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Tuesday, May 19, 2026

Something New, Something Old

Two excellent books, 50 yrs apart: 2026—1976

@6:18…

Dana Bush
Given this thought experiment that you put in this book, what do you think the meaning of life is?

Neil deGrasse TysonI think people search for meaning of life as though it's under a rock or behind a tree. But we have the power to create meaning in life. And for me, I want to learn something today that I didn't know yesterday and spend each day lessening, lessening the suffering of others. There's something that we all have the power to do, and maybe aliens want to do that too. We always make them evil. And I think it's because we're projecting our own evil ways onto them, knowing that's how we behave when we encounter cultures of lower civilization, lesser technology than ourselves. So yeah, I, I, meaning we can find it. And if we find aliens and they help us get more meaning out of the universe, more power to us.
Indeed.
 
 
"...PREVENT US FROM IMAGINING A UNIVERSE NOT TEEMING WITH LIFE?"
 
Let's rewind 50 years. Doris & David Jonas:
Chapter 1, Where Speculation Begins, pp 7-9

One of these days, our descendants, near or distant, are going to find life in some form on other planets, either in the solar system, in other parts of our galaxy, or in other galaxies.

The very fact that life has arisen on our earth is evidence enough that it must exist in other parts of the universe, for the elements of which the entire universe is composed are remarkably uniform. If some of these elements have combined in ways that produce life here in our solar system, they must, by the laws of chance and probability, have combined in an analogous ways elsewhere. Even in our galaxy, there must be some thousands of other planets, sustaining life, in some form, and all the forces of reason would suggest that it cannot be otherwise in other galaxies.

What miracles of chance and combinations of chances made it possible for life to evolve here on earth?

For life to arise on any planet, certain factors have to be present in certain combinations. The solar system of which the planet is part must have formed in a way that some or one of its evolving planets takes shape at a suitable distance from the blazing inferno of its central sun – neither so near that its surface temperatures inhibit life by intense heat, nor so far that life cannot arise because of insufficient solar radiation. The masses into which the swirling gases originally solidify must be within the range that permits a force of gravity, sufficient to hold and retain an atmosphere, since without a protective atmosphere, solar radiation would be too intense for life forms to be sustained, even if all the other elements of life were present.

The chance that these two factors alone – distance from the center, and the degree of mass that governs gravity occur together in just the right circumstance, puts a preliminary limitation on the possibility for life. Even after this has occurred, there must be a further series of chances following and working upon chances – and again interlocking with other chance happenings – so that atmosphere, water, rocks, and some soil come into being in states that conform a basis for the evolution of life. Of course there is a possibility, remote as it seems, that some form of life might arise on a lightless planet. should that planet be capable of generating heat of its own within a life sustaining range.

The information we have been able to gather from our own solar system suggests that ours is the only planet around our sun that sustained life. It could be that other suns, even thousands or tens of thousands of other suns, sustain no life at all on the planets that circle them. Given the myriad suns in our galaxy and the multiple myriads in the universe, it is impossible to believe that chances similar to those that occurred on earth have not also occurred on many other planets.

Once these miraculous chances have come about, however, the prerequisites for life are rather minimal: An element capable of forming self-replicating chains, like carbon, and another capable of combustion, like oxygen these, together with hydrogen and nitrogen, form and matrix that may merge with other elements to create all the varied, complex, and wonderful forms of life on earth – from amoeba and bacteria to plants and spiders and fishes and man.

What shapes may life have taken in other worlds? Have they developed into intelligent creatures, and, if they have, what sort of intelligences have evolved? Have other kinds of life developed high orders of intelligence capable of developing technologies, and, if so, what sort of technology has arisen from their special kinds of being? Shall we ever be able to communicate with these beings, if they exist, in any meaningful way?

One thing is certain: we have no reason to assume that evolutionary forces on other planets will produce forms or intelligence that are the same as ours, even though the basic raw materials must be similar. Whatever chance factors combined to produce any form of life, infinitely more, must combine to produce an advanced form.

Genetic inheritance is only a beginning. Two offspring of the same parents by chance born in different environments will produce eventual descendants so markedly different that after many generations, it will hardly be possible to realize that the ancestors of each line had parents in common.

The variables of habitat, the chance of availability of mates, natural selection, and sexual selection among the offspring will all have combined and recombined to produce members of the same species as buried as a pygmy, a Watusi, a Swede, a Chinese, or a magnesian, and eventually to divide into species, such as man, apes, and monkeys have separately descended from the same stem.

Our own earth provides an illustration of the almost incredible number of living forms that can possibly be derived from a single celled organisms that were once the triumph of evolution on our planet. All the species now extinct, and all those still flourishing form only apart of the total possibilities, for who knows how many new species will yet take shape?

