There are more living cells on Earth than stars in the universe: ~ 10^30 vs. ~ 10^22

These numbers come from a fascinating piece by Dennis Overbye summarizing work by a team of biologists and geologists. Selected clips:

According to the fossil record, geology and evolution have been engaged in a dance for 3.8 billion years, since our planet was only 700 million years old. It was then that the first single-celled creatures appeared, perhaps in undersea volcanic vents, feasting on the chemical energy around them.

The population of cells has been growing exponentially ever since, even through geological disasters and extinction events, which opened up new avenues of evolution.

The seeds for animal life were sown sometime in the dim past when some bacterium learned to use sunlight to split water molecules and produce oxygen and sugar. By 2.4 billion years ago, with photosynthesis well-established, the amount of oxygen in the atmosphere began to rise dramatically. The Great Oxidation Event was clearly the biggest event in the history of the biosphere.

Without photosynthesis, the rest of creation would have little to eat. But it is just one strand in a web of geological feedback loops by which weather, oceans, microbes and volcanoes conspire to keep the globe basically stable and warm and allow life to grow.

The carbonate silicate cycle, for example, regulates the amount of carbon dioxide in the atmosphere; the gas traps heat and keeps the planet temperate and mostly stable. Rain washes carbon dioxide from the air and into the ocean; volcanoes disgorge it again from the underworld. As a result, a trillion gigatons of carbon have been cycled from gas to life and back again over the millenniums. That’s about 100 times as much carbon as exists on Earth, which suggests that, in principle, every atom of carbon has been recycled 100 times.

The rise of cyanobacteria set off what is known as the Cambrian Explosion about 550 million years ago, when multicellular creatures — animals — appeared in sudden splendiferous profusion in the fossil record. We were off to the Darwinian races.

Crockford and his colleagues realized that they could trace the population growth of cells through time by measuring mineral isotopes and the amount of oxygen in old rocks. As a result, they were able to estimate the total life that Earth has produced since its beginning — about 10^40 cells, roughly 10 billion times more than currently exist.

Although this number sounds huge, it represents only 10 percent of all the cells that will come about by the time the curtain falls on life on Earth a billion years from now. As the sun ages, it will brighten, astronomers say, amplifying the weathering and washing away of carbon dioxide. At the same time, as Earth’s interior gradually cools, volcanic activity will subside, cutting off the replenishment of the greenhouse gas.

As a result, Dr. Crockford said, “it is unlikely that Earth’s biosphere will ever grow beyond a time-integrated ∼10^41 cells across the planet’s entire habitable lifetime.”

But for now, Dr. Crockford and his colleagues wrote in their paper, “the extension of today’s relatively high rates of primary productivity will likely squeeze more life into less time.” The more cells there are, the more times they will replicate, producing more mutations, Dr. Crockford explained. We inhabitants of Earth’s biosphere have a billion years’ worth of surprises ahead of us.

Self-Organization: Nature's Intelligent Design

I was to pass on this link to a talk by Clint Sprott, who initiated the Chaos and Complexity Discssion group that I was an active member of before leaving Madison WI. I remain on their email listserve. The slides for the talk can be downloaded here. Talk description:

Clint Sprott, Professor Emeritus, Department of Physics, UW-Madison, explains that although we believe that complex patterns must have a complex cause, patterns may spontaneously arise. This self-organization which occurs in nature can be described with simple computer models that replicate the features of the patterns.

How our genes support our illusory selves - the "Baldwin effect"

I have been thinking about giving more explanation of a paragraph from my Oct. 25 post, A Materialist's Credo:

Modern neuroscience has proved that our experienced perceptions of sensing and acting are these predictions. They are fantasies, or illusions, as is our sense of having a self with agency that experiences value, purpose, and meaning. Everything we do and experience is in the service of reducing surprises by fulling these fantasies. An array of neuroendocrine mechanisms have evolved to support this process because it forms the bedrock of human culture and language.

The sentence "An array of neuroendocrine mechanisms have evolved to support this process because it forms the bedrock of human culture and language." is invoking what is called "The Baldwin Effect" or Baldwin hypothesis. 

I decided to turn to Chat GPT-4 for some help.

Deric:  

What is the "Baldwin effect" in evolutionary biology, particularly with respect to human evolution?

ChatGPT: 

The "Baldwin effect" describes a mechanism by which learned behaviors can eventually become inherited traits through the process of natural selection. Named after the psychologist James Mark Baldwin, who proposed the idea in the late 19th century, this concept bridges the gap between phenotypic plasticity (the ability of an organism to change its phenotype in response to changes in the environment) and genetic evolution.

Here's a simplified overview of how the Baldwin effect works:
    1    Initial Variation: Within a population, there are variations in behavior. Some individuals can learn a new beneficial behavior in response to a change in the environment, while others cannot.
    2    Learning as a Temporary Solution: The ability to learn this behavior offers a short-term advantage. Those who can learn the new behavior have a better chance of surviving and reproducing.
    3    Genetic Fixation Over Time: Over generations, there can be genetic changes that make this learned behavior easier to acquire or even innate. As those with a predisposition to the behavior have a better survival and reproductive rate, genes that support the behavior become more common.
    4    Reduced Reliance on Learning: As the behavior becomes more genetically rooted, the population may become less reliant on learning the behavior from scratch. Eventually, what was once a learned behavior can manifest itself as an instinctual behavior.

With respect to human evolution, one could theorize the Baldwin effect playing a role in various capacities. For example, our ancestors might have learned specific skills, like tool use or certain social behaviors, that provided survival advantages. Over time, genetic predispositions towards these skills could have developed, leading to humans having innate tendencies or quicker learning capacities in these areas.

However, it's essential to note that proving the Baldwin effect in human evolution is challenging due to the intricacies of genetic and cultural evolution. Still, it offers an exciting perspective on the interplay between learning and genetics.

Deric: 

How might the Baldwin effect hypothesis be applied to the human invention of an illusory "I" or "self" capable of forming social groups, whose cohesion is reinforced by emotional behaviors driven by evolved neuroendocrine mechanisms?

