for Project Panama.
Manipulation and Imitation
So, why are AI companies foaming at the mouth to get their hands on books that seem to have nothing to do with their goals? If I had to guess, it has to do with a couple of factors.
The more of this type of data ingested for training, the more the system may be able to imitate humans under a variety of conditions. This can be used by users of the system to create a “personality” from the tool, or, more importantly, to manipulate people, fooling them into thinking the AI is actually a human. This manipulation could be applied in situations like customer service. I experienced this recently.
A broken water pipe forced me to call some local plumbing companies after hours. Quite a few of them were using a call service with what sounded like a human in a call center, complete with office background noise. This was clearly done to manipulate users. Oddly enough, when asked if they were AI, only a couple responded that they were. This is the type of manipulation that I find unacceptable. Gary Marcus recently wrote an article about this as well.
Of course, these conditions can also be used to claim that the AI has a consciousness or a self that needs to be protected. This is pure SciFi bullshit meant to ramp up the hype.
Another interesting and related condition is pastiche. The more of this type of data the model is trained on, the better it may get at imitating specific forms of human style. People can use these to fool themselves into thinking they are being creative.
As an example, generative AI can reliably generate books. They aren’t good books, or well-informed books, or well-written books, or accurate books, or present new information, or new perspectives, or any of the other countless characteristics we associate with a good book. But words slathered onto pages… This it can do reliably.
Generative AI hasn’t cured cancer yet, but it excels at creating slop. Slop is literally the number one use case for generative AI today, arguably more than coding. There’s no doubt that AI companies want more of this behavior to keep people engaged.
But let’s get back to books.
Next-Gen Nerds
When I was growing up, being called a nerd was considered a bad thing, and nerds read a lot. Now, they are popular, wear black t-shirts and blue jeans, and claim that reading is for losers. Their perspective is warped by an “optimization-at-all-costs” mindset. But don’t take my word for it.
In November of 2022, notorious tech bro and crypto con man Sam Bankman-Fried told a writer interviewing him, “I would never read a book.” He went on to say, “I’m very skeptical of books. I don’t want to say no book is ever worth reading, but I actually do believe something pretty close to that. I think, if you wrote a book, you fucked up, and it should have been a six-paragraph blog post.”
That’s the next-gen nerd’s perspective. An entire book should be six paragraphs. But why stop there? Why not six bullet points? Seems I just out-optimized the optimizer! In fact, many of their points can be addressed by reductio ad absurdum.
This perspective does not serve people well and further devalues books. The theory is that if books can be reduced to numbers, then the ideas they contain can be made “useful” in a programmatic or more efficient way. But ideas from books can’t be reduced to numbers, just like The Hitchhiker’s Guide to the Galaxy can’t be reduced to 42.
Oddly enough, when reducing books to numbers, you remove the content from context. Context, the very thing both humans and AIs need to make sense of things.
The idea that books are nothing but bloated friction is nonsense and could only be cooked up by delusional idiots. I acknowledge that poorly written books exist, and some books are 12 chapters when they should have been 6, but applying this perspective equally across all books is just plain stupid.
The Decline of Reading
Here’s a chart that should surprise no one.
Everyone knows you don’t become an influencer by reading. Or reflecting. Or thinking. You become an influencer by reacting. Thinking before you do something takes too much time. What should be concerning is the rate of the lines. Kids who don’t read turn into adults who can’t read. And we are seeing this play out.
Kids who don’t read turn into adults who can’t read.
Here’s another secret: no matter how good the AI gets, you’ll never become wise without doing the work yourself. Wisdom manifests from reading, writing, and a whole lot of reflection. All activities that are devalued today. I’ve previously covered how knowledge and understanding aren’t generated from bullet points, but let’s go a bit deeper.
In letter 27 of Seneca’s Letters on Ethics, he discusses how real joy depends on real study. In this letter, he describes a man named Calvisius Sabinus, a wealthy man who wanted to appear learned, who devised a shortcut. He spent a great deal of money on slaves, one to know Homer, another Hesiod, and nine more for each of the lyric poets.
After he assembled this group, he would pester his dinner guests by having these slaves at his feet and regularly ask them for verses to quote. Even with this assistance, it was observed that he’d often stop mid-sentence. When a man named Satellius Quadratus made fun of him, saying he should train his busboys to be literary scholars too, Sabinus responded that the slaves had cost him a hundred thousand sesterces apiece. To which Quadratus said, “You could have bought as many libraries for less.”
Sabinus’ optimization led to a mistaken assumption that the knowledge possessed by anyone in his household was his own. This perspective is not only wrong, but it also led to ridicule. Today, we have a similar situation with AI, and many would claim that the information contained in an AI tool is knowledge they themselves possess, except that it isn’t. This resembles a situation we had previously with Google search, so we shouldn’t be fooled merely by upgraded tech.
Excellence of mind cannot be borrowed or bought. -Seneca
Wisdom isn’t recall. After all, someone who memorizes things wouldn’t be considered wise. It’s the perspective that’s gained from study and reflection across a variety of sources. It’s the ability to connect the dots between concepts and form new ideas. Wisdom manifests in someone who puts in the work, which includes reading, writing, and a healthy dose of reflection, all things labeled by the tech bros as “friction.”
When Zeno of Citium (The founder of Stoic philosophy) visited the Oracle of Delphi with the question of what he should do to live his best life, the god replied, “He should have intercourse with the dead.” This is recorded in Diogenes Laertius’ Lives of the Eminent Philosophers. In modern times, people have changed this to “converse with the dead,” no doubt because of how intercourse is used today, but I think intercourse has a much deeper meaning. No pun intended.
The oracle’s response didn’t mean Zeno needed to engage a psychic medium or have a seance. The only true way to converse with the dead is to read. This is the meaning Zeno inferred as well.
I’m obsessed with the works of long-dead authors such as Seneca, Aldous Huxley, Marshall McLuhan, Neil Postman, Montaigne, and many others. I can’t send them letters or call them on the phone. I can grasp their perspective through their writing, through books, letters, and other artifacts they’ve left behind. I can highlight passages, write my own notes, create my own modern perspective, and even challenge these authors in my own way, given the time that has passed from them to me.
Reading is a superpower that we seem eager to relinquish, which is a shame, because in many cases, reading is the remedy for so much of what ails us today. Reading does broaden the mind. It demonstrates that even ancient people encountered many of the same problems we have today. It creates room for reflection that extends far beyond the act of reading. The quest for wisdom and conversing with the dead create a satisfaction that can’t really be matched by other activities. It’s a feeling that isn’t possible to explain, and it’s something that needs to be experienced.
Getting Useful Information From Books
There’s a time-tested way to get the information from books that doesn’t require destroying them and turning them into a statistical distribution: you can actually read them. Dated concept, I know. I have a large piece in draft on literacy more broadly, so we’ll keep this piece focused on reading.
People might claim that the joke is on me because I only have knowledge from the books I’ve read, whereas someone with generative AI has knowledge from all of the books, despite never reading any of them. This is an idiotic statement to make. Setting aside the issues with retrieval, hallucinations, and other technical issues, the user doesn’t actually doesn’t have the knowledge of any of these books. At best, they have pieces torn from context. These people are like Sabinus, without knowledge but happy to annoy dinner guests.
The great thing about books is that you don’t need to read them all. Just like an explorer doesn’t have to explore every square inch of the globe, a reader is free to explore their unique interests and forge their own path of knowledge and wisdom.
Another response could be, since the AI has been trained on the content of someone like Seneca, you could have a Seneca bot and ask it questions. But this approach doesn’t make sense either. First of all, even if this were an effective approach, you’d have to know the right questions to ask. Since you haven’t read the source material and aren’t confronted with concepts in the writing, the “right” questions would escape them.
Second, none of the responses from the bot would stick with you, or in some cases, make any sense. The responses won’t form a connection in the way the content is encountered in the context of reading a book. The bot is going to “tell” you something, while reading will “show” you something. Reading is a true experience. Being told something is ephemeral and throwaway. Experiencing something can last a lifetime, while being told something may last only seconds.
Experiencing something can last a lifetime, while being told something may last only seconds.
Finally, the bot will approximate a pastiche response based on what it may have encountered during its training. It’s going to fill in the blanks in whatever statistical way makes sense. It won’t be the true response based on what the author really knew or felt. However, this response does actually fool people, and we’ve seen it time and time again in the generative AI era.
Much of this makes so much more sense when stated out loud. What do you think is the best way to get value from George Orwell? Do you think throwing 1984 into a massive statistical distribution or reading the book? Reading a book sticks with you in a way other methods can’t match.
There’s a mismatch in the application of technical thinking here. The goal of reading a book is to change the landscape of your mind, not have immediate recall over chapter and verse. Thinking that the point of reading a book is to remember everything is a warped perspective caused by our modern technological environment.
Unable To Read
Many people find it difficult to read long-form content, things like books and longer essays, articles, maybe even this very one. This may be due to attention hijacking, inability to focus, or discomfort, for lack of a better term.
