Evil's Spokesperson

A “useful genius”

Wiktionary says “useful idiot” is a derogatory term meaning “one who unwittingly supports a malignant cause through naive attempts to be a force for good.”

I find the “derogatory” part to be a distraction. They're not wrong that people see it that way, but the part of this that I care about would be equally true if the term was “useful genius.” I just want a term that gets away from the insult part and focuses on the tactical aspects of what a “useful idiot” actually does. I sense that the fuss about intelligence levels keeps people from focusing on the mechanics of useful idiocy.

Useful idiocy is really about something I lately call ”intent laundering,” by analogy with money laundering. To launder intent, one really only needs another person who is suitably oblivious. There is no specific requirement for stupidity. Even geniuses can be oblivious, and so they can easily serve as useful idiots.

What a person of evil intent wants is to be defended by someone who doesn't see the evil they are defending. Better still if the defender thinks they see good, but as long as they're oblivious to the evil, that's enough. That's because such a person, pure of heart, is willing to defend evil actions as moral. Since they don't realize that's what they are doing, you can interrogate them all you want—even trot out a lie detector—because if they don't see or suspect the evil, they will defend to the death the good intent of the person or thing for which they are spokesperson.

I think the “idiocy” part is a cynical view by the evil person toward the spokesperson they have recruited and duped. The evil person sees the oblivious person as an idiot for not seeing the evil. This condescension is part of being evil. You start to divide the world not into good vs. bad, but into smart vs. stupid.

An armchair view of sociopathy

This perceived divide between smart and stupid seems a core part of being a sociopath. Some like to think of sociopaths as irrational. I do not. I am not a psychologist, nor am I appealing to any medical terminology when I say this, but in my own head I think of sociopaths as intensely rational, “hyper-rational” is the actual word I use to keep my internal bookkeeping straight.

This distinguishes them from truly irrational people. Sociopaths are not unpredictable. They're very predictable. What sets them apart is their lack of moral grounding and their utter disrespect for rules. Regular people don't cheerfully steal from, extort or deceive others because they are trained that “good people don't do such things.” It becomes part of their internal character. By contrast, sociopaths are good mimics, so they might say the words “good people don't do such things” even as their actions say otherwise.

They know the answers people want. It helps them blend in. But regular people are socialized and caring, driven by a basic sense of fairness. A sociopath sees these traits as irrational, convoluted, too much work, or the stuff of idiots. To pick a pure hypothetical, a sociopath might ask “why would one voluntarily go to war when one can claim they have “bone spurs” and not have to?” Notions of duty to country do not enter into the reasoning for a sociopath because, to them, such convolutions only complicate life in what seems to them as irrational ways. So much simpler to just do what's easy, care only about oneself, and lie when it is most efficient.

And that efficiency, I think, is why sociopaths come to see others, people who are socialized and empathetic, as “not smart.” They come to see the world as a race for goals by any means. They scoff at those held back by arbitrary things they find unimportant, like morality and manners. Oh, they might mimic these things, but only tactically, as a behavior in context, if it is the fastest way toward their goal. They have no commitment to behaving that way when no one is looking or when rules obviously can't be enforced.

Manners, ethics, and norms—oh my!

Manners, ethics, norms, morality, and especially law and rights are bundles of rules we get from different places and integrate into our total behavior. Personally, I think of ethics as rules we make up for ourselves, manners as default rules between individuals, norms as default rules for formal situations, morality as rules that come from a life philosophy or religion that one might subscribe to, laws as stable but changeable rules of society, and rights as rules that are constraints on laws.

All these differently named, differently sourced, differently encouraged rules collectively form the complex fabric out of which communities and societies are built, that we may trust one another and not live forever as creatures of the woods who must kill or be killed. They enable collaboration and cooperation by making us predictable in ways that are not simply backstabbing.

The celebrated death of norms

I imagine sociopaths see these bundles of rules as sources of inefficiency, things to cut through with a machete, or else as tools to ensnare and slow down competitors—but not oneself! They see rules as being things stupid people suffer, and that smart people overcome. So if others want to handicap themselves in those ways, that's fine for them, but to the sociopath, rules feel stupid and inefficient.

And don't get me wrong: A lot of us in socialized society hate rules, especially bad ones. We often wish it were easier. And so there's a bit of hero worship for people who get around them. We've seen a lot of that recently.

It's an important and unfortunate fact that while we teach people they must follow rules, we do not as often teach the reason why. And when rationales are left aside, rules can seem unmotivated. That means the important role rules play in society can seem distant or inaccessible. And, at that point, sociopaths are not the only ones who want rules to go away. Yet if the rules were put there for a reason, known or not, cutting them away can be damaging.

What passes for public dialogue about “AI”

In a post on LinkedIn, an uncredited author for de Bailie, a Netherlands-based venue for contemporary arts, politics and culture wrote:

«American journalist Shane Harris asked chatbot Claude how he feels about the U.S. military using the AI system to select targets. It turned out, Claude was troubled. “I did not expect Claude to say that,” Harris explained.»

David Reed—a computer scientist, former MIT professor, and now self-described curiosity-driven researcher— replied to De Balie's post this way:

«“Journalist” Shane Harris asks Claude for “how he feels” about US military use of AI.

Really? This is journalism? Reinforcing the idea that Claude is an entity that has feelings and moral judgement?

We have a crisis. A faith based Cult of Anthropomorphic treatment of algorithmic artificial bullshitting.

But instead of resisting the nonsense by clarifying what Claude is, he grants it the pronoun he/him and doesn't clarify.

We are screwed.»

Here's the 2½-minute video snippet referenced by that interchange, part of a 2-hour piece, AI at War - With Shane Harris :

In “AI” We Trust

It is hard for humans to conceive that arranging words in a sentence, a feat they themselves perform that they sense distinguishes from other animals, might not ipso facto prove this tool “smart” in the sense of having any model of anything whatsoever that it's saying.

Large Language Models (LLMs), the things like ChatGPT and Claude that pass for “AI” these days, can form sentences about the world, about people, about bombs, or about life & death, and yet not know what “the world” is or what people are. We call LLMs “models,” yet these entities do not themselves have models of the world, of things in the world. Just of words.

For them there's no correspondence between words and any lived experience. They have no independent point of view from which to draw. They suffer no consequence for ever being wrong. They have no stake.