ChatGPT:

The concept of an illusory "I" or "self" is deeply rooted in both philosophical discourses and cognitive science studies. When considered in the context of the Baldwin effect, the evolution of such a self-concept could be framed as an adaptive trait in the intricate web of human social structures. Here's one way to interpret this:   

    1    Initial Variation and Learning: Early human communities might have had members who had stronger self-awareness or more robust personal identities than others. Such individuals might have been better at recognizing their roles within groups, remembering past interactions, and predicting future interactions. This self-awareness might initially emerge as a learned or nurtured cognitive trait.
    2    Social Advantages: Individuals with a pronounced sense of self could have been more adept at forming and maintaining social bonds, making them crucial members of their communities. They might have been better at understanding social hierarchies, reciprocity, and the nuances of cooperation, which are essential for the survival and success of early human societies.
    3    Emotional Behaviors and Neuroendocrine Mechanisms: As these individuals navigated their social landscapes, their brains could have evolved neuroendocrine mechanisms to support the complex emotions related to social interactions—empathy, jealousy, gratitude, shame, etc. These emotions, in turn, would reinforce the cohesion and stability of social groups, ensuring the group's collective survival and success.
    4    Genetic Fixation Over Time: Over generations, the capacity for a strong self-concept and the accompanying emotional depth might become increasingly genetically ingrained. This evolution would mean that newer generations would be born with an innate predisposition towards these traits, reducing the learning curve required to acquire them.
    5    Cultural Evolution: Parallel to the genetic fixation, cultural mechanisms might evolve to further reinforce the idea of the self and its importance in the society—through stories, traditions, rituals, etc. The interplay between genetic predispositions and cultural learning might lead to the establishment of the 'self' as a foundational concept in human societies.

In this context, the Baldwin effect would suggest that our ancestors' learned behavior—forming a concept of self for social advantages—over time, became a genetically supported predisposition. This evolution would mean that the complex cognitive and emotional behaviors supporting a strong self-concept became more instinctual and less reliant on individual learning.

Unification of physics and biology by "Assembly Theory"

An international collaboration of researchers  in an open source article in Nature Magazine,  has developed a new theoretical framework that bridges physics and biology to provide a unified approach for understanding how complexity and evolution emerge in nature. Here is their abstract:  

Scientists have grappled with reconciling biological evolution with the immutable laws of the Universe defined by physics. These laws underpin life’s origin, evolution and the development of human culture and technology, yet they do not predict the emergence of these phenomena. Evolutionary theory explains why some things exist and others do not through the lens of selection. To comprehend how diverse, open-ended forms can emerge from physics without an inherent design blueprint, a new approach to understanding and quantifying selection is necessary^. We present assembly theory (AT) as a framework that does not alter the laws of physics, but redefines the concept of an ‘object’ on which these laws act. AT conceptualizes objects not as point particles, but as entities defined by their possible formation histories. This allows objects to show evidence of selection, within well-defined boundaries of individuals or selected units. We introduce a measure called assembly (A), capturing the degree of causation required to produce a given ensemble of objects. This approach enables us to incorporate novelty generation and selection into the physics of complex objects. It explains how these objects can be characterized through a forward dynamical process considering their assembly. By reimagining the concept of matter within assembly spaces, AT provides a powerful interface between physics and biology. It discloses a new aspect of physics emerging at the chemical scale, whereby history and causal contingency influence what exists.

Added note:  I am grateful to Julio Salazar for his comment below providing critiques of Assembly Theory :

On the Salient Limitations of the Methods of Assembly Theory and their Classification of Molecular Biosignatures 

The 8 Fallacies of Assembly Theory 

Assembly Theory and Agnostic Life Finding

Anthropic Claude's version of my writing on the Mind

This post describes the first of my personal encounters with AI  that has left me completely in awe of its capabilities. Since 1993 I have been placing the label *mind* at the beginning of paragraphs in my personal journal that I think are  relevant to understanding our minds. Here I pass on the results of asking Anthropic’s Claude GPT engine to process 56 pages of paragraphs with this *mind* label written so far in 2023. (Chat GPT-4 was unwilling to process more than ~9 pages at a time). The first paragraph of the 56 pages of text submitted to Claude was the following instruction:

"Claude, please organize, edit, reduce redundancy, condense, find major themes, patterns, connections and write a new version of the following series of paragraphs that I have written:"

The following is Claude's first response to the above prompt (Response 1),  then a 'retry' or regenerated version  (Response 2) which is shorter and more concise, and finally Response 3 is an even shorter response to the simple instruction:  "Claude, please organize and rewrite the following paragraphs of ideas marked with the label *mind*  from my personal journal into a continuous text that makes them more understandable to others as well as to myself:"

I am amazed by Claude's responses...

Response 1 (to first prompt above)

The Mind

-The mind is like space, the canvas on which experiences, thoughts, and feelings arise. It is not any one of the transient appearances within it.
-Thoughts and feelings are evolutionary mechanisms, ultimately serving to defend and propagate one's group. Kindness, compassion, joy - these arise impersonally, they are not intrinsic qualities of a "self."
-From a cosmic perspective, concepts like meaning and purpose play out on a small scale, driven by motivations that evolved to promote altruism and group bonding. Awe, wonder, reverence can be motivators to learn, persist, and reproduce.

The Self

-The self is a perceptual construct, an "emotion of ownership" assembled from models of others, emotions, perceptions etc. There is no fundamental self, only the feeling of occupying an expanded space of awareness.
-We exist as multiple input/output processes (eat, breathe, think, act). Various "avatars" or selves arise transiently from awareness, each with its own biases and correlates.
-Language and imagined futures enabled the evolution of complicated selves and societies. But selves dissociate us from nature, from being fully present.

Being vs Seeing 

-Awareness can be trained to disengage from thoughts and visceral reactions, to simply observe them without attachment. This allows more freedom in shaping one's experience.
-"Being" means resting as the space of awareness, not caught in any one transient appearance. "Seeing" means identifying a particular self/avatar and its storyline.
-As selves are seen and become opaque rather than transparent, the feeling of being an autonomous agent also becomes optional.

Equanimity

-Equanimity comes from seeing all appearances as equal, not needing to seek or avoid any of them. Pain and pleasure just are.
-Aging can allow more time simply being present vs constantly reacting. The body may dial down metabolic rate when not driven by a storyline.
-"There is no there there" - nothing to obtain, no final place. Just the dance of appearances and disappearance, only the present moment.