People often tell me they wish they had time to read. I tell them, “Yeah, like I have boatloads of free time.” When viewed this way, zoomed out, it appears that nobody has time to read. However, this isn’t the case.
It’s true that getting information from books requires purposeful action and commitment. However, once started, it’s not as bad as people make it out to be. In many ways, it’s like an exercise routine. The best way to get started, or to get back into reading, is to create a habit. Start with the intention and don’t beat yourself up about it when you miss the mark.
What do you typically do before you go to bed? For many, this is swiping through social media, reading news stories, or maybe watching TV. This is a prime block of time to target for a reading habit.
You don’t need to start big. Maybe try 15 or 30 minutes of uninterrupted time. You may get distracted or feel uncomfortable. It’s fine. Like any habit, it will take some adjustment. At some point, it will click.
Don’t let some sort of idealized conception of reading throw you off. There’s so much reading advice out there, and much of it is bullshit. For example, nothing is more bullshit than speed reading. If you were worried about wasting your time reading, then speed reading will confirm your worries.
All of the things you are told are bad habits, such as vocalizing as you read, re-reading sections, and reading slowly, are all positives that reinforce the concepts contained in the book. Your goal is to develop an understanding of the material, form new connections between concepts in the book and in the world, and even develop new ideas based on these. None of that happens during speed reading.
It’s true, people read at different paces. You may feel like you read slower than other people, but that’s probably not true. Besides, who cares? You are reading for you.
As you begin reading again, you’ll find what works for you and what doesn’t. For example, maybe you prefer physical copies of books or the convenience of an eBook reader. The format is irrelevant if it works for you. Also, maybe you need to put your devices in do-not-disturb mode or make other purposeful interventions. Be intentional, find what works, and push forward.
My Approach To Reading
Let me share my approach, because I feel it’s pretty simple. I’ve explored using book tabs and other reference techniques, but I don’t use them consistently. Some people use reference cards, but I’ve never felt the need to go this far. I read for about an hour and a half every night before I go to bed. I typically have at least one fiction and one non-fiction book I’m reading at a time.
I prefer physical copies of books because they feel more engaging to me, and I don’t have yet another “device” in my hands. However, for nonfiction books I’m really trying to dig into, I’ll buy all three formats: physical, ebook, and audiobook. The audiobook is mostly for use while running on a treadmill or driving on a road trip.
For the physical copy of the book, I have three things: a Zebra Mildliner in lemon yellow, a pen, and a notebook. As I encounter interesting content, it could be concepts, things I’d like to quote, or anything else, I highlight it. If there is an entire section of a page, then I’ll highlight the first sentence and make a note with my pen in the margin, so when I revisit it, I have the context.
As I have ideas or make connections, I’ll stop reading and capture my thoughts in the notebook. I may include a piece of the book’s content there, but not always. I will always annotate the page number for reference, though. This way, it’s easier to revisit in the future.
After I’m done reading, I’ll take all the highlights from the physical book and apply them to the same sections in the eBook. I then sync those highlights to Readwise for both ease of reference and spaced repetition. I also have a physical commonplace book where I write the highlighted items. However, I’m not very consistent with this activity.
You may question the efficiency of my approach, as it seems I’ve added unnecessary extra work for myself. It appears that using the ebook and syncing the highlights is far more efficient. Once again, the optimization is a trap. The friction is the point.
In the act of transferring the highlights to the ebook, I’m once again confronted with all of the concepts I’ve highlighted, this time, after reading the whole book. Although I don’t remember things word-for-word, when I see the highlight, I’m reminded of the context in which the highlight was created. New ideas form, and I note those in my notebook. This activity further reinforces the content in my mind. I will sometimes reread the page or section during this activity. This activity provides much value.
Someone may argue that an AI can digest the entire book and provide relevant highlights without having to read it. Hopefully, by now you can recognize the issue. Even if it did this accurately, you’d be confronted with highlights out of context. The meaning and important features would be unavailable to you mentally.
Conclusion
The current AI age is making us wisdom-poor and manipulation-rich. The damaging consequences of the devaluation of reading are on the horizon for an entire generation and generations to come. It’s separating us from the very skills we need to defend ourselves and keep us robust in the modern environment. It’s removing our ability to reflect as modern technology pushes us to react.
Many believe they can’t read long-form content anymore, but that’s only because they haven’t tried. By creating a habit and some purposeful interventions, we can get back on track to finding wisdom.
One mistake we continue to make, time and time again, is confusing innovation with progress. It’s true that in many cases, innovation is progress. We see the results of this every day, in the development of vaccines, antibiotics, and even indoor plumbing. The results of innovation have improved people’s lives across the globe, allowing them to live longer, healthier lives. These are examples of progress fueled by innovation, but this is hardly always the case. It’s a mistake to assume that innovation and progress are the same, despite people using the terms interchangeably. Thinking this way is a trap that lulls us into complacency.
Confusing Innovation With Progress
When people use the term “innovation,” they often mean technological innovation. People imagine everything from hoverboards to intergalactic space travel. It’s these larger-than-life imaginings implanted in our brains that companies exploit to sell products as progress. Apparently, the road to utopia is paved with forced obsolescence and mandatory upgrades. However, nowhere in the definition of technological innovation is there a qualifier that it must be beneficial to humans.
Innovation is about making money, after all, companies are in business to make money. This isn’t some terrible, disgusting secret. And no, we shouldn’t burn it all down because companies are trying to turn a profit. This is how the world works. However, we need to recognize this fact because it figures into our calculus of progress. Because when innovation makes life better for us, the making life better part is a byproduct of the innovation activity. There are certainly exceptions and exceptional people like Jonas Salk, but this is hardly the norm.
Progress, on the other hand, is advancement toward the betterment of humanity. Or, at least, that is what the definition should be. Granted, these are subjective measures, which make them difficult to pin down, but progress is typically something we know when we see, for example, reducing poverty or medical advancements that reduce disease. Basically, anything that makes human lives better as a whole, preferably ones that lead to human flourishing, although this is rarely the case.
The fact that progress is subjective is what many technologists don’t like. There’s no number to optimize. Of course, since it’s subjective, people’s perspectives on progress vary. This is what gets exploited to sell nonsense as progress. When innovation is packaged as progress by default, then there’s something to optimize.
Let’s take the example of brain-computer interfaces, a space that is certainly going to heat up. Here’s Elon Musk claiming that Neuralink will allow us to become one with AI.
This is certainly innovation, but is it progress? In some cases, the claim could be made that it is progress. This would be true if it corrected some impairment or disability. But otherwise, let’s think about the scenario. Imagine a world where you never know whether a thought or memory you have is truly yours. A world that signals the end of private thoughts and the beginning of a whole new world of manipulation and unintended consequences. Maybe it’s just me, but this doesn’t sound like progress. I’ve pointed out these risks in my public presentations on emerging technology, as well as my addressing Kurzweil’s nonsense.
The lines can certainly get blurry. Self-driving cars seem like progress until they take away the self-driving features and instead charge you a monthly fee to access them. Apparently, a monthly subscription fee is how we get to Mars. I’m not claiming technology should be free. I just don’t think monetization should be a rug pull.
Apparently, this is how we get to Mars, through a monthly subscription fee.
Detractors often bring their own set of problems. No innovation that leads to true progress benefits everyone on the planet equally and simultaneously. The idea that it can and should is delusional, and insisting on this as the criterion is disingenuous and won’t lead to any progress. It’s the mark of a performance by someone living in an alternate reality.
Much of what we’ve seen over the past couple of years is innovation for its own sake, with associated negative consequences.
Why Does This Distinction Matter?
Many would have us believe that this is a distinction without a difference, and that I’m being provocative, but the reality is, these are two separate terms with two separate definitions. Progress is a general term that all humans can understand, whereas innovation is a specialized term used by technologists. The blurring of the lines between the two makes innovation in whatever form easier to digest. Quite often, innovation is immediately labeled and packaged as progress to exploit this condition.
This packaging and blurring of the lines between progress and innovation have been with us for quite some time. In Aldous Huxley’s post-apocalyptic novel from 1948 titled Ape and Essence, the Arch-Vicar of the satanic church describes progress and nationalism as the two great ideas that Belial put into human heads. In this scene, innovation has clearly been labeled as progress.
Progress—the theory that you can get something for nothing; the theory that you can gain in one field without paying in another; the theory that you alone understand the meaning of history; the theory that you know what’s going to happen fifty years from now; the theory that, in the teeth of all experience, you can force all the consequences of your present actions; the theory that Utopia lies just ahead and that since ideal ends justify ideal means, it is your privilege and duty to rob, swindle, torture, enslave, and murder all those who, in your opinion (which is, by definition, infallible), obstruct the onward march to the earthly paradise. -Aldous Huxley (Ape and Essence)
There’s no doubt that Huxley isn’t describing progress as human flourishing; he’s describing technological innovation packaged as “progress.” This is no doubt because the term “innovation” was not a common one flaunted in the faces of the general public the way it is today. This matters for all the reasons Huxley points out in this very line, and it applies just as well to technologists today as it did back in 1948. We are seeing the conditions Huxley noted in this passage today.
Technology Is Never Neutral
People love to claim that technology is neutral, but this demonstrates a stunning lack of awareness of reality. Technology is never neutral. The mere presence of the technology changes people and their environments. This has been known for over half a century. Here’s Marshall McLuhan writing about it in the 1960s.
Our conventional response to all media, namely that it is how they are used that counts, is the numb stance of the technological idiot. For the “content” of a medium is the juicy piece of meat carried by the burglar to distract the watchdog of the mind. -Marshall McLuhan (Understanding Media)
To quote another sage on the same topic, back in the 1980s:
Only those who know nothing of the history of technology believe that a technology is entirely neutral. -Neil Postman (Amusing Ourselves To Death)
Technology, by some measure, always changes the environment in which it’s found. Take social media, for instance. Social media changes the communications landscape, forcing even people who opt out to reckon with the possibility of being left out of activities when a group decides to organize on a social media platform.
There’s not much we as individuals can do about this, other than be aware of the phenomenon so we can implement mitigations. If we recognize that technologies are not neutral, we must acknowledge trade-offs, even if trade-offs don’t appear in the short term. Once again, we can look to social media. Early in social media’s life, there didn’t seem to be any real trade-offs. This perspective seems quaint today.
This is the point of this post: we never get something for nothing. The bill comes due at some point. When innovation, regardless of impact, is automatically packaged as progress, it becomes a vehicle to shove it down our throats, to make us get in line, to label us Luddites, to strip us of our humanity, and disregard our concerns.
For example, I’m still struggling to understand how destroying art and artists and dehumanizing everyone on the planet is somehow a prerequisite to getting a cure for cancer. If you don’t let us loot the intellectual and creative property of everyone on the planet, then you won’t get a cure for cancer or eternal life. Seems Huxley was right.
Conclusion
We should want and insist upon innovation that’s actually progress, with progress defined as the betterment of humans. So many these days are bedazzled by technology because it is neat or cool and never ask any larger questions about what problems it actually solves and what the tradeoffs are.
The next few years will require vigilance because much of the innovation packaged as progress comes at the cost of stripping us of our humanity and agency, further pushing us toward becoming machines. We need to become much better at envisioning trade-offs and not blindly take every new application or technology for only its surface-level functionality. The real dangers lurk behind the curtain and are rarely exposed until it’s too late. Awareness of potential trade-offs allows us to keep our guard up, choose our technology use cases wisely, and defend our humanity to the best of our ability. In the current environment, it’s up to us to defend ourselves.
The entire modern world seems to be doing everything it can to rob us of our humanity. Everywhere we turn, every reaction we have is either mediated or a byproduct of our current technological environment. Pretty much every piece of content we encounter online is a form of manipulation. This tiresome cacophony of content overwhelms our senses and wears us down. But we have a superpower, it’s called literacy. Literacy creates robust humans and is our greatest weapon to defend our humanity. It creates space for us to reflect and withhold our reactions. However, maybe not for long, as the kryptonite of content, entertainment, and instant reactions destroys this superpower, turning us into mindless, predictable automatons.
I do make time for this “friction” every day. This isn’t said to sound elitist, after all, I still watch TV shows and movies too. I wouldn’t even say I’m a particularly good reader, but I make do. And making do with reading is the whole point. Reading isn’t like baseball, where trying hard isn’t enough to be a starter. Reading makes you better, and trying hard pays off no matter how good you are.
As a matter of fact, if you want to maintain your humanity in a world that’s doing everything to steal it from you, then literacy is your greatest weapon.
What Orwell feared were those who would ban books. What Huxley feared was that there would be no reason to ban a book, for there would be no one who wanted to read one. -Neil Postman
The Reading List For Robust Humans
It’s really hard to find books these days that provide a critical lens of technology or AI without also being filled with politics, biases, and other assorted bullshit. I feel that the world really does need a better class of critic.
I’ve read some highly recommended, well-reviewed AI books that were absolutely terrible. Mostly filled with junk food for biases. The few good points that were made were mercilessly beaten like a dead horse, revived, and then beaten again, which I can only assume happened for the sake of page count or the author’s own personal indulgences.
This post is my attempt to save you some time. There are many great books that didn’t make the list because it would have made it too long. So what I tried to do with this list is provide some objective books that examine the impact technology has on us humans, with a focus on impact, experience, background, and data. Although some of these books may cover similar ground, they are all worthy reads.
Technopoly: The Surrender of Culture to Technology – (1992) – Neil Postman
You may wonder how a technology book from 1992 can be relevant today. That’s because Neil Postman was a true oracle. He was the Marshall McLuhan of the 80’s and 90’s. He could cut through the noise and see the reality of things. Every single chapter is filled with insight, and the dated examples could be easily swapped out for today’s. Mostly, it’s a book that demonstrates people of the past saw the problems of our current time, long before they surfaced. It’s an amazing book, which is why it’s the first on my list.
Amusing Ourselves to Death: Public Discourse in the Age of Show Business – (1985) – Neil Postman
Okay, I couldn’t help myself. Here is a bonus Neil Postman book. Quite often, this book is the first port of call for Neil Postman. Despite the references to television, it’s an easy swap out for other technology. There’s so much interesting history here, such as the history of advertising, with some examples from the early days when our culture was more literate. Fascinating read.
I am saying we are losing our sense of what it means to be well informed. Ignorance is always correctable. But what shall we do if we take ignorance to be knowledge? -Neil Postman
Superbloom: How Technologies of Connection Tear Us Apart – (2025) – Nicolas Carr
Pretty much any of Nicolas Carr’s books are good, but this is his most recent book. I’d kind of describe it as a modernized, more approachable work on the impacts of communication technology than Marshall McLuhan. Although McLuhan’s work is referenced multiple times, Carr offers his own modern perspective on today’s technology and its impact on us.
More Everything Forever: AI Overlords, Space Empires, and Silicon Valley’s Crusade To Control The Fate of Humanity – (2025) – Adam Becker
If some of these other books are about the what, then Adam Becker’s book is about the why. It demonstrates just how kooky some tech leaders’ beliefs are. Such as the need to go to Mars to survive, despite its toxic soil. Or some of Kurzweil’s greatest hits, such as we should pave over the universe to convert atoms into computronium. I’ve covered some of this myself and highlighted Kurzweil’s nonsense, but this is a whole book dedicated to exposing the odd beliefs of the people who create the technology we use every day. He’s an astrophysicist, so the odd space beliefs are something he’s uniquely capable of addressing.
I will say, Becker gets a little preachy near the end of the book, but the work is solid. It’s a summary and origin story of the worst ideas to emerge from techno utopians.
Dark Data: Why What You Don’t Know Matters – (2020) – David J. Hand
I’ve been recommending this book to people since it was published in 2020. This isn’t a book about AI or technology’s impact on humanity, but about our inability to properly make sense of data. In this book, Hand identifies multiple categories of dark data that confound our ability to make sense of data. You’ll never look at a survey the same way again.
The Extinction of Experience: Being Human in a Disembodied World – (2024) – Christine Rosen
This book covers our preference for mediated experiences and what this means when we lose them. She covers experiences that are on the verge of extinction and makes us think about exactly what we are giving up.
Understanding Media: The Extensions of Man – (1964) – Marshall McLuhan
I struggled to add this book to the list because both Postman and Carr refer to and build on McLuhan’s work. I even referred to McLuhan multiple times in this very post. It’s for this reason, and because McLuhan is a true visionary, that I had to add this book to the list.
McLuhan was someone who could see the impact of technology on humans, despite no one else noticing. In this book, he covers the difference between hot and cold media, human impacts of augmentation, and the shrinking of the world due to electric technology. A world that has only further shrunk in the internet and social media age. Remember, the medium is the message.
It’s not a quick or easy read. Maybe it’s just me, but I found myself reading something, then going back to reread it. The references are a bit dated, as to be expected, but the content contained is as relevant today as it was back then.
Conclusion
This is just a start. Make 2026 the year you rekindle a reading habit. I set aside at least an hour a day before I go to bed. Once the habit forms, it’s easy to continue. Start with a few minutes a day if that’s all you have, and work from there. Welcome to the robust revolution!
Recently, Google, along with Shopify, Etsy, Wayfair, and Target, created Universal Commerce Protocol. A protocol that retailers can use in their AI agents to support product discovery, purchasing, and even support. However, I don’t think retailers understand the full impacts of agentic shopping. When viewed through the autonomous lens, this approach presents the act of shopping as friction, then removes it. Removing the shopping experience from the purchase of products will have the opposite economic effect than retailers hope for.
Companies are betting big that people will want agents to buy things on their behalf. But if this takes off, it could backfire, rewiring the shopping impulse in people’s brains and causing them to buy even less. I don’t think agentic shopping will take off because, once again, innovation is competing with culture. However, this requires a closer look.
Innovation Failures
One of the big reasons innovations fail has nothing to do with a technology’s capabilities and everything to do with the individuals building it not understanding people and culture. A perfect example of this is the vacation agent.
I’ve made fun of the vacation agent before. A nonsensical idea that could only be dreamed up by someone locked away in a room, having no idea what a vacation is. The big point is that the planning is part of the vacation. People don’t view researching activities for a vacation as a burden. It’s part of the fun.
These proposed innovations conflict with culture, which is why I predict that OpenAI’s device will fail. Introducing a device without a screen in a screen-based culture. Here again, we have people thinking it will be different. Sure, innovations come along that break the culture, but they have to be overwhelmingly compelling.
Now, the wonderful folks of Silicon Valley are here to give us agentic shopping, something that nobody actually wants. Every step of the way, proving yet again that they not only don’t understand humans but also don’t understand existing technology.
Shopping Technology
Let’s start with technology. We already have technology today that allows people to check prices to get the best deals. Whether it be flights, hotels, or products. In the US, you are bombarded with Trivago commercials while watching television. Browsers also save address and payment details, and you have options like Apple Pay to make the checkout process even more painless. The friction that’s left is much of what people find enjoyable and what retailers find necessary. (More on this shortly.)
It’s true that people today are using AI as a research tool on products, or at least there is no reason to think they aren’t. After all, they are using AI to self-diagnose their medical conditions. So, there’s no reason to think they aren’t also using it to research the products they may purchase. Companies view the purchase as purely the last step, connecting the dots, if you will. But there’s a big difference between connecting the final dots when a human is doing research and making decisions, and when an autonomous shopping agent does so.
Shopping
The joys of shopping come from outside the technical workflow. Simply put, shopping is fun for people, and our economy depends on that. But what people fail to realize is that shopping with autonomous agents isn’t shopping at all. You’ve amputated the impulse and transformed a fun experience into a purely utilitarian one by viewing shopping as friction. However, even though shopping seems simple, there are complexities that confound the autonomous shopping experience. Let’s start with price.
Shopping with autonomous agents isn’t shopping at all.
Is buying the cheapest thing really the best? Price is purely a number, easy to sort and prioritize. However, thinking that product selection is a matter of price is fooling yourself. What if you don’t get the cheapest thing for a month? What if the company has a bad habit of poorly packaging products? What if the company has poor support? The follow-up questions are endless. It’s true, you could try to account for these countless variables based on personal preference in the agent, but at some point, it becomes too tedious and varies from product to product.
In some cases, even when shopping for the same product, you might prefer the markings, such as the wood grain pattern, on one product over another, even though they are identical. The list here can be endless, and this choice is only for selecting between different options from the same vendor.
Often, you aren’t comparing apples to apples but apples to oranges, and you’re trying to decide between them. Similar products from different vendors or even different formats. For example, when choosing your next vehicle, you might be deciding between a car and a truck. Both vehicles are apples and oranges. In many cases, you might not be able to explain exactly why you made the choice you did.
Nobody likes dealing with salespeople at car dealerships, but browsing different interiors and options is actually fun. But don’t take my word for it, take our entire economy as proof. Advertisements are purely the bait. The hook comes when the browsing starts.
When purchasing services, it becomes even more complex. “Book the cheapest plumber for Tuesday” isn’t a prompting for success. However, let’s keep the conversation on products.
There is still tedium in the shopping process, and edge cases may emerge. For example, I think the idealized view of agentic shopping is something like this:
“Put together five dinners for the week based on my preferences and order all of the ingredients. Have them delivered on Monday.”
I can see where some would find this attractive. Grocery shopping is a far more utilitarian shopping activity than other forms of shopping. However, I’m far too picky about my ingredients, and I’d never trust a stranger to choose an apple or an onion for me. Actually, I’m far too picky about everything, so the question is: are picky consumers the norm or the outlier? Maybe dinners are the exception, but generalized technology rarely stays confined to specific use cases, and enough edge cases are needed to push it into mainstream use.
Will people use agents to outsource the shopping experience? Maybe. But technology choices like this are all about trade-offs, and none of those trade-offs are being considered, especially by retailers. Let’s talk about those now.
Manipulation and Gaming
The more automation is applied in the shopping experience, the more it opens the door to manipulation and gaming. It won’t be the best product vendors and products resorting to dirty tricks. Just like today, people have manipulated search engine optimization (SEO) to rank higher in search results. It’s never the best content at the top, but the people who used the right words to game the algorithm. At least with search engines, all of the content is visible, and we can tell what’s garbage. With an agent, it’s not only invisible to the user but also costs them money.
It’s never the best content at the top.
Of course, this opens the door to scammers as well, giving them new ways to exploit people. Generative AI is highly manipulable, and it’s extremely unlikely that scammers will not find unique ways to exploit these agents. Scammers are typically one step ahead, and it’s likely that the techniques they use will be exploited by marketers and advertisers.
Negative Economic Impacts
By optimizing the purchasing experience, AI agents remove the friction, in this case, known as shopping. The result could create devastating economic impacts. By removing the joy of shopping and turning purchasing into a utilitarian activity, this could cause people to buy fewer things or focus only on necessities. Our entire economy is based on people buying things they want, not necessarily things they need.
Removing the friction from purchasing may seem productive when viewed purely in terms of optimization, and if the trend picks up, there may be a short-term spike as people test the approach and impulse-buy items. However, this won’t last. The use of agents could rewire the brain’s reward system in a way that’s devastating for businesses.
Agentic shopping also removes a vital metric for tech companies, time on platform. More time on platform means more viewing ads for other products that customers may buy or encountering other products that are more preferable. The point of agentic shopping is to avoid time on platform altogether. Advertisers won’t be happy. They’ll insist that agents be further enshitified adding friction to the shopping process, possibly by adding ads or other interventions.
Adding friction to the shopping experience is actually preferable for companies. There’s a reason your local grocery store decides to rearrange the products periodically. It’s not to optimize the store, it’s to un-optimize it. The additional friction of walking around the store leads to additional purchases.
If the shopping impulse gets rewired in people’s brains, this could lead to devastating economic impacts. If I were someone who hated capitalism and wanted to see it fall, I’d be a huge fan of agentic shopping. It would be ironic if the innovations created to build more capital end up being its downfall. Technology has a powerful impact on humanity and can transform or destroy culture. Just look at Gutenberg, television, radio, the Internet, etc., as examples.
Conclusion
Companies are investing in technology that may cause their demise, driven by the fear of leaving revenue streams on the table. It’s that simple. They don’t want to be left behind. The irony is that the search for additional revenue may lead people to buy less.
Ultimately, I don’t think agentic shopping will take off. The shopping impulse ingrained in our culture is too strong, but if it does, the unintended consequences may have the opposite effect. In an attempt to get people to buy more, by removing the friction, they buy less.
People making predictions fall into three general camps: those selling something, delusional ignoramuses, and the rare case of thoughtful reflectors. I’d like to think I fall into the last category, but since I’m not selling anything, I fear I may be part of the former. Regardless of category, we seem to forget that the world confounds prediction through complexity, even for the most ardent of reflectors.
Another common playbook in our era is to make so many predictions that some are bound to come true, then cite those cases as proof that you are an oracle. I see this happening frequently. It’s the exploitation of our short attention spans. This isn’t magical foresight, it’s statistics.
Regardless of my opinion on tech predictions, people seem to love hearing them. While I was at the AI Security Summit in London, several people asked me for my predictions for 2026, since in my keynote, I described hype shifting back to embodied systems. I guess I asked for it. But, please don’t listen to me or anyone else making predictions about 2026. Well, at least I’m not trying to sell you anything.
I think people have an instinct that 2026 feels more uncertain than 2025. There is a sense of desperation in the air as companies push to prove there is no AI bubble by wallpapering everything with AI.
Now that I’ve complained about making predictions and how uncertain 2026 feels, here are my predictions/vibes/observations for 2026.
1. Agent Double Down
“No, no. Last year wasn’t the year of the agent. THIS year is going to be the year of the agent.” I can already hear people course-correcting from their predictions last year. 2025 was the year generative AI was going to take off, resulting in massive layoffs and tons of revenue. Instead, we hear speculation about the AI bubble about to pop.
Despite the ongoing issues and high manipulability of agents, people will continue to double down. We didn’t resolve any issues with agents in 2025, so they’ll be with us again in 2026. But with the doubling-down efforts, people will try to convince you that the issues are solved or didn’t matter much in the first place.
Most business leaders who ask for agents and insist on using AI have no idea how the technology works, what it’s capable of, or the associated risks. This is not a recipe for success. Deploying this technology successfully requires a firm understanding of capabilities and realities on the ground. Of course, having appropriate expectations helps too. This isn’t happening, as MIT found when they identified that 95% of GenAI pilots failed.
I’m not claiming that agents are useless. They have their uses and can be employed in certain scenarios to augment human activities. And yes, this can be done successfully. What I’m saying is, they aren’t the utopian, headcount-reducing technology we were promised in 2025, and the data bears this out.