Ch 11, Beyond Human Intelligence, pp 212-217

Intelligence begins with the sensitivity of a single cell, and by a process of biological accumulation and selection, transmitted genetically, reaches a current culmination in the complexity of the human brain. In the same way, the first chipped flint, by a process of cultural accumulation of knowledge passed on verbally and subjected to the selection of experience, reaches a current combination in spacecraft, cyclotron, and satellite relayed television. At the same time, the natural and necessary playfulness of the young mammalian as it explores its environment and learns how to live in it, overtime, and also by a cultural process of imitation, memory, and the transmission of knowledge and skills from generation to generation, reaches another apotheosis in the high cultures and great arts.

For the comparatively weak creature who must cope with an environment and rise to any situation or perish, the resources of mental equipment are applied first to the most urgent exigencies. The earliest application of intelligence is devoted to devising tools as weapons; those that follow aid the amenities of life; finally, religion, philosophy, and the arts make their appearance.

The kind of tools that are made will depend on the material that happens to be available, be they leaves, branches, stones, clay, or the presents or absence of minerals. Thus an interaction exists between the environment and creatures that affects the development of tools and cultures, as well as of census and intelligence.

In ancient Egypt, for example, the presence of the papyrus plant led to the fabrication of ropes, mats, sandals, and eventually paper; the presence of flax made possible the eventual perfecting of supremely fine linens. In central America, the presence of lava led to cutting edge tools of obsidian. Once a cultural habit becomes established, however, it remains impossible to predict either the route it will follow or its ultimate outcome. Who could have told that the sweet-potato washing habit established among the members of the famous Japanese Macau colony, and the subsequent shifting of sand from the grain in the sea, would so accustomed these forest animals playing in the water that they would eventually begin to swim? And in the face of this unlikely outcome of a recently established behavior pattern, who would dare to predict to what the newfound ability to swim might lead?

Yet strangely enough—or perhaps, not so surprisingly, in view of the basic uniformity of mankind’s cerebral mechanisms—no matter where, geographically, nor when, over the entire span of human history, local cultures have developed into advanced civilization, we find that man’s greatest thoughts, as epitomized in the writings of philosophers, show remarkable similarity. Some views on the nature and value of knowledge, intellect, and intelligence propounded by the wise men of China, so distant from us in place in time, are stunning in their modernities and still current validity.

In the misty beginnings of China’s long, cultural history, Lao the, expanding his concept of Tao, the way (of nature and wise living), is reported to have insisted that knowledge is not virtue, and neither is it wisdom, for nothing is so far from it a sage as in “intellectual.“ The worst government would be one of philosophers, he has said to have averred, they botch every natural process with theory; their ability to make speeches and multiply ideas is precisely the sign of their in capacity for action!

At a later period the philosopher, Chuang the, who lived about 370 BC, showed the sophistication of thinking that we find difficult to credit to those in early times. He wrote that problems are due less to the nature of things than to the limits of our thought; that is not to be wondered at that the effort of our imprisoned brains to understand the cosmos of which they are such minute particles should end in contradiction.

He spoke of the limits of intellect; the attempt to explain the whole in terms of the part has become gigantic immodesty, forgivable only on the grounds of the amusement it has caused, for humor, like philosophy, is a view of the part in terms of the whole, and neither is possible without the other. The intellect, said Chuang tze, can never avail to understand, ultimate things, for any profound thing, such as the growth of a child. In order to understand the Tao, one must “sternly suppress one’s knowledge“: we have to suppress our theories and feel fact. Education is of no help towards such an understanding: submission in the flow of nature is all important.

And Wang Yang Ming, who lived from 1472 to 1528, practically summarized our present thesis when he wrote: “the mind itself is the embodiment of natural law. Is there anything in the universe that exists independent of mind? Is there any law apart from the mind?“

Experts feel certain that the human brain has not undergone any significant biological change since the time of the Neanderthals, as evidenced in the excavations at the Shandiar caves high in the mountains of Kurdistan in northern Iraq, built fires, cared for their sick, conducted funeral rights, and put flowers with the bodies of their dead. In the last 20 to 30,000 years, we know from archaeological findings of both historic and prehistoric periods, a high degree of intellectual accomplishment that has been formally present in all the branches of our species throughout his existence. The brief excerpts we have given of an ancient Chinese thought about thought would certainly seem to bear out this opinion.

There is, however, an outcome of the cumulative nature of culture that we must not overlook. Increasingly, as intelligence adapt a living creature to its environment by the use of artifacts, and through the cultural transmission of knowledge, the creature and the environment, modify each other at an exponential rate. Perfect adaptation, of the order of the ants for the termites, which has existed in a balance between being and have unchanged over hundreds of millions of years, is not possible for mankind. The rapidity of change in our cultural habitat, presents a perpetual and continuing stimulus to bodily and, above all, to mental adaptation, which of necessity increases the demands on the new brain to device accommodation, and then the process speeds both the rate of change and the need for new changes.

And so, although we recognize that we have been mistaken in thinking that the technological advances of western men might indicate new departures from the human brains’ capacities, yet we have also to recognize that the technology is rapidly creating a totally new environment for our species this new Environment may well ultimately affect our species future development; precisely this technology may prove to be the turning point through which, in negotiating it, we may find ourselves in a process of extinction as Homo sapiens and in a stage of transition toward homo neocorticus

There are, of course, far too many imponderables  Involved to feel confident in predicting the future course of our species. Among these are the course of technology itself, and how far from natural processes it can carry us before it becomes subject to its own limitations. There is the matter of human population density, and whether it will be adjusted by natural means or can be adapted to the biosphere that is our habitat by cultural or social means. There is the question of the medical preservation of the “unfit“ and whether we can remain viable at all as a species with the increasing maladaptive dilution of our gene pools. And there is the possibility that ecological interference may ultimately make mankind’s existence untenable.

Our evolutionary development may be reaching the end of a line for biological, if not for cultural reasons, but we ourselves are inclined to discount this. We believe subtle biological factors to be operating that are not yet clearly discernible, but which may be recognizable in retrospect. Another factor as simple and probable as the advent of another Ice Age, for instance, would effectively alter and recalibrate the balance between men and nature, and must also be kept in mind as a possibility.

We believe that the possibility, and even the likelihood remain for a true evolutionary progression in the anatomical and physiological configuration of the brain, much like the progression that occurred between apes and man. In that case, the departure would be just as radical, and it would have as a consequence new behavioral response patterns that at this point we cannot visualize and about which we can only speculate.

To assume that this new superintelligence would occupy itself with creating a new, weird, and wonderful technology is a naïve exercise in human fantasy. Ultimately technology exists to serve the greater comfort of individuals, and a superintelligence may well find other means of achieving this end. Thus, were such a superintelligence to be found in some other planetary systems, we might be confronted with something totally alien to our understanding, and even to our imagination…
'eh?
 
This book has been out of print for 37 years. It has aged extremely well.  

Monday, May 18, 2026

The Singularity is already here in the U.S.

The Justice Department said it is creating a nearly $1.8 billion fund that could compensate Trump supporters who say they were wrongly investigated or prosecuted by previous administrations. The announcement came as part of a settlement with President Trump to drop a $10 billion lawsuit he filed against the IRS over the leak of his tax returns in 2019. Justice correspondent Ali Rogin reports.
I'm gonna have to file a claim.
 

MAY 19th UPDATE
 
Acting AG Todd Blanche today issued a 1-pg addendum to the Trump IRS lawsuit "Settlement." It henceforth indemnifies Donald Trump, his family, his businesses, and Trusts ("Plaintiffs") from any future investigations or IRS audits. Section C below.
 

The Singularity of Donald Trump.
 
apropos, Andrew Weissmann's new book just came out.
 
Amazon link.
Excellent thus far.
 

Friday, May 15, 2026

"Perception is an ILLUSION?"

 
Well, that's pretty unequivocal. That graphic is from a BigThink Youtube video. The speaker is neuroscientist Dr. Heather Berlin.
 
First time I saw that graphic, I had a fleeting reflexive reaction of "oh, yeah, the 'Subjectivism Fallacy'," stemming from my 1999-2004 Adjunct days teaching collegiate "critical thinking" classes. i.e., "there ARE NO 'objective truths,' everything is subjectively perceived in response to sensory stimuli." "So, (BobbyG retorts) if this assertion is 'false' (illusory), it deductively follows that it must also be TRUE."
 
Pedant. 
 
Yeah, Heather. It's just a 4-word (albeit clickbait-ish) headline.
 
 
The broader point is taken, Doc. Succintly put in 6:21.
 
OF PARTICULAR RELEVANCE THESE DAYS
 
"The provided sources examine the complex intersection of anthropomorphism, trust, and power within the field of artificial intelligence. One study investigates how linguistic cues, such as voice-based interfaces and the use of first-person pronouns, lead users to perceive large language models as more human-like and accurate. Complementary research explores the "Silicon Valley Effect", arguing that Big Tech companies strategically shape regulatory discourse to protect their commercial interests while potentially obscuring the human harms caused by their products. Further analysis focuses on the visual self-representations of ChatGPT, identifying recurring themes of futurism and social intelligence that promote the image of a "friendly assistant." Collectively, these texts highlight how human-like traits in AI can manipulate public perception, set unrealistic expectations of capability, and complicate the legal and ethical oversight of generative technologies."
[Sounds a bit like it was written by AI, no?]
AI as applied to social media (and "influence" industries broadly) is all about shaping your perceptions in ways that benefit them. "AI for Good?"
 
I'll fill in a bunch of multi-vector applicability ASAP...