The Path

-Let reflectivity trump reactivity. Deflect and distill input, only a fraction needs further attention.
-Release identification with any one avatar or self. Be the river and watcher, neither exclusively.
-Set optimal levels of arousal/valence/agency. Dial down judgment, dial up openness and curiosity.
-Practice simple narrative protocols Just take the next step, being gentle, grateful, generous, curious.

Response 2 (to first prompt above)

The mind is the space in which all experiences arise, rather than any one of the fleeting contents within it. My purpose is to stay present, share insights, and care for self and others. 

Everything is fundamentally impersonal, arising through evolution. Kindness, connection and community emerge to defend and propagate one's group. Awe, joy and meaning motivate learning and reproduction in an indifferent world.

The self is a construct, an emotion of authorship. My fluid identities are tools, not truth. I aim to be the space holding each "I" lightly, rather than clinging to any one.

Reactive habits link thoughts to feelings. Awareness can disengage this clutch, reducing reactivity. 

Equanimity comes from resting as awareness, not any transient contents. Suffering is resisting what is. 

Language generated complicated social order, but also dissociates us from nature. AI may allow a return to more natural, animal ways of being. I seek novelty, discern patterns, and train responses. 

Advanced age permits more resting in present awareness, not lost in narratives. I cultivate gratitude, generosity, curiosity and play. Small actions matter more than big purposes in uncertain times.

The body's wisdom matters most. Health requires some arousal and performance, but also untethered leisure. Balance is key. I aim for agency, pleasure and calm, dialing these as needed.

I share my path, as it has helped me. But each of us is unique, mysterious. People are not what I wish, but what they are. I offer gentle truth, not judgment or control.

Words appear from the ether, then pass. I craft brief tales, a secular Bible, hoping some may resonate. But nothing lasts. A quiet fullness remains, life's gift.

Response 3 (to second prompt above) 

The mind is the space where experiences arise. The self is an illusion, a story we tell. Equanimity comes from resting as open awareness, not any contents.

Human culture requires imagined selves and purpose. But they disconnect us from our fundamental animal nature. AI may free us from excess words and thoughts.

Stay present. Life's meaning is found in connecting, playing, being curious. Avoid sticking to any narrative or goal too tightly.

The body's wisdom matters most. Balance performance with untethered leisure. Calmly surf uncertainty. Dial agency, arousal and valence for wellbeing.

No experience lasts. Appreciate life's brevity. Share insights when inspired, but don't cling. There's no final destination, just this step, then the next.

Treat yourself and others with gentle curiosity, not judgment. We're all equally mysterious. Kindness matters more than control. Stay grateful.

The mind's complexity arises from simple parts interacting. Pay patient attention. Truth emerges slowly, then disappears into the mist.

 

What we seek to save when we seek to save the world

Yet anoather fascinating set of ideas from Venkatesh Rao that I want to save for myself by doing a MindBlog post of some clips from the piece.

...threats that provoke savior responses are generally more legible than the worlds that the saviors seek to save, or the mechanisms of destruction...I made up a 2x2 to classify the notions of worlds-to-save that people seem to have. The two axes are biological scope and temporal scope...Biolocial scope is the 'we' - the range of livings beings included as subjects in the definition of 'world'...Temporal scope is the range of time over which any act of world-saving seeks to preserve a historical consciousness associated with the biological scope. Worlds exist in time more than they do in space.

Constructing a 2x2 out of the biological and temporal scope dimensions we get the following view of worlds-to-save (blue), with representative savior types (green) who strive to save them.

Deep temporal scope combined with a narrow biological scope gives us civilizations for worlds, ethnocentrists as saviors. ..The End of the World is imagined in collapse-of-civilization terms.

Shallow temporal scope combined with a broad biological scope gives us technological modernity for a world, and cosmopolitans for saviors. A shallow temporal scope does not imply lack of historical imagination or curiosity. It merely means less of history being marked for saving...The End of the World is imagined in terms of rapid loss of scientific knowledge and technological capabilities.

Shallow temporal scope combined with narrow biological scope gives us a world defined by a stable landscape of modern nations...The End of the World is imagined in terms of descent to stateless anarchy. Failure is imagined as a Hobbesian condition of endemic (but not necessarily primitive or ignorant) warfare.

...the most fragile kind of world you can imagine trying to save: one with both a broad biological scope, and a deep temporal scope. This is the world as wildernesses...The End of the World is imagined in terms of ecological devastation and reduction of the planet to conditions incapable of sustaining most life. Failure is imagined in terms of forced extreme adaptation behaviors for the remnants of life. A rather unique version of this kind of world-saving impulse is one that contemplates species-suicide: viewing humans as the threat the world must be saved from. Saving the world in this vision requires eliminating humanity so the world can heal and recover.

I find myself primarily rooting for those in the technological modernity quadrant, and secondarily for those in the wildernesses quadrant. I find myself resisting the entire left half, but I’ve made my peace with their presence on the world-saving stage. I’m a cosmopolitan with Gaian tendencies.

I think, for a candidate world-to-save to be actually worth saving, its history must harbor inexhaustible mysteries. A world whose past is not mysterious has a future that is not interesting. If a world is exhausted of its historical mysteries, biological and/or temporal scope must be expanded to remystify and re-enchant it. This is one reason cosmopolitanism and the world-as-technological-modernity appeal to me. Its history is fundamentally mysterious in a way civilizational or national histories are not. And this is because the historical consciousness of technological modernity is, in my opinion, pre-civilizational in a way that is much closer to natural history than civilization ever gets.

For a cosmopolitan with Gaian tendencies, to save the modern world is to rewild and grow the global web of already slightly wild technological capabilities. Along with all the knowledge and resources — globally distributed in ways that cannot be cleanly factored across nations, civilizations, and other collective narcissisms — that is required to drive that web sustainably. And in the process, perhaps letting notions of civilization — including wishful notions of regulating and governing technology in ‘human centric’ ways — fall by the wayside if they lack the vitality and imagination to accommodate technological modernity

Turing, von Neumann, and the computational architecture of biological machines

I pass on the abstract of a PNAS perspective article by Hashim M. Al-Hashimi (motivated readers can obtain a PDF of the article from me).