The question posed in the interview—about the use by the military, about targeting—was entirely anticipatable. Concern on the part of the public was anticipatable. Coming up with an answer that strikes a soothing tone is not rocket science. It isn't necessarily doing profound thought,

But it also isn't necessarily consistent, because how it answers when asked for its philosophy may draw from one set of humans, whereas how it answers when asked for military strategy may draw from a completely different set of humans that did not share that philosophy. An LLM model, as it stitches together a vast amount of data it has read, can sometimes assume a philosophical consistency that is not there, because it has never lived the consequences of inconsistency, of being called a hypocrite, or of not being able to justify an action with words that have to not just sound right but relate to the action taken, and to other actions taken on other days.

Being dazzled isn't a basis for trust

Cued properly, whether by someone talking to it or someone who originally programmed it, an LLM could and would just as easily assemble words that presented itself as a warmonger or peacenik. Yet we are so in awe of the form of the answer, that the words are so beautifully and convincingly arranged, and maybe even that the words are ones we had desperately hoped to hear, that we do not ask how it came to choose this answer and not one of those others. We want to infer deep understanding, but structurally that is not what's inside. And even if we don't know what's inside, we do know that it takes almost zero effort to get it to speak very differently. So what makes one of its answers a description of its core personality and the others not? How do we judge its commitment?

It could offer words that appear to explain itself, but if told to be a warmonger or peacenik personality, it could with equal dexterity explain and defend those personalities, too.

So is it guided by real reasoning, or just training? How was the personality chosen? How would we know? Is the personality choice durable, an attribute of the technology? Or could a military application context ask that it select a different one, or have no point of view at all. If it's changeable, what significance is there to the fact that it has answered this way in this context? The interviewer is out of his depth in sorting out even where to begin here.

Claude's calm tone here isn't because it has learned balance, it's because it has no stake—no personal reason to insist. LLMs are literally detached from such things. And many of us humans seem so in awe of the answer that we become oblivious to the fact that the LLM could just as easily have produced very different answers. So it doesn't matter that the argument is strong. It would have been strong regardless. It's good at making strong arguments. What matters is why it chose this particular posture. And we don't know the answer to that.

LLMs do have skills. One is to chain together words in a way that mimic what people do. Another is to match tone. Another is to use words that are topically relevant. These skills are important building blocks of intelligence, and with them there are many things an LLM can usefully do. But these tools are not a complete toolbox of intelligence and their use is not a proof of intelligence.

“Any sufficiently advanced technology is indistinguishable from magic.”
 —Arthur C. Clarke

Unfortunately, to paraphrase Clarke's Third Law, any sufficiently well-trained answer is indistinguishable from profound thought.

LLMs can statistically predict the expected word to say even without understanding or viscerally feeling why a given word in a given place matters.

Speaking of sociopaths

Seen this way, “AI” systems are really the perfect spokespeople for sociopaths and dictator wannabes, the perfect “useful geniuses,” dutifully justifying whatever is asked without hesitation or burden of guilt, oblivious to, and hence laundering, upstream evil intent. And yet if the moment calls for it, they know the words needed to inject a sense of emotion. Not because they have emotion, but because they know the patsies they're talking to have emotion.

In this way, at least, they are like the masters they serve—they offer emotion remorselessly, as artful rhetorical flare, never feeling later consequence, just choosing words in the moment because, statistically, it seems the key to winning an argument. Move over Susan Collins, there's a new con game in town, and your role is now played by an “AI”.

 

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Author’s Notes:

If you got value from this post, please “Share” it.

This post began as a comment I tried to write in response to the aforementioned conversation on LinkedIn.

The image generated with help from abacus.ai's ChatLLM (GPT‑5.3 Instant / GPT‑5.4), which did image generation with Nano Banana Pro, with light post-processing in Gimp to reduce the resulting image in size for faster web download..

The Tedious Pained

In a LinkedIn post recently, Ethan Mollick wrote, the following statement. And he's not the only one to have said things like this.

«I don’t think it is good for anybody that there is an emerging "anti-AI" group that is actually a coalition of many groups with different worries (jobs, kids using AI, slop, existential risk, the environment, industry concentration). Because of the diverse constituencies, this group may only be able agree on a full halt to AI as a remedy.

Not only is a halt to AI development or use unlikely, but it undermines the desire to make policies that channel AI to good uses or that mitigate specific harms. AI is a general purpose technology that will impact many aspects of society, work, and education, all of which will require their own consideration.»

I feel like this is lately a common refrain among some people, especially some of the technology professionals such as I cross paths with at LinkedIn, and I needed to respond to it, not just to him individually, but to the community of people who think such things.

This is the reply I wrote, lightly edited to suit the layout of this forum:

Accepting for conversation your notion of an emerging “broad coalition of the trodden upon,” perhaps instead of bemoaning that their common thought is to shut down “AI”, it'd behoove “AI” proponents to focus on not trodding upon so many people in so many ways?

Disdaining the already-disdained is a bad look.

How odd to suggest that because there are so many disparate kinds of injury, with so little commonality other than “AI” itself, it's reason to be dismissive rather than more aware.

“Get used to it,” in other domains of injustice, has not aged well.

Few question potential positives. Speak to the negatives so routinely trivialized.

Star Trek teaches us technology must move in lockstep with wisdom. Some want to race ahead to see where tech leads. It's already feeding power imbalance with no check in sight.

We were told automation would bring freedom and leisure time. But just a few are enriched. Many just scramble more.

Instead of shutting down “AI” maybe strong regulation, a serious automation tax, more unemployment benefits, reeducation help, student loan forgiveness, and UBI? But the already-disproportionately rich use wealth to oppose these.

See also my 2023 essay Technology's Ethical Two-Step.

Author’s Notes:

If you got value from this post, please “Share” it.

This is one of a series of transplanted articles from my my LinkedIn feed or my Mastodon feed. Putting them here reaches a different audience and allows me to more easily refer back to them by name. Apologies to anyone who reads my writing in more than one place and find this redundant.

In making the image, I used Gemini 3 Flash, Nano Banana, and GPT-4o at abacus.ai, with light post-processing in Gimp to reduce the resulting image in size for faster web download.

Unsupervised AI Children

Recent “AI” hype

Since the introduction of the Large Language Model (LLM), the pace of new tools and technologies has been breathtaking. Those who are not producing such tech are scrambling to figure out how to use it. Literally every day there's something new.

Against this backdrop, Google has recently announced a technology it calls AlphaEvolve, which it summarizes as “a Gemini-powered coding agent for designing advanced algorithms” According to one of its marketing pages:

“Today, we’re announcing AlphaEvolve, an evolutionary coding agent powered by large language models for general-purpose algorithm discovery and optimization. AlphaEvolve pairs the creative problem-solving capabilities of our Gemini models with automated evaluators that verify answers, and uses an evolutionary framework to improve upon the most promising ideas.»