Thursday, May 14, 2026

The Trump UFO release

 
Lotta new (reality-based serious) stuff on deck. Check back in...

Tuesday, May 12, 2026

Brian J. Driscoll, FBI patriot


My intent today had been to begin on continuing another topic (AI, evolution, exobiology, sentience/cognition stuff), but then tonight I watched CNN Anderson Cooper 360. Most of the hour was devoted to an interview of former Acting FBI Director Brian Driscoll—(a decorated 27 yr career FBI veteran). He was summarily fired by Trump's FBI Director Kashyap Pramod Patel (better known lately as K.Edgar.Boozer) in August 2025 in a blatantly illegal act of political vengeance at the behest of Donald Trump.
 
 
Brian is suing. Read the civil complaint here. He has a great attorney, Margaret Donovan. I would Polymarket her winning this case.
 
More to come...

Friday, May 8, 2026

I could not recommend this new book by Danielle Crittenden more highly.

 
I got onto this via an Atlantic excerpt. Bought it and read it overnight. I totally get it, and I have learned a ton in 2 days. Thank you, Danielle and David.

 
Prior relevant riffs of mine: A Billion Tons of Human Bones

Thursday, May 7, 2026

The "Accelerationists" vs the "Doomers."

AI For Good?
 
Pending book release. Pre-pub excerpt from The Atlantic.
The Secret to Understanding AI
“Imagine the tech without the tech companies.”
By Josh Tyrangiel

In the before times—before machines could hallucinate, before compute was a noun—it was not uncommon to go several weeks without someone telling me the world was about to end. Similarly, a whole season might pass without anyone assuring me that it was also, simultaneously, about to become perfect.

That particular luxury died on November 30, 2022, when OpenAI released ChatGPT to the public. What followed was less a news cycle than a weather event—a tropical depression that would not budge. Within weeks, millions of people had their first experience with generative AI. Within months, every major technology company had announced its own version of a large language model, or a partnership, or a pivot. Venture capital arrived drooling. Most people in tech think about money, but AI-profit projections are different—like CFO fan fiction, written in Excel. In 2023, the McKinsey Global Institute estimated that $4.4 trillion in annual corporate profits could be up for grabs from generative AI alone. Morgan Stanley estimated $40 trillion more in operational efficiencies. The words artificial intelligence went from obscurity to a constant hum, present in every earnings call, every school-board meeting, and far too many arguments at dinner tables.

Yet for all of the noise, a simple question stayed unanswered: What exactly was this new technology going to do for people? Not for corporations or the billionaires who aspired to become trillionaires, but for people with mortgages and sick parents and children struggling to learn things…
May 12th release date.
AMAZON BLURB
In contrast to the wave of noisy polemics around AI, AI For Good explores how, in practice, it can actually improve our lives and tells the stories of everyday citizens at the forefront of this new “AI entrepreneurship.”

AI is often framed as a force of radical transformation, either catapulting us into a utopian future or dragging us toward existential ruin. But this book tells a different story. It’s not about high-profile tech CEOs who want to use AI to “break shit,” but about a bunch of smart pragmatists using AI to make the world better.

Josh Tyrangiel’s journey into AI began with a late-night YouTube video featuring General Gustave Perna, the retired four-star general who orchestrated the distribution of Covid vaccines during Operation Warp Speed. Perna’s success—and the end of the pandemic—depended on AI’s practical ability to synthesize and standardize vast amounts of logistical data. AI wasn’t the hero of the story—it was the tool that helped real people get things done.

This book follows those people, who make up a kind of AI counterculture. It explores AI’s quiet revolution in government services, medicine, education, and human connection—places where it’s being used to amplify human judgment rather than replace it. It tells the stories of teachers, doctors, and bureaucrats who often stumbled into AI as a means to solve specific, tangible problems, often with no prior software expertise.

While the loudest voices in AI debate doomsday scenarios and trillion-dollar market opportunities, this book focuses on those working in the messy, incremental, but deeply impactful space of AI practice. However, there is one big caveat—success is not guaranteed. Change is hard. Institutions move slowly. But even in failure there are lessons for everyone who’s interested in using AI—carefully, thoughtfully—to build a better world today.
I have too many books in play at the moment (about 8), but I'll be adding this to the list when it's released.
 
SOME OTHER READS JUST ADDED TO THE STASH

 
Dispatches from Grief is intensely personal for this "Girl Dad."


 
The greatest pitfall in the search for extraterrestrial life—according to science fiction, anyway—is foolhardy researchers somehow bringing aliens to Earth to wreak havoc.

But after decades of exploring our seemingly sterile solar system, real-world scientists today are much more concerned with the opposite problem: The possibility that Earth’s life will escape our planet to contaminate other worlds, sabotaging the quest to find any genuine “second genesis” of biology around the sun. Imagine that a multibillion-dollar robotic mission found wriggling microbes on Mars and that follow-up studies then revealing those “aliens” had DNA and other biomolecular machinery that showed they were emigrants from Earth.