In the mid-1930s, the English mathematician and logician Alan Turing invented an imaginary machine which could emulate the process of manipulating finite symbolic configurations by human computers. His machine launched the field of computer science and provided a foundation for the modern-day programmable computer. A decade later, building on Turing’s machine, the American–Hungarian mathematician John von Neumann invented an imaginary self-reproducing machine capable of open-ended evolution. Through his machine, von Neumann answered one of the deepest questions in Biology: Why is it that all living organisms carry a self-description in the form of DNA? The story behind how two pioneers of computer science stumbled on the secret of life many years before the discovery of the DNA double helix is not well known, not even to biologists, and you will not find it in biology textbooks. Yet, the story is just as relevant today as it was eighty years ago: Turing and von Neumann left a blueprint for studying biological systems as if they were computing machines. This approach may hold the key to answering many remaining questions in Biology and could even lead to advances in computer science.

Multilevel cultural evolution - new theory and practical applications

I want to point to a exceptionally lucid and well written expostion by David Sloan Willson et al. and pass on the opening paragraphs of their article that frames the context for understanding how group level selection operates at multiple levels, from cells to societies to the entire earth system. I strongly recommend reading through it slowly and carefully. If that seems a bit much, skip down to the section titled "The earth system as the ultimate unit of selection.'  (added note: for a comprehensive game theoretic analysis of evolutionary dynamics within and among competing groups see Cooney et al.)

Darwin’s theory of evolution is celebrated for its explanatory scope, prompting the geneticist Theodosius Dobzhansky to declare in 1973 that “nothing in biology makes sense except in the light of evolution”. However, what became the “modern synthesis” can also be called the “great constriction.” The study of evolution was confined almost entirely to genetic evolution, relegating the study of human cultural change to other disciplines.

It was not until the 1970s that evolutionary thinkers started to go back to basics by defining natural selection as Darwin did—any process that combines the triad of variation, selection, and replication—irrespective of the proximate mechanisms. The first mathematical models of cultural evolution were based on population genetics models developed 50 y earlier.

Today, the study of cultural evolution in humans and other species is in full swing —and these advances in basic scientific knowledge have practical applications. In this article, we will first review major developments in our basic understanding of human cultural evolution. Then, we will show how they can be applied to a diversity of positive change efforts, no matter what the scale (e.g., from the individual person to global governance) or topic domain. We elaborate for the topics of complex systems science and engineering, economics and business, mental health and well-being, and global change efforts.

Here is the text from the section near the end of the article titled "The earth system as the ultimate unit of selection.' 

The earth system as the ultimate unit of selection.

We have seen that multilevel selection is like a perverse alchemist who turns gold into lead. Self-preservation—a good thing—becomes disruptive selfishness. Helping kith and kin—a good thing—becomes cronyism and nepotism. The welfare of my nation—a good thing—leads to international conflicts. Thriving economies—a good thing—leads to overheating the earth. Nearly everything that is pathological at higher scales can be traced to behaviors that are prosocial at smaller scales.

The only solution to this problem is for policies to be formulated with welfare of the whole-earth system in mind. This is not sufficient by itself, as we will elaborate below, but the basic logic of multilevel selection reveals that it is necessary. There is no invisible hand to permute lower-level interests into higher-level welfare other than our own conscious efforts.

Superficially, it might seem that selection at the planetary scale is impossible because our planet is not competing with any other planets. What makes planet-level selection possible is a decision-making process that makes planetary welfare the target of selection, orients variation around the target, and identifies and replicates better practices, realizing they will be sensitive to context. This is how conscious cultural evolution takes place at smaller scales, as described in the previous sections, and can also take place at the global scale.

The concept of the whole earth as a cooperative system and the primary social identity of an individual was beyond the imagination only a few centuries ago. Nevertheless, when it comes to cultural evolution, the past does not predict the future. Given the myriad forms of globalization that have taken place during the last century, it is difficult not to consider the whole earth as a single system that must transition from CAS2 (“survive”) to CAS1 (“thrive”). Human social groups are nearly always socially constructed. To say “I am first and foremost a human being and citizen of the earth” is no more difficult than to say “I am an American” or “I am a Christian.”

Many people have already adopted a whole-earth ethic, which does manifest as action to a degree—but they do not have a common and authoritative theoretical framework to invoke and from which to derive effective policies. This is in contrast to neoclassical economics and its elaborate mathematical justification of the invisible hand metaphor. Multilevel selection reveals the invisible hand metaphor to be profoundly untrue. It is simply not the case, in economics or any other policy domain, that the lower-level pursuit of self-interest robustly benefits the common good. However, multilevel selection does lead to another, more legitimate conception of the invisible hand metaphor. We must act in two capacities: as designers of whole systems and as participants in the systems that we design. As designers, we must have the welfare of the whole system in mind, which is the opposite of the invisible hand metaphor. As participants, we can indeed respond to our local concerns without having the whole system in mind. Put another way, selection at the level of whole systems is the hand, which winnows the small set of lower-level behaviors that benefit the common good from the much larger set of lower-level behaviors that undermine the common good.

Can a theory of events-in-time - our future history - ever be crafted?

I first drafted this as I usually do to pass on clips that attempt to extract the core points from a fascinating brief piece by Venkatesh Rao.  I then decided to ask Chat GPT 4, Google's bard and Microsoft Bing to "Please condense the core ideas in the following document into a few paragraphs:"  The response from Chat GPT 4 was amazing, so I paste it in here before giving you my clips :

Venkatesh Rao explores the idea of the "End of History" as an analogy to the "End of Biology," where biology transitioned from an independent area of intellectual inquiry to one subservient to the sciences of non-living matter. The End of History could signify a move away from vitalist understandings of the logic of events-in-time. Rao acknowledges that the End of History theory is not widely popular due to its non-constructive nature, as it subverts vitalist understanding of events without providing a parsimonious and generative alternative.

Rao suggests that deeper logics of events-in-time exist in nature, with biological evolution and thermodynamics offering more complex explanations than a mere "one damn thing after another" perspective. He proposes that events-in-time might be viewed as the trace of an irreversible, non-ergodic computation process, with long-term collective memory playing a significant role. History, as we have understood it so far, might be considered a particular memory architecture with a specific irreversible and non-ergodic structure to the evolving computation. This perspective could potentially pave the way for a more refined and deliberate understanding of future events, reducing events-in-time after the End of History to a specialized kind of computation.

Here are my clips that Chat GPT 4 used to generate the above condensation:

What if the Hegel-Fukuyama idea of the End of History is something like Darwin’s idea of natural selection?

The Darwinian century began with The Origin of the Species in 1859 and ended with the discovery of the structure of DNA in 1953. Humanity experienced an End of Biology moment somewhere between those bookend events…a demotion of the discipline from an independent area of intellectual inquiry to one subservient to the sciences of non-living matter…Biology went from being an inscrutable aspect of providence to an emerging engineering discipline, subservient to physics and mathematics by way of chemistry.

By analogy, the End of History moment is something like an end to vitalist understandings of the logic of events-in-time…There is no role for divine agency, and no justification for assigning a particular positive or negative valence to apparent secular tendencies in the stream of events…The fact that the theory is historicist without being normative is perhaps what makes it so powerfully subversive. The End of History theory is the historicism that kills all other historicisms. Past the End of History, notions like progress must be regarded as analogous to notions like élan vital past the End of Biology. …it is undeniable that 30 years in, the End of History theory is still not particularly popular…One obvious reason is that it is non-constructive. It subverts a vitalist understanding of events in time without supplying a more parsimonious and generative alternative.

In Fukuyama’s theory, there are no notions comparable to variation and natural selection that allow us to continue making sense of events-in-time. There are no Mendelian clues pointing to something like a genetics of events-in-time. There is no latent Asimovian psychohistorical technology lurking in the details of the End of History theory…Perhaps one damn thing after another is where our understanding of events in time ought to end, for our own good.

I think this is too pessimistic though. Deeper logics of events-in-time abound in nature. Even biological evolution and thermodynamics, which are more elemental process aspects of reality, admit more than a one damn thing after another reading. History, as a narrower class of supervening phenomena that must respect the grammars of both, ought to admit more interesting readings, based on broadly explanatory laws that are consistent with both, but more specific than either. Dawkins’ memetic view of cultural evolution, and various flavors of social darwinism, constitute first-order attempts at such laws. Some flavors of cosmism and transhumanism constitute more complex attempts that offer hope of wresting ever-greater agency from the universe.

So what does explain the logic of events-in-time in a way that allows us to make sense of events-in-time past the End of History, in a way that improves upon a useless one damn thing after another sense of it, and says something more than the laws of evolution or thermodynamics?

I don’t have an answer, but I have a promising clue: somehow, events-in-time must be viewed as the trace of an irreversible, non-ergodic computation process, in which long-term collective memory plays a significant role.

History, as we have understood it so far, is something like a particular memory architecture that assumes a particular irreversible and non-ergodic structure to the evolving computation. The contingency and path dependence of events-in-time in human affairs is no reason to believe there cannot also be theoretical richness within the specificity. A richness that might open up futures that can be finely crafted with a psychohistorical deliberateness, rather than simply vaguely anticipated and crudely shaped. 

Perhaps, just as life after the End of Biology was reduced to a specialized kind of chemistry, events-in-time, after the End of History, can be reduced to a specialized kind of computation.

The fundamentals of empathy

Akinrinade et al. show that the neuropeptide oxytocin is responsible for emotional fear contagion, and involves the same regions of the brain in zebrafish and in mammals, suggesting this most basal form of empathy could have evolved many, many millions of years ago.

Emotional contagion is the most ancestral form of empathy. We tested to what extent the proximate mechanisms of emotional contagion are evolutionarily conserved by assessing the role of oxytocin, known to regulate empathic behaviors in mammals, in social fear contagion in zebrafish. Using oxytocin and oxytocin receptor mutants, we show that oxytocin is both necessary and sufficient for observer zebrafish to imitate the distressed behavior of conspecific demonstrators. The brain regions associated with emotional contagion in zebrafish are homologous to those involved in the same process in rodents (e.g., striatum, lateral septum), receiving direct projections from oxytocinergic neurons located in the pre-optic area. Together, our results support an evolutionary conserved role for oxytocin as a key regulator of basic empathic behaviors across vertebrates.

Humans are more than AI machines - OpenAI's chatGPT edits a MindBlog preliminary draft

I am feeling majorly freaked out now. .. I asked ChatGPT to improve one of the draft paragraphs that I mentioned in this past Tuesday's post. 

My request to ChatGPT: 

Please make improvements to the following draft of a blog post: 

We humans are AI machines. As with the nerve networks of GPT-4, our developing neuronal connections in the embryo are reinforced by learning correlations that link, sensory and motor capabilities. What we have that is missing in the silicon and metal nerve nets of large language models is a developmental history and memory of physical movement in a rich, chemical and physical environment interacting with the genetic developmental program that evolved over millions of years through variation and selection - we are Darwin machines that function in a much richer environment that current AI implementations. There is no reason in principle that we could not begin to construct a machine based on silicon and other elements than carbon, that does not depend on our current energy cycles fueled by the sun, oxygen, and carbon dioxide. Such a machine might develop, as we do, by moving through and developing a history in a distinctive physical and chemical environment.

The response from ChatGPT:

Here is an improved version of the draft blog post: 

Humans Are More Than AI Machines As artificial intelligence (AI) continues to evolve, it's easy to see the similarities between our cognitive processes and those of machines like GPT-4. However, while our developing neuronal connections in the embryo are reinforced by learning correlations that link sensory and motor capabilities, what sets us apart from silicon and metal nerve nets is our developmental history and memory of physical movement in a rich, chemical, and physical environment. 

Unlike machines, we are Darwin machines that function in a much richer environment that current AI implementations. Our genetic developmental program has evolved over millions of years through variation and selection, giving us a unique ability to adapt to our surroundings. We have a developmental history and memory of physical movement in a rich, chemical, and physical environment that has helped shape us into the complex beings we are today. 

There is no reason in principle that we could not begin to construct a machine based on silicon and other elements than carbon, that does not depend on our current energy cycles fueled by the sun, oxygen, and carbon dioxide. However, it's important to note that such a machine would need to develop, as we do, by moving through and developing a history in a distinctive physical and chemical environment. Without this, it may be impossible to replicate the complexity of our cognitive processes and our unique ability to adapt to our environment. 

In conclusion, while our cognitive processes share similarities with AI machines like GPT-4, we are much more than that. Our developmental history and memory of physical movement in a rich, chemical, and physical environment have shaped us into the complex beings we are today. As we continue to explore the possibilities of artificial intelligence, it's important to remember that there may be certain aspects of our cognitive processes that cannot be replicated in machines. 

When I ask ChatGPT to regenerate the response,  it does a better job with the beginning of the draft and has a more inspirational conclusion - a synthesis of the two versions would work best:

Here's a second improved version of the draft blog post:

Humans are often referred to as "AI machines," as our developing neuronal connections in the embryo are reinforced by learning correlations that link sensory and motor capabilities, much like the nerve networks of GPT-4. However, what sets us apart from large language models is our rich developmental history and memory of physical movement in a complex chemical and physical environment, which interacts with the genetic developmental program that evolved over millions of years through variation and selection. We are "Darwin machines" that function in a much richer environment than current AI implementations.

While current AI implementations are limited by their lack of a developmental history and memory of physical movement, there is no reason in principle that we could not construct a machine based on silicon and other elements than carbon. Such a machine could potentially develop, as we do, by moving through and developing a history in a distinctive physical and chemical environment.

However, it is important to note that our current energy cycles are fueled by the sun, oxygen, and carbon dioxide, which have been instrumental in our development as a species. As we continue to explore the possibilities of AI and machine learning, we must be mindful of the unique characteristics that make us human and strive to incorporate them into any machine-based systems we develop. Only then can we truly achieve the potential of AI as a tool for human progress.

 

Note: Microsoft Bing's performance in the above  task was much less impressive, not as useful.

The road to our larger brains

Bertrand et al. address the question of how and why mammals evolved large brain sizes relative to their body mass by characterizing the timing and pattern of mammal brain development across the Early Jurassic to the middle Cenozoic (∼200 million to 30 million years ago) when the ecological niches vacated by the extinction of large reptiles were being filled by large mammals. Here is their abstract:

Mammals are the most encephalized vertebrates, with the largest brains relative to body size. Placental mammals have particularly enlarged brains, with expanded neocortices for sensory integration, the origins of which are unclear. We used computed tomography scans of newly discovered Paleocene fossils to show that contrary to the convention that mammal brains have steadily enlarged over time, early placentals initially decreased their relative brain sizes because body mass increased at a faster rate. Later in the Eocene, multiple crown lineages independently acquired highly encephalized brains through marked growth in sensory regions. We argue that the placental radiation initially emphasized increases in body size as extinction survivors filled vacant niches. Brains eventually became larger as ecosystems saturated and competition intensified.

Evolutionary models of financial markets.

Levin and Lo's introduction of a PNAS special issue on evolutionary models of financial markets is an interesting read. A few clips:

The brilliant evolutionary insights of Darwin and others have revolutionized our understanding of the world. Darwin was impressed by the “tangled bank” of elaborate forms that emerged from the undirected processes of evolution to produce the complexity of the biological world. Through continuous innovation coupled with the deceptively simple filter known as natural selection, the characteristics of species and their interactions change in response to changing environments. However, evolution is not limited only to the biological world. Wherever the evolutionary forces of reproduction, variation, and selection exist—as they do in financial markets—evolutionary consequences will follow. There are of course major differences as well between the nature of the evolutionary process in ecological and economic contexts, largely influenced by the relative importance of top-down control, and the degree to which predictive models and long-term planning can be invoked. These are, however, differences of degree.

There are profound similarities between financial systems and the biosphere. Both are complex adaptive systems in which individual agents act to enhance their own interests and objectives, leading to self-organization and emergent features. In viewing global financial markets as comprising a complex-adaptive biological system, researchers in this area intend to develop more effective models to understand these systems. This is not only of theoretical interest, but also has the practical aim to promote economic growth while maintaining financial stability, with the ultimate goal of allocating resources more efficiently through better financial methods.

Evolution is about short-term, relative optimality with respect to other participants in the system. In the biosphere, natural selection acts to improve reproductive success relative to the benchmark of other genomes, within and across species. Evolutionary change can thus be thought of in terms of differential fitness: that is, small differences in reproductive rates between individuals over time leading to large differences in populations. Even the very mechanisms of evolution—including those that generate new variation—are subject to constant modification. In the financial world, the evolutionary forces of mutation, recombination, reproduction, and selection often work on financial institutions and market participants through direct competition, finance “red in tooth and claw.” Financial concepts and strategies thus reproduce themselves through cultural transmission and adoption based on their success in the marketplace. These strategies undergo variation through financial innovation, analogous to mutation or genetic recombination in a biological system, but take place at the level of information and abstract thought in financial contexts. It is “survival of the richest.”

The evolutionary lens provides a natural way to introduce biological concepts into financial and economic analysis. As the evolutionary biologist Theodosius Dobzhansky said, “Nothing in biology makes sense except in the light of evolution” (5). The same may hold for the financial world. Phenomena that have been difficult to analyze within a traditional economic framework, such as growth, size, scale, self-organization, the lifecycle of products and industries, bull/bear market cycles, and the rate of variation or innovation within a system, are all subject to evolutionary forces, whether they take place in the Petri dish or on the trading floor. Biological experiments thus may be able to directly inform economic insights, and market behavior may be able to shed light on evolutionary mysteries in the biological world.

Evidence that monkeys have conscious awareness of self - they know what they saw.

Ben-Haim et al. Disentangle perceptual awareness from nonconscious processing in rhesus monkeys  

Significance

Many animals perform complex intelligent behaviors, but the question of whether animals are aware while doing so remains a long debated but unanswered question. Here, we develop a new approach to assess whether nonhuman animals have awareness by utilizing a well-known double dissociation of visual awareness—cases in which people behave in completely opposite ways when stimuli are processed consciously versus nonconsciously. Using this method, we found that a nonhuman species—the rhesus monkey—exhibits the very same behavioral signature of both nonconscious and conscious processing. This opposite double dissociation of awareness firstly allows stripping away the long inherent ambiguity when interpreting the processes governing animal behavior. Collectively, it provides robust support for two distinct awareness modes in nonhuman animals.