The truth is, if your use case has a low cost of failure and can tolerate errors and manipulations, you don’t need to wait for a new innovation. You can deploy agents today. How well they perform, on the other hand, is a different story. Performance will vary by use case and environment.
2. Embodiment Hypes Again
Although the hype of generative AI will continue in 2026, we’ll see much more hype of embodied systems. Embodied systems are those that interact and learn from the real world. Think robots, self-driving cars, drones, etc. This category is certainly no stranger to hype.
Embodied systems are always ripe for hype because they tend to be more tangible and less behind-the-scenes. There will undoubtedly be some real improvements in this area. Unfortunately, these real improvements will provide ammunition for the hype cannon. Any modest improvement will be pointed to as exponential. For example, Elon Musk recently said robots wouldn’t just end poverty, but also make everyone rich. Utopian abundance is often talked about but never rationally explained.
3. Security Issues Continue To Rise
Security issues will not only persist but also accelerate. How can they not? With more AI writing more code and more code being pushed by inexperienced people, that’s a recipe for security issues. But to quote the late American philosopher Billy Mays, “But wait, there’s more!” As more applications are developed to outsource functional components to generative AI, the application itself becomes highly vulnerable.
Unknowns will continue to plague applications and products, leading to security issues. If you’ve seen any of my conference presentations over the past couple of years, you’ll have heard me talk about these unknowns. For example, we now have conditions in which developers don’t know what code will execute at runtime.
We security professionals aren’t doing ourselves any favors. Much of the guidance on AI security is overly complex, doesn’t align with real-world use cases, and doesn’t help organizations realize value quickly. We are not rising to the occasion.
4. AI Backlash Builds
AI backlash will continue to build in 2026. A vast majority of people on the planet find tech bros abhorrent. Talking about technology as if it’s magic and CEOs foaming at the mouth to replace people leaves a bad taste in the mouth. Also, the shoving AI into every possible crevice of our existence isn’t a condition that a vast majority of people want. We are getting AI in everything, whether we want it or not.
2026 will be a challenging year for tech companies. They have to prove their investments are paying off. As we enter the fourth year of the generative AI craze, companies are still hemorrhaging money. This will lead to more intense claims, hype, and AI in everything. Backlash will certainly result. As to what form this backlash takes or how big it becomes, it’s anyone’s guess.
5. Negative Human Impacts Gain More Attention
When you mention the topic of AI’s negative impacts on humans, people almost universally think of job displacement. However, this isn’t even the most impactful effect on humans. The human impacts of AI have been a focus of mine for years. This is the main focus of Perilous.tech where I’ve covered topics such as cognitive atrophy, skills decline, devaluation, dehumanization, and on and on.
I believe more people are recognizing the human impacts of AI, and it will receive far more attention in 2026. Today, the most extreme examples, such as people committing suicide or AI psychosis, get all of the attention, but this is starting to shift.
I recently saw Jonathan Haidt mention these cognitive and developmental issues, referencing both Idiocracy and The Matrix. Two references I’ve also made in the past couple of years. These are natural conclusions once you consider the facts on the ground. AI can make you stupid and overconfident in an environment that seems like it’s already saturated with stupid and overconfident people.
6. OpenAI’s Device Flops
OpenAI is working on a device, and it’s going to be the most world-changing thing ever. It will demonstrate that OpenAI absolutely has a moat. After all, they’ve hired Johnny Ive! You sense my sarcasm.
I’m not sure what form OpenAI’s device will take or even if it will be launched in 2026, but it’s rumored to be a small, screenless device with a microphone and camera. This road has been traveled before, a couple of examples are the Humane pin and the 01 light. These devices failed for the same reason OpenAI’s will. It’s not that these devices lacked capabilities, it’s that they directly conflicted with culture. We have a screen-based culture, and now OpenAI expects people to give up the screens? No chance.
People are accustomed to having their experiences mediated, and screens are a large part of that. There’s an idealized vision that people will wear these devices and use them to make sense of the world. Unfortunately, in our current culture, people aren’t curious about the world or look at it with a sense of wonder. They want to transform the world into content. Everyone on the planet now has camera eye, and nobody is going to trust a wearable to frame content.
The device will also be visible to others, so it will signal something about you as a person, and what it signals is nothing good. In addition, if the device has a microphone and camera, public shaming will further lead people to either abandon it or avoid purchasing it altogether, regardless of its functionality.
There’s also the verification aspect. People have become accustomed to degraded tech performance, and they will just not want to talk to their neck and hope that the device takes some action on their behalf. They’ll want to verify.
Remember the GPT Store? Yeah, nobody else does either, including the influencers who claimed it was the new AppStore. We’ll get overwhelming hype followed by a belly flop the size of the US economy, regardless of whether the device is launched in 2026 or 2027.
Conclusion
Buckle up, we aren’t through the hype yet. We are in an era where faith in gods is replaced by faith in tech, and people can gamble on the mundane aspects of daily life. 2026 is going to be weird.
It says much about our current moment that “slop” is Merriam-Webster’s 2025 word of the year. Seems mediocrity is having a moment. In this moment, a delusion has taken hold, centered on AI and the future of work: the AI creativity delusion. For the past couple of years, companies and influencers have told us the world is our slop oyster. If we can imagine it, we can slop it. Ideas and creativity are what matter, and everything else should be automated. We are told that, despite the goal of replacing humans in the workplace, the near-term future of work is humans, still in the loop, doing what they do best, flexing their creativity and letting AI do the rest. Although conceptually sound, this vision falls apart under even the slightest analysis, and it will hit younger generations the hardest.
The AI Creativity Delusion and the Expertise Loophole
Let me address the AI creativity delusion fueling the push for AI-powered coworkers. The premise goes that humans at work will flex their creativity by delegating their AIs to handle other tasks. This way, the human does what they are good at (creativity and ideas), and the AI does what it’s good at (everything else). Many may nod in agreement. However, this premise falls apart under scrutiny. We’ll get to this in a moment, but first, a loophole.
I should note a loophole in AI tool productivity: the expertise loophole. This loophole applies only under specific circumstances, namely when the user already has domain expertise. A user with domain expertise and an understanding of how AI tools fail can provide corrections or put the tool back on track. You need to understand the task, what the correct outputs are, and have enough experience to know when you aren’t getting the right answers.
Expertise also informs when to use AI tools and when not to, because an expert understands what needs to be done and which tasks AI can assist with in delivering the best results. I believe it’s this expertise loophole that blinds people to the real issues we are about to face.
Given the conditions of the expertise loophole, any productivity gains are temporary and apply only to specific job tasks for a limited time. As experienced people leave, less experienced AI-powered coworkers cannot fill the gaps. Mainly because they never have an opportunity to gain experience, the very experience they need to develop creativity in the domain. Secondarily, they outsource the social aspects of their jobs, further isolating themselves from their co-workers. It’s a one-two punch that’s hard to recover from.
A significant flaw in the creativity argument is the misconception that ideas are unique, precious resources that must be protected and fostered. I’ve written about this before, explaining that ideas are common, run-of-the-mill daily occurrences for everyone on the planet. Most ideas are ill-thought-out, half-baked, or just plain stupid. This is our reality.
The Younger Generation as AI-Powered Coworkers
I read an article recently, where a Gen Z founder claims that the younger generation will have an advantage in the workplace because they are growing up fluent in AIand this is helping them stand apart from their older peers. This is the sort of unadulterated, bubble-living bullshit we’ve come to expect these days. Younger generations may be growing up in the flatulence of AI, but that’s something else entirely.
Prolific AI use will ultimately make the younger generation worse off, as they are not set up for success in key areas that align with their value as employees.
I’ll make a claim of my own, and it’s the exact opposite. Prolific AI use will ultimately make the younger generation worse off, as they are not set up for success in key areas that align with their value as employees. This would be true even in a reality where generative AI is near-perfect, and we all know we are far from that.
I’m not attempting to beat up on younger generations. I feel for them, and I want to help. There have been so many ways they haven’t been positioned for success, and now generative AI comes along, putting more nails in the coffin.
These companies want to make you less capable and more dependent.
These companies want to make you less capable and more dependent. If you are dependent, you’ll not only need to use their tools to do your job but also in your day-to-day life. This is not a great option.
Marshall McLuhan said that every augmentation is an amputation. Framing technology in this way opens the door to unforeseen circumstances. In the case of younger generations, the amputation happens before the limb even has a chance to develop. In our case, rather than a physical limb, we are referring to cognitive and social abilities.
When we peer beneath the paint, we find that the very skills needed to make someone valuable at work are precisely those not being developed by overly ambitious AI-powered coworkers. The ones not communicating with their coworkers because their bots attend their meetings and respond to email and text communication.
Revisiting Creativity In Younger Generations
How does someone develop their creativity in the first place without experience? They don’t. Generative AI today can assist people with experience in specific tasks and under certain conditions. It helps with some tasks better than others. This is because someone with experience, especially domain experience, knows how to approach certain solutions, identify the right conditions, and know when the system is malfunctioning. An experienced professional can flex their creativity in this environment. The same cannot be said of the effectiveness of younger generations in the same jobs, despite having access to the same tools. Effectiveness will decline sharply across multiple dimensions.
