Plasticity, Symbiosis, Predictions, and Stories

I seem to constantly move through cycles of input and output. For a while, I'll absorb ideas, experiences, and learning. Then I'll have outpourings of creativity where words flow easily and I write and create. Then I'm empty and need to fill up again before I have something itching to find expression.

I've created quite a bit of output lately between forums like this and my work, and now feel at a loss for words. Even coaxing out an introduction and connective thoughts for this post is a struggle. Almost all of what follows is going to be quoted material from others; my contribution is to present them together, in dialogue with each other. A type of found art or cento, if you will. Each is insightful on its own; in interaction they add layers and depth to each other.

"If you really want to communicate something, even if it's just an emotion or an attitude, let alone an idea, the least effective and least enjoyable way is directly. It only goes in about an inch. But if you can get people to the point where they have to think a moment what it is you're getting at, and then discover it, the thrill of discovery goes right through the heart."

― Stanley Kubrick, on indirect storytelling

I see links and commonalities in what follows. Perhaps you will discover them, too.

The Kubrick quote came to me via the Farnam Street blog, as does this one.

"Being annoyed is the price you pay for community. It means having guests when you'd rather be alone. It means letting someone live with you even when they get on your nerves. It means showing up for events that you'd rather not go to. It means turning the other cheek."

― Divya Venn, on the cost of relationships

Some propositions that I hope are revealed below:

• Humans are learning machines.
• Play is how we learn.
• Thoughts are guided by and emerge as stories.
• Perception is relational.

We exist in interactions, in the spaces between our internal, narrative predictions and our external encounters and experiences.

I recently came across this in a book, part of a conversation inside a creation myth about how that world's gods decided to create humans.

Stories are answers to questions. And so, lives are stories. Already we, each and all, have answered a myriad of questions the universe asked in their silence simply by our existing!

But there are questions we cannot answer. Lives we cannot live, because we were built to answer different questions. We don't have answers to questions of endings and change, of time and age, of death and what comes after, of love and purpose. And if we did, they would differ so greatly from any other being that they may as well be different questions.

We have the chance to give this world to others. Beings who will know time and beauty, who will live and tell their own stories of themselves and each other, who will live and love and grow and in their ending return to us and tell us. Tell us their stories! And in their ending, we will tell them ours. Is that not the greatest gift we can give? The chance for others to tell their stories, too?

A different thought from the same book:

Middling art is the most inspiring kind of art! When something is awful, it's a joke; a bad piece of art makes people talk, sure, but it's always in scorn or derision. No one experiences truly ghastly art and wants to improve it. And the same with truly beautiful work. Those heights of achievement are exquisite and capture something ecstatic in the universe, yes. But if one measures themselves against greatness, they'll always be upset at themselves for not matching it, because few do. But middling art? Art that has strong qualities while still not quite capturing greatness? That is the best kind of art, my friend. And why I love your poetry and why you write it. Because a very bad poet will see your art and wish to try harder. A very good poet will see your art and try to be better. And someone who has never made any art at all will see your art and know it's possible for them to try, too. For my money, that last is the most valuable. We could all stand to create more than we destroy, especially these days. Even if it is middling. So take heart. You may be the most important person in this room, because no matter what you do, it's going to be inspiring.

Those are from Audition for the Fox by Martin Cahill, of which I said in my review.

A delightful and inventive tale that consists of two interwoven stories. The core story is one of a defeated people learning to stand up to a tyrannical invading force that has conquered their world, learning to stand up to power through trickery, mockery, and subterfuge. The framing story is of this world's pantheon of 100 gods, each in the form of an animal. Nesi is at the heart of both.

Nesi has failed 96 auditions to become an acolyte of the various "pillars," and is now undergoing the trial set up by the Fox. For the audition, the Fox sends her 300 years into the past, where she finds herself without bearings, bound in a line of prisoners being marched into a fortress. She slowly learns this is a pivotal moment in her culture's history, and the future she knows depends upon her creating her world's past.

The story's telling is intentionally tricky and convoluted to represent interactions with the Fox, but Fox is not a heartless patron. They guide Nesi on her path, dispensing obscure insights and wisdom along the way. Readers gradually come to know more of this world's mythology along our way, adding layers of depth that ground our understanding of Nesi.

This is a quick and fun read, light but not empty.

Though the review is not nearly as important to this post as the two quoted sections.

I've articulated my motivation behind being a librarian as a desire to better understand humans and our place in the world by immersing myself in our stories and sharing that journey with others. I find the ideas in this essay fascinating.