Abstract

Scholars have long debated whether animals, which display impressive intelligent behaviors, are consciously aware or not. Yet, because many complex human behaviors and high-level functions can be performed without conscious awareness, it was long considered impossible to untangle whether animals are aware or just conditionally or nonconsciously behaving. Here, we developed an empirical approach to address this question. We harnessed a well-established cross-over double dissociation between nonconscious and conscious processing, in which people perform in completely opposite ways when they are aware of stimuli versus when they are not. To date, no one has explored if similar performance dissociations exist in a nonhuman species. In a series of seven experiments, we first established these signatures in humans using both known and newly developed nonverbal double-dissociation tasks and then identified similar signatures in rhesus monkeys (Macaca mulatta). These results provide robust evidence for two distinct modes of processing in nonhuman primates. This empirical approach makes it feasible to disentangle conscious visual awareness from nonconscious processing in nonhuman species; hence, it can be used to strip away ambiguity when exploring the processes governing intelligent behavior across the animal kingdom. Taken together, these results strongly support the existence of both nonconscious processing as well as functional human-like visual awareness in nonhuman animals.

(Note: Establishing double dissociation of awareness used a nonverbal spatial-cueing paradigm. Motivated readers can email me to obtain a PDF of the article which describes this paradigm.)

The case against reality

Over the past year I've dipped into and out of Donald Hoffman's ideas several times, looking back at Geffer's article in Granta Magazine, Hoffman's TED talk, and sections of his 2019 book "The Case Against Reality: Why Evolution Hid the Truth from Our Eyes." Mainly for my future reference (I forget things, and use my MindBlog posts to go back and look them up), I'm attempting to put down the bare bones of his arguments with a selection of clips from these various sources.

As we go about our daily lives, we tend to assume that our perceptions — sights, sounds, textures, tastes — are an accurate portrayal of the real world...If they were not, wouldn’t evolution have weeded us out by now?...This hunch is wrong. On the contrary, our perceptions of snakes and apples, and even of space and time, do not reveal objective reality...It is a theorem of evolution by natural selection that wallops our hunches.

Does natural selection really favor seeing reality as it is? Fortunately, we don't have to wave our hands and guess; evolution is a mathematically precise theory. We can use the equations of evolution to check this out. We can have various organisms in artificial worlds compete and see which survive and which thrive, which sensory systems are more fit. A key notion in those equations is fitness...Fitness is not the same thing as reality as it is, and it's fitness, and not reality as it is, that figures centrally in the equations of evolution... we have run hundreds of thousands of evolutionary game simulations with lots of different randomly chosen worlds and organisms that compete for resources in those worlds. Some of the organisms see all of the reality, others see just part of the reality, and some see none of the reality, only fitness. Who wins? ...perception of reality goes extinct. In almost every simulation, organisms that see none of reality but are just tuned to fitness drive to extinction all the organisms that perceive reality as it is. So the bottom line is, evolution does not favor veridical, or accurate perceptions. Those perceptions of reality go extinct. Fitness beats truth (This is the "FBT theorem").

A metaphor can help our intuitions. Suppose you’re writing an email, and the icon for its file is blue, rectangular, and in the center of your desktop. Does this mean that the file itself is blue, rectangular, and in the center of your computer? Of course not...The purpose of a desktop interface is not to show you the “truth” of the computer—where “truth," in this metaphor, refers to circuits, voltages, and layers of software. Rather, the purpose of an interface is to hide the “truth” and to show simple graphics that help you perform useful tasks such as crafting emails and editing photos. If you had to toggle voltages to craft an email, your friends would never hear from you. That is what evolution has done. It has endowed us with senses that hide the truth and display the simple icons we need to survive long enough to raise offspring... Perception is not a window on objective reality. It is an interface that hides objective reality behind a veil of helpful icons...Evolution has shaped our senses to keep us alive. We have to take them seriously: if you see a speeding Maserati, don’t leap in front of it; if you see a moldy apple, don’t eat it. But it is a mistake of logic to assume that if we must take our senses seriously then we are required—or even entitled—to take them literally.

We used to think that the Earth is flat because it looks that way. Then we thought that the Earth is the unmoving center of reality because it looks that way. We were wrong. We had misinterpreted our perceptions. Now we believe that spacetime and objects are the nature of reality as it is. The theory of evolution is telling us that once again, we're wrong. We're misinterpreting the content of our perceptual experiences. There's something that exists when you don't look, but it's not spacetime and physical objects. It's...hard for us to let go of spacetime and objects...we're blind to our own blindnesses...By peering through the lens of a telescope we discovered that the Earth is not the unmoving center of reality, and by peering through the lens of the theory of evolution we discovered that spacetime and objects are not the nature of reality. When I have a perceptual experience that I describe as a red tomato, I am interacting with reality, but that reality is not a red tomato and is nothing like a red tomato...And here's the kicker: When I have a perceptual experience that I describe as a brain, or neurons, I am interacting with reality, but that reality is not a brain or neurons and is nothing like a brain or neurons. And that reality, whatever it is, is the real source of cause and effect in the world -- not brains, not neurons. Brains and neurons have no causal powers. They cause none of our perceptual experiences, and none of our behavior. Brains and neurons are a species-specific set of symbols, a hack.

Sexiest birds on the planet - Manakins have the best moves

Elizabeth Pennisi describes reports from a recent virtual meeting of the Society for Integrative and Comparative Biology on the genetic underpinnings of the elaborate plumage and dance displays of Ecuador's club winged manakin, products of sexual selection:

For a glimpse of the power of sexual selection, the dance of the golden-collared manakin is hard to beat. They court with their flashy plumage, loud wing clapping, and acrobatic leaps and twists to gain the fussy female's favor. (As biologists have understood since Charles Darwin, such exhibitionism evolves when females choose to mate with males that have the most extravagant appearances and displays—a proxy for fitness.) Now, by studying the genomes of the golden-collared manakin (Manacus vitellinus) and its relatives, researchers are exploring the genes that drive these elaborate behaviors and traits. With four manakin genomes, and two already published, researchers are now able to describe the genetic underpinnings behind some of the birds' displays. In addition, by mapping traits and genes onto the manakin family tree, researchers are beginning to trace the stepwise genetic changes that led to the most elaborate displays and determine whether sexual selection works differently from natural selection.

