Once again, the appeal of The Rockford Files [Media Notes 164 B]

Once again I find myself working my way through The Rockford Files thinking, “Gee, this is my intellectual comfort food, I should write a post about that.” And once again I discover, “Hey! I’ve already written that post.” And so I have.

That means that, to justify this post, I’ve got to cover new material, so I will. Here’s what I said in that previous post:

Garner is a handsome middle-aged man, six feet and perhaps an inch or two tall. He plays an easy going character, James Rockford, who is masculine without being macho. He can handle himself in a fight, which he frequently has to do, but he’s not a martial artist or a superhero. He’s competent, but vulnerable and takes his lumps. He likes sports, going to games, going fishing, often with his dad. He’s single, but is attractive to women, and kind. He’s had affairs in the past, and has one or three in the course of the show, he may even have been close to marriage.

Much of the appeal stems from the fact that he’s an interstitial character, if you will. He falls between the keys, lives in the cracks. While he makes a living, just barely, he’s not chained to a 9-to-5 job. He’s not been broken to harness.

I also noted that he doesn’t live within the confines of work mode. He’s not a slave to Homo economicus.

Moreover, he’s not married. His police buddy Lt. Becker is married, but Rockford himself is not. We do see Becker’s wife in a handful of episodes, but that’s all. She’s there as an adjunct to Rockford’s relationship with her husband. That’s all she could be in the show. So it doesn’t make sense to have her in too many episodes. She’d be in the way.

But why couldn’t Rockford himself be married? We know that he’s thought about, maybe even came close in the past. But married himself? How would that change the dynamic that makes the show work?

What if he’d married his attorney, Beth Davenport? It seems that they’d dated in the past and she pretty much confessed that she’d thought of him as a husband. Well, if they’d have gotten married, what kind of life would they have lived? I can’t imagine her living with him in that trailer; that’s not at all her style, not at all. Nor can I imagine him living her life style, with the elegant apartment. What of his PI business? Would he have taken it upscale to suit her clientele as a lawyer? I don’t think so.

Now, can I translate that paragraph into a statement about audience preference? That is, whoever finds Rockford appealing, male or female, finds him appealing as he is, an interstitial bachelor who likes women, dates them occasionally, and has longer term affairs, but that’s it. Whatever the basis of the show’s appeal, it’s incompatible with marriage as we currently conceive it.

Now, David Chase wrote and produced many episodes of The Rockford Files. But he’s best known as creator of and writer for The Sopranos. Marriage is central to that show, both Tony’s relationship to his wife and his two children, in addition to his many responsibilities as a gangster. What I’m suggesting is that, in a way, Tony Soprano is a Jim Rockford who’s married. Obviously, they’re very different types of people. Tony Soprano is overbearing, aggressive, and violent in a way that Jim Rockford his not. And if Jim Rockford is interstitial, then Tony Soprano is interstitial on steroids. And where Jim had is lawyer, Beth, Tony Soprano had his psychiatrist, Jennifer Malfi. That’s a very different kind of relationship – and I note that Rockford’s most substantial affair within the show was with a (blind) psychiatrist.

What interests me is that neither Rockford nor Soprano are “broken” to work mode. They make their living in (something like) play mode. I’m thinking something like: If you want to center a program around a Rockford-like character AND have him be married, you have to make him a gangster to do it. That is to say, our conventions about men, women, and marriage are such, that that’s what you have to do.

Do I believe that? Not quite. After all, I just made it up. It’s worth exploring with shows like Breaking Bad and Ozark, both about married couples (forced) to live on the wild side. The Hunting Wives? Sex/Life? Hmmmm....

On the pleasure of making music

I recently posted a video in which Adam Neely argued against using AI to make music. In that video he showed the CEO of Suno, Michael Shulman argues, “It’s not really enjoyable to make music now. It takes a lot of time. It takes a lot of practice.” Hence the justification for an AI program that does all the work for you.

I’m with Neeley on this one. I note further that the idea and practice of being merely a consumer of music, without being able to make your own, is relatively recent. Before the invention of sound recording in the late 19th century and the invention of broadcast media in the 20th, before those things happened the only music was live music. If you wanted to listen to music, you have to be in the presence of live performers. To be sure only a small group ever became full-time professional musicians, but a somewhat larger group became reasonably competent amateurs. And I strongly suspect that everyone participated in some active music-making or associated dance more than is the place today.

Passive listening is a different kind of experience. To be sure, it is now possible for anyone to experience the best possible performances through sound recording and broadcast, and that is surely a good thing. But it’s not quite as good as being there in person. And in either case the pleasure is not the same as making your own music, even if your music is, shall we say, a bit basic.

Wayne Booth makes that point in his book, For the Love of It: Amateuring and Its Rivals (1999), which is grounded in his love of cello playing. Here’s a couple of excerpts:

So what will be the main point here? Well, obviously not the totally, finally inaccessible perfection but the playing itself, good and bad. We usually manage to rise above the distractions and play, for the sake of the playing. While much of the rest of the world is negotiating costs and benefits of a different kind, we are negotiating interpretations—and when things go well, the pay-off is beauty, friendship, and joy. (About the many in the world who can afford neither kind of negotiation—the impoverished, the hungry, the deprived—I'll not say much, and what I say will be said guiltily. To fiddle while much of the world burns is surely wicked, but everyone who has read this far is to some degree already caught up in the wickedness. Will I be able to say any more in my defense than that some kinds of fiddling come closer to redeeming the world than some other kinds?)

Later:

What I hope will harmonize the debating voices is an unqualified celebration of what it means to take on any difficult and complex task for the sheer love of the task itself, with no possibility of future pay-off. In a world filled increasingly with easy pleasures why take on a tough love that requires daily practice, burdens you with a sense of critical failure, and risks leading others to accuse you of wasting your time—and theirs? Or, if you are bored with the easier pleasures, why not instead give yourself more of the pleasure yielded by getting ahead professionally? Steady devotion at the office will get you somewhere, while steady devotion in front of a music stand or learning jazz trombone or gardening—well, won't you just end up about where you began?

And this:

I am an amateur cellist with an uncomfortable vulnerability to that word "lack" in the second definition. I do love to play the cello—especially when others are playing with me; over the years it has come to feel less and less like a mere addendum to life, a pastime, a hobby, and more and more like something beyond even an added luxury: it's now a necessity. But though I "practice" the art lovingly, "for my own pleasure," practice at least an hour a day, I often practice it with little ease and never with any skill remotely resembling "professional."

There’s more at the link.

The idea that we should rest content with having AI generate tunes for us, that ultimately we don’t need humans making music at all because the AIs can do it “better,” that betrays a frightfully shallow conception of being human, of living. It reduces being human to being simply a consumer of experiences, which seems to me to be the ultimate motivation of the fantasy that we’re living in computer simulation, that we’re not doing anything at all but are rather being done to. That’s the (ultimate) triumph of Homo economicus over Homo Ludens.

Elle (from the world of Legally Blonde) [Media Notes 186]

I’ve just been through the first season of Elle (on Amazon), which is a prequel to Legally Blonde, from 2001. And so I decided to re-watch Legally Blonde, which I had enjoyed when it first came out in theatres and then some years later when it was streamed. I decided that I preferred the Legally Blondes over The Devil Wears Prada 2.