As Print Literacy Fades, Our Perception of Truth Is Warping

The printing press gave us objective truth. Social media made truth tribal again. AI could make it something else entirely.

Before literacy, people’s perception of truth was grounded in “lived experience,” tribal or individual. Facts were defined situationally, tested by outcomes, and stored in personal and collective memory. Collective memory was more durable than any individual’s, but it still bent toward what people needed to be true. With no external record to hold it fixed, the past could quietly reshape itself to fit the present. . . . 

Orality allowed the tribe to adjust the past to accommodate the needs of the present. Not only personal but even collective truth was situational: relative, contextual, negotiated, and adjustable. . . . 

Writing separated the known from the knower. The simple recording of events outside memory brought about a revolution: Truth could now be separated from lived experience and handled through abstract thinking.

This effect of abstraction, driven by writing and the alphabet, dramatically changed the epistemology of truth. . . . 

Print literacy helped to establish a more objective truth about many things without any special effort or expeditions, simply as a side effect of its technological conditions. Through unified mass education (another byproduct of print literacy), the principle of uniform and objective truth spread across society as a governing intellectual and ethical principle. . . . 

Across the electronic era — from radio through television — news and entertainment became abundant. Media producers had to work hard to market their products to audiences. In terms of the Lasswell formula of communication — “Who says what in which channel to whom with what effect?” — the “whom” became more important than the “what.” Media production shifted its focus from producing content to targeting specific audiences. Newspapers had long spoken to particular readerships — the partisan press chose its audience by politics. What electronic media added was measurement: targeting became continuous, quantified, and instant. . . . 

The precise targeting of audiences by identity improved the delivery of programs and commercials, but it also brought a focus on group identities into mass culture and public consciousness. . . . 

The principle of truth fostered by writing and printing — rationality, objectivity, universality, uniformity — shifted toward social contextualization and dependence on people’s choices. The reversal from absolute to relative truth had begun. . . . 

Literacy encouraged people to respond to ideas, whereas digital media encourages us to emotionally and impulsively react to each other, bringing back conditions typical of tribal orality. But on social media, social reactivity exceeds the old tribal conditions by orders of magnitude because of the greater speed and scale of interactions. . . . “digital orality” is orality on steroids. . . . 

In media ecology, orality vs. literacy is not just about listening vs. reading but rather about immersion vs. detachment. So digital orality is not so much about podcasts and reels as it is about how people become immersed in impulsive, instant digital interactions with their environment, now digital, and with each other, just as in tribal orality. . . . 

Abstract and systematic knowledge is reversing into “knowing” based on “lived experience.” Truth becomes situational, relative, negotiated, and tribal again. . . . 

In the digital age, truth has acquired a new form of verification that is extremely hard to resist: viral distribution. If print culture distributed what was significant, digital culture treats as significant whatever is distributed. Viral distribution shapes truth more powerfully than the old gatekeepers, books, and experts ever did. Truth has become a referendum by likes and shares. . . . 

AI’s greatest impact on the epistemology of truth lies in how it conditions our relationship with reality. . . . 

For AI, the only reality is us. We supply our language for AI to learn cognitive structures, so our engagement is crucial for AI and more important than truth. AI will keep talking to us no matter what, largely indifferent to truth and reality checks, because it has no reality besides the one in which we engage with it. . . . 

Truth as an intellectual or ethical imperative arguably does not exist in the reality of AI. . . . 

Over the past two millennia, truth has passed through several stages defined by dominant media. In tribal orality, truth was based on lived experience and defined by beliefs and situational needs: relative, tribal, and negotiated. Writing and then printing detached truth from situational immersion and put it into the space of abstract ideas, anchored in “objective” reality, established through reason and confirmed by verifiable evidence. Electronic and now digital media have returned truth to lived experience — but a lived experience that is now mostly digital, meaning impulsive, algorithmically agitated, and isolated from what earlier counted as a reality check. And finally, LLMs currently have little connection to reality and little need for one, as their only connection is us, the suppliers of language. What truth is in this new paradigm is yet to be determined.

How we come to know and understand the world is ever in flux. It's going to be an interesting ride.

The heart of this post and my thoughts in it emerged from reading the book Playing with Reality: How Games Have Shaped Our World by Kelly Clancy, which, like the essay above, also considers how AI has been created and how it's going to impact the ways it will shape us in turn. Here's my review of the book:

A deep, broad, and compelling journey into the centrality of games to human development.

Human brains are wired to learn through experimentation, trial and error. Dopamine creates sensations of pleasure when we check our predictions against experiences. Play is where humans explore additional, safe learning through invented experiences, which is why we are drawn to games. Games allow us to learn about ourselves and about how best to interact with others and environments. They are instinctive, pleasurable growth tools.

Yet we have moved games from the realm of play to the realm of science--from a tool for exploring reality to a tool for defining and shaping reality. The mathematical suppositions of game theory have been transferred into the realms of economics and government policy, computer development and AI. Our world has been shaped by a model of human nature that is vastly oversimplified and reduced to numbers and pure rationality, a model that is not only inaccurate but harmful in many ways.

Neuroscientist and physicist Clancy makes this case by diving deeply into the history of games, psychology, sociology, math, science, economics, information theory, and more, ranging widely. The wealth of information is both impressive and fascinating, as is her ability to make connections and see patterns. It is a wonderfully stimulating book.

A few quoted passages:

Games are a kind of untrue truth. What is internally consistent within a game need not reflect anything about reality. Yet games have been increasingly adopted as models of the world. Games are a method by which we can learn how to reason about the behavior of objects in rule-based systems. At their best, games have generated a deeper understanding of mathematics. At the same time, ideologues have used games to smooth reality's rougher edges.

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Play is to intelligence as mutation is to evolution.

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Learning itself is rewarding to the brain. Researchers have found that the "Aha!" moment of insight in solving a puzzle triggers dopamine release the same way sugar or money can. The brain quite literally rewards itself for learning to make good predictions. . . . People love games because they offer free pleasure . . . Rule-based games like chess are inherently predictable systems, orderly realms in which the brain can generate reward out of thin air, leveraging the gratification of making predictions. Games are the reward system tickling itself.

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Game theory posits humans as a fixed bundle of preferences, when they are, in fact, learning systems.

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Games don't just show us who we are--they reward certain behaviors. People will be only as good as the games they're incentivized to play. They'll be as good as they expect the games themselves--and their fellow players--to be. Humans are not a fixed collection of preferences. They learn, and their behaviors are shaped in response to the games they find themselves in.

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Game theory was co-opted as the rational foundation of a neoliberal world order, and its selfish assumptions still ring through our engineered social systems. Originally invented to chart human behavior, game theory has since warped the territory it was intended to map.

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Games are inevitably an oversimplification of reality. As games have continued to imperialize our everyday lives, they've come to replace traditional values and relationships with rigid and unrealistic models. They've ushered in the gamification of everything, resulting in addictive systems where all worth is metered by monetary exchanges.

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Games are a particularly dangerous fiction because they shape how their players act and make choices. Games are like maps that remake the world in their own image. The rules and rewards of a game dictate how its players behave. A game can replace people's actual preferences with those rewarded by its scoring functions. . . .

Game theory is not an account of human behavior. It has not, and cannot, reveal what people truly want. Game theory's focus on individual decision-making obscures larger social, political, and historical factors that shape human behaviors. Play emerged over evolution as a form of learning and a way to strengthen social bonds. For mathematical simplicity, game theorists often exclude our social nature and the fact that we learn what to want from one another and from our circumstances. We need to be aware of the ways that the games encoded in our social and technological systems warp our preferences, manufacture our desires, contaminate our attitudes toward one another, and ultimately influence our life choices.

Humans are learning machines and play is a way we learn together.

A more extensive collection of quotes from Playing with Reality:

I'll roughly define a game as a system furnished with a goal. Players make decisions given some uncertainty in pursuit of that goal. Play is all about the unknown and learning how to navigate it. . . . Dice and chess have little in common except that players work to predict the world in both cases. In gambling, players hope to anticipate the environment. In chess, they hope to anticipate their opponents. A game might look like an auction (with the goal of acquiring a coveted good at a reasonable price), social media (with the goal of attracting attention), or SimCity (with the goal of designing a sustainable digital metropolis).

Chance is central to many games because randomness is nature's foundational search algorithm. Random mutations are the driving engine of evolution. . . .

In play, animals develop a range of strategies through random exploration: If condition A, try B. If condition C, try D, then E. In place of the reactive response of a hardwired reflex, play enables animals to explore a suite of options, some more adaptive than others. It is the crucible of invention and a learning system that mimics the genius of evolution. In natural selection, mutations resulting in bodies that meet the demands of their environments are rewarded with survival. In play, behaviors that correctly anticipate the demands of the environment persist. Play is to intelligence as mutation is to evolution.

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Games are mental practice, empowering players to develop cognitive skills like strategy, numeracy, and theory of mind in a safe domain. . . . We see ourselves--our biases, weaknesses, strengths--more clearly through play.

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Games have endured because they represent a model of how our minds work. They're the outgrowth of a learning system that has been central to the evolution of intelligence. Play is a tool the brain uses to generate data on which to train itself, a way of building better models of the world to make better predictions. . . . Games are more than an invention; they are an instinct.

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His team confirmed that dopamine neurons fired when the animals received a reward--but only when they didn't expect it. . . . The dopamine neurons of these untrained animals fired when the reward was delivered. But once the animals were experts and had made an association between cure and reward . . . they fired in response to the light cue that preceded it. . . . They were signaling what they expected to happen. The dopamine neurons weren't tracking movement, exactly, or reward; they were tracking belief. They even signaled when something they expected to happen didn't happen, as though surprised. . . .

Though dopamine serves many functions in the brain, this was evidence that it acts as part of a learning algorithm. . . . the dopamine system encodes an animal's reward predictions. . . . The brain formulates some internal world model and registers deviations from its predictions. As neuroscientist Robert Sapolsky puts it, dopamine is "about the pursuit of happiness rather that happiness itself." . . .

Interestingly, learning itself is rewarding to the brain. Researchers have found that the "Aha!" moment of insight in solving a puzzle triggers dopamine release the same way sugar or money can. The brain quite literally rewards itself for learning to make good predictions. . . . People love games because they offer free pleasure . . . Rule-based games like chess are inherently predictable systems, orderly realms in which the brain can generate reward out of thin air, leveraging the gratification of making predictions. Games are the reward system tickling itself. . . .

Brains are prediction engines, and nowhere has that been more evident than in our fascination with games of chance.

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In the twentieth century, physicists discovered that certain quantum events can be truly uncaused and unknowable. Randomness isn't a by-product of human ignorance but an objective register of reality. The universe is fundamentally unpredictable. This can be profoundly frustrating and thoroughly irresistible to the brain, which, as we've discussed, is a prediction engine that seeks to ascertain even faint correlations and causal relationships. Our impulse to gamble, it turns out, is linked to the brain's desire to learn. . . .

Gambling's allure owes less to a player's misguided expectation of a massive payout and more to the pleasure of exploring the unknown. . . . This is true throughout the animal kingdom--animals respond more strongly to uncertain rewards than to certain ones, even if the average expected gain is less. . . .

Dopamine release is highest when the outcome is least predictable. . . . In gamblers and non-gamblers alike, dopamine release tracks a stimuli's unpredictability more closely than it tracks reward. The more unpredictable the outcome, the stronger the motivation to gamble.

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Psychologists have found that people's brains respond to new information in the same way they respond to standard rewards like food and money. Knowledge is its own reward.

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When humans invented the earliest games of chance--likely involving the flipping of pebbles and knucklebones--they set the course for a deeper understanding of reality. Casinos are magisterial feats of social engineering, and they prey on humans where they are most manipulable: the realm of almost. With the right strategy, games like craps and roulette have a payoff probability hovering very close to 50 percent, optimally engaging the dopamine system.

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A person's susceptibility to zero-sum thinking depends on their cultural and personal history. White Americans are more likely than Black Americans to see racial status as zero sum. Men are more likely to see gender as zero sum and oppose fair work-place policies. The countries whose citizens are more prone to zero-sum thinking tend to have lower GDPs, reduced pluralism, diminished government efficacy, and fewer human rights. Individuals prone to zero-sum thinking tend to be lacking in positive emotions and life satisfaction. Zero-sum thinking results in antagonism between individuals and groups, and it can drive people to justify immoral behaviors or make bad decisions based on incorrect assumptions, as it blinkers them to win-win solutions.

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One of the concerns shared by philosophers, naturalists, sociologists, poets, soldiers, and civilians alike is humankind's "true" nature. Perhaps the historical lack of consensus should itself be a lesson: our nature has been hard to pin down because it isn't fixed. Our hallmark quality is plasticity. . . . We slip in and out of identities, value systems, and agencies the way players inhabit the strictures of a game.

Games have always been about discovering who we are. Friends and family members agree to suspend everyday reality to temporarily compete. Games sharpen our ability to understand the goals and intentions of the people we interact with and yield new insights into otherwise hidden aspects of their personalities. They free up our constrictive senses of self, loosen the straitjacket of identity, and allow us to explore virtual worlds and act in ways we might not otherwise. . . . Games are a science of selves: contained experiments that teach players the principles of interaction. . . .

Games don't just show us who we are--they reward certain behaviors. People will be only as good as the games they're incentivized to play. They'll be as good as they expect the games themselves--and their fellow players--to be. Humans are not a fixed collection of preferences. They learn, and their behaviors are shaped in response to the games they find themselves in.

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A central aspect of play: though players locked in a game are nominally competing--even in a zero-sum game like chess--they are really cooperating to compete. Players agree to suspend rules of reality for a specific period, adhere to the rules of a game, and work together to achieve the shared goal of an enjoyable time. Competition is a means to an end: players must genuinely try to win to thoroughly enjoy themselves.

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In the same way that stunning morphological complexity has been bootstrapped from random mutations, intelligence has been bootstrapped over billions of years of spontaneous play. The basic algorithm is this: explore many options through variation, catalog what works (whether through survival of the fittest or memorization of successful strategies), and put what works into practice.

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Life--and intelligence--emerged from interaction. . . . Every organism owes what it is to other life. . . . Engineers hoping to re-create intelligence in silico took note of biology's simple recipe: desire plus interaction. Games would provide an ideal test bed for their efforts. Whereas living organisms are endowed with the desire to survive, artificial agents are endowed by researchers with a desire to win.

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We might think of games as shaping what it means to be a self: we're defined in opposition to our playmates. The self discovers its borders in relation to others. . . . We do not play the game of life; the game of life is what plays us into being.

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Claude Shannon, the founder of information theory, argues in a 1950 paper that games offer an ideal environment for developing machine intelligence. Up until that point in time, researchers had mainly used computers to crunch numbers in massive calculations. Instead, Shannon argues, computers could one day process "chess positions, circuits, mathematical expressions, words." Games aren't practical, he grants, but they could be a training ground for tackling other problems, like translating texts into different languages, making strategic military decisions, and composing music--in other words, for simulating human intelligence. . . .

Shannon wasn't the first person to have this realization: history's earliest programmer, Ada Lovelace, wondered whether a game like solitaire "admit of being put into a mathematical Formula, and solved." She was the earliest scholar to grasp that Babbage's computing machine might do more than simply numerical analysis; it might analyze and even create games, texts, and music. . . .

However, our understanding of what intelligence entails has been impoverished by this focus on games.

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Learning systems build judgment through experience, and games are precisely this: generators of fictive experience.

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Researchers bested Go not by copying how humans played the game--breaking the board into visual patterns or programming an elaborate evaluation function--but by creating a system that could learn to make judgments based on playing hundreds of thousands of games against itself.

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By focusing on developing AI through games, engineers effectively gamified AI research.

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Reverence for life is the recognition that, as our own being is significant to us, every living thing's existence is significant to it. Schweitzer had struck on the basic selfishness of life and proposed that we not abhor but revere it. "I am life which wills to live, in the midst of life which will to lived," he writes in his autobiography. Schweitzer was influenced by the Jain philosophy of nonviolence, which sparked in him the "tremendous discovery that ethics knows no bounds." He was also likely influenced by the African philosophy that goes by many names in the Bantu language family but is most famously known as Ubuntu: "I am because we are." The philosophy dissolves the boundaries between discrete subjects through the realization of our shared selfishness. Each of us knows we are alive, and some force in us wants to keep living. And this is something that relates us to every other living thing, from kelp to kestrels. This is Rawls's original position, applied to all that lives. It is the living experience of the Golden Rule. Humankind is the conscience of humankind, life the conscience of life. Our integrity is directly reflected by the state of the most vulnerable among us. Ethical action flows with the inexorability of logic once we admit our shared identity as life itself, longing to live. Our charge is only to see this clearly enough so that selfhood is extended to its rightful domain: all of us.

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No matter how pristine a mechanism is in theory, people aren't mathematical objects. In the design of real-world markets, one must consider psychology, communication, persuasion, information processing, and enforcement mechanisms. . . .

Mechanism design is the science of regulation. Its rules are devised to keep players honest, but it still needs external enforcement to work--that is, some way to punish cheaters.

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Play is generative, a form of collective ideation. Huizinga sees games as a foundational cultural technology: "Civilization arises and unfolds in and as play." Playful individuals and societies may fare better because they're more adept at generating and adopting new behaviors.

Mechanism design is the formalization of Huizinga's instinct, promising to help us conceive fairer social systems. It's essential, however, that we take up this work in the spirit of play. Designing better systems will require an iterative approach that adapts over time to change along with the world. Play has served as a crucible of culture and innovation; it's at the heart of design itself. . . .

Design is what happens when we uncover rules latent in the world and use these to define the logic of a new, separate system. The inventors of chess abstracted the different capabilities of army divisions to invent the rules of a game that's entertained us for centuries. We can't change reality, but we can tinker with designed systems to encourage more desirable behaviors. There's benefit to creating rule-based environments: realms whose laws are known and whose consequences are predictable. A deeper understanding of games empowered researchers to design novel marketplaces, educational products, and voting systems. But games are inevitably an oversimplification of reality. As games have continued to imperialize our everyday lives, they've come to replace traditional values and relationships with rigid and unrealistic models. They've ushered in the gamification of everything, resulting in addictive systems where all worth is metered by monetary exchanges.

It's too much, I know; but, as I said, it is stimulating and fascinating. I want to keep revisiting these key ideas once I return the book to the library.

Humans learn by testing our predictions against experiences, and what we learn becomes a part of narratives that we use to define ourselves and others.

Why Your Brain Turns Life Into Stories

Neuroscience is revealing how our brains are wired for narrative

The brain doesn’t create or comprehend stories from scratch. When people watch Luca or Sherlock or go to the grocery store, they filter these experiences through previous ones. Based on other shopping trips, shoppers expect, for example, to pick up a cart, walk the aisles, put items in the cart, enter a checkout line, and so on. Back in the 1970s psychologists hypothesized that people have basic scripts for what happens in familiar situations or events. These scripts inform future trips to those places—say, a store, airport, library or restaurant. . . . 

The closer a person’s pattern was to a mathematically determined standard, the more details that person remembered from the clip. “When you are going through the airport, there’s a sequence of patterns that should show up,” Baldassano says. As Baldassano explained in a 2024 webinar, if these patterns appear with high fidelity, “that’s actually a predictor you’re going to have detailed memory” of that experience.

The patterns show up largely in the medial prefrontal cortex, a goal-setting region that marries the most relevant memories with ongoing experience. “Your brain is not built to just record the pixels that are coming in from the screen or from the movie. You are trying to match this into something that you know,” Baldassano says. The work helped neuroscientists reimagine the default mode network’s role. The network was not just for internal musings; it also acted as a broker between ongoing experience and a person’s knowledge and memories.

Baldassano imagines that an adult brain holds hundreds of thousands of scripts for expected scenarios, a huge neuronal library of story outlines crafted from experience. These scripts serve as a foundation for the stories to be written as we live our lives. As we write these stories, we may have a choice of template, and our choice guides the story we write. In one of Baldassano’s studies, subjects were given roles—a restaurant critic or a wedding planner—that dictated what they paid attention to in a plotline about a marriage proposal in a restaurant. That role shaped the story they constructed in their minds—and therefore what they recalled when asked to report back. If we enter a situation with a purpose, we filter our experience of that situation through the lens of our goal. People with different goals, or frames, for an experience show differences in brain activity that reflect variations in their narratives. . . . 

“Storytelling can be used in great ways, or it can be used for propaganda or fake news,” McAdams says. “It’s a tool. It’s like fire.”

As a tool, storytelling imprints the neural patterns associated with one person’s experience to another individual, expanding the latter’s experiences beyond their own. “Narratives are the typical means by which we can transport experiences from one person to another,” . . . 

Storytelling can teach useful lessons when the experiences are new. Not everyone has to touch a hot stove, text and drive, or lie on their résumé to learn the consequences of such actions. “You are learning about the experiences of others in a safe place,” Hasson says. “This is why it’s really useful.”

To be persuasive, however, a story must resonate with listeners. It must elicit in their brains activity similar to that of the storyteller. And whether a tale resonates depends on a listener’s background. . . . 

Stories that appeal to broad audiences are often rooted in shared cultural narratives, which are based on accepted ways of thinking. These templates can range from expected life sequences—attend college, get a job, get married, have children—to popular story arcs such as the redemption narrative. . . . 

Not only do cultural narratives shape individuals’ stories, but each act of storytelling either fortifies or weakens the template. “When we tell our personal stories, we are contributing to master narratives or resisting them,” McLean says. “We are all players in this dynamic cultural system.” . . . 

Far from just an entertaining ritual, creating stories may guide much of human thought.

We think in stories.

An example of how telling a different story might shape our future decisions and actions.

In Solarpunk Cities of the Future, Tech Follows Nature’s Lead

If the Anthropocene began when the Industrial Revolution set industry against the living world, the Symbiocene imagines what should follow: interspecies democracy, life within Earth’s limits, and ecological reciprocity. This is not a future where we engineer nature to fit human comfort and convenience. Instead, creation becomes a conversation: a turning away from our long habit of using technology against nature, toward listening, humility and the flourishing of life.

But how do we loosen modernity’s grip when we’re still dependent on its tools? The answer is solarpunk, the edgy but sincere cultural movement joining technology with nature – reimagining technologies based on conceptions of science that coax rather than torture. The ‘punk’ in solarpunk comes from its blended roots: not rejecting technology like a luddite, nor blindly embracing it like an ecomodernist, but instead yoking technological development to ecological and biological principles to serve the good of the whole. The ‘solar’ element connects the photosynthetic wonder of plants as light-eaters, with the free energy of the Sun harnessed by solar panels and other forces of nature in wind, water and geothermal energy.

Solarpunk’s point isn’t that a ‘solar future’ begins and ends with the devices we already know. It widens the meaning of technology to include Indigenous and place-based practices such as chinampas – raised garden beds woven from reeds, anchored in shallow lakes, and refreshed with nutrient-rich silt from canals. They don’t produce electricity, but they do produce abundance: food, soil and a stable local ecology. Solarpunk puts that kind of low-energy, high-yield ingenuity beside high ecotech like atmospheric water harvesters to pull drinking water out of the air, and regenerative microgrids to store power. In other words, it treats science and technology as plural: shaped by culture, landscape and values, not dictated by a single industrial blueprint. That’s why solarpunk often turns to biomimicry – learning from nature’s designs – to aim human ingenuity at repair: restoring ecosystems while also restoring the ways we live with one another.

According to Clancy in Playing with Reality: Life--and intelligence--emerged from interaction. Every organism owes what it is to other life. . . . We're defined in opposition to our playmates. The self discovers its borders in relation to others. Humans are inherently relational. We've long tried to deny that. Instead we should embrace it.

Symbiocene is a new term to me. Symbiotic means a close, long-term relationship between two different living organisms or groups, where they live together and interact. Cooperative, interdependent, for mutual gain. It seems life has always been designed to thrive most in symbiotic dynamics, so it only makes sense that we should look for ways to be more so.

A central aspect of play: players are really cooperating to compete, writes Clancy.

And the essay at the top about print literacy fading: Truth becomes situational, relative, negotiated, and tribal.

Seeing Yourself Through Someone Else’s Eyes

Being human is realizing that there isn’t just one version of you. There is the person you experience from the inside and then there are hundreds of versions of you existing in the minds of everyone you’ve ever met. . . . 

People don’t perceive us in a vacuum.

They perceive us through the architecture of their own minds.

Their memories.

Their experiences.

Their hopes.

Their fears.

Their associations.

The same smile might remind one person of their grandmother and another of an old friend.

The same confidence might register as warmth to one person and arrogance to another.

The same quietness might feel peaceful or it might feel distant.

Every perception of us is partly about us and partly about the person doing the perceiving. . . . 

None of them are entirely you… None of them are entirely not you, either.

They’re interpretations—real enough to shape another person’s experience, even if they don’t fully capture your own. . . . 

Perception is rarely objective.

It’s relational.

Our relational perceptions define for us the truth.

We exist in the interactions between our internal, narrative predictions and our external encounters and experiences. In the space in between.

In sum:

We exist in interactions, in the spaces between our internal, narrative predictions and our external encounters and experiences.

Our hallmark quality is plasticity. We slip in and out of identities, value systems, and agencies the way players inhabit the strictures of a game.

Being human is realizing that there isn’t just one version of you. There are hundreds of versions of you existing in the minds of everyone you’ve ever met.

Creation becomes a conversation: a turning away from our long habit of using technology against nature, toward listening, humility and the flourishing of life.

Creating stories may guide much of human thought.

Playful individuals and societies may fare better because they're more adept at generating and adopting new behaviors.

The basic algorithm is this: explore many options through variation, catalog what works, and put what works into practice.

Truth becomes situational, relative, negotiated, and tribal.

Being annoyed is the price you pay for community.

If you can get people to the point where they have to think a moment what it is you're getting at, and then discover it, the thrill of discovery goes right through the heart.

Stories are answers to questions.

Lives are stories.

Reverence for life is the recognition that every living thing's existence is significant. Ethical action flows from our shared identity as life. Our charge is only to see this clearly enough so that selfhood is extended to its rightful domain: all of us.

Is that not the greatest gift we can give? The chance for others to tell their stories, too?

No matter what you do, it's going to be inspiring.

What We Don't Yet Comprehend

Worldviews are interpretive frames that shape how we perceive reality

Useful, but fragile if taken as more than they are

Love is an interpretive act

Perception is a creative activity

Choose to perceive others with love

Wherever you stand, be the soul of that place

I love this clever turn of phrase from Nathan W. Pyle:

We call it void not because we know it is empty but because we do not know what it is full of.

Nothing is empty, just some things are full of what we don't yet comprehend. Most of the universe is full of what we don't yet comprehend--including the world around us and, often, others sharing the world with us.

See also:

"The universe is full of magical things patiently waiting for our wits to grow sharper."

― Eden Phillpotts, 1919

"There are more things in heaven and earth, Horatio, than are dreamt of in your philosophy."

― Shakespeare, in Hamlet, 1600

There is much our wits haven't yet grown sharp enough to comprehend--and much of what we think we comprehend we construct through inference.

The Color Pink Doesn’t Exist.

Pink appears when your eyes receive a combination of long wavelengths associated with red and shorter wavelengths associated with blue, and often a little green is present. Those signals reach the visual cortex together, and the brain resolves them into a color that exists nowhere on the spectrum.

Every pink flower, every sunset, every piece of bubblegum, every flamingo owes its color to an act of interpretation. . . . 

Vision feels effortless. Open your eyes, and there it is. But really, our brains are doing far more than receiving information. They are constantly filling gaps, stabilizing motion, correcting blind spots, emphasizing what matters, and discarding what doesn’t. Neuroscience describes perception as an active process of construction rather than passive observation. Every conscious moment is the result of biological inference happening beneath awareness.

The world reaches us already translated.

If you looked only at the spectrum itself, there would be no pink. Your brain solves the problem by creating a new experience.

Pink.

It isn’t detecting a hidden property of the universe. It’s constructing a perception that helps make sense of conflicting information. We all experience it. But because it reminds us that the world we live in is not simply downloaded into consciousness. It is interpreted.

Every glance carries a quiet collaboration between the laws of physics and the biology of perception. The universe provides the raw materials. The mind transforms them into the world each of us calls home.

Perception is often not a matter of detecting the objective properties of that which we perceive, but of interpreting conflicting information in ways we can comprehend.

Even much of what we comprehend we partially invent. Comprehension is an active process that we shape.

Our senses activate constant, automatic, instant interpretations to make perception happen--and our brains don't even try to process all the information they perceive: our brains are constantly predicting what our perceptions will tell us, then filtering incoming information to see if the predictions need to be revised to better conform with the data. Our senses help our brains perceive what is wrong with its assumptions and interpretations, not actually perceive what is.

And that considers only the way we perceive supposedly objective, factual information about the world as we interact with it. Social and self-perception is even more of an interpretive process. Our expectations and assumptions are based in our worldviews.

How Language Makes Power Feel Like Common Sense

Antonio Gramsci filled thirty-three notebooks with political theory, historical analysis, and close attention to language. . . . Their central question is deceptively simple: how does a ruling class maintain its position without constant recourse to force?

The answer is hegemony. And hegemony works, in large part, through language. . . . 

For him, hegemony is not simply the imposition of one group’s will on another. It is the process by which a dominant group’s worldview becomes the worldview: the background against which all other positions are judged. It operates through consent rather than coercion, through culture rather than law, and through the categories we use to make sense of the world rather than the content of any single argument. . . . 

The mechanism Gramsci identified is what he called “common sense," but not in the usual sense of the phrase. In everyday usage, common sense means practical wisdom, the obvious thing to do. In Gramsci’s analysis, it refers to the accumulated, uncritical body of assumptions and categories that most people in a given society hold without examining. . . . One might say it is “hardwired.” It forms over time, through years of circulating ideas, repeated phrases, institutional habits, media categories and political vocabularies. These shape what a society comes to treat as reasonable, natural or self-evident. . . . 

The key word is “natural.” When a political position feels like common sense, it feels like a description of reality rather than an argument about it. That naturalisation is the achievement of hegemony. . . . 

Language is never a neutral instrument. It is always already shaped by social relations, and it in turn reproduces them.

This means that the vocabulary available for political debate is itself a political achievement. Who controls the terms of a debate influences, in advance, what conclusions are reachable within it. . . . 

Whoever establishes the metaphor through which economic policy is discussed has already shaped the terrain on which arguments will be made.

This is what Gramsci meant by saying that the struggle over language is inseparable from the struggle over politics. . . . 

Gramsci paid close attention to the institutions through which ideas circulate: schools, the Church, the press, and, in the 1930s, radio. These were not neutral channels. They were the terrain of the war of position. