World-Spanning Thoughts

That’s a blog-tag I added recently. I’ve currently got two posts with that tag. This will be the third. I’ve got a vague impression that I’ve got other posts on that topic, but under a different tag for pretty much the same idea, but I can’t think of what that tag might be.

Anyhow, I’m writing this post to jog my memory and to cement some specific label – e.g. world-spanning thoughts – for the idea. I’ve had the idea kicking around for a while, but sticking a label to it has been tricky.

What’s the idea? It goes like this. We’re creatures that have to, are driven to, make sense of the world around us. Everything we see or hear or smell or taste or touch, everything has to have some account, some place in an overall scheme of things. “World-spanning thoughts” is a label, one label, I’m sticking on this impulse, this imperative, this desire.

I associate this with the theory of William Powers. It’s not that I got the idea from him. Rather, an organism with a mind that works according to his account, such an organism needs to make sense of everything. Hence world-spanning thoughts.

Actually, not all such organisms. To the extent that Powers is current, all animal perception, action, and cognition is organized in this way. BUT, we humans have language. And that changes everything. Now we’ve got an open-ended need to make sense of it all. That’s an all-together different kind of beast.

Why does language affect/effect us this way? Good question. I’ll take it under advisement.

It worked!

I think I’ve found the other label I’ve had for this idea: meaningful_life.

Five epochs of energy and evolution

Bumped to the head of the queue because it is relevant to my idea that the (possibly local) universe has seen three arenas  – matter, life, and culture – so far and may be on the cusp of birthing a fourth or as yet indeterminate nature.

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Olivia P. Judson, The energy expansions of evolution, Nature Ecology & Evolution 1, Article number: 0138 (2017)

doi:10.1038/s41559-017-0138

Abstract: The history of the life–Earth system can be divided into five ‘energetic’ epochs, each featuring the evolution of life forms that can exploit a new source of energy. These sources are: geochemical energy, sunlight, oxygen, flesh and fire. The first two were present at the start, but oxygen, flesh and fire are all consequences of evolutionary events. Since no category of energy source has disappeared, this has, over time, resulted in an expanding realm of the sources of energy available to living organisms and a concomitant increase in the diversity and complexity of ecosystems. These energy expansions have also mediated the transformation of key aspects of the planetary environment, which have in turn mediated the future course of evolutionary change. Using energy as a lens thus illuminates patterns in the entwined histories of life and Earth, and may also provide a framework for considering the potential trajectories of life–planet systems elsewhere.

Free energy is a universal requirement for life. It drives mechanical motion and chemical reactions—which in biology can change a cell or an organism1,2. Over the course of Earth history, the harnessing of free energy by organisms has had a dramatic impact on the planetary environment3,​4,​5,​6,​7. Yet the variety of free-energy sources available to living organisms has expanded over time. These expansions are consequences of events in the evolution of life, and they have mediated the transformation of the planet from an anoxic world that could support only microbial life, to one that boasts the rich geology and diversity of life present today. Here, I review these energy expansions, discuss how they map onto the biological and geological development of Earth, and consider what this could mean for the trajectories of life–planet systems elsewhere.

Fecundity and Implementation in a Complex Universe

I'm bumping this post from October 2011 to the top of the queue for two reasons: 1) in its discussion of abundance it contains seeds to the idea of arena, which I have made one of my fundamental philosophical concepts, and 2) it employs chess as a metaphor.

 

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Or, Compositionism in the Pluriverse

As I’ve indicated several times before, one of the reasons I’m finding object-oriented ontology (OOO) and Latour so congenial is that I’ve had similar ideas, often in conjunction with the late David Hays. But we arrived at those ideas, not through immersion in continental philosophy and thought, but through the cognitive and neurosciences. In that we have been a bit like Latour in that we’ve mostly been trying to figure out how things work out there in the world, not trying to do philosophy. But we did some, if not philosophy, philosophy-like thinking.

Thus we came to believe that reality is inherently complex and that, consequently, the way to empirical truth was not through dispersing phenomenal complexity in favor of a deeper underlying simplicity. We came to talk of a universe that not only has spawned multiple Realms of Being, but that might well spawn more of them. Had we known William James’ term pluriverse I’m sure we would have adopted it.

We didn’t and so we couldn’t. Instead we talked of the universe as being fecund (Hays proposed the term), with later Realms of Being implemented in ones that had evolved earlier. Our notion of implementation, which derives from computer science, seems kin to Latour’s notion of composition. Objects of one kind can be said to be implemented in, composed of, objects of some other kind. But the implemented/composed objects cannot be reduced to the objects of which they are composed/implemented.

We never attempted a systematic exposition of this notion, but I did outline it briefly in a review of John Horgan’s The End of Science. You can download a PDF of the complete review from my Academia page, here. I have reprinted the discussion of fecundity and implementation below.

Note that it is not at all clear that where Hays and I talk of Realms of Being that we are talking of Being in the sense of object-oriented ontology. Most likely we’re not. But this is a matter of mere terminology, not fundamental conceptualization.

* * * * *

A New World: The Fecund Universe

One of the people Horgan talked to is Paul Feyerabend, the well-known philosopher of science. At the time Feyerabend was working on his autobiography (Killing Time) and on another philosophy book, one he was unable to complete before he died.

Tentatively titled The Conquest of Abundance, it addressed the human passion for reductionism. “All human enterprises,” Feyerabend explained, seek to reduce the natural diversity, or “abundance,” inherent in reality. “First of all the perceptual system cuts down this abundance or you wouldn't survive.” Religion, science, politics, and philosophy represent our attempts to compress reality still further. Of course, these attempts to conquer abundance simply create new abundances, new complexities.

This has the feel of the emerging world view, especially the line asserting that “these attempts to conquer abundance simply create new abundances.” That abundance is what the new view is about. It is a topic the late David Hays and I discussed under the rubric of fecundity—Hays suggested the term—and that is the word I shall use. I have no particular reason to believe that our discussions paralleled Feyerabend's ideas in any detailed way, but “abundance” and “fecundity” share a thematic similarity.

Let us start with an analogy. Consider the game of chess. It has a finite number of pieces and is played on a board which is finite in size; the rules governing play are finite in number and restrict each move to a finite number of steps; and all games must end in a finite number of steps, though it is possible for a game to end in a draw. Thus described chess is an inherently simple game. And yet it is rich enough to tax the abilities of very intelligent and creative people who devote their lives to playing it. A substantial community of people devotes a great deal of time and effort, not only to playing chess, but to studying it and teaching it, writing books and articles and, in the last half-century, programming computers to play the game.

The devotees of the simple world are like those who think that, when you know the rules of chess, you know all there is to know about the game. All the rest is either mere appearance, mere contingency, or mere engineering; whatever it is, it is only merely so. To the devotees of fecundity the rules are only the starting point and all the rest, that is what we must understand. And, more to the point, that is what we can understand, if not just yet, and not necessarily exhaustively and finally.

Of course we need to look beneath the surface of things. But there is no reason to think that what we will find will be simple. On the contrary, I believe that complexity inheres in the basic fabric of nature (Benzon and Hays 1990a). That complexity is necessary and not contingent. It is that inherent complexity which makes the universe so fecund, so full of abundances.