Now, I’m not sure I’m in the target demographic for either films. Maybe I’m at some edge of the demographic for Prada, but nowhere near the demographic for Blonde. But it seems to me that Blonde serves its demographic better than Prada serves its. Prada is about the imperious editor of Runway magazine, modeled after Vogue. I’m sure I’ve looked at Vogue once or three times, but that’s it. However I’ve long looked at the fashion coverage in the Sunday New York Times and I generally look at photos of the “looks” on display at important award shows and, of course, the Met Gala. So I’ve got some interest. I don’t have any interest in Cosmopolitan, but I’ve certainly leafed through issues. I have a vague sense that my sister may have read it decades ago. While Blonde is not about Cosmo, it does treat Cosmo as the bible, mentions it frequently, and splashes its cover on the screen often enough. Elle Woods swears by it.

Well, I suspect that the readers of Cosmo are more honestly served by Elle Woods in her various incarnations than the readers of Vogue are served by Prada 2, I don’t remember the original well enough to judge. But I do remember that speech about cerulean:

I can believe the substance of the speech. But what does that have to do with the line I remember from Prada 2: “You don't have what it takes. I'm sorry, but you're not a visionary. You're a vendor.”

I know Miranda thinks of herself as a visionary. A visionary of what? Of design? That’s the designers, no? Or is it her eye for design that makes her a visionary, an eye that crafts the editorial style of her magazine? Does that make her a style visionary or merely an astute vendor? I’m sure that Prada 2 doesn’t make the distinction, or tries and fails, but perhaps the original Prada did, I just don’t remember it well enough.

But there is no such pretension about Legally Blonde. Yes, there’s some snobbery and some cliquishness, but the movie wasn’t really about them nor is the prequel series. They prove to be superficial and harmless. The movie presents us with what we initially take to be a dumb blonde prom queen who swears by Cosmo and shows us that she is, or can easily be, a smart, resourceful, and tenacious young woman. In the movie she follows her handsome, shallow, and transactional boyfriend to Harvard Law School. She proves to have shrewd judgment about people and a good legal mind, dumping idiot boyfriend in the process. Elle gives us the same characteristics stretched over an eight episode series. She figures out who’s scamming the high school budget and develops fast friendships with grunge Seatle teens whose sensibility seems (and is) at odds with her perky pink California glam. She grows.

What we’ve got is a light romp with Homo Ludens in Blonde vs. a highly polished trek with Homo economicus in Prada.

What can we learn from Nordic happiness?

Nicholas Kristof, What We Should Learn From Nordic Happiness, NYTimes, July 4, 2026.

You want security, health care and the American dream? Look to Scandinavia.

“We actually live the American dream,” Jens Stoltenberg, a former prime minister of Norway who is now the finance minister, told me. “The American dream, it’s more reality in the Nordic countries than in America.” Image

Skeptics have argued that generous welfare benefits and the resulting high taxes have held back the Nordic economies. Perhaps a bit. “Farewell, Nordic model,” The Economist wrote in 2006. But Norway is now richer than the United States per capita, and Norwegian workers are more productive than American workers, with higher output per hour. Scandinavians live longer than Americans, and people are happier. The five Nordic countries — Denmark, Finland, Iceland, Norway and Sweden — all rank among the six happiest countries in the world in the World Happiness Report, based on Gallup polling.

Yet the Nordic countries are themselves facing significant challenges, including fiscal pressures, immigration, widening inequality and perhaps some breakdown in the social consensus. Some doubt whether the model can survive here, let alone be exported to countries that are larger, less homogeneous and more suspicious of taxation.

On the other hand, it’s not an alien model but, for Americans, a path we once blazed. Lawrence Katz, a Harvard economist, told me that the United States and Scandinavian nations pursued similar policies from the 1940s through the 1960s. That was the period when the United States rapidly expanded educational opportunities, had strong unions and, in the 1940s, experimented with universal child care. The post-World War II period is sometimes thought of as a golden age, for the economic pie both grew and was sliced more equally.

“The U.S. in the mid-20th century was sort of like Scandinavia today,” Katz said. But America changed course in the 1970s and eventually embraced the Reagan revolution.

One reason for the retreat, I’ve argued, was racialized political rhetoric that characterized some safety-net programs and investments in opportunity — used by Americans from all walks of life — as handouts primarily benefiting Black people, with a particular emphasis on caricatures of the “welfare queen.”

Three misunderstandings:

When Americans discuss the Nordic system, they sometimes suffer from three misunderstandings.

The first is that these are socialist countries. While they are often run by social democrats, they have market economies. Sweden did experiment in the 1970s and ’80s with quasi-socialist policies, but the upshot was an economic crisis. As Johan Norberg, a Swedish writer, put it: “We have been socialists and we’ve been successful — but never at the same time.”

The second misunderstanding is that because of their strong welfare systems, citizens of Nordic countries lie around while collecting benefits. Sure, some people do manipulate the system, but the labor force participation rate is higher in Nordic countries than in the United States.

The third is that in the case of Norway, its success is mostly a reflection of its oil wealth. Oil has given Norway a nice cushion, but the country has also managed the cushion unusually well — putting it in what is one of the world’s largest sovereign wealth funds. Moreover, according to Geir Axelsen, the director-general of Statistics Norway, the increase in female labor force participation in Norway since the early 1970s appears to have added roughly as much to the country’s gross domestic product as oil has.

How it came about:

To understand how the Nordic socioeconomic system evolved, I dropped by the office of Kalle Moene, an economist at the University of Oslo. The system began in the 1930s, he said, when workers in thriving sectors of the economy agreed to hold down their wage demands to support sectors that were struggling.

That principle — sacrificing to help those not doing so well — still underpins the region’s business model. Norwegians who are better off are willing to give up some income to ensure that people in blue-collar jobs get by.

Moene argues that this wage compression promotes innovation and dynamism by boosting the profitability of growth industries and by lowering profits in lagging industries.

There's more at the link.

Friday Fotos: The Last Frontier of AI

No photographs this Friday. Instead, images created by ChatGPT.

I used quite a long prompt for the first image, but the prompt came in two parts. The first part was the longest. I won’t put that up. Though I used it to ensure a rich conceptual context for ChatGPT, you don’t really need it to get a feel for what’s going on. Nor will I give you ChatGPT’s short verbal response, which I’d asked for. Why? I suppose I wanted to verify that it had “understood” the material. Anyone, I then gave it one last paragraph and asked it to base it’s image on that. I will give you that paragraph, followed by the rest of that session. After that, and “below the fold,” I give you some of the recent images that got me thinking along these lines. Click on an image to enlarge it.

* * * * *

If that's right, then the last frontier isn't more capability in the pattern-matching sense — bigger weight spaces, richer latent connections, better approximations of the associative regime. It's the specific, non-scalable, non-parallelizable fact of an individual mind's biography, which generates paths through possibility space that are real, productive, and genuinely inaccessible to any system that hasn't lived a life. That would be consistent with everything the day's argument has built toward: embodiment, developmental history, tacit knowledge distributed across time in a single nervous system rather than across space in a community or a corpus. The doppelganger, if it's ever built, would need a biography, not just a bigger dataset. And a biography, by definition, can only be lived once, by one entity, in one order. That may be the thing that doesn't scale, and it may be exactly why it counts as the last frontier rather than a soon-to-be-automated intermediate stage.

I like that, I like it a lot. Let me tell you what I’m thinking. Over the last year or so I’ve had you create a lot of images, various types for various purposes. One of the things I’ve been thinking about is creating fine-art images. Some of the images I’ve had you do are near fine art; in fact, some are parodies of existing fine art images. I’m particularly interested in the combination of concrete identifiable imagery and abstract imagery, especially abstract imagery suggesting biology (cells, DNA) and information systems. You’ve got that in this image. So let’s play around with it a little. Give me a distinctly different take on the subject. Perhaps an aerial view of some landscape where the viewing is flying over in a biomorphic vessel and the territory below flows toward natural realistic imagery in one direction and abstract informatic imagery in the opposite direction.