First, they’ll never develop the social and communication skills necessary to be effective members of an organization. Second, they’ll not gain the experience needed in a given domain. Finally, they’ll never develop the mythical creativity discussed in AI circles due to a lack of expertise and social skills. All of this will be due to the overreliance on generative AI tools.
Let us examine some aspects of AI-powered coworkers. AI-powered coworkers using generative AI tools to attend meetings, take notes, and create action items. They use generative AI tools to communicate with co-workers. Using generative AI tools summarize documentation, books, and countless other sources of knowledge. Using pre-made generative AI tools to perform the job tasks. And the list goes on. This may look productive, but it’s not effective, and that’s a critical difference. There is a subtle deception at work here because AI tools can make people feel more productive and even powerful, even when they are not.
You can’t summarize your way to expertise, you can’t build relationships by outsourcing communication, and you can’t get experience by not doing things. Does this sound like a successful future workforce? Yet this is exactly the vision on offer, and this fuels the AI creativity delusion.
We have a distorted view of creativity, perceiving it as exercised by lone geniuses, but the reality is that most of the creativity needed for success in a business context is exercised in groups through relationships and collaboration. The same relationships and collaboration that aren’t developing in the AI-powered coworker scenario. When people start treating their coworkers like apps, nothing good happens.
The reality is that most of the creativity needed for success in a business context is exercised in groups through relationships and collaboration.
This should all make sense. When has anyone ever admired someone’s creativity when they didn’t actually know anything? It even seems silly to say out loud. To break the rules, you must know where the rules are and what hard constraints exist, and that requires awareness and expertise.
Knowing a tool doesn’t make you an expert; it makes you a tool. But let’s dig a bit deeper with a specific example.
We are told that meeting recording and transcription services free us from taking notes, allowing us to focus on what’s happening. However, this couldn’t be further from the truth. People pay LESS attention when they think a meeting is recorded, especially when they think it’s going to be summarized and bulleted for them. The reality is, taking notes IS paying attention.
When the human brain summarizes, it stores and reinforces. In a learning scenario, when people began taking notes on a computer, they could record everything the teacher said. But, this isn’t the benefit people thought it was. It seems that the act of taking notes with pen and paper forces us to distill what’s being said down to its essence, which is much better for learning and retention. I know it’s hard to believe, but pen and paper are technology too.
Not only that, but if we view this from a social context, there is a courtesy and respect that occurs when people see you taking notes, rather than simply grinning like a dipshit, or when people see you performing background tasks while they are talking. But, oh no. My AI has got this covered.
So you’re going to have a hard time convincing me that people who use LLMs to summarize and respond to their emails and text messages, attend meetings on their behalf, and have no domain experience or developed any workplace social skills are going to have a leg up on the competition.
What’s Old Is New Again
Some things never change. I’ve been on this tools impacting humans beat for quite some time. Back in 2010, I gave a series of talks at security conferences titled “Your Tools Are Killing You.” The premise was that people were completely reliant on their tools and couldn’t perform the task otherwise. If the tool was blind to an issue, the human was likewise blind to it. Newer people to cybersecurity learned the tool, not the task. These conditions ultimately reduced people’s effectiveness at their jobs. Sound familiar? However, the generalized nature of generative AI makes this far worse.
Mediocrity Is The Future Of Work
In September, Harvard Business Review published an article on how AI-generated “workslop” was destroying productivity. In essence, workers using AI tools were passing low-quality content to co-workers, which required them to do more work. This is a sort of productivity shell game where a speedup in one area causes a slowdown in another, pretty far from AGI if you ask me.
When everything is slop, everything is mediocre. We’ve allowed companies to reframe what’s acceptable into mediocrity. We don’t hire employees to give the bare minimums. Nobody responds to a job interview with, “If you hire me, I promise to do just enough.” This is hardly a selling point. When you hire someone to paint your house, you don’t think a mediocre job is acceptable, but if you receive a mediocre report, somehow it’s now fine if it is labeled as “AI-powered.” All the mistakes and inaccuracies are just how things are now.
AIs don’t care about quality; that’s a human’s job. Yet quality is on a steep decline. Some are making low-quality work product acceptable because AI is in the loop. But what happens when people forced to use AI tools in the workplace stop caring about the quality of the work they produce? Nothing good.
Encouraged or forced to use AI for everything, humans will be nothing more than meat-sack automatons providing the embodiment for AI. Most jobs don’t consist of a single task, which is why AIs still need humans in the loop for the current and near future. This vision is hardly motivating or inspirational.
Conclusion
We’ve built our AI temple atop fissures, allowing escaping gases to induce hallucinations, fooling us into thinking we are predicting the future. We remain blinded to the real issues confronting us and their negative impacts. We cling to the AI creativity delusion. Which, ironically, prevents us from using AI tools to their full potential.
Creativity doesn’t come without experience, and most of the creativity needed for success in a business context isn’t the work of lone geniuses, but through collaboration. If we don’t identify and correct these issues soon, we are all but dooming younger generations. We are currently in the f—k around stage, but the find out stage is on the horizon.
In the current landscape of technology hype, technological immodesty underpins everything. Hype trumps everything else, meaning systems can’t be just good at one thing. They need to be good at everything. Systems can’t just be capable. They need to be superintelligent. Once this happens, imagine all of the amazing things they’ll do! We don’t have an intelligence explosion, but we do have an immodesty explosion.
It’s the lack of modesty that compels speculation on topics such as artificial superintelligence before we’ve even achieved AGI. But speculating on artificial superintelligence makes you an ASS, an Artificial Super Speculator. Speaking of asses, people like Ray Kurzweil cloak themselves in immodesty and disregard for reality when they talk about computronium, nanotechnology, or wanting to convert the entire universe into a giant supercomputer. But immodesty has consequences beyond people making asses of themselves.
Technological Immodesty
Technological modesty was introduced in Paul Goodman’s 1969 article Can Technology Be Humane? In the article, Goodman describes technological modesty.
Currently, perhaps the chief moral criterion of a philosophic technology is modesty, having a sense of the whole and not obtruding more than a particular function warrants.
Okay, that’s incredibly academic. In a more common vernacular, what he’s saying is, don’t claim shit can do things it can’t. This is best illustrated with an example. This example comes from the 1992 book Technopoly by Neil Postman.
Norbert Wiener remarked that, if digital computers had been in common use before the atomic bomb was invented, people would have said that the bomb could not have been invented without computers.
I hope this example prompts some reflection. We can’t fathom how ancient humans were able to accomplish things without modern technology. We look at the stones of Puma Punku or the pyramids at Giza and assign a higher likelihood to aliens than to human ingenuity. No offense to Giorgio Tsoukalos. We struggle to imagine a time before our current technologies existed, which is why we often can’t view the past without peering through the eyepiece of the present.
Immodesty isn’t a modern construction, but we’ve supercharged it, adding nitrous oxide and flames shooting out the tailpipes. This is made easier with the arrival of more advanced technology that many don’t understand. And when tech leaders are in public, they can’t help but flaunt it. Here’s a recent example.
So, robots won’t merely eliminate poverty, they’ll make everyone wealthy? Exactly how is that supposed to work? It’s nonsensical performance art, something I’ve written about before. In short, being modest or even realistic, for that matter, doesn’t pay the bills. So, all aboard the hype train.
The number of times I’ve seen and heard the technology and magic quote from Arthur C. Clarke is mind-boggling. People wield this phrase like a weapon, as though it’s evidence for some wildly speculative technology. As a refresher, or for anyone who’s never heard it, here is the quote: “Any sufficiently advanced technology is indistinguishable from magic.” When people quote this phrase, they mean it as proof of the inversion.
When pointing out this inversion, Colin Fraser summed up what people actually mean when they utter Clarke’s phrase: ”Anything indistinguishable from magic can be achieved with sufficiently advanced technology.” This simple inversion is what many of us have been pushing back against for the past few years. This is the pinnacle of technological immodesty, the golden cap atop the polished limestone pyramid.
What’s The Problem?
On the surface, this seems irritating and not problematic. It just seems like the hype boys be hypin’. This is true in some cases. However, there are real-world impacts. Most importantly, it means we won’t address today’s problems since magic fairy dust is coming to solve our woes. You can see this play out when you hear someone like Eric Schmidt saying we should go “all in” on data centers because we aren’t going to meet our climate goals anyway. AI is just going to “figure it out.” Oh yes, More data centers, please!!! Notice the hype of his referring to AI as “alien intelligence?”
The entire gambit runs from the benign to the absurd and everything in between. For example, when the technology to eradicate mosquitoes surfaces, people in the e/acc community are all for it.
That’s right. This dunce cap doesn’t understand the ethical concerns for wiping out an entire species. Even the discussion on the post is stupid. The ethical concerns aren’t for the “suffering” of the mosquitoes. The problem centers on the consequences of eliminating an entire species from the planet. They view an entire species as an affliction like Polio or ALS, which makes the thought experiment of wiping them out a simple binary. You know, the little things. I loathe the e/acc community for making me defend mosquitoes.
In another example, Elon Musk wants to block out the sun with satellites. Yup, I’m sure nothing bad would come of that. I believe it was Dienekes who, when informed that satellites would block out the sun, responded, “Then we’ll TikTok in the shade!”
Dario Amodei claims technology (his technology) will cure cancer and double our lifespan in just a few years. At some point, technology will allow us to eradicate cancer and possibly double our lifespan. Side note: Doubling our lifespan isn’t exactly the benefit it seems to be if we can’t address cognitive decline. Statements like these exploit our intuitions about technological capabilities. By adding the word “soon,” he creates an air of believability, hyping his own technology in hopes of attracting further investment. Let’s not forget that none of his predictions have come true. This is like spraying a pile of manure with perfume and claiming that it never smelled.
Not to be outdone in speculative bullshit, Ray Kurzweil wants to pave over the entire universe, converting its atoms into computronium to build even larger supercomputers. Cool huh? This is nothing more than speculative tech bro porn. This is a lack of modesty on a cosmic scale.
Even if this were possible, what gives us the right to wipe out entire planets? You know all of those sci-fi superhero movies where the heroes of Earth need to defend against the massive dark force threatening to destroy us? Kurzweil wants us to create that dark force to nom nom entire planets and belch out compute. Sorry, you’re going to die, folks, but think of all the compute we’ll have!
There are countless examples like these that go far beyond mere product overhyping. So, you might wonder why people say shit like this. Well, it’s for a few reasons. Either their paycheck depends on it, they enjoy a public performance, or they want to sound smarter than everyone else. Take your pick. There’s an old saying: never trust a prediction when a person’s paycheck depends on it being correct. Sage advice.
One of the biggest problems that arises from a lack of technological modesty is the devaluation of both humans and nature. What is the worth of a single human or even an entire planet in the face of an intergalactic nom nom machine? Even on a smaller scale, we see people who want to replace other people with technology. AI coworkers, AI friends, AI art, and the list goes on and on. In another inversion, instead of us using technology, technology uses us.
We allow people wielding tech like a magic wand to trivialize and devalue everything that makes humanity unique. And for what? The benefits are supposedly implied, but the details are never specified.
We Are Bad At Imagining The Future
Take a moment to reflect on the fact that most of the AI predictions you’ve heard over the past few years have not only been wrong, but completely absurd. Nearly all of them. Absurd predictions fuel hype, which the press picks up, which in turn fuels more absurd predictions. We don’t reward people for being right; we reward them for being bold.
Humans are also bad at imagining the future. By most accounts, we should have flying cars and hoverboards by now. But risks of the past seem quaint by today’s standards. In a complex world, it’s hard to imagine how situations will change and adapt, especially when technology solves problems.
Harry Harrison’s 1966 novel about overpopulation and scarce resources, called Make Room! Make Room!, contains a shocking statement at the end of the book intended to invoke fear.
CENSUS SAYS THE UNITED STATES HAD BIGGEST YEAR EVER END OF CENTURY
344 MILLION CITIZENS IN THESE GREAT UNITED STATES
HAPPY NEW CENTURY!
HAPPY NEW YEAR!
This statement may have invoked fear in 1966, but today it looks quaint. We are roughly there population-wise already, and people eat soybeans and lentils because they want to, not because they have to. We aren’t in the Make Room! Make Room! scenario because of advances in technology, agriculture, and trade.
Yeah, yeah. I know, spoiler alert. The book came out in 1966. If you haven’t read it yet, then I don’t know what to tell you.
Not only is overpopulation not a problem, but some are warning that population collapse is the problem, and we need to increase the population, something Elon Musk has taken it upon himself to address personally. The real world is a complex place, filled with unforeseen problems and solutions. It’s just not possible to speculate very far into the future, yet that’s what we are all being prodded to do.
My site focuses on technology risks, so this is what I highlight. The benefits of technology are far-reaching, and this is important to keep in mind as we identify potential risks. It’s because of technology that we can live longer and that the planet can support its population. Even technologies that carry risks can be evaluated in terms of trade-offs. The problems I call attention to are people wielding speculative technologies like a magic wand, casting imaginings far and wide.
When it comes to problems caused by technology, we are told not to fret because a solution is on the way. We are told that any problem created by technology can be solved by applying even more technology. But this technology layering distracts from the root cause of the underlying issues, and of course, creates even more issues. The original problem lies at the center of an onion wrapped in petals, creating more problems. Or in some cases, there was no problem at all.
In other cases, solving technology problems with more technology may very well be true. However, there are many situations in which this doesn’t make sense. For example, we aren’t going to solve the loneliness epidemic with AI friends. Many people have a technology-shaped hole at the center of their being that won’t be solved with more technology.
Injecting Reality Into Technological Immodesty
Unfortunately, there isn’t much we, as individuals, can do on a large scale to address this, except roll our eyes. We must remain robust against the influence of speculative bullshit. Some of us need to stay grounded in reality and able to identify future risks without being thrashed about by the tornado of irrationality and hype. Hype creates fear, and fear can be weaponized.
On a smaller scale, in our conversations, when someone brings up something like nanobots, computronium, wiping out species, the need for humans to leave Earth for our survival, how AI or robots will end poverty and create a utopia, or any of the countless other examples of speculative bullshit, ask these people two simple questions. Why do you think that? How will that work? Make people explain their position. You’ll typically find they either have no clue or are talking about magic instead of technology.
When you inject a bit of reality into the conversation, and someone claims, “But you aren’t Ray Kurzweil!” Simply respond with, “Thankfully!” Modesty is born from the recognition of reality, and reality has been in short supply lately and will be for quite some time.
Technology is all about tradeoffs. Ask people what they believe the tradeoffs are. It’s incredibly rare to get something for nothing, or even cheaply, for that matter. A vast majority of the time, people haven’t considered any tradeoffs or are blind to their existence.
Conclusion
Technology has and will continue to improve human lives. It’s because technology has successes that it’s so easy for people to speculate about future technology. I’m hopeful that technological advances allow us to find cures for afflictions like cancer and Alzheimer’s and overall make people’s lives better. These would be major accomplishments. Also, indoor plumbing kinda rules.
I’m not making the case for a regression to some previous era. What I’m saying is, we shouldn’t let people talk about technology as though it’s magic. This environment not only causes massive harm but also allows charlatans and hucksters to run rampant. Unfortunately, we have a lot of work ahead.
Humans are incredibly creative, especially when it comes to wasting time. Throughout the ages, we’ve explored time-wasting with zeal, inventing new methods and distractions to pass the time and avoid contemplation. In the current age, that tool is generative AI. Generative AI has transformed not into an indispensable productivity tool, but into a babysitter. While AI companies push hard to convince enterprises that their tools are a great fit for business use cases, for many people, it has become a way to fill time exploring AI slop in its many forms. Welcome to the world of sloputainment.
Sloputainment: Next-Generation Time Wasting With AI Slop
No matter your position on generative AI’s usefulness for day-to-day productivity, it’s undeniable that generative AI truly excels at producing slop. The risks and impacts of slop outputs are aligned with the context in which they are generated. In business or safety-critical use cases, slop can have a significant negative impact, causing damage and endangering people. However, people messing around on the internet or playing with these tools on their own typically present a lower risk. There are exceptions, for example, using generative AI to bully or harass others, but, largely, that’s not what most people use them for.
In a previous post, I commented that people secretly like slop and that it is here to stay. Slop is a way for people to entertain themselves, pass the time, and generate content. Something we all witness daily.
Ethan Mollick, one of AI’s biggest cheerleaders and proponents of its productivity, spends much of his time playing around with image and video generation. Or at least, this is what his social media feed suggests.
The AI music generation app Suno reported annual recurring revenue of $150 million. You don’t think all these people are getting gold records out of this, do you?
And, before someone mentions, “But, did you see the number 1 country album was AI,” let me stop you there. You should watch this video instead of listening to that garbage.
Not only does the song suck, but apparently, someone only had to spend 3k for this publicity. Pretty good investment.
Using AI to make music makes someone no more of a musician than a child wearing a firefighter’s helmet makes them a firefighter. Nobody is going to see a child with a firefighter’s helmet on and send them into a burning building, remarking that’s what they signed up for.
Using AI to make music makes someone no more of a musician than a child wearing a firefighter’s helmet makes them a firefighter.
People are even using AI for gender reveals in totally normal ways, such as smashing into the Twin Towers or taking down the Hindenburg. You know, perfectly normal, totally sane shit.
OpenAI is even making the shift towards porn. This isn’t the move a company makes when they are on the cusp of AGI. It’s a move you make when you are hemorrhaging money and desperate for any avenue whatsoever to revenue.
Sloputainment is popular because it checks critical boxes. It’s a form of entertainment for the person creating it. A form of entertainment that requires no talent or effort, resulting in extremely low friction. Also, it creates content that the person can share on social media. Many constantly search for things daily to transform into content, fearing that a single day without posting on social media will make them irrelevant. The fact that sloputainment checks both the entertainment and content boxes all but guarantees it’s here to stay.
Sloputainment and the Illusion of Productivity
But directly using AI to create slop images and video is only one form of sloputainment. There is another form that masks itself as productivity or hustling. In a new trend, people boast publicly about how they’ve abandoned things like video games in favor of building software. Largely inconsequential software projects for themselves, but the task is transformed into content. And their perspective based on isolated projects is transformed into an entire worldview.
Why it’s bad to let AI creep into every moment and aspect of your life? I don’t know, why is that bad? With some people, there’s no delineation or line they won’t let AI cross. Don’t get me wrong, I’m sure it’s fun for people playing around with this stuff. I mean, building things with Legos can be fun, too. But nobody is confused when they build something with Legos that they are building the next big thing. That something really could come out of it, and that they may be onto the next multi-million-dollar app. This isn’t AI psychosis, but it is delusional.
There is a distinction that needs to be made here between the forms of sloputainment. The only way to get good at something is to practice it. For example, you can’t get good at building AI agents without building agents, which is why vibe coding doesn’t teach you much about real-world development. Even the person who coined the term vibe coding understands this. This activity is different than people just posting slop images to social media.
The issue is the undercurrent of hustle bro culture, which gives the impression that if you aren’t hustling, you’ll be left behind. In many ways, this public performance is meant to show that their personal activities are better than everyone else’s. It’s self-flagellation in the era of generative AI. People playing around with things to learn and understand is good. People replacing other activities in their personal lives with the illusion of productivity is bad.
In many ways, these activities resemble people playing around with their friends, similar to garage bands having fun jamming on nothing in particular. However, secretly hoping in the background that they get their big break and a gold or platinum album. Only, instead of a gold or platinum album, this is their award. It’s fitting that in the generative AI age, you get awards for spending money instead of making it.
It’s fitting that in the generative AI age, you get awards for spending money instead of making it.
However, instead of representing people enjoying the output of their creative pursuits, it’s just representative of a system chewing up tokens. The dystopia says, “Nom nom.”
Sloputainment Is Content
AI is not only making everything entertainment, but as a byproduct, it’s creating content. This is the knockout punch for our modern information junk food diet. It’s the ice cream piled high on a cake, topped with potato chips, chocolate, caramel, and a pound of M&Ms for breakfast, lunch, and dinner.
Social media has rewired our brains to see everything and everyone as content. The whole world is our content oyster, and nothing escapes the content lens. It’s why you see things like idiots defacing coral reefs with graffiti. If only this were AI slop. This is why some people have no problem using AI to harass other people and organizations. As I mentioned back in 2020, harassment is the true legacy of technologies like deepfakes. This does seem to be bearing out in the age of generative AI.
I think what bothers me most about this hustle bro nonsense is that it gives the impression of devaluing so much of what is truly valuable. I mean, quiet contemplation looks like time wasting to morons in motion. Which is Newton’s Fourth Law of motion, morons in motion, stay in motion. It’s also why so many people get so many things so wrong. They are so busy hustling that they never stop to contemplate, you know, to get things right.
It takes me forever, by generative AI standards, to write an article like this. Writing is thinking, and in each of these articles, I’m working my way through the topics like everyone else while attempting to give them the level of contemplation they deserve. If this site were about content instead of contemplation, I’d be blasting out AI-slop articles with clickbait headlines, trying to game SEO. You know, like over 99% of the internet. Instead, I’m content to labor away in obscurity. If writing is thinking, then generating with AI is the lack of thinking. This gets lost in the tidal wave of content slop.
If writing is thinking, then generating with AI is the lack of thinking.
Sloputainment is Entertainment
Somewhere along the way, we conned ourselves into thinking everything needs to be entertainment. Things now have to be converted into entertainment to be valuable. Even something as mundane as our own data can now be transformed into entertainment. I mean, Google created NotebookLM, allowing the generation of a podcast from our data. Because learning from reading, analyzing, and engaging with ideas is boring, and only losers would learn that way. We now have to be entertained to learn.
There’s a problem, though. When something is viewed as entertainment, it appears to have a more truthful weight or feeling. To use modern vernacular, you could even say that data-as-entertainment emits truth vibes. Where we may question an AI overview or summary, we are less likely to question the same data in the form of a podcast that sounds like humans or a video presentation with a human voice, but it’s the same data with the same issues. Especially since much of this data doesn’t conflict with our biases, otherwise, we wouldn’t consider it entertainment.
Where we may question an AI overview or summary, we are less likely to question the same data in the form of a podcast that sounds like humans or a video presentation with a human voice.
Take Graham Hancock’s Ancient Apocalypse docuseries on Netflix. Presented on a platform like Netflix, stunning locations, cinematic shots, but all 100% pure, unadulterated bullshit. Yet presenting the content this way lends it weight and credibility. Of course, it doesn’t help that the docuseries doesn’t feature any actual experts either.
Graham Hancock is a fraud with no expertise and a peddler of bullshit. Yet, he was given a platform to spread his nonsense to a wider audience. AI-as-entertainment platforms risk doing the same for every type of content and data. We risk embedding falsehoods and misperceptions deep in our brains due to formatting issues.
We risk embedding falsehoods and misperceptions deep in our brains due to formatting issues.
Text presented in paragraph form with easily clickable links is a much better, easier way to verify content than an audio podcast you listen to in the car or while doing something else. The same can be said of video presentations or cartoon talking heads. But paragraphs have higher friction than podcasts.
Admittedly, NotebookLM is neat technology, but the disconnect lies in failing to distinguish between a technology being cool and the value it truly provides, and in a far greater disconnect about what the technology does to us. You know, the tradeoffs. So much of our current moment consists of waving hands, directing our attention to how cool a technology is without consideration of use cases or impacts.
I’m sure this is just a continuation of a trend that Neil Postman identified as starting with television. But AI supercharges it. Imagine, instead of a podcast, next up will be video. As a matter of fact, while I was writing this post, Google updated NotebookLM to include generative video overviews, taking data entertainment to the next level. Using video, we can learn about someone like Neil Postman not by engaging with his work but through cartoon summaries that may or may not capture the important aspects. An approach Postman would detest, but no doubt see coming. There is a good chance these summaries miss important details as they focus on what’s most interesting, shocking, or exciting. We are about to “true crime” everything.
I should note that the impacts aren’t the same for all types of information. For some things, simple summaries are fine. However, the difficulty we face is understanding where the true delineation point lies, and, of course, the tendency to overestimate our knowledge based on trivial information.
There was an early attempt to use AI to cut together movie trailers. The AI identified the most “exciting” aspects of the movie, explosions, car chases, etc., but it didn’t connect with people or follow a story. It was just a bunch of cutscenes with no through line. Now, everything is cutscenes, fueling our entertainment addiction. There’s a lot of history that’s boring but important, and we risk paving over history as we reengineer it into entertainment.
We risk paving over history as we reengineer it into entertainment.
If you are lucky, there’s a memory of an entertaining school teacher who made classes more tolerable, and you may have even learned more because of it. We also have memories of learning things from documentaries. These memories may lead us to think that entertainment is the best way to engage with a topic and learn. However, there’s a distinction between entertaining and entertainment.
Entertaining is a method that still requires friction to get to a goal. It’s just that the friction becomes more tolerable due to heightened interest and engagement. For example, the entertaining school teacher still required the same reading and homework assignments. Entertainment is content that promises a complete reduction of friction. No need to read a book or engage with the content, watch this AI-generated short instead. Remember, knowledge and understanding aren’t generated from summaries or bullet points.
You may be thinking that there’s not a lot of harm in these activities, and for the most part, this is correct. How each person wastes their time is up to them. Fair enough, to each their own. However, consider that when we use AI to harass other people, we cause them harm. When we use AI to create entertainment masquerading as something else, we harm ourselves. This is what I take issue with: the tradeoffs that nobody considers and the false perception that hustling this way is the only way to make progress in the modern age.
There is no doubt that people use generative AI daily for productivity tasks. Great. And if people truly are using these activities to learn, fair enough. However, things like vibe coding and AI summaries don’t teach valuable lessons. Quite often, the lessons come afterward, when you get owned or try to apply your newfound summarized knowledge.
Conclusion
Sloputainment leaves so many things undiscovered, about ourselves, others, and the world. With every prompt, it steals from us, taking our time, understanding, and even our sense of who we are. We get sucked into the content vortex spinning chaotically around a hollow center with no ability to center ourselves, and it takes effort to break free.
Wasting time isn’t a modern concept. However, we have supercharged it with AI. In On The Shortness of Life, Seneca explains that it isn’t that life is too short, but the fact that we waste so much of the time we have. Seems some things haven’t changed since the first century AD. But we’ll close with some words from the great American philosopher, Sebastien Bach, who posed this concept in a series of questions:
Is it all just wasted time? Can you look at yourself, When you think of what you left behind? Is it all just wasted time? Can you live with yourself, When you think of what you've left behind?