Fecundity is about the capacity of one Realm of Being to give rise to another Realm. In a fairly standard version—see Horgan's account of the views of physicist Philip Anderson, one of the founders of the Santa Fe Institute (pp. 209-210)—the inorganic gives rise to the realm of life; life gives rise to mind; and mind perhaps gives rise to culture. Culture may well give rise to something else, and that something else will in turn give rise to something yet all-together new, and so forth. The laws of a higher realm must be consistent with those of the lower realms, but they are not derived from those laws. Each realm has its own laws, and there is no inherent limit to the number of realms. Hence there is no reason to believe that the universe is inadequate to our cognitive needs. [In The End of Science Horgan argued for a mismatch between the universe and our minds such that the latter could not, in principle, fully know the former.]

The relationship between a higher realm and the one(s) which gave rise to it can be said to be one of implementation. The term is from computing and designates a phenomenon which is ubiquitous there. A computer is, of course, a physical device, a complex bit of engineering. The nature of these devices has changed considerably in computing's short history, from mechanical relays and vacuum tubes in the 1940s and 1950s to transistors and integrated circuits in the 1960s and 1970s to ever denser microchips starting in the late 1970s and continuing to this day and on into the future, though not very far into the future--just what technologies will supplant microchips is not at all certain, but many things are in the works. In order for these circuits to compute anything they must implement certain logical functions. The nature of those functions is quite independent of the medium in which they are implemented. Nor can one in any meaningful way reduce the logical function of a circuit to the physical laws of the device implementing the circuit. Those physical laws tell you what will happen at a certain point Q when the voltage goes above a certain value, but they tell you nothing about why Q is connected to O and P and R and S in a certain way. That pattern of connections is dictated by logic, not physics.

The implementation of logical functions in physical circuits is only one side of implementation, the hardware side. Most implementation is on the software side. High-level languages are implemented in assembly language and end-user programs are implemented in high-level languages. Currently one of the most popular languages is one called C, with a sibling called C++. It requires one implementation to run on a “Wintel” machine, one for the Macintosh, another for a Sun Sparcstation, and so forth. The C language is the same in each case; it has the same nouns and verbs. But the assembly language which implements those nouns and verbs is specific to the machine it runs on. Further, the assembly language for a given machine can implement the nouns and verbs of other high-level languages, such as Basic, Pascal, Fortran, or Cobol. The fact that one language is used to implement another is not the same as asserting that the high-level language is reducible to the lower level language. Each language establishes its own domain, its own realm; implementation is the relationship between one realm and another.

Of course, it is one thing to explore implementation in the world of computing. It is rather different to assert that the relationship between biology on the one hand and physics and chemistry, on the other, is one of implementation. That requires an argument which I am not prepared to make, though some practitioners of artificial intelligence and artificial life seem to take it as a matter of faith. Given the work that Hays and I did on natural intelligence (Benzon and Hays 1988) I feel a little more confidence about the relationship between psychology and neurobiology; for that article proposed five principles governing the implementation of mind in brain. The most ambitious research program under the aegis of AI is about the implementation of mind in computer. However doubtful I am about what AI has so far achieved—Horgan quotes Marvin Minsky as asserting that consciousness is a trivial matter he resolved long ago (p. 184)—that goal doesn't seem to be inherently problematic. However mind operates, it is a realm unto itself. Its laws are not reducible to those of biology or those of computing, though it may well be possible that they can be implemented in either. Beyond mind, David Hays and I have speculated in personal conversation that the phenomena of social role (Linton 1935) and double-contingency social interaction (Parsons 1951) are the seeds of a new realm which we might as well call culture. We could then say that culture is implemented in mind, though explicating that is another matter entirely.

If this is how the universe operates then the closest one could come to what Horgan calls The Answer would be to understand how one realm could give rise to another. That is perhaps where Ilya Prigogine’s work comes into play (Horgan, pp. 216-221; Benzon and Hays, 1990a, pp. 36-37). However, while Horgan's Answer is complete unto itself, the Answer implied by Prigogine’s work assures us only that the universe generates yet further fundamental questions.

Tight Like This: A Tale of High Adventure in Ancient Nubia [the fourth arena]

Yet another bump, and less than two years after the previous bump, In August of 2022. This time I'm preparing for the 3QD piece that's due of Mar. 24, for posting on the 25th.

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I'm bumping this to the top of the queue. Why? Because I can, that's why. Because the world's got to change and it's got to change NOW. You know, now's the time! We've been mugged by the future and don't realize it. We're still waiting for jet packs when the time for jet packs has done come and gone. There isn't going to be any AGI (artificial general intelligence) coming down the pike, not in time to make a difference and maybe not ever. Get real and figure out how we're doing to deal with a network of self-driving cars that can learn. Anyhow, this is going to require major changes in how we think, and that's going to require a new mythology. I figure maybe old Golfotep and the Mystic Jewels have something to say about that.

I published this on The Valve some years ago and, as the introductory note says, I'd published it on Meanderings, now defunct, before that. No doubt I will republish it somewhere else sometime in the future. Or maybe someone will make it into a movie. Who knows.

Oh, and be sure to check out Tight Like This (this is Wynton Freakin' Marsalis, Armstrong link in text below).  High drama & low-down hoochie coochie. 

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Jivometrics

Back in the mid 1990s, about the time Mosaic was being unleashed on the internet, I met a fellow in the African-American Forum at AOL Online. Called himself Cuda Brown. We hit it off and began emailing privately. Before you know it we were collaborating on a website called Meanderings - which later became Gravity. Cuda did most of the work, including all of the HTML coding and the back-end database coding. I helped editorially, wrote some pieces, and did some art.

One day I sent Cuda an email containing a spur-of-the moment paragraph satirizing Afrocentrism, something much discussed at Meanderings. While Cuda and I were sympathetic, we were doubtful about the more inventive flavors of the brew. Thus I had improvised something about golf being invented by one Pharoah Golfotep: the primo white-shoe Anglo country club plus-fours game was invented in ancient Egypt. What could be sillier? Over the next two weeks, however, this little bit of satire jes grew and grew, like Topsy, and became something else.

So, we posted it in Meanderings, which may have become Gravity by that time, I forget. And people read it. In time, however, Gravity died. Since then I've been looking for a place to revive “Fore Play.” Well, here it is. Let's call it a cultural studies primer for the new millennium.

Some of it is a bit dated. Who remembers Dennis Rodman, much less his experimental tonsorial stylings? Back then Tiger Woods was more potential than achievement – but what potential! – while boom boxes have now bifurcated into iPods and beat boxes. "Muggles" hadn't become a Potteresque term of art for – well, just what exactly, non-magicals? (I've never read any of the books.) Back then I used it as the name of a Louis Armstrong blues and I'm sticking to it. It's also old New Orleans slang for something Bill Clinton didn't inhale.

Otherwise, it's pretty much now as it was then. Only back then the turn of the millennium was in the future. Now it's in the past.

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Fore Play:

A Lesson in Jivometric Drummology


Jefferson Ribonucleic Parker IV

aka

Mr. Ribs

Tiger Woods is only the most recent in a long line of fine black golfers. In saying that I refer to players other than the moderns such as Charles Sifford, Jim Thorpe, Jim Dent, Lee Elder, Calvin Peete, and Renee Powell. Truth be told, the tradition of sepia swing masters started in ancient Egypt, where the game was invented. In that company Woods would be no more than a middling player.

By today's standards Tiger is ferociously talented and filled with promise for the future. Perhaps he'll become the best in post-modern times, the primo putter of the 21st Century, the first master to break par on the New Savanna. But those African drivers of ancient Egypt were giants the like of which haven't been seen in thousands of years.

Their stories, like so many stories, have been suppressed by the Europeans. Fortunately many of those stories have been collected by The Order of Mystic Jewels for the Propagation of Grace, Right Living, and Saturday Night through Historic Intervention by Any Means Necessary. The Jewels are dedicated to preserving the ancient stories and to intervening in history in ways variously clever and indirect. They are the chief source of that version of Afrocentric thinking known as Jivometric Drummology. In her classic study, Klactoveededstene: Riffing the Noumena, Ella Birks Roach defined the basic concept thus:

Jivometric Drummology: A philosophical system grounded in African and African-American musical practice. “Drummology” indicates that the governing logos is that of the drum, of rhythm, of hands and sticks coaxing sound from skin, of people joining together, each playing a simple rhythm, with the many simple rhythms melting into a single stream of infinite diversity. “Jivometric” is here because of the way it rolls off the tongue and tickles the ear; its meaning is secondary to its sound. Jivometrics is thus a principle of grace. When jivometrics is in play outer sonic auras join in the creation of tones played by no one, but heard by all. A treatise may have drummological ideas, but if the language lacks grace, then the treatise is not jivometric -- jiveturkey is all too often the appropriate term. In the most profound works of this school jivometrics and drummology are joined through agape

The Mystic Jewels, however, are not mere signifiers. They signify with a stern purpose. For example, Harriet Beecher Stowe was invented by the Mystic Jewels. They knew the abolitionists would never get beyond a lot of grand indignant talking so they figured a novel that stirred the imagination would be just the thing. A light-skinned sister named Eleanor Gough McKay changed her name to Harriet Beecher, married Calvin Stowe, and wrote Uncle Tom's Cabin. That book, as President Abraham Lincoln acknowledged, is what gave the North the guts to wage the Civil War.

Anyhow, my mother's father, Cassius Photon Gaillard, aka Slim, was a Mystic Jewel and took a special interest in the history of golf. The following story is based on information from his papers.

• • • • • • •

The Origin of Golf and the Lights in the Sky

Golf was invented by the ancient Egyptians – well, that's what we call them now, but they were really Nubians, and proud of it, too. Most of the details have been lost, but the general shape and thrust of the story has been preserved.

It began in the reign of Pharaoh Ramses Golfotep LVII of the 'N Baa Dynasty. One day Rams was hanging out with some of his friends in the Lark Meadow gazebo at his summer palace. As usual, they were playing bid whist and sipping Mount Gay and Coke, with a twist of lemon. As so often happens, they got to talkin' trash about their wives and girl friends. Ramses talked about how he particularly liked going into a special glade with his wife Cleopatra and a boom box loaded with some righteous jams. The best time was early evening when things were cooling down and the sun lit the sky with orange fire. They'd meander down this long narrow opening among the palms and get to a secluded spot ringed with patches of sand. The ground was firm and the grass kept closely cropped so they could dance freely. Inevitably the dancing would lead to a little fooling around, and that little fooling around generally led to more and before you know it Cleo was baking Ramses' sweet potato in her oven. That was some fine sweet potato pie they'd cook up. Yes indeed.

Mind Regulation in the 4th Arena

I’ve been thinking and writing a bit on the theme of a coming Fourth Arena, where the First Arena is the world of inanimate matter, the Second is the world of life, and the Third is the world of culture. What’s the Fourth about? I don’t know.

But I’m thinking it has something to do with mind. I figure mind arose in the universe in the Second Arena. Just where in the Second Arena (hereafter A2), I don’t know. I doubt that it makes sense to ascribe minds to bacteria. To insects maybe? Not likely. Vertebrates, sure, somewhere among the vertebrates. I’m not sure where, but it doesn’t matter now.

But with A3, mind can elaborate itself through culture. What’s next beyond culture? Not sure, and not sure where this is beginning.

What I’m thinking about is mind-regulation and, in particular, mind-regulation in conjunction with “intelligent” computers. If we’re going to be working more closely with a variety of computers, what’s that imply about mind-regulation? Here I’m not thinking about Musk-style physical linkage between brains and computers, though – who knows? – we may well have that for non-therapeutic purposes, for mind-augmentation or whatever. 

What if I set out to deliberately alter my mood through interacting with ChatGPT? 

At the moment I’m thinking more along the lines of my various interactions with ChatGPT. For the most part they just same-old same-old; nothing happening. Every once in a while, however something special happens, and I’m delighted, laughing to beat the band. I’m thinking, in particular, about moments during the sessions in which I created the story of the OpenWHALE, whaling ship of between two worlds, of the Jolly Green Giant chronicles. I didn’t create those things for the purpose of provoking laughter in myself, or in anyone else. But what if I did? What if I set out to deliberately alter my mood thought interacting with ChatGPT?

That’s the kind of thing I have in mind. We do all kinds of things to alter our mood. We take drugs of various sorts. Meditation. Bio-feedback. We go to movies, listen to music, read books, and so forth. We may do those things for entertainment, but they also change our mood – and isn’t entertainment itself mood-changin?

I’m thinking of other things as well. Writing sometimes comes easily to me, other times it comes hard. Sometimes I avoid it, put it off, for reasons I don’t understand – I’m doing that right now with my report on last year’s work with ChatGPT. Would interaction with a computer assistant help me over the hump? Could we create computer assistants that come to know our moods and adjust themselves accordingly? Is that what virtual reality is for?

I don’t know. I’m thinking about it. 

What about computers and the flow states they enable?

Stop thinking about the future through the eyes and ideas of the past.

The problem with most of the thinking about the future effects of AGI, superintelligence, and so forth, is that its looking at the future through the eyes of past – well, it's the present now.

But when the future actually unfolds, our minds will change accordingly. As a result, these various current speculations, whether utopian, dystopian, or some-other-topian, will seem quaint and old-fashioned. It's like those articles that show up every now and then comparing how the future looked to Victorians with what actually happened. It turns out they were wrong. Way wrong.

But then how could they really know? Same with comparing "The Jetsons" with the world now, or Kubrick's "2001." We're living in the future they imagined. And – surprise, surprise! – they got it wrong. Just like we're inevitably getting it wrong with our speculations of superintelligence and AI Doom. The problem isn't that it's too science fiction. It's the WRONG science fiction.

We need to learn how to think differently. We need to evolve a new conceptual system, with a new ontology. One that's in concert with artificial intelligence and machine learning rather then thinking of it as some exotic Other. We keep comparing it to us, and us to it, and so the future seems really strange and scary. Paradoxically, if we accept these things as something new and deeply different, they won't seem so strange and threatening.

What's so special about us? Why do we insist on specialness?