When I was young I was deeply impressed by a book called Pagoo, illustrated by Holling Clancy Holling. There must be copies of that on the web. I know there are since I’ve seen them. That’s tidepool imagery. Take the concept we’re evolving and apply it to that.

I’ve had you design various kinds of imaginary currency. Take the imagery we’ve been working with and base the design of imaginary currency on it. But don’t use real numbers or alphabetic characters anywhere. Yes made-up squiggles and designs that have the texture of print, but aren’t.

Now I want to go Hegelian. Think of the first image we generated as the Thesis. The next three are variations on the Antithesis. I want you to combine Thesis and Antithesis to produce a Synthesis. Render it in a square aspect ratio.

This is promising. I’ve got to eat. But I’ll be back to do some more exploration along these lines.

* * * * *

ChatGPT gave me a somewhat odd response to that, as follows:

Sounds good. This line is worth continuing: biography + tidepool ecology + information space + currency/ornament as a synthetic fine-art language.

What's odd about that? It’s just a little too specific for what I’ve been thinking. But that’s OK. I’ve collected some recent images below. These are what set me to thinking along these lines. FWIW, I’m not quite sure what I think of these images. But I do think I’ll continue experimenting. 

ADDENDUM & BTW, a couple of hours later: On the whole I find the images below the fold more compelling than those above the fold. Hmmm.....

Outline – Play: How to Stay Human in the AI Revolution

I've been working on this book project for some time now. An earlier title was Homo Ludens Rising: A Manifesto for the Fourth Arena and I posted an outline for the project under that title a year ago. I have since revised the project considerably, and given it a new title as well (suggested by my friend, David Porush): Play: How to Stay Human in the AI Revolution. While I have posted the new title here and there, I've not posted the new outline. Here it is, below the image which was created by ChatGPT.

The prose is entirely AI generated, the overview by ChatGPT and the rest of it by Claude. The process behind that outline, however, was long and complicated, involving both chatbots and me.

About the Book

This book explores how artificial intelligence is forcing a rethinking of what we know, how things act in the world, and what forms of life we value. Rather than treating AI primarily as a labor-displacing technology or an existential threat, it approaches large language models and related systems as cultural technologies—on a par with markets, corporations, and media—that demand new forms of epistemic trust, institutional design, and self-understanding.

The book first diagnoses how modern societies became trapped in work mode, organized around Homo economicus and equilibrium machines privileging efficiency, stability, and monetized value. The book then recovers Homo ludens—the human capacity for play, exploration, and generativity—which has always persisted in the margins, especially in art, music, and science fiction.

Midway through, the analysis shifts into speculative fiction set in the year 2150, using narrative rather than argument to make a different world feel real. In this future, a society centered in Kisangani has developed low-energy, generative forms of artificial intelligence and human–AI partnership that support play, creativity, and care rather than substitution and control. The final chapter returns to the present with a long-term orientation for building institutions, technologies, and cultural norms capable of sustaining such a transition.

Chapter 1: The Grammar of Truth, Revised

The opening chapter frames the challenge posed by contemporary AI as primarily epistemological. Large language models generate fluent and persuasive outputs without transparent grounding, unsettling long-standing assumptions about truth, authorship, and evidence. To understand why this feels so unsettling, the chapter steps back to examine how language has historically functioned as an epistemic regulator — how truth claims were once tightly bound to direct experience and communal accountability, and how modern institutions transferred that work to credentialing, citation, and peer review.

The chapter introduces a key distinction between equilibrium machines — designed to settle into stable, repetitive behavior, the engines of the Industrial Revolution — and generative machines, capable of producing structured novelty. Language itself is a generative machine; LLMs are its latest and largest instantiation. Just as the steam locomotive forced an ontological displacement by performing autonomous motion once considered uniquely animal, LLMs force one by performing linguistic performance once considered uniquely human. The unease is real, but it arises from a mismatch between new mechanisms and inherited categories, not from anything supernatural.

This reframing opens a fork that will shape the rest of the book: AI can be developed either as a substitute for human labor, reinforcing the competitive logic of Homo economicus, or as an augmentation of human generative capacity, aligned with play, exploration, and creativity. The choice is cultural and institutional, not technical. The chapter closes with a reflexive account of how it was itself produced through human-AI collaboration, using that process as a concrete case study of what institutionalization of generative machines might look like in practice.

Chapter 2: Trapped in Work Mode

This chapter shifts from machines to lived experience. It opens with a concrete and familiar phenomenon: the disorientation many men face upon retirement, evidence of a deeper cultural condition in which identity and worth have been tightly bound to work. From this starting point, the chapter generalizes: work mode is a pervasive orientation in which time is structured by schedules, worth measured by output, and personal identity tied to labor markets.

Within this framework, AI registers automatically as threat — a competitor or replacement. Contemporary fears of displacement arise less from AI's intrinsic properties than from the evaluative lens imposed by Homo economicus. The chapter is diagnostic rather than prescriptive: its task is to make the contingency of work mode visible, and to loosen the reader's identification with it.

Chapter 3: The Rise and Collapse of Homo Economicus

This chapter provides the historical backbone. Homo economicus is not a natural form of human existence but the product of specific technological and institutional developments centered on equilibrium machines. The chapter opens with hunting-and-foraging societies — presented not as romantic precursors but as sophisticated systems featuring flexible coordination and distributed intelligence — before tracing the gradual subordination of generative human capacities to equilibrium-oriented systems through agriculture, the division of labor, and finally the Industrial Revolution.

The apparent "collapse" of Homo economicus is not the failure of rationality as such, but the exhaustion of a form of life overextended beyond its proper domain. Conrad's Heart of Darkness enters here as a moral counterpoint, marking the moment when economic rationality becomes global and self-undermining.

Chapter 4: Homo Ludens — Exploration, Play, and Freedom

Homo ludens has never disappeared. It has persisted in marginal, protected, or undervalued forms: play, art, music, language, ritual, and exploration. This chapter's central claim is that human freedom and creativity are not opposed to mechanism but are grounded in a special class of mechanisms — decoupled, autonomous generative systems maintained far from equilibrium.

Play is treated not as leisure or escape, but as a mode of engagement in which generative mechanisms are allowed to operate openly — disciplined exploration of possibility rather than chaotic freedom. By the chapter's end, Homo ludens is no longer a romantic ideal but a viable and already-existing mode of life, newly salient as generative machines re-enter the center of social and cultural life.

Chapter 5: Science Fiction Imagines the Future

Science fiction has long functioned as a collective ludic laboratory — a cultural space in which societies explore alternative forms of life unconstrained by existing economic arrangements. Moving through Forbidden Planet, 2001: A Space Odyssey, The Matrix, and Spielberg's A.I., the chapter arrives at its central case: the Star Trek universe, which is fundamentally post-scarcity. In that world, exploration, learning, diplomacy, and self-cultivation replace work mode as the primary orientation. Deep Space Nine complicates this without abandoning the baseline, reintroducing moral ambiguity and political conflict. The chapter pays particular attention to the Trill and the Changelings as early narrative explorations of distributed identity and non-unitary selfhood — anticipating the doppelganger concept developed in later chapters.

Science fiction emerges not as speculative appendix to theory but as a parallel cognitive technology, preparing readers to inhabit rather than merely analyze an alternative world.

Chapter 6: The Transformation — Kisangani 2150

This chapter marks a deliberate shift in mode. Having established ludic principles conceptually, the book moves fully into speculative narrative to explore what happens when those principles become the organizing basis of a society. The setting is Kisangani in the year 2150, developed in dialogue with Kim Stanley Robinson's New York 2140.