Astrobiologically speaking, we would have met the enemy—and it would be us. Taking a cue from sci-fi, you might call such life-forms “Klingons,” for their presumptive hitchhike to the Red Planet as stowaways in spacecraft sent from Earth.

“Planetary protection” is the term scientists use for efforts to prevent otherworldly invasions of all sorts; to date, most of it has focused on Mars, but the practice applies to all potentially habitable environments within reach of our spacecraft. In the 1970s, for example, NASA did its best to keep its twin Viking landers Klingon-free before launching them to Mars. And if the NASA-led international Mars Sample Return effort ever manages to bring its precious payload back to Earth, the agency will be tasked with quarantining those specimens as if they contain extreme biohazards rather than lifeless bits of rock and soil…
Imagine my surprise. apropos of some prior riffs on astrophysics and exobiology.
 
OFF-TOPIC, CHEERS... 
More shortly... 

Wednesday, May 6, 2026

Rest in Peace, Sir

Ted Turner
Ted Turner was a very good man.

Tuesday, May 5, 2026

"AI" Query

 
Well, that first pass took less than 10 seconds.
 
 The under-the-hood details slog will surely be "bring a Snickers, you gonna be a while."
 

The NYT tally comprises an A thru Z Trump-spleen-target breakout setting forth every diss by Trump. Hillary Clinton, Joe Biden, and Obama alone consume screen page after screen page of crass Twitter jibes.
 
There's probably a book here. The crudities spanning the 59 years of Donald's "adult" life would surely fill volumes. 
 
Anyone recall "Bushisms?" Quaint by comparison. SMH chronic lexical incoherence, to be sure, but nil venom.

Sunday, May 3, 2026

Dr. Sherry Turkle, MIT

“Friction is the nature of the human condition.”
    
The Sherry Turkle quote above is from Kara Swisher's wonderful CNN "Live Forever" docuseries (S1.E3). The main topic concerns "loneliness in the age of AI."
 
Yeah, friction, more broadly, is the inescapable condition of life writ large.
 
"EQUILIBRIUM IS DEATH"
A long time ago, here, there, and everywhere else, everything was all together and unreasonably hot. One day, a very, very long time from now, everything will be very, very far apart, and incredibly cold, and nothing will ever happen again. But between those two intervals—on the descent from the Big Bang to the end of time—things can happen. We live in that liminal moment, after the cream has been added to the cosmic coffee, when galaxies convect, the larger swirls begetting smaller swirls, and fractals thread themselves all the way down through creation. But just as the tiny hurricanes of cream in your coffee don’t swirl endlessly over the course of breakfast, this filigree of physical reality—the galaxies, the stars, the planets, the cellular machinery of life—is temporary. It’s endlessly dissipating. In fact, it all exists in the service of getting us as quickly and efficiently as possible to that uniform, universal café au lait at the end of time. Toward tranquility, equilibrium. 

While equilibrium might seem desirable in our own lives, in practice equilibrium is the end. Equilibrium is death. But though the universe as a whole might be straining toward that ultimate end—toward an exhausted state of uniformity and maximal disorder, when everything everywhere is the same temperature, when all debts have been settled, all contradictions have been resolved, and no more work can ever be done again—we still, thankfully, find ourselves far from that final state of equilibrium. The sun still shines, and so we make hay. In fact, we can only ever find ourselves in this brief moment, impossibly early in cosmological history when the universe is still so outrageously far from reaching equilibrium that interesting things can still happen. Life, love, everything we care about—these are all so-called far-from-equilibrium phenomena. And it was in this universal straining toward equilibrium, on a restless young planet, that life emerged. It was here that carbon dioxide was transformed to living matter, and the Earth became the Earth…


Brannen, Peter. The Story of CO2 Is the Story of Everything: How Carbon Dioxide Made Our World (pp. 20-21). (Function). Kindle Edition.
 
Yeah, that's pretty tangential. True nonetheless. writ large...
 
I've cited Dr. Turkle before.

 
UPDATE
 
I notice increasing CNN YouTube short vids pumping Kara's dpcuseries. e.g.,
 
 
This shortie goes to the S1.E3 topic—"mitigating loneliness w/out chatbots."

More shortly...