Scott Aaronson has just posted "The Problem of Human Specialness in the Age of AI."

For the past year and a half, I’ve been moonlighting at OpenAI, thinking about what theoretical computer science can do for AI safety. [...] In addition to “how do we stop AGI from going disastrously wrong?,” I find myself asking “what if it goes right? What if it just continues helping us with various mental tasks, but improves to where it can do just about any task as well as we can do it, or better? Is there anything special about humans in the resulting world? What are we still for?”

Here's a comment I posted over there:

@Matteo Villa, #31:

Should we not just let go of human specialness, just like humanity had to do when discovering that we are not at the centre of the universe and not even at the centre of our solar system?

I've been wondering the same thing. It's not as though the universe was made for us or is somehow ours to do with as we see fit. It just is.

From Benzon and Hays, The Evolution of Cognition, 1990:

A game of chess between a computer program and a human master is just as profoundly silly as a race between a horse-drawn stagecoach and a train. But the silliness is hard to see at the time. At the time it seems necessary to establish a purpose for humankind by asserting that we have capacities that it does not. It is truly difficult to give up the notion that one has to add “because . . . “ to the assertion “I’m important.” But the evolution of technology will eventually invalidate any claim that follows “because.” Sooner or later we will create a technology capable of doing what, heretofore, only we could.

Something I've just begun to think about: What role can these emerging AIs play in helping us to synthesize what we know? Ever since I entered college in the Jurassic era I've been hearing laments about how intellectual work is becoming more and more specialized. I've seen and see the specialization myself. How do we put it all together? That's a real and pressing problem. We need help.

I suppose one could say: "Well, when a superintelligent AI emerges it'll put it all together." That doesn't help me all that much, in part because I don't know how to think about superintelligent AI in any way I find interesting. No way to get any purchase on it. That discussion – and I suppose the OP (alas) fits right in – just seems to me rather like a rat chasing its own tail. A lot of sound and fury signifying, you know...

But trying to synthesize knowledge, trying to get a broader view. That's something I can think about – in part because I've spent a lot of time doing it – and we need help. Will GPT-5 be able to help with the job? GPT-6?

BTW, before the Copernican Revolution we weren't special (by "we" I mean Europeans and their descendants; I don't know off hand how the rest of the world thought about these matters). Earth was as the "bottom" of the cosmos. Of course that was a very different cosmos from the one we're imagining today. That was a cosmos ordered by God.

Maybe the evolutionary psychologists have something to day about this need to think of ourselves as the masters of the universe. 

ADDENDUM: Perhaps some of my thoughts about the (coming) Fourth Arena are relevant:

• Stakes in the Sand: Prediction, Cultural Ranks, and the Fourth Arena [+LLM Bonus]
• We’ve stepped over the threshold into the Fourth Arena, but don’t recognize it
• Welcome to the Fourth Arena – The World is Gifted
• The Fourth Arena 2: New beings in time
• The Fourth Arena: What’s Up in the world these days? We’re moving to a new, a new what?
• Living with Abundance in a Pluralist Cosmos: Some Metaphysical Sketches – That post has a link to my working paper of that title, Living with Abundance in a Pluralist Cosmos: Some Metaphysical Sketches, which is the "founding document," if you will, of my thinking about this. It also lists 8 propositions in my proposed metaphysics and contains links to and absracts of some relevant working papers.
• The Abundance Principle and The Fourth Arena

Meditation, Psychedelics, Computers, and the Mind

Early in the millennium I had an idea for a book, tentatively entitled, Mind Hacks R Us: Computing & Tripping to the Millennium's End, and I wrote a formal proposal under that title. I was unable to find a taker, but I kept the proposal around.

The rest of this post consists of two sections. The first is the prose introduction to the proposal. The second is a series of queries I put to ChatGPT about meditation, psychedelics, the computers, and the mind. What I’ve got on my mind, obviously, is what the future could hold:

Beyond AI displacing workers, creating new kinds of jobs, and solving all sorts of puzzles and problems, what are the possibilities for the general development of and flourishing of minds?

I’ve written about a Fourth Arena beyond the three arenas that the universe has so far evolved: inanimate matter, life, and culture. That’s where this post is headed. Note that I have a variety of posts under the tags, mhacks, and Arena.

Mind Hacks R Us

During the last half of the 20th century various groups of insiders and outsiders adopted mind-altering drugs and computer technology to create cultural spaces in which we imagined and realized new venues for the human mind. These spaces engaged fundamental issues of freedom and control, of emotion and reason, which have bedeviled humans everywhere, and elaborates them in the through modern science and technology. The psychoactive drugs which, in some sense, free us, have been synthesized through laboratory techniques we have invented, but only recently. The computers which extend our powers of control and order in often surprising ways embody logical forms that date back to Aristotle but where only recently brought to fruition in the late nineteenth century work of George Boole and others. Science and technology thus provide us with objective physical touchstones for the otherwise abstract powers and activities of our hearts and minds.

Taken together with that great Victorian invention, childhood innocence, the technologies of drugs and computers would constitute a cultural arena which served as incubator, nursery, and playground for some of the major lines of development in late twentieth century culture. For, if a society is to progress it needs cultural playgrounds where new ideas can be conceived, tested and developed. Psychedelic drugs and computing – and their associated cultures – functioned as such playgrounds in the latter half of the 20th century. They were, in fact, among the most important cultural playgrounds in America.

Given the fundamental differences between drugs and computers – what they are and how people use them, between Dionysian drugs and Apollonian computers – it is not surprising that different groups of people have been most interested in one or the other. What is most curious is that these people, and their creations, have often interacted, either directly or indirectly. In some cases, drug people and computer people are one and the same, as was the case in the San Francisco-Silicon Valley area during the 1970s.

Well before that, back in the 1950s, the Josiah Macy Foundation sponsored one series of high profile conferences about psychoactive drugs and another about computers. The cybernetics conferences – a series of about a half dozen of them – were chaired by MIT’s Grand Old Man of neuroscience, Warren S. McCulloch, and included such scientific luminaries as John von Neumann, Norbert Wiener, Claude Shanon, Gregory Bateson and Margaret Mead. Late in the decade, with the help of money from the CIA, the Foundation sponsored conferences on LSD; Bateson and Mead figured in those conferences as well. Both drugs and computers promised to reveal, in their different ways, the material basis of mind. And both were new in the 1950s, and so held forth only promise – but promise of what?

The answer to that questions depends, of course, on what people were looking for, what they wanted beyond what they knew and understood. In one way or another people looked to drugs and computers for powers beyond the ordinary, for transcendence of the human condition, and, more rarely, for insight into that condition. Thus if we are to understand the way in which drugs and computers have affected our culture over the last 50 years, we have to start with the aspirations we brought to drugs and computers.

Back in 1940s – and before – and continuing through the present. Animated films directed specifically at children (with their parents in tow) is the matrix in which these forces were brought together, a “universal kid space” in which fancy and fantasy are given full-rein. Walt Disney is the key catalytic figure. The images themselves came to depict human movement with a gravity-defying fluid grace heretofore realized only in the abstract designs of music, though shamans have imagined themselves in such flights while under the ritual influence of sacred drugs and sacred music. But the technology required to create those images embodied a relentless assembly-line logic that was new in the scope and precision of its repetitive actions. By directing these animated pictures specifically at children, film-makers freed themselves from the bonds of reality and allowed themselves freely to imagine idealized worlds quite unlike any places that humans had actually seen and inhabited. Disney’s Fantasia is the apotheosis of this cultural movement. It represents a fully-adult imaginative achievement that would have been impossible to those particular adults, raised as they were, without the facilitating guise of a commercial product aimed at children.