The narrative centers on the Mystic Jewels — a loosely coordinated transnational network of dissidents, creatives, and technologists who converge on Kisangani over the late 21st and early 22nd centuries, experimenting with alternative institutional forms and generative technologies. Their relative invisibility is described using Wakanda-style stealth as a metaphorical shorthand. The chapter culminates when the Jewels reveal themselves publicly — not as revolution, but as the exposure of an already-functioning alternative. Ludic mode, long practiced in protected spaces, is shown to be capable of scaling into a viable social order.

Chapter 7: At Play in a World of Doppelgangers

This chapter allows the reader to inhabit a mature ludic society from the inside, through extended dialogue among young Kisanganians and their Mirrors — computational doppelgangers that function not as tools or replacements but as long-term cognitive partners. The chapter centers on ritual moments that articulate the ethical settlement Kisangani has reached with artificial intelligence, including an adolescent initiation ritual and a later rite confronting the asymmetry between human mortality and the potential non-mortality of doppelgangers.

Kisangani's doppelgangers are inseparable from its energy regime: highly efficient, continuously learning cognitive systems aligned more closely with biological nervous systems than with conventional AI infrastructure. Over time, some persist beyond the lives of their human partners, blending into the city's ecological fabric as distributed attentional processes. Intelligence in Kisangani is quiet, local, and low-legibility to the outside world. The chapter ends with a gentle destabilization of the boundary between vision and reality: the future is not argued for, but visited.

Chapter 8: A Thirty-Year Plan

The final chapter returns from Kisangani to the present, translating the book's conceptual insights into a long-horizon program of action. Using the paired figures of chess and language to represent two distinctly different computational regimes, the chapter argues that the future of AI cannot be secured by scaling existing architectures alone. Sustaining generative, continuously learning systems — capable of supporting augmentation rather than substitution — requires coordinated progress across conceptual, cognitive, technical, and institutional dimensions.

The plan presented is deliberately programmatic rather than granular. It identifies the kinds of research, institutional experimentation, and cultural reframing required if AI is to support a transition from Homo economicus to Homo ludens, without locking the future into specific technical implementations. The chapter closes by reframing "work" itself — not as labor to be optimized away, but as stewardship: the collective task of building and maintaining conditions under which generative intelligence, human and artificial, can coexist productively over time.

Welcome to the Fourth Arena.

We need new economic indicators

We have the stock market figures everyday. Maybe also we could have figures on the number of homeless people too.

And the media can report daily on those homeless figures. pic.twitter.com/Wgc2w9Bglb

— David Graeber Institute (@Graeber_social) June 24, 2026

New Book Project: Language, Memory, and Mind: A Supplement to The Computer and the Brain

As you may know, I’ve been working on a book project, Play: How to Stay Human in the A.I. Revolution. For some reason I’ve been unable to finish the proposal, though I’ve got lots of stuff and a number of the chapters are substantially drafted. But I keep finding myself distracted into thinking about basics, very basic things about computing and A.I.

At the very end of his life, John von Neumann wrote a slim book, The Computer and the Brain (1958). It grapples with the problem of how computation can be implemented in a physical medium and does so in a way that is basic, both simple and straightforward and profound. We’ve learned a great deal about both the brain and the computer since then, but as far as I know, no one has revisited von Neumann’s project and extended it to include what we have since learned. That’s what I propose to do in this book.

Now, I have no intention of trying to summarize what we’ve learned on those two topics since 1958. That’s working at the wrong level. When von Neumann was writing he, and by extension, we, had no conception of distributed representation much less how it could be achieved physically. Now we do. That’s what needs to be added to von Neumann’s exposition.

I have no intention of repeating what von Neumann did. In particular, I will not revisit his material on analog computing. Rather, I want to augment his discussion. Fortunately the new material is of such a nature that I should be able to write short book that can be read as a stand-alone discussion or as a supplement to von Neumann’s book. I’m imagining a sophisticated general audience of the sort that reads 3 Quarks Daily.

My working title: Language, Memory, and Mind: A Supplement to The Computer and the Brain. I expect the book to be 100 to 120 pages long (30K to 40K words).

I have uploaded a bunch of material (100K words or more) to Claude and asked it to review that material and put together and initial outline. I’ve appended that below the asterisks.

* * * * *

Preface

How to use this book — with or without von Neumann. What it adds to his argument. What it doesn't attempt. Brief note on the collaboration with Claude that produced parts of the text.

Introduction: Von Neumann's Unfinished Argument

What he got right: the architectural mismatch between brains and computers — memory and computation separated in the digital machine, unified in the neuron. The energy efficiency puzzle he couldn't explain. His honest acknowledgment that the brain's organizational principles lay beyond the framework he'd built. The concepts he lacked that this book supplies.

Chapter 1: Two Paradigm Cases

The chess-language contrast as the entry point. Chess has a bounded, well-defined geometric footprint — 8×8 board, six piece types, explicit rules, finite tree. Language has an unbounded, poorly-defined geometric footprint — rooted in the full complexity of physical and social reality. Chess was AI's founding benchmark precisely because it seemed to demand the highest human intelligence while yielding to computational treatment. Moravec's paradox: the easy problems are hard and the hard problems are easy. Transcendent versus non-transcendent coding — programmers can observe and specify a chess engine completely from outside; nobody can specify an LLM from outside, including its creators. Where we now stand.

Chapter 2: Location and Content

A collection of photographs. Solid objects at specific locations — finding by address is natural, finding by content requires going to each photo in turn. The combinatorial explosion that follows. The formal argument: solidity localizes content; localized content can only be retrieved by address. What holography does physically — interference patterns distribute information about each stored object across the whole plate, so that any partial cue can activate the whole. Lashley's ablation experiments: memory didn't disappear when specific cortical tissue was removed because memory was never stored in specific locations in the first place. Von Neumann's energy efficiency puzzle, now answerable: the brain doesn't spend energy moving content to a processor because memory and processing are the same physical substrate.

Chapter 3: The Brain as Content-Addressed System

The McCulloch-Pitts neuron-as-logic-gate: computationally fruitful, architecturally wrong. What neurons actually are — active units and memory units simultaneously, connected in massive parallel. Distributed representations: concepts as patterns across populations of neurons, not stored at specific cell addresses. Yevick's logical necessity argument in plain terms: the world contains two categories of object, geometrically simple ones that sequential symbolic processing handles efficiently and geometrically complex ones that only holographic parallel processing handles efficiently; the world contains both; therefore any adequate cognitive system must implement both regimes. Path tracing and pattern matching as the two fundamental operations on any cognitive network. Freeman's cinematic model — global coherence frames at 10-12 Hz as the atomic unit of biological cognitive processing — and its correspondence to speech production rates.

Chapter 4: Language as a One-Dimensional Projection

The semantic network as the right model for conceptual structure: meaning as position, each node defined by its pattern of relations to other nodes. Sydney Lamb's principle. The multidimensional character of the conceptual network versus the one-dimensional character of any spoken or written string. Language strings as 1D projections of the multidimensional network — necessarily lossy, hence paraphrase and ambiguity. The colored beads thought experiment: strip away semantic content, replace each token with a color, and you have a 1D image — making visible the purely formal structure the LLM operates on. Words as abstract addresses in an abstract space. Why classical computational linguistics hit combinatorial explosion: it was trying to reconstruct the multidimensional structure in a location-addressed system.

Chapter 5: What Large Language Models Actually Are

The transformer architecture in plain terms. The weight space as distributed content-addressed memory — concepts are patterns smeared across billions of parameters, not stored at specific addresses. The forward pass as the atomic processing unit, corresponding to Freeman's global coherence frame: one complete transit through the weight space producing one output token. The token string as a path through the abstract address space, with each forward pass mediating between the 1D sequential surface and the multidimensional distributed interior. What LLMs do well — pattern matching over the weight space, which is what their architecture naturally supports. What they do poorly — sustained sequential path tracing requiring precise state maintenance, common sense grounded in embodied experience, continuous learning. Why these limitations aren't engineering failures awaiting a fix but structural consequences of implementing holographic-like processing on location-addressed hardware with training only on 1D projections.