Thursday, April 30, 2026

Psychology and Artificial Intelligence

 
Ran into this podcast today on YouTube. Found it quite interesting, particularly given all the the fractiousness engulfing the AI technology debate. Good use of 48 minutes of your time.
(~@3:23, interesting Dr. Keaton observation) “…For me personally, I hate when we teach our undergraduates—as you know as often is done—we basically just teach them a string of Nobel prize winning experiments and just connect the dots, and you go through the twists and turns—brought up this statement by Feynman—that the difference between knowing the name of the thing and knowing something about it is the most dangerous gap in all of science.” [More on that bit of Zen shortly.] 
Tom Griffiths' latest:
 
This book is about how the human mind comes to understand the world—and ultimately, perhaps, how we humans may come to understand ourselves. Many disciplines, ranging from neuroscience to anthropology, share this goal—but the approach that we adopt here is quite specific. We adopt the framework of cognitive science, which aims to create such an understanding through reverse-engineering: using the mathematical and computational tools from the engineering project of creating artificial intelligence (AI) systems to better understand the operation of human thought. AI generates a rich and hugely diverse stream of hypotheses about how the human mind might work. But cognitive science does not just take AI as a source of inspiration. What we have learned about the mathematical and computational underpinnings of human cognition can also help to build more human like intelligence in machines. 

The fields of AI and cognitive science were born together in the late 1950s, and grew up together over their first decades. From the beginning, these fields’ twin goals of engineering and reverse-engineering human intelligence were understood to be distinct, yet deeply related through the lens of computation. The rise of the digital computer and the possibility of computer programming simultaneously made it plausible to think that, at least in principle, a machine could be programmed to produce the input-output behavior of the human mind. So it was a natural step to suggest that the human mind itself could be understood as having been programmed, through some mixture of evolution, development, and maybe even its own reflection, to produce the behaviors we call “intelligent.” In these early days, AI researchers and cognitive scientists shared their biggest questions: What kind of computer was the brain, and what kind of program could the mind be? What model of computation could possibly underlie human intelligence—both its inner workings and its outwardly observable effects? 

Now, almost 70 years later, these two fields have matured and (as often happens to siblings) grown apart to some extent. Cognitive science has become a thriving, occasionally hot, but still relatively small interdisciplinary field of academic study and research. AI has become a dominant societal force, intellectually, culturally, and economically. It is no exaggeration to say that we are living in the first “AI era,” in the sense that we are surrounded by genuinely useful AI technologies. We have machines that appear able to do things we used to think only humans could do––driving a car, having a conversation, or playing a game like Go or chess—yet we still have no real AI, in the sense that the founders of the field originally envisioned. We have no general-purpose machine intelligence that does everything a human being can or thinks about everything a human can, and it’s not even close. The AI technologies we have today are built by large, dedicated teams of human engineers, at great cost. They do not learn for themselves how to drive, converse, or play games, or want to do these things for themselves, the way any human does. Rather, they are trained on vast data sets, with far more data than any human being ever encounters, and those data are carefully curated by human engineers. Each system does just one thing: the machine that plays Go doesn’t also play chess or tic-tac-toe or bridge or football, let alone know how to see the stones on the Go board or pick up a piece if it accidentally falls on the floor. It doesn’t drive a car to the Go tournament, engage in a conversation about what makes Go so fascinating, make a plan for when and how it should practice to improve its game, or decide if practicing more is the best use of its time. The human mind, of course, can do all these things and more—independently learning and thinking for itself to operate in a hugely complex physical, social, technological, and intellectual world. And the human mind spontaneously learns to figure all this out without a team of data scientists curating the data on which it learns, but instead through growing up interacting with that complex and chaotic world, albeit with crucial help with caregivers, teachers, and textbooks. 

To be sure, recent and remarkable developments in deep learning have created AI models which, with the right prompting, can be used to perform a surprisingly diverse range of tasks, from writing computer code, academic essays, and poems, and even to creating images. But, by contrast, humans autonomously create their own objectives and plans and are variously curious, bored, or inspired to explore, create, play, and work together in ways that are open-ended and self-directed. AI is smart; but as yet it is only a faint echo of human intelligence. 

What’s missing? Why is there such a gap between what we call AI today and the general computational model of human intelligence that the first computer scientists and cognitive psychologists envisioned? And how did AI and cognitive science lose, as has become increasingly evident, their original sense of common purpose? The pressures and opportunities arising from market forces and larger technological developments in computing, along with familiar patterns of academic fads and trends, have all surely played a role. Some of today’s AI technologies are often described as inspired by the mind or brain, most notably those based on artificial neural networks or reinforcement learning, but the analogies, although they have historically been crucial in inspiring modern AI methods, are loose at best. And most cognitive scientists would say that while their field has make real progress, its biggest questions remain open. What are the basic principles that govern how the human mind works? If pressed to answer that question honestly, many cognitive scientists would say either that we don’t know or that at least there is no scientific consensus or broadly shared paradigm for the field yet…


Griffiths, Thomas L.; Chater, Nick; Tenenbaum, Joshua B. (2024). Bayesian Models of Cognition: Reverse Engineering the Mind (Preface). Kindle Edition.
Another of his books.