Fantasia, then, is the starting point for my main narrative. Psychedelic drugs take the mind to a different dimension, one that is often as more real than the mundane world. So it was with Fantasia. But Fantasia was constructed in a technological matrix which would soon give birth to the digital computer and, along with it, another series of idealized versions of human possibility, of a future in which machines relieved us of further work and toil. That too was part of the Disney vision.

From there I follow the development of computers and the emergence of psychedelic drugs as people use them to explore different ways of solving the same socio-cultural problem: How do you take the best aspects of the child-oriented world of animated films and make it the basis of a way of life? We have to drop the posture that this fantasy world is only for children and find a way to accept and rework selected aspects of it into lived adult reality.

Psychedelic culture dealt with this problem by trying out an ethic of in-the-moment hedonism that also included strains of romantic pastoralism, on the one hand, and Eastern mysticism on the other. Computer culture dealt with the same issues by offering a workplace ethic of libertarian entrepreneurship and dreams of a future where everyone can achieve a technologically-supported nirvana. These lines of cultural development have converged on science fiction, fantasy, and games as common venues for cultural exploration and expression. In either case, life is conceived along different lines than those described in the buttoned-down middle-class combat zone depicted in William Whyte, The Organization Man, David Riesman, The Lonely Crowd, or Vance Packard, The Status Seekers.

This cultural reworking is by no means complete. Nor has it been an easy matter. On the contrary, it has often been confusing, difficult, and painful. As such things always are. Always.

ChatGPT on meditation, psychedelics, the computers, and the mind

What can you tell me about the various styles and practices of meditation?

Meditation encompasses a wide range of practices and styles, each with its unique techniques, goals, and cultural origins. Here are some of the most popular styles and practices of meditation:

1. Mindfulness Meditation (Vipassana):
• Originating from Buddhist traditions, mindfulness meditation involves paying attention to the present moment without judgment. It often focuses on breath awareness and observing thoughts and sensations.
2. Transcendental Meditation (TM):
• TM is a mantra-based meditation technique. Practitioners repeat a specific mantra to achieve a state of relaxed awareness, promoting inner calm and stress reduction. TM has its roots in ancient Vedic traditions.
3. Loving-Kindness Meditation (Metta):
• This form of meditation emphasizes the cultivation of love and compassion. Practitioners focus on sending positive intentions and well-wishes to themselves and others, gradually expanding the circle of compassion.
4. Zen Meditation (Zazen):
• Rooted in Zen Buddhism, Zazen involves sitting in a specific posture and focusing on the breath or a koan (a paradoxical question or statement). The goal is to develop insight and experience a direct, unmediated awareness of existence.
5. Yoga Nidra:
• Also known as yogic sleep, Yoga Nidra is a guided meditation that induces a state of conscious relaxation. It's often used for deep relaxation and stress reduction, allowing practitioners to explore the inner world through guided imagery.
6. Guided Meditation:
• In guided meditation, a teacher or a recording leads participants through a series of visualizations or mental exercises. It can be tailored for various purposes, such as stress relief, personal growth, or healing.
7. Body Scan Meditation:
• This mindfulness-based practice involves systematically bringing attention to different parts of the body. It helps increase body awareness and release tension.
8. Chakra Meditation:
• Derived from Indian spiritual traditions, chakra meditation involves focusing on energy centers (chakras) within the body. Practitioners aim to balance and align these energy centers for overall well-being.
9. Mantra Meditation:
• Beyond TM, various meditation practices involve repeating specific sounds, words, or phrases (mantras). This repetition can help quiet the mind and deepen concentration.
10. Movement-Based Meditation (Tai Chi, Qigong):
• Practices like Tai Chi and Qigong combine meditation with gentle, flowing movements. These aim to cultivate mindfulness, balance, and harmony between mind and body.
11. Breath Awareness Meditation:
• Focusing on the breath is a common element in many meditation practices. Techniques range from simple breath awareness to more structured practices like Anapanasati in Buddhist traditions.

It's important to note that the effectiveness of meditation can vary from person to person, and individuals may find that different styles resonate with them at different times in their lives. Experimenting with various techniques can help you discover what works best for your preferences and goals.

Stakes in the Sand: Prediction, Cultural Ranks, and the Fourth Arena [+LLM Bonus]

Prediction is a tricky business. Since the motion of the planets is governed by mechanical laws which we understand, predicting their positions is a relatively straightforward matter. It is my understanding, though, that over the long term (several 10s of millions of years) their motions are chaotic in the mathematical sense of the word. Why? Because of weak gravitational effects among them.

Similarly, earth’s weather system is governed by mechanical laws which we understand. However, chaotic effects are relatively large, gathering high-resolution data on which to base predictions is difficult, and the computational resources needed are huge. Consequently, predictions for a few days are accurate enough to be useful, but usefulness tapers off rapidly thereafter.

Predicting human affairs is extraordinarily tricky. A great deal of effort and technical sophistication is routinely deployed in predicting economic events – fluctuations in securities markets, inflation, government revenues, etc. – the outcomes of elections. These efforts are not entirely useless.

And then we have the various efforts of the Rationalist community to predict the arrival of AGI and the extermination of humankind by Superintelligence. I regard these as epistemic theater more akin to divination than real prediction.

The rest of this post is about some of my own efforts at prediction.

Prospero Computing System

Back in 1976 David Hays and I reviewed the computational linguistics literature for a journal that was then called Computers and the Humanities. We began the article by defining computational linguistics and concluded it with a fantasy, a computer program so powerful that it was capable of reading Shakespeare texts in a way that was interesting but not human. We called it Prospero. It was a reasonable fantasy at the time. I figured that we might have such a Prospero system in twenty years. Hays knew better and refused to put dates on such fantasies.

Well, 20 years from 1976 would be 1996. No such system existed at that time, nor was any on the horizon. Whoops! Got that wrong.

The fact is, my attention was elsewhere at the time and I didn’t even notice that history had falsified by youthful prediction. I don’t recall just when I noticed that failure. I don’t even know whether it was before or after the turn of the millennium. Whenever it was, I noted it, but was not distressed. A whole new intellectual landscape had grown up and that’s where my attention was.

These days, of course LLMs can “read” Shakespeare in some sense. But not in the sense that Hays and I had in mind back in mid-1970s. We were thinking of a system that, in the first place, could reasonably be said to simulate the operations of the human mind, with explicit arguments based on empirical evidence validating the simulation. That still doesn’t exist and I hesitate to ‘predict’ when it might. In the second place, this system would be transparent such that, when it had read a Shakespeare play (or any other work of literature) we could look under the hood, as it were, and follow its operations. Regardless of the extent to which LLMs can be said to simulate the operations of the human mind, we can’t observe their inner workings.