Chapter 6: What the Analysis Implies.

The first principles of intelligence are not the first principles of computation. Why scaling won't close the gap: scaling improves the quality of the holographic approximation but doesn't change the architectural mismatch, provide embodied grounding, or enable continuous learning. The fast takeoff fantasy as physics-free reasoning — every self-improvement step requires moving billions of parameters between physically separated memory and compute on real hardware that consumes real energy. The TSMC problem: the most critical hardware infrastructure in the world runs on tacit knowledge distributed across human communities that no LLM can access or replicate. What a genuinely adequate artificial cognitive system would require, in the terms this book has developed. The research program that's needed and why it requires multi-generational public investment rather than industrial R&D on commercial timescales. The human-machine collaboration that's already underway and what it can and cannot achieve.

Conclusion: The Mismatch, Named

Von Neumann saw the gap and couldn't name what was on the other side of it. This book names it: content addressing, requiring distributed storage, implemented in biological tissue through interference-like neural dynamics, approximated in LLMs through distributed weights on location-addressed hardware, grounded in embodied experience that no text-trained system has. The naming matters because you can't close a gap you can't see clearly.

Appendix: A Chronology of Chess, Language, and AI

From the working paper, lightly edited.

Mathematicians are concerned that exploitation by the AI industry threatens the long-term intellectual interests of the field

Siobhan Roberts, As A.I. Makes Strides in Mathematics, Mathematicians Urge Caution, NYTimes, June 2, 2026.

Mathematicians issue a declaration:

On Tuesday, a group of 16 mathematicians, in consultation with colleagues and math organizations worldwide, published the Leiden Declaration on Artificial Intelligence and Mathematics. It aims to “frame the conversation about future directions,” said Dame Ursula Martin, one of the authors, and a mathematician and computer scientist at Oxford.

This effort comes as A.I. models have been making headlines with successful results in research-level mathematics. In late May, OpenAI, the maker of ChatGPT, announced that one of its models had disproved a notable 80-year-old mathematics conjecture in the field of combinatorial geometry.

The conjecture is one of some 1,200 problems posed by the Hungarian mathematician Paul Erdos. While some of these “Erdos problems” are considered throwaway questions of narrow interest, others have proved influential and field shaping. Along with a research paper describing the proof, OpenAI released a companion paper by several independent mathematicians. Jacob Tsimerman of the University of Toronto, an expert in the adjacent subfield of number theory, commented: “This is a really impressive piece of work, and I would accept it for any journal without hesitation.”

Potential problems:

Among the potential threats that the Leiden Declaration authors articulate are accuracy and reliability: Journal editors are already complaining about a flood of plausible seeming A.I.- generated papers and proofs that have turned out to be incorrect, and in ways that are difficult for mathematicians to discern.

Perhaps most pointedly, the authors raise the question of whether the many A.I. companies tackling mathematics — major players such as OpenAI, Google DeepMind and Anthropic, or start-ups such as Harmonic, Math, Inc. and Axiom Math — are keeping the field’s best interests in mind. “Technology companies’ involvement in research,” they write, “raises the risk that research questions are prioritized and incentivized because of their amenability to A.I. methods and models, rather than their deeper significance to understanding.” In turn, they point out, this disadvantages researchers who choose not to use the technology, and those who do not have access to it.

For Rodrigo Ochigame, a historian and anthropologist of computing and artificial intelligence at Leiden University in the Netherlands, and one of the statement’s authors, the latest OpenAI proof illustrates why this sort of collective reckoning in the discipline is necessary. “The story follows the same pattern as many other announcements by commercial A.I. developers,” Dr. Ochigame said. “The A.I. model is proprietary and unavailable to anyone outside the company. We get a flashy promotional video, while basic information needed to assess the scientific meaning of the result is kept secret. The company disclosed nothing about the methods, human-written prompts, training data, or computational resources consumed.”

Much of the article consists of a videoconference and email dialog with Dr. Ochigame, Dr. Martin and mathematician Michael Harris of Columbia University:

MARTIN: What OpenAI has done is throw a great deal of resources at Erdos problems, and got lucky with this one. That’s remarkable, and impressed the experts. We are not told about the model’s failures. [...]

To think of mathematics in terms of precise and neatly stated problems, like high school exams or the list of Erdos problems, is to misunderstand and diminish what makes mathematics so powerful and significant. Mathematics is not just about solving problems — it is also the cultivation of ideas, understanding, judgment, and human insight.

HARRIS The purpose, from my perspective, is to recover control of the narrative about the values and the goals of mathematics from the A.I. industry. Mathematicians are concerned that the values of the profession are being misrepresented, not intentionally but due to the media campaign on the part of the industry, which seems to want to promote the belief that they are in a position to transform mathematics — “the A.I. revolution in math,” as one headline put it not long ago. [...]

We want to affirm certain values that have characterized the profession: openness, honesty, giving credit where credit is due, sharing, transparency about methodologies, and access for independent verification of results.

An aspect of mathematics that is cherished by mathematicians is that it is one of few successful examples of a gift economy — that is to say, its economy is somehow an island of idealism in our society.

OCHIGAME Several A.I. companies are investing in dedicated teams focusing on mathematics, using problems as benchmarks and publications as training data. They are training their models to prove theorems not because they want to advance mathematical knowledge, but because they hope that such training will improve the models’ reasoning abilities more generally. [...]

MARTIN It’s important not to lose sight of the fact that what the A.I. companies are doing, what you can achieve with this technology, is absolutely extraordinary. I don’t think we’re challenging that. We’re challenging the framing, we’re challenging the behaviors around it.

I share the concern that these mathematicians express, that the commercial exploitation of mathematics is inimical to long-term research interests.

There's more at the link.

Jaron Lanier talks sense about AI with Neil deGrasse Tyson [Homo Ludens]

YouTube:

There Is No AI Really (It’s Just People), with Jaron Lanier

Is the internet too far gone or can we still fix it? Neil deGrasse Tyson, and co-hosts Negin Farsad and Gary O’Reilly, sit down with Jaron Lanier, computer scientist, and father of virtual reality, to diagnose what went wrong with the web, how it’s changed with AI, and ideas for a new path back.

Learn about Jaron’s initial dream behind virtual reality and why it's been a commercial disappointment. Why does VR make some people sick? We break down why VR didn’t take off like he had hoped. Are lawsuits the way of beating social media addiction?

We discuss social media and the mathematical force at the heart of the internet's dysfunction: the network effect. Lanier explains how low-friction digital networks inevitably centralize power, concentrate wealth, and reward the loudest voices. What does a media-addicted personality look like? Is everyone vulnerable? We discuss the dominant business model in Silicon Valley, how it taps into the fight or flight response, and how it contributes to the internet we have today.

Can the internet be saved? We explore alternative business models and address the tech oligarchs who appeared on the U.S. presidential inauguration stage, and that the current wave of public discontent may be the beginning of a real correction. How does AI contribute to the problems of today’s internet? We talk about the problems with mythologizing AI and take it out of its black box. We explore his concept of "data dignity" — the idea that data originates with people, and should be compensated as such. Plus we address the difficulty with privacy and that maybe outlawing predicting human behavior.