Everyone has a basic understanding of how the physical world works. We learn about physics and chemistry in school, letting us explain the world around us in terms of concepts like force, acceleration, and gravity—the Laws of Nature. But we don’t have the same fluency with the concepts needed to understand the world inside us—the Laws of Thought. You have probably heard of Newton’s universal law of gravitation. But you might not have heard of Shepard’s universal law of generalization—a simple principle that describes the behavior of any intelligent organism, anywhere in the universe. While the story of how mathematics has been used to reveal the mysteries of the external world is familiar to anybody who has taken even a casual interest in science, the story of how it has been used to study our internal world is not. This book tells that story. 

A little over three hundred years ago, a small group of philosophers and mathematicians began to pull together the threads that make up modern science. They developed a keen sense of observation, a talent for conducting experiments, and a new set of tools for expressing mathematical theories. Over the following centuries, observation, experiment, and mathematics have been combined to reveal both the smallest and the largest things in the physical universe in ever-increasing detail. But those philosophers and mathematicians weren’t just interested in the physical universe. They were also interested in the mind, and they wanted to use the same mathematical tools to study it. Thomas Hobbes wrote about the possibility of understanding “ratiocination” as “calculation,” asking whether we might imagine thoughts being added and subtracted. René Descartes imagined numbers being assigned to thoughts in much the same way that they are assigned to collections of physical objects. Gottfried Wilhelm Leibniz spent his life trying, and ultimately failing, to find a way to use arithmetic to describe human reason. 

The first success in using mathematics to analyze thought wouldn’t appear until the middle of the nineteenth century, when George Boole cracked the problem that Leibniz hadn’t been able to solve by coming up with a new kind of algebra. That first success had far-reaching consequences, leading to the development of formal logic and computers. The first attempts to evaluate mathematical theories of thought by comparing them to human behavior wouldn’t appear until the middle of the twentieth century, in the Cognitive Revolution that launched the field of cognitive science—the interdisciplinary science of the mind. Cognitive scientists have since come to recognize the limits of formal logic as a model of human cognition, and have developed completely new mathematical approaches—artificial neural networks, which illustrate the power of continuous representations and statistical learning, and Bayesian models, which reveal how to capture prior knowledge and deal with uncertainty. Each has something to offer for understanding the mind. 

In the twenty-first century, knowing the Laws of Thought is just as important to scientific literacy as knowing the Laws of Nature. Artificial intelligence systems demonstrate on a daily basis that yet another aspect of thought and language can be emulated by machines, pushing us to reconsider the way we think about ourselves. Understanding human minds and how much of them can be automated becomes critical as we plan our careers and think about the world that our children will occupy. By the end of this book you will know the basic principles behind how modern artificial intelligence systems work, and know exactly where they are likely to continue to fall short of human abilities…


Griffiths, Tom (2026). The Laws of Thought: The Quest for a Mathematical Theory of the Mind (Introduction). Kindle Edition.     
QUICK UPDATE
 
I finished Episode 3 of NetFlix's "3 Body Problem." Bought volume 1 of the print trilogy snd have begun reading. Pretty cool.
 
UPDATE
From Science Magazine
Large language models (LLMs) are artificial intelligence (AI) algorithms that are trained on vast amounts of data to learn patterns that enable them to generate human-like responses. Reasoning models are LLMs with the added capability of working through problems step by step before responding, thus mirroring structured thinking. Such AI systems have performed well in assessing medical knowledge, but whether they can match physician- level clinical reasoning on authentic diagnostic tasks remains largely unknown. On page 524 of this issue, Brodeur et al. (1) demonstrate that AI can now seemingly match or exceed physician-level clinical diagnostic reasoning on text-based scenarios by measuring against human physician performances on clinical vignettes and real-world emergency cases. The findings indicate an urgent need to understand how these tools can be safely integrated into clinical workflows, and a readiness for prospective evaluation alongside clinicians.

AI has the potential to support a broad range of health care applications, from clinical decisions to medical education and the provision of patient-facing health information. LLMs have passed medical licensing examinations and performed well on structured clinical assessments, raising the prospect that they could help alleviate global health care workforce shortages. However, passing examinations is not the same as being a doctor, and demonstrating physician-level performance on authentic clinical tasks is a fundamentally harder challenge (2).

Brodeur et al. evaluated OpenAI’s first reasoning model, o1-preview (released in September 2024), across five experiments that assess diagnostic performance on clinical case vignettes against physician and prior-model baselines. A sixth experiment compared o1 with prior models, and physicians across three diagnostic touchpoints on 76 actual emergency department cases. Across the experiments, the o1 models substantially outperformed prior-generation nonreasoning LLMs (e.g., GPT-4) and, in many cases, the physicians themselves. For example, when provided with published clinicopathological conference cases, GPT-4 achieved exact or very close diagnostic accuracy in 72.9% of cases, whereas o1-preview achieved this in 88.6% of cases. Further, in actual emergency department cases, o1 achieved 67.1% exact or very-close diagnostic accuracy at initial triage, outperforming two expert attending physicians (55.3% and 50.0%), with blinded reviewers unable to distinguish the AI output from human. This advance sets a new evaluation benchmark—testing AI against physician performance, and ideally alongside physicians, on authentic clinical tasks...
Lengthy, detailed discussion. Seriously of interest to me, in light of my long experience working for and with physicians.
 