With one exception, which I’ll get to at the end of this post, I see little point in making predictions the future course of work in AI, though I occasionally do so, more or less as a way of participating in current discussions.

Cognitive Evolution

In the summer of 1981 I was part of a team NASA put together to make recommendations about what NASA should do to become current with AI. The team produced a two-volume report, with the second volume being various documents written by individuals on particular issues. I contributed something I called, Executive Guide to the Computer Age, which contained the following illustration:

That diagram was based on a chapter in my 1978 doctoral dissertation, Cognitive Science and Literary Theory (Department of English, SUNY Buffalo). The point of the diagram is obvious, culture is evolving at an increasing rate which seems to converge on the present, where we find, among many other things, research in artificial intelligence.

That diagram doesn’t predict anything but it has implications for how we think about the future in the near and mid-term – and forget about the long term. Something BIG is going on.

David Hays and I refined the underlying analysis in a paper we published in 1990, The Evolution of Cognition. In that paper we refined the analysis I my dissertation by identifying each rank, as we called them, in that diagram with a with an advance in informatics, from speech, to writing, to calculation, and finally to computation. When then explained why each informatic advance enabled the construction of new systems of thought.

In our discussion of the current era we observed:

Beyond this, there are researchers who think it inevitable that computers will surpass human intelligence and some who think that, at some time, it will be possible for people to achieve a peculiar kind of immortality by “downloading” their minds to a computer. As far as we can tell such speculation has no ground in either current practice or theory. It is projective fantasy, projection made easy, perhaps inevitable, by the ontological ambiguity of the computer. We still do, and forever will, put souls into things we cannot understand, and project onto them our own hostility and sexuality, and so forth.

A game of chess between a computer program and a human master is just as profoundly silly as a race between a horse-drawn stagecoach and a train. But the silliness is hard to see at the time. At the time it seems necessary to establish a purpose for humankind by asserting that we have capacities that it does not. It is truly difficult to give up the notion that one has to add “because... “ to the assertion “I’m important.” But the evolution of technology will eventually invalidate any claim that follows “because.” Sooner or later we will create a technology capable of doing what, heretofore, only we could.

Note that we wrote this in 1990, before Deep Blue beat Kasparov in a chess match in 1997. With that in mind, read out last sentence again: Sooner or later we will create a technology capable of doing what, heretofore, only we could. We didn’t attach any dates to that statement.

I suppose that, in view of that statement, I could say that nothing that’s happened in the last 30 years surprises me. But that’s not at all true. Developments in deep learning in the second decade of the millennium surprised me and, of course, GPT-3 came as a bit of a shock. But the long term course of what’s going on, unless we screw it up, which is certainly possible, unless we screw things up, we’re moving into a world where we partner with increasingly intelligent machines.

Cosmic Evolution

Where’s that taking us? Consider an article I published in 3 Quarks Daily on June 20, 2022: Welcome to the Fourth Arena – The World is Gifted, Here’s how it begins:

The First Arena is that of inanimate matter, which began when the universe did, fourteen billion years ago. About four billion years ago life emerged, the Second Arena. Of course we’re talking about our local region of the universe. For all we know life may have emerged in other regions as well, perhaps even earlier, perhaps more recently. We don’t know. The Third Arena is that of human culture. We have changed the face of the earth, have touched the moon and the planets, and are reaching for the stars. That happened between two and three million years ago, the exact number hardly matters. But most of the cultural activity is little more than 10,000 years old.

The question I am asking: Is there something beyond culture, something just beginning to emerge? If so, what might it be?

THAT’s what’s going to emerge from a partnership between humans and intelligent machines. A fundamentally new phenomenon, beyond life and beyond culture. Just what that’s going to be like, I cannot say. That’s in the realm of science fiction.

Intelligibility of LLMs

Finally, we have the question: What’s going on inside large language models? That’s a special case of the more general question: What’s going on inside artificial neural nets? I think that by the end of 2024 we will know enough about the internal processes of LLMs that worries about their unintelligibility will be diminishing at a satisfying pace (except perhaps at LessWrong, where the prospect of intelligibility is as likely to cause anxiety to increase). Instead, we will be figuring out how to index them and how to use that index to gain more reliable control over them.

Unfortunately I cannot offer a strong argument on this. I’ve been spending a lot of time working with ChatGPT and have so far completed a dozen or so working reports – the top dozen reports on this list. That work in itself does not add up to the argument the previous paragraph begs for.

I’ve not stopped working, I have ideas that aren’t in those reports, and I have a collaborator, Visvanathan Ramesh at Goethe University, Frankfurt.

We shall see.

What are the 10–20 year prospects for AI?

First, while I do mean AI in general, most of my comments will be based on language technology (large language models, LLMs) because 1) that’s what I’ve been thinking about ever since the launch of ChatGPT, and 2) my understanding of language, of human language not just computational approaches to language, is broader and deeper than my understanding of vision and visual media, and even music.

My hope, not a prediction, hope, is that it will become REAL. What do I mean by that? That’s what this post is about.

Venture capitalists have three time horizons

My friend in venture capital, Sean O’Sullivan (who was my boss at MapInfo in the ancient days), tells me there are three time-horizons: 3 months, 12 months, and three years. So, in talking about 10-20 years I’m way out over the end of my skis. That’s fine.

But let’s begin by looking at those near-term prospects, the ones on which money is ventured – and lost or gained. If we set the clock at November 31, 2022, when ChatGPT was released to the public, then we are over 2/3 of the way into the first time-horizon. What has happened?

WOOSH!!! That’s what.

The public at large is more aware of AI than they have been before. In particular, the number of people who have been able to interact directly with an advanced AI (as opposed to Siri, Alex, and the like) has gone up dramatically, though, with more than 30 million users world-wide, it would still be less than 10% of the population of the United States. And that’s a lot.

Note, however, that secondary schools and colleges and universities are now scrambling to formulate policies and plans for dealing with ChatGPT in the classroom and research. Last week I answered a survey seeking ideas about the inclusion of ChatGPT as an author on research papers. Anything that impacts the educational system is going to have a very wide influence indeed.

Microsoft’s investment in OpenAI, the company that produces ChatGPT, has gone up and Microsoft is integrating its capabilities into various products and is on the verge of releasing its souped-up version of Bing, its search engine. Google has done to DEFCON 1 and is preparing to release a souped-up version of its search engine. I have no idea what Meta is planning, but surely they’re working on something, perhaps (almost certainly) involving the Metaverse. And, judging from comments by Yann LeCun, their VP for AI, their plans go well beyond LLMs.

How is this going to play out over the coming year? More of the same, I suppose. And the same for the 3-year horizon. A lot of the investments and entrepreneurial ventures will fail but some won’t. That’s just how things are. But three years is much too soon for things to settle down.

Why then even bother to speculate about 10 or 20 years down the road? Because I think too many eggs are going into the wrong basket and there won’t be enough investment in other technologies. By wrong basket I mean current deep learning architectures and extensions of them.

Gary Marcus has been banging the drum for symbolic AI (aka GOFAI), not that we abandon deep learning, but that we add symbolic AI, into the mix. For what it’s worth, David “IBM’s Watson” Ferrucci believes that as well and has founded a company, Elemental Cognition, that integrates deep learning and explicit logical reasoning. I agree them. But I fear it will take time for that message to sink in.