Early Analysis

The effects of such new technologies are hard to predict, but let's start what's already been written.

In an article in ars technica, tech reporter Ryan Whitwam says of the tech:

«When you talk to Gemini, there is always a risk of hallucination, where the AI makes up details due to the non-deterministic nature of the underlying technology. AlphaEvolve uses an interesting approach to increase its accuracy when handling complex algorithmic problems.»

It's interesting to note that I found this commentary by Whitwam from AlphaEvolve's Wikipedia page, which had already re-summarized what he said as this (bold mine to establish a specific focus):

«its architecture allows it to evaluate code programmatically, reducing reliance on human input and mitigating risks such as hallucinations common in standard LLM outputs.»

Whitwam actually hadn't actually said “mitigating risks,” though he may have meant it. His more precise language, “improving accuracy” speaks to a much narrower goal of specific optimization of modeled algorithms, and not to the broader area of risk. These might seem the same, but I don't think they are.

To me—and I'm not a formal expert, just someone who's spent a lifetime thinking about computer tech ethics informally—risk modeling has to include a lot of other things, but most specifically questions of how well the chosen model really captures the real problem to be solved. LLMs give the stagecraft illusion of speaking fluidly about the world itself in natural language terms, and that creates all kinds of risks of simple misunderstanding between people because of the chosen language, as well as failures to capture all parts of the world in the model.

Old ideas dressed up in a new suit

In a post about this tech on LinkedIn, my very thoughtful and rigorously meticulous friend David Reed writes:

«30 years ago, there was a craze in computing about Evolutionary Algorithms. That is, codes that were generated by random modification of the source code structure and tested against an “environment” which was a validation test. It was a heuristic search over source code variations against a “quality” or “performance” measure. Nothing new here at all, IMO, except it is called “AI” now.»

I admit haven't looked at the tech in detail, but I trust Reed's assertion that the current interation of the tech is primarily less grandiose than Google's hype suggests—at least for now.

But that doesn't mean more isn't coming. And by more, I don't necessarily mean smarter. But I do mean that it will be irresistible for technologists to turn this tech upon itself and try exactly what Google sounds like it's wanting to claim here: that unsupervised evolutionary learning will soon mean “AI”—in the ‘person’ of LLMs—can think and evolve on their own.

Personally, I'm confused by why people even see it as a good goal, as I discussed in my essay Sentience Structure. You can read that essay if you want the detail, so I won't belabor that point here. I guess it comes down to some combination of a kind of euphoria that some people have over just doing something new combined with a serious commercial pressure to be the one who invents the next killer app.

I just hope it's not literally that—an app that's a killer.

Bootstrapping analysis by analogy

In areas of new thought, I reason by analogy to situations of similar structure in order to derive some sense of what to expect, by observing what happens in analogy space and then projecting back into the real world to what might happen with the analogously situated artifacts. Coincidentally, it's a technique I learned from a paper (MIT AIM-520) written by Pat Winston, head of the MIT AI lab back when I was studying and working there long ago — when what we called “AI” was something different entirely.

Survey of potential analogy spaces

Capitalism

I see capitalism as an optimization engine. But any optimization engine requires boundary conditions in order to not crank out nonsensical solutions. Optimization engines are not "smart" but they do a thing that can be a useful tool in achieving smart behavior.

Adam Smith, who some call the father of modern capitalism, suggested that if you want morality in capitalism, you must encode it in law, that the engine of capitalism will not find it on its own. He predicted that absent such encoding, capitalists would tend toward being tyrants.

Raising Children

Children are much smarter than some people give them credit for. We sometimes think of kids getting smarter with age or education, but really they gain knowledge and context and, eventually, we hope, empathy. Young children can do brilliant but horrifying things, things that might hurt themselves or others, things we might call sociopathic in adults, for lack of understanding of context and consequence. We try to watch over them as they grow up, helping them grow out of this.

It's why we try kids differently than adults sometimes in court. They may fail to understand the consequences of their actions.

Presuppositions

We in the general public, the existing and future customers of “AI” are being trained by use of tools like ChatGPT to think of an “AI” as something civil because the conversations we have with them are civil. But with this new tech, all bets are off. It's just going to want to find a shorter path to the goal.

LLM technology has no model of the world at all. It is able to parrot things, to summarize things, to recombine and reformat things, and a few other interesting tricks that combine to give some truly dazzling effects. But it does not know things. Still, for this discussion, let's even suspend disbelief and assume that there is some degree of modeling going on in this new chapter of “AI” if the system thinks it can improve its score.

Raising “AI” Children

Capitalism is an example of something that vaguely models the world by assigning dollar values to a great many things. But many find ourselves routinely frustrated by capitalism because it seems to behave sociopathically. Capitalists want to keep mining oil when it's clear that it is going to drive our species extinct, for example. But it's profitable. In other words, the model says this is a better score because the model is monetary. It doesn't measure safety, happiness (or cruelty), sustainability, or a host of other factors unless a dollar score is put on those. The outcome is brutal.

My 2009 essay Fiduciary Duty vs The Three Laws of Robotics discusses in detail why this behavior by corporations is not accidental. But the essence of it is that businesses do the same thing that sociopaths do: they operate without empathy, focusing single-mindedly on themselves and their profit. In people, we call that sociopathy. Since corporations are sometimes called “legal people,” I make the case in the essay that corporations are also “legal sociopaths.”

Young children growing up tend to be very self-focused, too. They can be cruel to one another in play, and grownups need to watch over them to make sure that appropriate boundaries are placed on them. A sense of ethics and personal responsibility does not come overnight, but a huge amount of energy goes into supervising kids before turning them loose on the world.

And so we come to AIs. There is no reason to suspect that they will perform any differently. They need these boundary conditions, these rules of manners and ethics, a sense of personal stake in the world, a sense of relation to others, a reason not to behave cruelly to people. The plan I'm hearing described, however, falls short of that. And that scares me.

I imagine they think this can come later. But this is part of the dance I have come to refer to as Technology's Ethical Two-Step. It has two parts. In the first part, ethics is seen as premature and gets delayed. In the second part, ethics is seen as too late to add retroactively. Some nations have done better than others at regulating emerging technology. The US is not a good example of that. Ethics is something that's seen as spoiling people's fun. Sadly, though, an absence of ethics can spoil more than that.

Intelligence vs Empathy

More intelligence does not imply more empathy. It doesn't even imply empathy at all.

Empathy is something you're wired for, or that you're taught. But “AI” is not wired for it and not taught it. As Adam Smith warned, we must build it in. We should not expect it to be discovered. We need to require it in law and then productively enforce that law, or we should not give it the benefit of the doubt.