ALSO IN SCIENCE TODAY: BOOK REVIEW
 
Amazon blurb.
Lively. . . . Rousing. . . . Prophecy—roving, intelligent, irreducibly idiosyncratic—can expand our sense of possibility, starting now.” —The New York Times Book Review

Tech empires are the prophets of the modern day, and like the ancient oracles and medieval astrologers that preceded them, they're not in it for the common good—they're in it for power. Award-winning University of Oxford professor Carissa Véliz brilliantly argues why we must reclaim that power, and shows us how.

“A masterpiece. . . . The most important book you will read for years.” —Roger McNamee, New York Times bestselling author of Zucked


For thousands of years, oracles, seers, and astrologers advised leaders and commoners alike about the future. But predictions are often power plays in disguise, obfuscating accountability and stripping individuals of their agency. Today we face the same threat of powerful prophets but under a new facade: tech.

Not only do modern predictions made by tech companies advise on war, industry, and marriages, but artificial intelligence also now determines whether we can get a loan, a job, an apartment, or an organ transplant. And when we cede ground to these predictions, we lose control of our own lives.

Drawing on history’s cautionary tales and modern-day tech companies’ malfeasance—from surveillance and biased algorithms to a startling lack of accountability—Carissa Véliz demonstrates that big tech’s prophecies are just as shallow, dangerous, and unjust as their ancient counterparts’. What she uncovers in the process is chilling. Artificial intelligence is increasing risk in business and society while creating a false sense of security. In this incisive, witty, and bracingly original book, Véliz contends that the main promise of prediction is not knowledge of the future but domination over others. Powerful people use predictions to determine our future. Prophecy is an invitation to defy those orders and live life on our own terms
SCIENCE MAG
As I finished reading Prophecy, by philosopher Carissa Véliz, the soundtrack of The Matrix hummed in my mind, howled by the band Rage Against the Machine (“Wake up! Wake up!”). In fact, a weird kind of intellectual synesthesia took place throughout my perusal of the book, as I could also hear the dystopian slogan from George Orwell’s 1984 furiously sung by the same band: “Who controls the past now controls the future, who controls the present now controls the past.”

Véliz’s scholarship focuses on ethics and artificial intelligence (AI)—two realms that often refuse to meet. In 2020, she published Privacy Is Power, warning readers against the algorithmic invasion that has continued to take hold of our personal data, feeding the techno-golems of Silicon Valley and threatening our sanity and liberty. This book is her second major admonition.

Prophecy is about the power of predictions, especially when they are maliciously misleading. The structure of the book is dialectic: The first part expounds the promise of predictions and their influence throughout history, and the second articulates their manifold perils and related abuses of power, particularly in the current age of AI oracles. The third and final part of the book seeks a resolution, namely, how to rethink predictions and resist their deceptive lure.

Predictions have always been with us, from ancestral wisdom that told us when to sow and reap to mathematics used to optimize decisionmaking under uncertainty. Forecasts are ultimately guesses—educated or naïve, right or wrong, innocuous or consequential. They can also be deliberately deceptive, not anticipating the future but rather covertly shaping it. When such predictions are then turned into promises and ossified into decrees, we are in trouble.

Using predictions as prescriptions to benefit one’s agenda is not new. Rulers have always done so. But current AI empires make such a practice unprecedentedly pervasive and pernicious.

AI, argues Véliz, is the new diviner—the ultimate prediction machine. Mirrored on the fashionable idea that our brains are inference devices, such artificial prophets are dangerous. Digital technologies now rule our personal and professional lives, as well as the fate of countries and civilizations. They tell us who to date, what to watch, who to hire, when to start a war, and so forth. These simulacra are presented as deep knowledge, even truth, and then turned into self-fulfilling prophecies. Perils abound, as predictions also give us a false sense of security, increasing risks and lacking accountability...
'eh? 
 
More shortly...

Tuesday, April 28, 2026

"Enough is Enough."

And, given the past few shitstorm days, I have most certainly had enough.

 
I need a bit of a diversion.
 
Surfing NetFlix tonight. Ran into a SciFi series I'd not heard of.
 

8 episode series 1. Apparently re-upped for a Season 2. From a 3-book trilogy, which I will buy and read. I paused Episode 1 about halfway through to post this.


Oddly resonant. Stay tuned.

Sunday, April 26, 2026

"Digital Gold, or Fool's Gold?”

 
I've posted on Ben and his work before.
See more prior crypto-related posts here.