My current thinking

Meanwhile, I’ve been thinking things over. In particular, I’ve been thinking about mechanistic interpretability, which is a set of methods and interested within the larger scope of explainable AI. Mechanistic interpretability is the practice of reverse engineering the internal activities of neural nets, including LLMs. I’ve been pondering the question: What guidance can we find in the careful analysis of the output of LLMs, such as the one driving ChatGPT?

The final paragraph from my post, ChatGPT: Tantalizing afterthoughts in search of story trajectories [induction heads] (February 2) expresses my optimism about mechanistic interpretability:

Does anyone want to wager on when the opaqueness of advanced LLMs gives way to translucency? What about transparency? Those strike me as being more sensible wagers than betting on the emergence of AGI. The emergence of AGI depends on luck and magic. Figuring out how deep neural nets work requires only insight, hard work, and time.

This is from end of my working paper, ChatGPT intimates a tantalizing future (third revision, which I posted a couple of days ago):

Large language models already seem to be using symbolic mechanisms even though they were not designed to do so. Those symbolic mechanisms have simply emerged, albeit implicitly. What will it take to make them explicit?

We do not want to hand-code symbolic representations, like researchers did in the GOFAI era. The universe of discourse is too large and complex for that. Rather we need some way to take a language model and bootstrap explicit symbolic representations into it. It is one thing to “bolt” a symbolic system onto neural net. How do we get the symbolic system to emerge from the neural net, as it does in humans?

During the first year and a half of life, children acquire a rich stock of ‘knowledge’ about the physical world and about interacting with others. They bring that knowledge with them as their interaction with others broadens to include language. They learn language by conversing. In this way word forms become indexes into their mental model of the world.

Can we figure out a similar approach for artificial systems? They can converse with us, and with each other. How do we make it work?

Let’s think ahead to the next generation

I’m guessing that a decade or so should be enough time for deep learning to have run its course. Note that by this I do not mean that deep learning will disappear. I assume that it will become a permanent technology in the standard repertoire, but the novelty will have worn off and its limitations will be understood and widely accepted. A lot of venture capital will have been burned-through (the nature of the business). But we will also have seen a lot of interesting technology, some of it dead-ended, but some still alive and kicking.

When GPT-3 first appeared in the middle of 2020 I posted my quick take on the future of AI, which I reiterated at the end of December: Thoughts on the implications of GPT-3, two years ago and NOW [here be dragons, we're swimming, flying and talking with them]. I have no reason to revise that so soon.

Beyond that, it’s tricky. There is a reason venture capitalists don’t think beyond 3 years out; so many event streams are interacting that 3 years is the limit investment-worthy prediction. I don’t have any crystal ball. But I’m not so much concerned about the emergence of specific product streams. At the moment I’m thinking a bit more abstractly.

As you may know, back in the 1990s David Hays and I wrote a number of articles, both together and individually (and Hays wrote a book) on a theory of cultural ranks (here’s a guide). The general idea is that with the emergence of speech, writing, calculation, and computing over the last, say, 50K years and at inter-rank intervals decreasing by roughly an order of magnitude, each of those informatic technologies is able to support a more sophisticated family of architectures for thought, expression, and action. In private conversation we talked of a fifth cultural rank which we suspected was emerging around us. But we never published anything about it because it was too difficult to conceptualize. Conceptualizing the fourth rank, computing, was all we could manage. A fifth rank? What’s it about? What’s the new informatic technology?

THAT’s what’s on my mind. When scaling up on deep learning systems fails to take us all the way to AGI, or even noticeably closer, when superintelligence seems as chimerical as ever, will the “thought leaders” in this space sober up and think more seriously and deeply? Will we make more progress toward new systems of thought? That’s what I was thinking back in August when I posted, Which comes first, AGI or new systems of thought? [Further thoughts on the Pinker/Aaronson debates].

I have two reasons for not taking AGI and superintelligence seriously. On the one hand neither is very well-defined. As Steven Pinker remarked in one of his debates with Scott Aaronson, superintelligence is more like a superpower than a well-articulated technical concept. And so it is with AGI. My other reason, though, is simply that I have a different way of thinking about intellectual and technological advance. I have this theory of cultural ranks. To be sure, I can’t articulate the underpinnings of the next rank, the one we’re struggling toward at the moment, but I can point to the past, noting that in time we’ve always managed to develop new systems of thought that encompassed and eclipsed the old ones. What should that process stop? Why, in particular, should human thought stagnate while the machines we’ve created will surpass us?

For that is the unstated presupposition of those who keep predicting and hoping for the emergence of AGI. They seem to believe that human thought has come to a standstill and the best we can do is wait for the machines to evolve and hope they don’t destroy us. Though, some are hoping to stave off that development by either slowing down that emergence of AGI or figuring out how to “align” it with human values. There doesn’t seem to be the faintest hint of an inkling of an idea that human thought is advancing.

What I’m thinking is that the effort to advance beyond the technology we’ll have in a decade or so will take us up to the next level. One where we’re working on fundamentally new physical platforms for computing, where neuromorphic technology begins to emerge from the laboratory into practical deployment. Just as dogs and humans coevolved over tens of thousands of years early in human history, so we will co-evolve with these new neuromorphic devices into a world where thoughts of AGI and superintelligence seem as quaint as angels dancing on the head of a pin.

We’ve stepped over the threshold into the Fourth Arena, but don’t recognize it

First there was the world of inanimate matter, the First Arena. Life arose from that, the Second Arena. Only 100s of thousands of years ago humans evolved from higher primates and the Third Arena, human culture, appeared. We are now on the threshold of the Fourth Arena. How do we characterize it?

Note: These thoughts are off the top of my head [thinking-out-loud]. It was all I could do to get them out. That’s enough for now. Refinement will have to wait.

* * * * *

OpenAI released GPT-3 in the summer of 2020. It was clear to me that, yes, it has that potential. I registered my response, initially in a comment over at Marginal Revolution, and then on New Savanna, First thoughts on the implications of GPT-3 [here be dragons, we're swimming and flying with them]. Having explored ChatGPT for the past two weeks, that potential emerges before me with even greater clarity. Of course, we could blow it, nothing is guaranteed. But still...

One must wonder, dream, and hope.

Foundation Models as digital wilderness

Let us start with these deep learning models trained on large bodies of data. ChatGPT has such a model at its functional core. They have been termed Foundation Models because they “can be adapted to a wide range of downstream tasks.” I have come to think of each such models as repositories of digital wilderness.

What do we do with the wilderness? We explore it, map it, in time settle it and develop it. We cultivate and domesticate it. AI safety researchers call that alignment. The millions of people who have been using ChatGPT are part of that process. We may not think of ourselves in that way, but that, in part, is how OpenAI thinks of us. Even as we pursue our own ends while interacting with ChatGPT, OpenAI is collecting those sessions and will be using them to fine-tune the system, to align it.