You've gotta watch this - A billion year journey of Earth's tectonic plates

The article by Andrews in the New York Times describes the history of tectonic plate theory and brings into vivid focus how us humans are just a transient eye blink in the history of our planet. I pass on a YouTube version of the fascinating animation in the article:

 

Evidence that aerobic exercise reverses aging.

Brett et al. show (in mice) that aerobic exercise rejuvenates quiescent skeletal muscle stem cells in old mice and accelerates muscle tissue repair:

Ageing impairs tissue repair. This defect is pronounced in skeletal muscle, whose regeneration by muscle stem cells (MuSCs) is robust in young-adult animals, but inefficient in older organisms. Despite this functional decline, old MuSCs are amenable to rejuvenation through strategies that improve the systemic milieu, such as heterochronic parabiosis [i.e. connecting the circulatory systems of young and old mice). One such strategy, exercise, has long been appreciated for its benefits on healthspan, but its effects on aged stem-cell function in the context of tissue regeneration are incompletely understood. Here, we show that exercise in the form of voluntary wheel running accelerates muscle repair in old mice and improves old MuSC function. Through transcriptional profiling and genetic studies, we discovered that the restoration of old MuSC activation ability hinges on restoration of Cyclin D1, whose expression declines with age in MuSCs. Pharmacologic studies revealed that Cyclin D1 maintains MuSC activation capacity by repressing TGF-β signalling. Taken together, these studies demonstrate that voluntary exercise is a practicable intervention for old MuSC rejuvenation. Furthermore, this work highlights the distinct role of Cyclin D1 in stem-cell quiescence.

Great graphics - a review of cerebral cortex structure/folding from mice to humans.

I pass on this open source review article for the small number of MindBlog readers who might find it useful in their teaching. The summary color graphics of increasingly larger vertebrate brains (Mouse, Marmosett, Macaque, Chimpanzee, Human) show overall appearance and cell number, myelin patterns, and cortical parcellations. Here is the technical abstract:

Advances in neuroimaging and neuroanatomy have yielded major insights concerning fundamental principles of cortical organization and evolution, thus speaking to how well different species serve as models for human brain function in health and disease. Here, we focus on cortical folding, parcellation, and connectivity in mice, marmosets, macaques, and humans. Cortical folding patterns vary dramatically across species, and individual variability in cortical folding increases with cortical surface area. Such issues are best analyzed using surface-based approaches that respect the topology of the cortical sheet. Many aspects of cortical organization can be revealed using 1 type of information (modality) at a time, such as maps of cortical myelin content. However, accurate delineation of the entire mosaic of cortical areas requires a multimodal approach using information about function, architecture, connectivity, and topographic organization. Comparisons across the 4 aforementioned species reveal dramatic differences in the total number and arrangement of cortical areas, particularly between rodents and primates. Hemispheric variability and bilateral asymmetry are most pronounced in humans, which we evaluated using a high-quality multimodal parcellation of hundreds of individuals. Asymmetries include modest differences in areal size but not in areal identity. Analyses of cortical connectivity using anatomical tracers reveal highly distributed connectivity and a wide range of connection weights in monkeys and mice; indirect measures using functional MRI suggest a similar pattern in humans. Altogether, a multifaceted but integrated approach to exploring cortical organization in primate and nonprimate species provides complementary advantages and perspectives.

Same-Sex behavior in animals - a new view.

Monk et al. offer a fresh perspective on the "problem" of how same-sex sexual behavior could have evolved. It is a problem only if different-sex sexual behavior is the baseline condition for animals, from which single-sex behavior has evolved. The authors suggest that same-sex behavior is bound up in the very origins of animal sex. It hasn’t had to continually re-evolve: It’s always been there. The arguments of Monk and collaborators are summarized in a review by Elbein:

Instead of wondering why same-sex behavior had independently evolved in so many species, Ms. Monk and her colleagues suggest that it may have been present in the oldest parts of the animal family tree. The earliest sexually reproducing animals may have mated with any other individual they came across, regardless of sex. Such reproductive strategies are still practiced today by hermaphroditic species, like snails, and species that don’t appear to differentiate, like sea urchins.

Over time, Ms. Monk said, sexual signals evolved — different sizes, colors, anatomical features and behaviors — allowing different sexes to more accurately target each other for reproduction. But same-sex behavior continued in some organisms, leading to diverse sexual behaviors and strategies across the animal kingdom. And while same-sex behavior may grant some evolutionary benefits, an ancient origin would mean those benefits weren’t required for it to exist.

But how has same-sex behavior stuck around? The answer may be that such behaviors aren’t as evolutionarily costly as assumed. Traditionally, Ms. Monk said, any mating behavior that doesn’t produce young is seen as a waste. But animal behavior often doesn’t fit neatly into an economic accounting of costs and benefits.

Here is the abstract of Monk et al.:

Same-sex sexual behaviour (SSB) has been recorded in over 1,500 animal species with a widespread distribution across most major clades. Evolutionary biologists have long sought to uncover the adaptive origins of ‘homosexual behaviour’ in an attempt to resolve this apparent Darwinian paradox: how has SSB repeatedly evolved and persisted despite its presumed fitness costs? This question implicitly assumes that ‘heterosexual’ or exclusive different-sex sexual behaviour (DSB) is the baseline condition for animals, from which SSB has evolved. We question the idea that SSB necessarily presents an evolutionary conundrum, and suggest that the literature includes unchecked assumptions regarding the costs, benefits and origins of SSB. Instead, we offer an alternative null hypothesis for the evolutionary origin of SSB that, through a subtle shift in perspective, moves away from the expectation that the origin and maintenance of SSB is a problem in need of a solution. We argue that the frequently implicit assumption of DSB as ancestral has not been rigorously examined, and instead hypothesize an ancestral condition of indiscriminate sexual behaviours directed towards all sexes. By shifting the lens through which we study animal sexual behaviour, we can more fruitfully examine the evolutionary history of diverse sexual strategies.