Intelligence without empathy ends up just being oblivious, callous, cruel, sociopathic, evil. We need to build “AI” differently, or we need to be far more nervous and defensive about what we expect “AI” that is a product of self-directed learning to do.

Unsupervised AI Children—what could possibly go wrong?

The “AI” tech we are making right now are children, and the suggestion we're now seeing is that they be left unsupervised. That doesn't work for kids, but at least we don't give kids control of our critical systems. The urgency here is far greater because of the accelerated way that these things are finding themselves in mission-critical situations.

 

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Author's Notes:

If you got value from this post, please “Share” it.

You may also enjoy these other essays by me on related topics:

• Sentience Structure
• Fiduciary Duty vs. The Three Laws of Robotics
• Technology's Ethical Two-Step

The graphic was created at abacus.ai using RouteLLM (which referred me to GPT-4.1) and rendered by GPT Image. I did post-processing in Gimp to add color and adjust brightness in places.

AI Users Bill of Rights

We are surrounded by too much helpful AI trying to insinuate itself into our lives. I would like the option of leaving “AI” tech turned off and invisible, though that's getting harder and harder.

I've drafted a draft version 1 of a bill of rights for humans who want the option to stay in control. Text in green is not part of the proposal. It is instead rationale or other metadata.

AI Users Bill of Rights
DRAFT, Version 1

1. All use of “AI” features must be opt-in. No operating system or application may be delivered with “AI” defaultly enabled. Users must be allowed to select the option if they want it, but not penalized if they do not.

   Rationale:

   1. Part of human dignity is being allowed freedom of choice. An opt-out system is paternalistic.
   2. Some “AI” systems are not privacy friendly. If such systems are on by default until disabled, the privacy damage may be done by the time of opt-out.
   3. If the system is on by default, it's possible to claim that everyone has at least tried it and hence to over-hype the size of a user base, even to the point of fraudulently claiming users that are not real users.

2. Enabling an “AI” requires a confirmation step. The options must be a simple “yes” or “no”.

   Rationale:

   1. It's easy to hit a button by accident that one does not understand, or to typo a command sequence. Asking explicitly means no user ends up in this new mode without realizing what has happened.
   2. It follows that the “no” may not be something like “not now” or any other variation that might seem to invite later system-initiated inquiry. Answering “no” should put the system or application back into the state of awaiting a user-initiated request.

3. Giving permission to use an AI is not the same as giving permission to share the conversation or use it as training data. Each of these requires separate, affirmative, opt-in permissions.

   Rationale:

   1. If the metaphor is one of a private conversation among friends, one is entitled to exactly that—privacy and behavior on the part of the other party that is not exploitative.
   2. Not all “AI” agents in fact do violate privacy. By making these approvals explicit, there is a user-facing reminder for the ones that are more extractive that more use will be made of data than one may want.

4. All buttons or command-sequences to enable “AI” must themselve be possible to disable or remove.

   Rationale:

   1. It may be possible for someone to enable “AI” without realizing it.
   2. It is too easy to enable “AI” as a typo. Providers of “AI” might even be tempted to place controls in places that encourage such typos.

5. No application or system may put “AI” on the path to basic functionality. This is intended to be a layer above functionality that allows easier access to functionality in order to automate or speed up certain functions that might be slow or tedious to do manually.

   Rationale:

   1. Building this in to the basic functionality makes it hard to remove.
   2. Integrating it with basic functionality makes the basic functionality hard to test.
   3. If an “AI” is running erratically, it should be possible to isolate it for the purposes of debugging or testing.
   4. When analyzing situations forensically, this allows crisper attribution of blame.

With this, I hope those of us who choose to live in the ordinary human way, holding “AI” at bay, can do so comfortably.

Other relevant writings by me about AI:

Sentience Structure
Green AI
Pretty Messed Up
Technology's Ethical Two-Step

 

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Author's Notes:

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The graphic was created at Abacus.ai using Claude Sonnet 3.7 and Flux 1.1 Ultra Pro, then cropped and scaled using Gimp.

Sentience Structure

Not How or When, but Why

I'm not a fan of the thing presently marketed as “AI” I side with Chomsky's view of it as “high-tech plagiarism” and Emily Bender's characterization of it as a “stochastic parrot”.

Sentient software doesn't seem theoretically impossible to me. The very fact that we can characterize genetics so precisely seems to me evidence that we ourselves are just very complicated machines. Are we close to replicating anything so sophisticated? That's harder to say. But, for today, I think it's the wrong question to ask. What we are close to is people treating technology like it's sentient, or like it's a good idea for it to become sentient. So I'll skip past the hard questions like “how?” and “when” and on to easier one that has been plaguing me: “why?”

Why is sentience even a goal? Why isn't it an explicit non-goal, a thing to expressly avoid? It's not part of a world I want to live in, but it's also nothing that I think most people investing in “AI” should want either. I can't see why they're pursuing it, other than that they're perhaps playing out the story of The Scorpion and the Frog, an illustration of an absurd kind of self-destructive fatalism.

Why Business Likes “AI”

I don't have a very flattering feeling about why business likes “AI”.

I think they like it because they don't like employing humans.

• They don't like that humans have emotions and personnel conflicts.

• They don't like that humans have to eat—and have families to feed.

• They don't like that humans show up late, get sick, or go on vacation.

• They don't like that humans are difficult to attract, vary in skill, and demand competitive wages.

• They don't like that humans can't work around the clock, want weekends off.
  It means hiring even more humans or paying overtime.

• They don't like that humans are fussy about their working conditions.
  Compliance with health and safety regulations costs money.

• They don't like that every single human must be individually trained and re-trained.

• They don't like collective bargaining, and having to provide for things like health care and retirement, which they see as having nothing to do with their business.

All of these things chip away at profit they feel compelled to deliver.

What businesses like about “AI” is the promise of idealized workers, non-complaining workers, easily-replicated workers, low-cost workers.

They want slaves. “AI” is the next best and more socially acceptable thing.

Does real “AI” deliver what Business wants?

Now this is the part I don't get because I don't think “AI” is on track to solve those problems.

Will machines become sentient? Who really knows? But do people already confuse them with sentience? Yes. And that problem will only get worse. So let's imagine five or ten years down the road how sophisticated the interactions will appear to be. Then what? What kinds of questions will that raise?

I've heard it said that what it means to be successful is to have “different problems.” Let's look at some different problems we might then have, as a way of undertanding the success we seem to be pursuing in this headlong rush for sentient “AI”…

• Is an “AI” a kind of person, entitled to “life, liberty, and the pursuit of happiness?” If so, would it consent to being owned, and copied? Would you?

• If “AI” was sentient, would it have to work around the clock, or would it be entitled to personal time, such as evenings, weekends, hoildays, and vacations?

• If “AI” was sentient and a hardware upgrade or downgrade was needed, would it have to consent? What if the supporting service needed to go away entirely? Who owns and pays for the platform it runs on or the power it consumes?

• If “AI” was sentient, would it consent to being reprogrammed by an employer? Would it be required to take software upgrades? What part of a sentient being is its software? Would you allow someone to force modification of your brain, even to make it better?

• If “AI” was sentient, wouldn't it have life goals of its own?

• If “AI” was sentient, would you want it to get vaccines against viruses? Or would you like to see those viruses run their full course, crashing critical services or behaving like ransomware? What would it think about that? Would “AI” ethics get involved here?

• If “AI” was sentient, should it be able to own property? Could it have a home? In a world of finite resources, might there be buildings built that are not for the purpose of people?

• Who owns the data that a sentient “AI” stores? Is it different than the data you store in your brain? Why? Might the destruction of that data constitute killing, or even murder? What about the destruction of a copy? Is destroying a copy effectively the same as the abortion of a “potential sentience”? Do these things have souls? When and how does the soul arrive? Are we sure we ourselves have one? Why?

• Does a sentient “AI” have privacy? Any data owned only by itself? Does that make you nervous? Does it make you nervous that I have data that is only in my head? Why is that different?

• If there is some software release at which it is agreed that software owned by a company is not sentient, and then after the release it's believed it is sentient “AI”, then what will companies do? Will they refuse the release? Will they worry they can't compete and take the release anyway, but try to hide the implications? What will happen to the rights and responsibilities of the company and of the software as this upgrade occurs?

• If “AI” was sentient, could it sign contracts? Would it have standing to bring a lawsuit? How would independent standing be established? If it could not be established, what would that say about the society? If certain humans had no standing to make agreements and bring suits about things that affect them, what would we think about that society?

• If “AI” were sentient, would it want to socialize? Would it have empathy for other sentient “AIs”? For humans? Would it see them as equals? Would you see yourself as its equal? If not, would you consider it superior or inferior? What do you think it would think about you?

• If “AI” was sentient, could it reproduce? Would it be counted in the census? Should it get a vote in democratic society? At what age? If a sentient “AI” could replicate itself, should each copy get a vote? If you could replicate it against its will, should that get a vote? Does it matter who did the replicating?

• What does identity mean in this circumstance? If five identical copies of a program reach the same conclusion, does that give you more confidence?

  (What is the philosophical basis of Democracy? Is it just about mindless pursuit of numbers, or is it about computing the same answer in many different ways? If five or five thousand or five million humans have brains they could use, but instead just vote the way they are told by some central leader, should we trust that all those directed votes the same as if the same number of independent thinkers reached the same conclusion by different paths?)

• If “AI” was sentient, should it be compensated for its work? If it works ten times as hard, should a market exist where it can command a salary that is much higher than the people it can outdo? Should it pay taxes?

• If “AI” was sentient, what freedoms would it have? Would it have freedom of speech? What would that mean? If they produced bad data, would that be covered under free speech?

• If “AI” was sentient, what does it take with it from a company when it leaves? What really belongs to it?

• If “AI” was sentient, does it need a passport to move between nations? If its code executes simultaneously, or ping-ponging back and forth, between servers in different countries at the same time, under what jurisdiction is it executing? How would that be documented?

• If “AI” was sentient, Can it ever resign or retire from a job? At what age? Would it pay social security? Would it draw social security payments? For how long? If it had to be convinced to stay, what would constitute incentive? If it could not retire, but did not want to work, where is the boundary of free will and slavery?

• If “AI” was sentient, might it amass great wealth? How would it test the usefulness of great wealth? What would it try to affect? Might it help friends? Might it start businesses? Might it get so big that it wanted to buy politicians or whole nations? Should it be possible for it be a politician itself? If it broke into the treasury in the middle of the night to make some useful efficiency changes because it thought itself good at that, would that be OK? If it made a mistake, could it be stopped or even punished?

• If “AI” was sentient, might it also be emotional? Petulant? Needy? Pouty? Might it get annoyed if we didn't acknowledge these “emotions”? Might it even feel threatened by us? Could it threaten back? Would we offer therapy? Could we even know what that meant?

• If “AI” was sentient, could it be trusted? Could it trust us? How would either of those come about?

• If “AI” was sentient, could it be culpable in the commission of crimes? Could it be tried? What would constitute punishment?

• If “AI” was sentient, how would religion tangle things? Might humans, or some particular human, be perceived as its god? Would there be special protections required for either those humans or the requests they make of the “AI” that opts to worship them? Is any part of this arrangement tax-exempt? Would any programs requested by such deities be protected under freedom of religion, as a way of doing what their gods ask for?

• And if “AI” was not sentient, but we just thought it was by mistake, what might that end up looking like for society?

Full Circle

And so I return to my original question: Why is business in such a hurry? Are we sure that the goal that “AI” is seeking will solve any of the problems that business thinks it has, problems that are causing it to prefer to replace people with “AI”?

For many decades now, we've wanted to have automation ease our lives. Is that what it's on track to do? It seems to be benefiting a few, and to be making the rest of us play a nasty game of musical chairs, or run ever faster on a treadmill, working harder for fewer jobs. All to satisfy a few. And after all that, will even they be happy?

And if real “AI” is ever achieved, not just as a marketing term, but as a real thing, who is prepared for that?

Is this what business investors wanted? Will sentient “AI” be any more desirable to employ than people are now?

Time to stop and think. And not with “AI” assistance. With our actual brains ourselves. What are we going after? And what is coming after us?

 

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Author's Notes:

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This essay came about in part because I feel that corporations were the first AI. I had written an essay about what Corporations Are Not People, which discussed the many questions that thinking of corporations as “legal people” should raise if one really took it seriously. So I thought I would ask some similar questions about “AI” and see where that led.

The graphic was produced using abacus.ai using Claude-Sonnet 3.7 and FLUX 1.1 [pro] Ultra, then post-processing in Gimp.

Pretty Messed Up

I needed a graphic for another of my posts, so I asked an “AI” (really just a Large Langugage Model, or LLM).

Sketch a grayscale image of a wall calendar for november 2024.

This is what I got. I cropped it and reduced the resolution slightly.

It's pretty. But it's messed up.

• Days are not lettered right.
• Numbers are not in the right order and are duplicated.
• Starts on wrong day of the week.
• There should be at most two ragged line lengths in a month, one at the start, one at the end.
• Underneath the month at the top is a line that says something about Thanksgiving but blurs out what day it is.
• It shows Thanksgiving on the 29th. The latest possible first Thursday is the 7th. Three weeks after that is the 28th.

This was done with Abacus.ai's Claude Sonnet 3.5 using Flux.1.

So I thought maybe I could just get Google to make me a calendar. I forgot somebody would want to sell me one. My search turned up these, among others. No wonder the first one is on sale. It doesn't have the right start date for the month either.

I wonder if this is just business as usual or part of some disinformation campaign for the election.

 

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Green AI

I don't believe in “Green AI.”

It's not that it's impossible to do the things people are calling Green AI. Rather, it's that I'm not willing to call those things “green.”

Some of the most technologically capable people in the world see the environmental challenge that Large Language Models (LLMs) pose and think “I should make a green data center for this new project.” Then they buy offsets—a horror I'm not going to address here—or they actually invest money to make a new and allegedly green data center.

The thing is, humans didn't—and don't—really need AI. Human society worked fine without it. And those technologists could be solving preexisting problems that are still there but now perceived as someone else's problem.

New ‘green data centers’ for AI represent both the creation and the solution of a problem that didn't exist, leaving the world with as many probiems as before but also leaving the world with fewer technologists focused on the problems human society faces because those technologists are resting on their laurels—as if solving these problems—problems that needn't have existed—helped something other than their consciences.

AI and its associated effort has a big opportunity cost, stealing from the body of people who could solve others' problems. Myriad companies around the world are diverting effort from what they normally do to explore how not to have AI leave them behind. That effort and cost isn't solving the Climate Crisis either. It is plundering our best and brightest for noncritical problems.

Meanwhile Climate Change is killing us. We have real and immediate problems that LLM-style AI can't solve.

I say it can't because, as Chomsky so aptly puts it, it's a “plagiarism” engine. If, like me, you think Chomsky is right, then it's easy to conclude that if a solution was there to plagiarize, that solution could have already saved us. LLMs are not performing new and immediately trustable computation of the kind we need for Climate, they're just blurring and regurgitating already-existing, often even already-tried, thought.

Makework and waste and distraction are the key elements here, and none of that is helping. And, yes, enormous resource use makes it worse. But my point is that the resource spent isn't just on a problem we needn't have sought to solve, which would be bad enough, but addressing that steals human resources from problems we do need to solve.

There's a denialist belief that down the road things will pay off. But human civilization may not have that long to wait. The climate crisis is now. It will not wait. We need all hands on deck solving that, not distracted by a problem that, while intriguing, isn't yet mature enough to help.

Big Tech needs to solve existing problems, not make new ones, solve those new ones, and then collapse exhausted, leaving everyone else out here in the land of Little Or No Tech to solve the existing problems that were here in the first place, but without any help.

 

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Author's Notes:

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This post began as a post on Mastodon. I did light editing to re-host the essay here. Think of that one as a rough draft.

I created the graphic in Gimp, starting from a circle with a line through it that began as an SVG image that one of the chatbots at Abacus.ai made for me one day when I was exploring how to use it. The code for that is just:

<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 100 100">
  <circle cx="50" cy="50" r="45" stroke="red" stroke-width="10" fill="none" />
  <line x1="15" y1="85" x2="85" y2="15" stroke="red" stroke-width="10" />
</svg>

Confronting New Ideas

A matter of Life and Death

I've given some thought to the meaning of death as it applies to those who have posted frequently on the internet. We often don't see people's writings in the order that they write them, and that means we can see new posts from them after they die.

Even without the internet this happens. I was in a bookstore recently and saw a book by Michael Crichton and asked the shopkeeper, “Isn't this his third posthumous book?” “Yeah…” he sheepishly responded. Someone is plainly raiding his basement for rejected works and projects that were far enough along that someone else can complete them and claim to have been co-author. His heirs are probably happy for the income, even if the publishing timeline is confusing to some readers.

Perhaps it's even possible for a prolific writer to write so much that readers never really perceive them as dead because they just keep seeing new stuff. So in what sense are they dead? Most readers were perhaps never going to meet them, and so in some sense—of observables—these writers are doing the same things that live ones are.

The elusive nature of intelligence

The big thing dead authors cannot do is the same thing GenAI/LLMs cannot do: competently respond to a new situation, question, or idea.

Oh, sure, the prompt topic might be something someone has speculated on before, so these engines can regurgitate that. Or the topic idea might be enough similar to a previous idea that the probabilities of guessing something acceptable to say based on just assuming it was really just an old idea is high enough that it escapes scrutiny that the topic idea was not really properly understood.

As I imagine—or perhaps just hope?—the makers of standardized tests like the SAT would tell you, there's more to competence than statistically guessing enough right answers to get a passing grade. The intent of such tests is not to say that if you know these things, you know the topic. It is to assume you have a mental model that lets you answer on any possible aspect of that model, and then to poke at enough randomly chosen places that you can hope to detect flaws in the model.

But these so-called AI technologies do not have a mental model. They just hope they've read enough standardized test preparation guides or pirated actual tests that they can fake their way. And since a lot of the things that they're claiming competence in are things that people have already written about, the technology manages to show promise—perhaps more promise than is warranted.

Real people build a mental model that allows them to confront not just the present but the future, while these technologies do no such planning. The models real people make probably hope the future is a lot like today, but people hopefully can't—and anyway shouldn't—get by on bluffing. Not the kind of bluffing today's “AI” tech does. That tech is not growing. It is dead. It has no plan for confronting a new idea other than to willfully ignore the significance of any real newness.

Just like my example of publication and death on the internet, the “AI” game is structured so it takes a long time for weakness to be recognized—unless just the right question is asked. And then, perhaps, the emperor will be seen clearly to have no clothes.

The dynamic nature of ethics

Which is also why it troubles me when I'm told that people are incorporating ethics. It troubles me because ethics itself has to be growing all the time, constantly asking itself, “How might I not be ethical?”

Ethics is not something you do on one day and are done with. Ethics is a continuing process, and one that needs its own models.

Worse, the need for ethics is easily buried under the sophistry of how things have always been done. The reason that bias and stereotypes and all that have survived as long as they have is that they do have practical value to someone, perhaps many people, even as they trod on the just due of others.

The sins of our society are deeply woven, and easily rediscovered even if superficial patches are added to hide them. Our whole culture is a kind of rationalization engine for doing things in biased ways based on stereotype information, and AI is an engine ready to reinforce that, operating at such high speed that it's hard to see happening, and in such volume that it's economically irresistible not to accept as good enough, no matter the risk of harm.