Timestamps:
00:00 - Introduction: Jaron Lanier
06:17 - The Thinking Behind Virtual Reality
08:33 - Why VR Flopped
16:57 - Social Media Addiction Lawsuits
21:42 - The Social Media Addicted Personality
22:42 - The Internet’s Business Model
30:28 - Is Social Media Equally Bad for Everyone?
36:22 - AI’s Changes to the Internet
38:39 - Stop Mythologizing AI
43:30 - There Is No AI
52:24 - Data Dignity & Inventing a New Jobs Under AI
58:19 - Why Privacy is Difficult
01:06:20 - Is the Internet Toast?
01:08:28 - Everyone’s Suing AI
01:10:54 - Closing Thoughts

The rise of DIY rituals in the 21st century

YouTube:

Can Rituals Save Us? | Robert Wright & Bruce Feiler

0:00 Teaser
0:52 Bruce’s new book on ritual, A Time to Gather
3:12 The "Lifequake" that led Bruce to study ritual
8:10 The current "shadow ritual" renaissance
12:42 What is a ritual?
15:26 The origins of the shadow ritual renaissance
18:25 Forest bathing and the essence of ritual
26:11 Ritual as the original human algorithm
31:39 Honor walks: a quintessentially modern ritual
36:23 Rituals across Christianity
42:07 What rituals do
46:47 Heading to Overtime

* * * * * 

I discuss ritual in my book on music, Beethoven's Anvil: Music in Mind and Culture, pp. 79-82:

Subjectivity is an aspect of neurodynamics, and neurodynamics is open to the world through sensory organs and through the motor system. When people are coupled with one another through musicking, each steers her own raft of subjectivity in the collective sea of neurodynamics. The motions of each raft are transmitted to the others through the sea, as Huygens’ clocks transmitted vibrations to one another through the walls. These subjectivities thus adjust themselves one to the other, for they are all components of the same process.

Let us reconsider, then, the musicking with which we opened this chapter. We were at a party where lots of musicians were jamming. Near the end of a jam on Bob Dylan’s “Knocking on Heaven’s Door,” several people spontaneously joined in on the refrain. It wasn’t planned ahead of time, nor did those singers discuss it among themselves while the rest of us were playing.

When I originally told the story I talked of my deliberate intention to “drive” the group by playing a simple line and “bearing down.” That decision was a conscious one, though not as clear and differentiated as it may seem when I spell it out in words, and it resulted in a certain shift of my consciousness. “Bearing down” is something I do quite often when playing. It involves attending to and adjusting the tension in my trunk musculature but has no specific differentiated effect on the music beyond a certain intensity and emotional tone. In this case I was playing a very simple melodic line, but I will also bear down while playing the most complex lines. In that situation, my fingers and tongue may be spitting out 10s of notes per second, but they’re on their own; I’m still attending to muscles in my abdomen, shoulders and back, and my buttocks. Those are the muscles that most strongly affect the overall airflow, and that’s what I care about when I’m bearing down.

And that, by our conception of consciousness, is where my nervous system is reorganizing and making minute adjustments. I have no introspective awareness, of course, of just what neural areas are reorganizing, but I’d guess that we are dealing with circuitry involving both emotional expression and voluntary control of large muscles. Even as I am attending to those muscles, I am always listening to the sound, not just mine, but the group’s. I’m bearing down just so in order that the sound I hear may also be just so. But my sound is only a part of the group sound and, at this particular point, it was a subordinate part. What this means is that my nervous system’s reorganizational activity is responsive to the sound made by each and every person in the musicking group. I am attuning my motor and emotive system to the sound that is the joint activity of this group. And each one in the group is, in turn, doing the same thing. Each one, merely by being a conscious musician, is making minute adjustments to his nervous system in response to the sounds that all are creating.

We are now in territory explored by Walter Freeman in a recent essay on music and social bonding. Freeman is interested in those rituals where a core group of celebrants move from one status in society to another, as from child to adult or single to married. In these rituals, as individuals are conveyed from one social status to another—recall our discussion in the previous chapter—they require changes in the collective neuropil. Funerals, of course, are also in this class. As the bodies of the dead are conveyed to a final resting place, the living must disengage from their attachments to those who are no longer among the living. In this case, and entire persona (see Figure 1 in the previous chapter) must be disengaged from active use in the collective neuropil. Conversely, when a child is born, the group must undertake a ritual that creates a new persona in the collective neuropil.

In all of these situations the bonds between individuals must be altered in fundamental ways that require considerable neural reorganizing. Freeman suggests that such rituals involve a neuropeptide called oxytocin. He asserts that oxytocin "appears to act by dissolving preexisting learning by loosening the synaptic connections in which prior knowledge is held. This opens an opportunity for learning new knowledge. The meltdown does not instill knowledge. It clears the path for the acquisition of new understanding through behavioral actions that are shared with others.” As the oxytocinated individuals are moving to the rhythms of well-established ritual, their synaptic connections are restructured in patterns guided and influenced by the events in the ritual. Obviously, the microdynamics of each individual will be unique; but they will be shaped by rhythmic patterns common to all . These rituals provide a space in which individuals can mold themselves to one another as the infant molds her actions to those of her mother.

Such ritual would likely have benefits on less extreme occasions than those requiring the restructuring of social relations—think of our little jam session. Social life is difficult and taxing. Hostilities build up. Such ritual may well help take the edge off of growing tensions, reconciling individuals to one another and allowing them to “reset” their relationships on more favorable terms.

Thus we have another core hypothesis:

Freeman’s Hypothesis: By attending to one another through musicking, performers attune their nervous systems to one another, restructuring their representations of others. This results in more harmonious interactions within the group.

Each individual consciousness may be an island of Cartesian subjectivity, but in the close coupling of musicking, those subjectivities are intimately and delicately conditioned and regulated by one another.

Perhaps such rituals play a role in helping to establish and maintain the subjective continuity of the neural self. By entering into a wide variety of emotional states (with their various neurochemical substrates) in a socially controlled situation, individuals in a community ritual create an "equal access zone" in mental space where each can experience and contemplate extremes of joy and anger, tenderness and hate, and know that all these feelings have a place in their shared world.

America and China have different attitudes about and approaches to AI and work

Ross Douthat, Why China Isn’t Worried A.I. Will Replace Its Workers, NYTimes, May 14, 2026.

The United States and China are really the only two countries that matter right now in shaping the A.I. future. As President Trump and President Xi Jinping meet in Beijing, there’s a kind of Cold War atmosphere, with people talking about an A.I. arms race. But who is winning? Are we even in a race at all? Kyle Chan, a foreign policy fellow at the Brookings Institution, says it’s hard to call it a race because the U.S. and China have very different A.I. goals.

I presented the conversation to Claude (Sonnet 4.6 Adaptive) and asked it for a summary. 

 * * * * *

I have uploaded conversation to the project area, filename “China AI workers.”

It is between Ross Douthat, who writes for The New York Times, and Kyle Chan, who is a foreign policy fellow at the Brookings Institution. I would like you to summarize the conversation for me. I’m particularly interested in the Chinese attitude toward AI in general and the (proper) relationship between AI and humans.

This is a rich and wide-ranging conversation. Here's a summary, with particular attention to the themes you flagged.

Overall frame

Douthat's central premise is that the U.S. and China are in an AI "arms race," but Chan's main contribution is to complicate and largely deflate that framing. China, he argues, is running a different kind of race, not the same race at a slower pace.

The Chinese approach to AI: practical, not transcendent

The sharpest contrast Chan draws is between the American fixation on AGI — the idea of a "machine god" that surpasses all human capability — and the Chinese orientation toward diffusion and application. China wants AI in food delivery, ride-hailing, health care, government services, and factory floors. They want smaller, cheaper, more deployable models, not necessarily the most powerful frontier model. Chan puts it directly: Beijing is not "AGI-pilled."