Yes, it would be nice to have a system “pre-aligned” before it is released to end users. But I don’t think that’s how things are going to work out. The process by which these engines are trained on large amounts of data is powerful, but it is also messy. While some alignment can be achieved by a small in-house team tweaking the system, ultimately it will have to interact with a much larger body of users. Why not think of alignment as a process concomitant with use?

What are the business implications of a technology where the end users will inevitably playing an important role in fine-tuning and evolving the technology they are using?

Robots and the physical world

One problem that has come up is that of embodiment. These Foundation mMdels, these tracts of digital wilderness, have no access to the real world. Language models are trained on texts, visual models are trained on images. Neither have the capacity to interact with the world.

In an essay he wrote shortly after he took a position as VP of AI for Halodi Robotics, Eric Jang wrote:

Reality has a surprising amount of detail, and I believe that embodied humanoids can be used to index that all that untapped detail into data. Just as web crawlers index the world of bits, humanoid robots will index the world of atoms. If embodiment does end up being a bottleneck for Foundation Models to realize their potential, then humanoid robot companies will stand to win everything.

Those robots will thus be creating more digital wilderness. But also helping to develop it, to align it.

Symbolic Systems and alignment

One issue that has come up is that of the role of the Old School technologies of symbolic systems. Are they obsolete or, on the contrary, will the remain important? While there is wide-spread sentiment that they are obsolete, and that the technology can achieve its fullest flowering simply by scaling up machine learning, I disagree, nor am I alone.

The question is how we are going to integrate symbolic technology with machine learning. One problem is that, traditionally, such systems have been developed “by hand.” The code must be crafted by people who are experts in the application domain. This is costly and time-consuming.

Off-hand I don’t what can be done. Yes, work is being done with hybrid systems where symbolic technology is grafted on to and underlying base of machine learning. I would like to see symbolic capabilities emerge from the underlying artificial neural net technology – perhaps analogous to the way in which language develops in humans, something I’ve discussed in my recent working paper, Relational Nets Over Attractors, A Primer: Part 1, Design for a Mind, Version 2.

I note, though, that I regard the development of symbolic technology as a stream in the overall process of aligning software grounded in vast plots of digital wilderness. It will thus be a gradual process distributed widely thoughout the community of users.

AI as platform, Adept

Two years ago venture capitalist Mark Andreesen talked of AI as a platform, not a feature. He said:

I think that the deeper answer is that there’s an underlying question that I think is an even bigger question about AI that reflects directly on this, which is: Is AI a feature or an architecture? Is AI a feature, we see this with pitches we get now. We get the pitch and it’s like here are the five things my product does, right, points one two three four five and the, oh yeah, number six is AI, right? It’s always number six because it’s the bullet that was added after they created the rest of the deck. Everything is gonna’ kind of have AI sprinkled on it. That’s possible.

We are more believers in a scenario where AI is a platform, an architecture. In the same sense that the mainframe was an architecture or the minicomputer is an architecture, the PC, the internet, the cloud has an architecture. We think AI is the next one of those. And if that’s the case, when there’s an architecture shift in our business, everything above the architecture gets rebuilt from scratch. Because the fundamental assumptions about what you’re building change. You’re no longer building a website or you’re no longer building a mobile app, you’re no longer building any of those things. You’re building an AI engine that is, in the ideal case, just giving you're the answer to whatever the question is. And if that’s the case then basically all applications will change. Along with that all infrastructure will change. Basically the entire industry will turn over again the same way it did with the internet, and the same way it did with mobile and cloud and so if that’s the case then it’s going to be an absolutely explosive....

I agree, and believe that Adept: Useful General Intelligence, is moving in that direction. From their blog:

In practice, we’re building a general system that helps people get things done in front of their computer: a universal collaborator for every knowledge worker. Think of it as an overlay within your computer that works hand-in-hand with you, using the same tools that you do. We all have parts of our job that energize us more than others – with Adept, you’ll be able to focus on the work you most enjoy and ask our model to take on other tasks. For example, you could ask our model to “generate our monthly compliance report” or “draw stairs between these two points in this blueprint” – all using existing software like Airtable, Photoshop, an ATS, Tableau, Twilio to get the job done together. We expect the collaborator to be a good student and highly coachable, becoming more helpful and aligned with every human interaction.

This product vision excites us not only because of how immediately useful it could be to everyone who works in front of a computer, but because we believe this is actually the most practical and safest path to general intelligence. Unlike giant models that generate language or make decisions on their own, ours are much narrower in scope–we’re an interface to existing software tools, making it easier to mitigate issues with bias. And critical to our company is how our product can be a vehicle to learn people’s preferences and integrate human feedback every step of the way.

Judging from what they’ve written, they’re not quite where Andreesen’s conception is, but they’re moving in that direction. All you have to do is put AI at the heart of the application, rather than treating it as an add-on, and you’re there.

Robot Toys, an exercise for the reader

Do some research on the state of robotic toys and companions. Start with, say, the 1990s Tamagotchi, which wasn’t a robot at all, but a little gadget one had to care for. Do a web search on “robot toys.” Think about the Tamagotchi, think about children and dolls/action figures, and think about those robot toys. Take what you find and insert it hear. Perhaps ChatGPT can help you.

Robots and Humans, living and working together

In 1995 Neil Stephenson, published The Diamond Age: Or, A Young Lady's Illustrated Primer. It centers on a young girl, Nell, who is given a precious book, A Young Lady's Illustrated Primer, which she has with her as she grows up. It serves her as both a tutor and a companion.

That’s where we’re headed. But I have no idea when we’ll get there, a century, two, three? Who knows.

At a very young age each child will be given such a book, or perhaps a robot – why not both? – which will stay with them for the rest of their life, functioning variously as a companion, tutor, and workmate, their personal robot companion (PRC).

At the moment time of their third birthday. By this time the child has plenty of experience getting around physically and is getting better with speaking. They will have seen other kids with their PRCs and no doubt have interacted with them. They’ll know that, when the time comes, they’ll be getting one too.

The robot will have to be of an appropriate size, a book too for that matter. I will have to be replaced at the appropriate age. That will require a ritual, as did the original gifting of the PRC, and/or book.

We will evolve toward a society where robots, AIs, and people will be constantly interacting with one another. There where will communities of mixed groups, others of only one kind of being. I have no idea what that will be like. But it does sound like the Fourth Arena will be deeply entrenched in that world.

Beyond AGI, super-intelligence, and the Singularity

What about AGI (artificial general intelligence)? What about it? Originally it was simply AI, and it was right about the corner. But, alas, it really wasn’t. “AGI” was coined in the first decade of the millennium to revivify those old hopes.

While I followed work in AI back in the day, I did it out of a sense of professional obligation. I didn’t think it was going anywhere. The very different AI that we’ve got now IS going somewhere. It’s time to ditch those old dreams in favor, both of current reality and what we can build in the near-term future, and of new dreams.

I feel much the same about the idea of super-intelligence. Oh, I know how the word was used. I could follow the conversations. But I don’t think there is anything there, no substantial conceptual development.

I feel the same about the idea of a Technological Singularity. AGI recursively rewriting its own code until FOOM! super-intelligence? Nah. Not going to happen. Someone termed it The Rapture for Nerds. That sounds about right.

No, something else is afoot. We’re living on the cusp of the Fourth Arena. What could be grander?