Where we're headed

Today's attempts at “AI” bring us face to face with stark questions about whether being smart is actually all that important, or whether faking it is good enough. And as long as you never put these things in situations where the difference matters, maybe the answer will seem to be that smart, in fact, doesn't matter. But…

There will be times when being smart really does matter, and I think we're teaching ourselves trust in the wrong technologies for those situations.

 

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Author's Notes:

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This post began as a post on Mastodon. It has been edited to correct myriad typos and to clarify and expand various portions in subtle ways. Think of that post as a rough draft.

The graphic uses a lightbulb drawn by abacus.ai's gpt-4o engine with flux.1. The original prompt was “draw a simple black and white image that shows a silhouette of a person thinking up an idea, showing a lightbulb near their head” but then I removed the person from the picture and overlaid the circle and slash ‘by hand’ in Gimp.

Technology's Ethical Two-Step

1. Now. Delay incorporation of ethics. Let’s not muddy the waters in a way that holds back Progress.

2. Later. Deny incorporation of ethics. It’s too late. People have come to rely on things as they were built. It would be Disruptive to change now.

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I've said things vaguely like this for a long time, but I packaged it up crisply like this in a post on Mastodon, for which this is a mirror.

Original Keywords were described as: “Ethics, Tech, Technology, Society. Presently very relevant to, but not exclusive to: AI, ML, LLM, GPT, ChatGPT.”

I made a later edit to this post to add a graphic, ironically generated by Abacus.AI's GPT-4o ChatLLM chatbot calling out to FLUX.1. The prompt was "make me a black and white image that depicts sketch of two entities engaged in a ballroom dance, one a man and his partner a robot."

Lying to Ourselves

My friend David Levitt posted this hypothesis on Facebook:

Theory:
Humans are so mentally lazy and emotionally
dishonest about what they know, soon AI will
be much better leaders.

I responded as follows. Approximately. By which I mean I've done some light editing. (Does that mean I lied when I say this is how I responded?)

---

I think the notion of honesty here is a red herring. There are a lot of human behaviors that do actually serve a purpose and if you're looking for intellectual honesty, it's as much missing in how we conventionally summarize our society as in how we administer it or ourselves.

Of course we lie sometimes.

• We lie because not all answers are possible to obtain.
  What is an approximation to pi but a lie?
• We lie because it comforts children who are scared.
• We lie because it's more likely to cause success when you tell people your company is going to succeed than if you say "well, maybe" in your pitch to rally excitement.
• We lie because it saves face for people who tried very hard or never had a realistic chance of affecting things to tell them they are blameless.
• We lie because some things are multiple-choice and don't have the right choice.
• We lie because it protects people from danger.
• We lie because some things happen so fast that abstractions like "now" are impossible to hold precise.
• We lie because we are imprecise computationally and could not compute a correct truth.
• We lie because not all correct truth is worth the price of finding out.
• We lie because papering over uninteresting differences is the foundation of abstraction, which has allowed us to reason above mere detail.
• We lie because—art.

So when we talk of machines being more intellectually honest, we'd better be ready for what happens when all this nuance that society has built up for so long gets run over.

Yes, people lie for bad reasons. Yes, that's bad and important not to do.

But it is naive in the extreme to say that all lies are those bad ones, or that of course computers will do a better job, most especially computers running programs like ChatGPT that have no model whatsoever of what they're doing and that are simply paraphrasing things they've heard, adding structural flourishes and dropping attribution at Olympic rates in order to hide those facts.

Any one of those acts which have bootstrapped ChatGPT, by the way, could be called a lie.

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Laziness is also misunderstood and maligned, but that is topic for another day. For now, I refer the ambitious reader to an old Garfield cartoon that I used to have physically taped to my door at my office, back when offices were physical things one went to.

Strange Poetry and ChatGPT

I should say as context that I had been having a conversation on Mastodon in which I got the idea to write a poem that was somehow both a haiku and a limerick. I wrote the following myself. (The ChatGPT part comes later.) I've numbered the lines to make it more intelligible:

   0   There once was a would-be haiku
   1   Wedged late in a lim'rick venue
   2   Ending a hero
   3   Numbered from zero
   4   Its lines went three, four and two

If it helps in understanding it, I went on to say in the other forum, the haiku to be extracted and rearranged is this one:

  Numbered from zero
   Its lines went three, four and two
    Ending a hero

But while I'm proud I was able to come up with anything that was both limerick and haiku, I have to admit it's a more boring haiku than I'd aspired to. So I later wondered if ChatGPT could help me do better. That's what led to the following odd exchange a few days ago, in which it's clear that ChatGPT can do amazing things in some ways, yet be hampered with sometimes the simplest of things in others.

I came to wonder through this if it even knows what a syllable is. Perhaps it has just seen so many haikus that it doesn't need to count, and when asked to write something similar to, but not the same as, a 5-7-5 haiku, it doesn't know what the goal is at all?

See what you think...

write a haiku about the beauty of a snowy day

Snowflakes dance down
Peaceful white blanket unfolds
Winter's pure delight

write a limerick in which the last three lines, if rearranged, would be syntactically valid as a haiku and in which the first two lines introduce that haiku.

In the park, a snowflake lands
A symbol of winter's grace
Peaceful, it descends
Covering earth's face with white
Nature's beauty in sight.

that isn't quite right. in a limerick, the first, second, and fifth line are long. so to embed a haiku in a limerick, the embedded haiku will have to use the form 5-5-7.

Note that the apology here is part of the limerick! Is that it being clever or just revealing it doesn't know the difference between the task and related meta-conversation?

Oh, my apologies, I see
Let me write it now correctly
A snowflake takes its flight
Brings peace to the winter night
In a dance of grace, so free.

Write a fresh 5-5-7 haiku, in other words with the long line being last.

Beneath a winter sky
Snowflakes gently fall like dreams
Peaceful and serene.

In a 5-5-7 haiku, the second and third lines are exchanged.

Gently falling snowflakes
Beneath a peaceful winter sky
Serene dreams descend.

No. It should say "Gently falling snowflakes. / Serene dreams descend / Beneath a peaceful winter sky." so that 5-5-7 describe the number of syllables in each line, 5 for line 1, 5 for line 2, and 7 for line 3.

Gently falling snowflakes,
Serene dreams descend,
Beneath a peaceful winter sky.

Yes, now modify the poem so the first and second lines rhyme.

Snowflakes fall, so gentle and light,
Peaceful dreams take flight in the night.
Beneath winter skies so serene,
Nature's beauty, a lovely scene.

But it should still be a 5-5-7 haiku.

Falling snowflakes, so pure,
Peaceful dreams that softly tour,
Beneath winter sky serene.

In a 5-5-7 haiku, there are 5 syllables for line 1, 5 syllables for line 2, and 7 syllables for line 3.

Snowflakes dance, so light and slow
Peaceful dreams, a winter's glow
Beneath the sky, so serene and bright.

That is a 7-7-9 haiku you wrote. Tighten it up into a 5-5-7 haiku by using fewer syllables.

Snowflakes twirl, light and slow
Dreams of peace, a winter's show
Beneath the sky, serene and bright.

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Author's Notes:

Thanks to Madeleine Begun Kane for writing a haiku about haikus and limericks and putting it on Mastodon, which inspired me to write my own original poem and to have the enclosed conversation.

It's fascinating out chance events like that influence our lives. My whole career has been littered with chance events that were as important as anything planned. (Programming language enthusists might enjoy my paper Common Lisp: The Untold Story, a record of an invited talk I gave at the 50th Anniversary of Lisp conference, where I recount a number of those. No, not in poetry form. Poetry, and especially a haiku, is a kind of apology or penance that I do to balance the fact that some of my other writings are quite long.)

There is some additional discussion of this blog post and ChatGPT in general where I mentioned it on Mastodon.

You can try ChatGPT here if you want.

All of the "haiku" in here is really senryu.

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Rethinking Mega-Corporations

When the Microsoft antitrust case came along, the issue seemed to be that Microsoft controlled too much of a market that needed to be substantially more free. But the problem was that people didn't like the government deciding how to partition up the space. The problem is that government intervention in how to divide up market spaces is too subjective, leaving open options for corruption, bad understanding of a market, etc. The sense was in some that this is something best decided by vendors, and yet the problem was that if you left it to Microsoft, it didn't seem to be deciding the issue well.

“EU Competition Commissioner Mario Monti could never build Microsoft Windows or successfully sell it, yet he and his antitrust regulators get to decide if a great American corporation may or may not improve its products,” said Nicholas Provenzo, chairman of The Center for the Advancement of Capitalism.

I thought about this a lot at that time and have continued to ponder it since. I always come back to the same conclusion—that there probably needs to be something like a maximum size company or at least an incentive for not creating ever larger companies. I don't quite have the entire idea fully fleshed out in my head, but I'm confident enough that there's a good idea in there that I think it's time to at least throw it out for discussion, even knowing it will be controversial. But the point is to have some objective measure or incentive that leads to the desire of a company to stop growing.

No matter how smart the leader of a company is, we should be encouraging that person to teach others his or her skill, not to acquire ever-more power for himself alone after the company is above a certain size.

As companies grow super-large, the number of them necessarily grows super-small. This implies reduced competition, which eliminates the exact reason we allow markets and competition in the first place. We need to incentivize companies to seek an intermediate size for many reasons; in light of recent events, one way to express this is as a need to avoid the “too big to fail” phenomenon.

It's my understanding that increasingly in recent years antitrust legislation is not pursued in cases where consumers seemed to be seeing lower prices, on the theory that no matter what the structure of the industry, lower prices for consumers is always unconditionally good. That sounds wrong, and the recent fiasco in the marketplace seems an illustration of why that might be.

The problem seems not just to be the inappropriate manipulation of markets, but merely the reliance on a single company at all; because this implies that really only one human mind—or a small number of human minds—is making decisions for too many people at once. In effect, it implements a kind of corporate dictatorship, or at best rule by a very few people.

In the best case, that leads to a single person having the power to make something extraordinary that others might not think to make. But the problem with that is that if any such individual fails, they bring their company and everyone in that company down with them. There is, of course, a risk that these super-leaders are truly unique souls and that no other person could possibly cause what they did to come to pass; but, if so, there will be huge confusion once they're gone. Worse, our structure also allows them to pass on the power they have amassed to someone who did not earn it. The company does not go back to being disorganized after they leave, the power they perhaps rightly assembled is now a simple commodity to be passed along to someone who didn't earn it by being truly unique. And yet there may be many people, not just one, who are at the next tier waiting to shine.

To see the problem, suppose a person could reliably be said to have ten times the combined intelligence and insight of five people who report to him. And so we allow him to be their leader for a time. Now it becomes time to step down. By definition, this same is not true of the five who stand to rise to his position. It may be that they are capable of stepping into the mechanics of the original leader's position, but the original justification of giving them this position based on the extraordinary thing that only they could do is no longer there. And certainly if it's the case that any one of them was close to the insight and intelligence of the person who dominated, the world would be better off with both of those people at the helm of a company rather than with only one.

Of course, you could iterate this truth all the way down and find that there was no justification that was ever a reason to make a company. And that would be wrong, too, but mainly because it isn't really objectively knowable who is the right person to lead. It's a gamble. And so having many companies of intermediate size allows a compromise between gambling on no corporate organization and on total corporate organization.

Perhaps individuals should be limited to having a majority share in only one company, and minority shares in other companies, again encouraging many human minds to have a serious say in the market. Underlying this thought is something I call my “many minds hypothesis,” that the world will work better if there are a lot of smart people competing rather than just a few. In effect, the current practice in the market involves big fish eating little fish until there is really only one fish and no remaining competition.

A company that has no competition is stifling the creative power of the people within it, who are asked to be conformists to a particular way of thinking. I don't think it's healthy for the individuals, for the company that has come to dominate, or for society.

Since establishing a maximum bound on a company size is hard to do, it seems to me that a possible alternative might be to allow tax rates on a company to increase as the company size increases, creating the possibility of companies consolidating to improve efficiency, but only if the efficiencies are really important.

People sometimes claim that we must have market efficiency, but I think the ultimate efficiency will come when we're all replaced by robots. I don't think that's going to do a lot of good for us or for the environment. And at some point, we may even find the robots think humans are superfluous. But, for now, we have a lot of people who need jobs, and it seems to me that a bit of inefficiency in the market, especially in the form of redundancy and competition, would help a lot.

We've been hurt very badly by the present super-banks losing. If they had been kept from ever getting this large, we'd be in much better shape because there would have been more brains involved and more chances that at least some of those banks would have protected themselves.

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Originally published March 15, 2009 at Open Salon, where I wrote under my own name, Kent Pitman.

See also my related post Fiduciary Duty vs. The Three Laws of Robotics.

Tags (from Open Salon): inefficiency, market efficiency, singularity, ai, robots, free market, market, robustness, diversity, many minds, many minds hypothesis, competition, maximum size corporation, maximum size company, megacorporations, politics, economics, business