He sees this as continuous with how China approached the internet era: not as a transformative metaphysical event, but as infrastructure to be integrated into daily life and governance. The Chinese state is also notably more willing to use open-source models, giving away AI capabilities to gain adoption at scale — both domestically and in the Global South — which is a strategy the commercially driven American labs largely ignore.

The proper relationship between AI and humans: tool, not god

This is where the conversation is most relevant to your homo ludens framework. Chan describes Beijing's view of AI as essentially instrumental — AI serves human economic and social purposes. The Chinese government is actively hostile to AI use that it considers "nonproductive": AI companions, AI boyfriends/girlfriends, even excessive gaming. The fear is that young Chinese will waste time on AI-mediated entertainment and social substitution when they should be building the economy.

There's a revealing parallel Chan draws: the same regulatory instinct that cracked down on video games and private tutoring platforms is now being pointed at AI companionship apps. The state's implicit position is that AI must serve the collective project — not become a substitute for human connection, productivity, or reproduction. This is a deeply anti-mystical, anti-transcendent view of the technology.

So the Chinese "proper relationship" between AI and humans is essentially: AI augments human labor, fills demographic gaps (falling birthrate, shrinking workforce), and extends state capacity. It does not replace human flourishing or social life; it should not become an end in itself.

The demographic driver

Chan adds an important materialist dimension: China's embrace of robotics and AI is partly driven by sheer demographic necessity. Their labor force peaked over a decade ago, youth unemployment is near 17%, and the birthrate is roughly two-thirds the U.S. rate. This produces a different calculus than in America — the question isn't whether a robot waiter displaces a human worker, but whether you have a waiter at all. AI and robotics fill a structural labor hole, which makes China more tolerant of automation than Western economies that still have more human workers to protect.

The public mood: anxiety about falling behind, not about being displaced

Where American anxiety about AI tends toward fears of job loss, surveillance, or existential catastrophe, Chan describes Chinese popular anxiety as nearly the inverse: fear of not using AI enough, of being left behind in a hyper-competitive labor market. Individual workers, companies, and policymakers all share this orientation. Chan calls this a "mirroring" — the individual's fear of losing competitive edge mirrors China's national fear of falling behind the U.S. technologically.

On AGI and existential risk: skeptical distance

Chan thinks it's telling that when Trump relaxed chip export controls, Chinese AI companies wanted the chips but Beijing declined — preferring to build domestic semiconductor capacity rather than become dependent on American supply chains. This, he argues, is not the behavior of a country sprinting toward superintelligence. A true AGI race would involve gobbling up every available chip. China is playing a longer, more measured game.

He also pushes back gently on the "race" metaphor itself: the intermediate risks (cyberwarfare, biosecurity) are, in his view, underrated and real; the AGI-superintelligence scenario is overblown. He ends by urging dialogue between the U.S. and China on shared risks from rogue actors and open-source proliferation, while acknowledging the deep mutual distrust that makes formal arms-control agreements essentially impossible at this stage.

A thought for your book

Chan's portrait of Beijing's AI worldview sits almost perfectly at the opposite pole from Silicon Valley's quasi-religious eschatology — no Omega Point, no machine god, no homo deus. What you might find generative: the Chinese model is also, in its own way, a version of homo economicus applied to AI — purely instrumental, collectively economistic, hostile to play and to what the government calls "wasted time." It's not an alternative to the Silicon Valley eschatology so much as its mirror image — the same foreclosure of genuine play, just in a different ideological register.

AI’s New Trillion Dollar Mission (is BS)

YouTube:

This week on Prof G Markets, Scott Galloway and Ed Elson discuss the growing belief in Silicon Valley that AI won’t just replace workers, but managers too. Then, they break down the proposed pied-à-terre tax in NYC and why they believe taxing luxury second homes makes sense. Finally, they unpack why alcohol stocks are struggling while GLP-1 drugs are booming, and what that says about the future of American consumer behavior. [...]

Timestamps:
00:00 Preview
00:26 Today's number
01:04 Today's episode
05:23 AI's new mission
24:35 Ad break
26:55 The wealth tax debate is heating up
46:10 Ad break
48:41 The death of the night out
01:08:56 Week ahead
01:11:11 Scott's prediction
01:12:51 Ed's prediction
01:14:05 Credits

Starting at about 20:08, Scott Galloway:

And that is there is something to be said of and there's a balance here. I've in my companies, I'm doing some virtue signing right now. I've always said there should be two or three people and I've always had small companies, right? They they start at zero. Once we have a someone in HR or CFO, I either step step down from the CEO role or become the chairman because I I don't have those skills to scale a company and I don't want to deal with that stuff.

But until then, I've always said we should have two or three people that are one or two bad decisions away from living in their car. They're not, you know, they're they have bad judgment. They're they do stupid shit all the time. They're not what I'd call there's no way they're leaving us for Google. Let me put it that way. A little bit down on their luck maybe. And guess what? The business can be a great means of a little bit of social good.

And also the notion this is basically the notion that part of an organization if you think of stakeholders and I didn't get this. So, I always thought my goal was to pay people less than market and figure out other tricks of the trade to get them to stay and retain them. And then what you realize as you get older is that what is more rewarding is to build a profitable company and slightly overpay people. And if there's some fat in the organization and if there's a few people who quite frankly are, you know, not going to get a job anywhere else but work, you know, work hard or good people and maybe they're not, you know, amazing. Okay, that's okay too. And in some countries, the objective of a lot of the owners is to increase employment. Now, you have to balance that with making sure the organization can survive and has profitability.

But this is again this singular messiah complex that is nothing. There's only one stakeholder and it's shareholders. and I can figure out technology to replace people and we can all work singularly and then eventually the AI will take out those singular teams and replace them and then there will just be one. It'll be Jack Dorsey and Elon Musk who each own 49% of the world and do a lot of ketamine and if they're good enough they will provide UBI for all of us such that we don't uh rise up and kill them.

I I I'm not a fan, Ed. I'm not a fan of this whole line of thinking. I think it's [ __ ] and I think it's unhealthy and I think it's nihilistic.

Capitalists vs. Capitalism

In terms I’m developing for my book, Play: How to Stay Human in the A.I. Revolution, capitalism is an economic system both dominated by captalists and organized to suit the dictates of Homo economicus.

On the Appeal of Tne Rockford Files [Media Notes 164 A] {Beware of work-mode!}

I've been watching The Rockford Files again and though I should write up a post about the appeal of the show. But I decided to check the blog first and, wouldn't you know it, I'd already written that post, in June of 2025. So instead I'm just bumping that post to the top of the queue along with a prefatory note. If you look toward the end of the post, the highlighted areas, you'll see that I brought up work mode, pointing out that Rockford doesn't seem possessed by it. 

Now that I'm explicitly thinking in terms of a contrast between Homo economicus and Homo Ludens that in itself seems sufficient to revisit this post. I'm thinking that might be a good way of analyzing the show. Rockford's wayward buddy, Angel Martin, also manages to keep work mode at bay. He met Angel where? Prison, that's right, prison. But he was pardoned. Jim – that's his name, "Jim Rockford" – and Angel are contrasted with Rocky, his retired truck-driving father, and his good friend, Dennis Becker, an overworked cop. Rocky's always after to Jim to get a legit job, like driving a truck.

That's a beginning. I wonder how far we could get with that? Here's the original post, though I added a phrase at the very end.

* * * * * 

I’m currently working my way through The Rockford Files for the fourth, if not the fifth, time. I watched the program when I was originally broadcast back in 1974-1980, and I’ve watched it online several times in this century. Part of the program’s appeal certainly comes from the star, James Garner.

Garner is a handsome middle-aged man, six feet and perhaps an inch or two tall. He plays an easy going character, James Rockford, who is masculine without being macho. He can handle himself in a fight, which he frequently has to do, but he’s not a martial artist or a superhero. He’s competent, but vulnerable and takes his lumps. He likes sports, going to games, going fishing, often with his dad. He’s single, but is attractive to women, and kind. He’s had affairs in the past, and has one or three in the course of the show, he may even have been close to marriage.

Much of the appeal stems from the fact that he’s an interstitial character, if you will. He falls between the keys, lives in the cracks. While he makes a living, just barely, he’s not chained to a 9-to-5 job. He’s not been broken to harness.

He’s an ex-convict who’s been pardoned. Was he ever guilty? Probably not, but I don’t recall off hand. Does it matter? He’s damaged goods. He lives in a beat-up trailer on the beach at Malibu, a marginal dwelling in a desirable location.

He makes his living as a private investigator, which is depicted as a marginal occupation in this, and other shows, but not always. While he’s a decent and honest man, he does quite a bit of sneaking around and more than a little deception. There are a number of episodes where he orchestrates a complex con, though on behalf of a good cause. Always.

He’s got a good friend on the police force, Lt. Dennis Becker, but is otherwise persona non grata with the police force. And he’s friends with a good lawyer, Beth Davenport, who once had a crush on him. He’s also got an ex-con pal, Angel Martin, who’s a bit more marginal than he is, and cowardly as well, yet somehow manages to retain Rockford’s loyalty.

All of which is to say, he doesn’t work within the confines of work-mode, as I’ve been writing about it. Life is not easy for Jim Rockford. He’s often broke, and in at least one episode that I can remember, in danger of losing his home. But his life is interesting and challenging.

I wonder, off hand, how many TV shows present us with lives that are NOT dominated by work mode? And in work-place shows, just how is work depicted? How much entertainment presents us with alternatives to work-mode? And how often is the alternative presented as a critique of work-mode?

Is The Rockford Files a critique? I don’t think so. It’s not pointed enough. Perhaps that’s why it’s been so popular. It presents a clear alternative, a clear difference-from, but it never goes so far as to present the work-a-day world as a soul-destroying trap, though the depiction of Becker comes awfully close to that. 

* * * * * 

Also about The Rockford Files: Myth-Logic and a Lady Librarian in The Rockford Files, Myth-Logic and a Lady Librarian in The Rockford Files 2.

Pretty Woman [Media Notes 179]

I’ve seen Pretty Woman (1990) at least three times, once when it came out, once before on streaming, and just last night. I like it. It’s a nice romantic comedy and something of a fairy tale, but that’s OK, I suppose.

It is very much a story of its time. Richard Gere plays a corporate raider, Edward Lewis, but not one so ruthless as Michael Douglas playing Gordon Gekko in Wall Street (1987). Julia Roberts plays a Hollywood street walker, Vivian Wood. Lewis picks her up, because he knows where his hotel is, but also because she seems to know something about the car he’s borrowed from his lawyer (a Lotus), and ends up engaging her for the week. She accompanies him to several business meetings, but also to a night at the opera. They fall in love, of course; he relents on the deal he’s been chasing; and she goes back to New York with him where, we are to presume, they live happily ever after.

The world, of course, is not like that, not quite. And I doubt that anyone over twenty who saw the movie believes that. But it’s a nice alternative to the  self-glorifying  Gordon Gekko. I can even believe that Gordon Gekko would have liked it, or if not Gekko himself, perhaps his understudy, Bud Fox (played by Charlie Sheen). Corporate raider types are not long on self-knowledge, no more than today’s Silicon Valley tech bros, and so are as vulnerable to fairly tales as to tales of Viking raiders.

And perhaps that’s why I like it. It’s as though Gordon Gekko is so reprehensible in his thralldom to Homo economicus that Hollywood just had to show us an antidote. It picked a perennial, the Hooker with a Heart of Gold, disguised, in this case, as a hooker who knows how to drive a stick shift and carries a rainbow assortment of condoms in her thigh high boots. Which is to say, the film acknowledges that we need some kind of Homo ludens alternative, even one that includes a bunch of rich folks stomping divots on a polo field, not to mention that Mr. Lewis betrays his soulfulness by noodling on the lounge piano in the wee hours of the morning.

The movie resonated with the public and made Julia Roberts a star. From the Wikipedia entry:

Pretty Woman received mixed reviews from critics upon release, but widespread praise was directed towards Roberts' performance and her chemistry with Gere. It had the highest number of ticket sales in the US ever for a romantic comedy, with Box Office Mojo listing it as the number-one romantic comedy by the highest estimated domestic tickets sold at 42,176,400, slightly ahead of My Big Fat Greek Wedding (2002) at 41,419,500 tickets. The film grossed US$463.4 million worldwide and at the time of its release, was the fifth-highest-grossing film of all time worldwide, behind only E.T. the Extra-Terrestrial ($701 million at the time), Star Wars ($530 million at the time), Indiana Jones and the Last Crusade ($474 million at the time), and Jaws ($470 million at the time). It was also the highest-grossing R-rated film of all time (surpassing Rain Man) until it was surpassed by Terminator 2: Judgment Day in 1991, but remained the highest-grossing R-rated film released by Walt Disney Studios (surpassing Cocktail), holding the record for 34 years until Marvel Studios' Deadpool & Wolverine surpassed it in 2024.

From critic snippets Wikipedia:

Pretty Woman received mixed reviews from critics, with positive reviews praising the stars' chemistry and the dialogue. On review aggregator Rotten Tomatoes the film holds an approval rating of 64% based on 78 reviews. The website's critical consensus states, "Pretty Woman may be a yuppie fantasy, but the film's slick comedy, soundtrack, and casting can overcome misgivings." On Metacritic, the film has a weighted average score of 51 out of 100, based on 18 critics, indicating "mixed or average reviews." Audiences polled by CinemaScore gave the film an average grade of "A" on an A+ to F scale.

The film's detractors criticized the overuse of the "hooker with a heart of gold" trope.[14] Others opined that the film sugarcoats the realities of sex work. [...]

Owen Gleiberman of Entertainment Weekly gave the film a "D," saying it "starts out as a neo-Pygmalion comedy" and becomes a "plastic screwball soap opera", with the "kinds of characters who exist nowhere but in the minds of callowly manipulative Hollywood screenwriters". Gleiberman conceded that with the film's "tough-hooker heroine, it can work as a feminist version of an upscale princess fantasy." [...] 

Roger Ebert of the Chicago Sun-Times gave a positive review, praising how the film is about "a particularly romantic kind of love, the sort you hardly see in the movies these days". He added it "protects its fragile love story in the midst of cynicism and compromise. The performances are critical for that purpose. Gere plays new notes here; his swagger is gone, and he's more tentative, proper, even shy. Roberts does an interesting thing; she gives her character an irrepressibly bouncy sense of humor and then lets her spend the movie trying to repress it. [...]

The New York Times' Janet Maslin wrote: "Despite this quintessentially late 80's outlook, and despite a covetousness and underlying misogyny [...] 'Pretty Woman' manages to be giddy, lighthearted escapism much of the time. [...]

Carina Chocano of The New York Times said the movie "wasn't a love story, it was a money story. Its logic depended on a disconnect between character and narrative, between image and meaning, between money and value, and that made it not cluelessly traditional but thoroughly postmodern." In a 2019 interview, Roberts expressed uncertainty over whether the film could be made today due to its controversial premise, commenting, "So many things you could poke a hole in, but I don't think it takes away from people being able to enjoy it".

I’m with Ebert on this one.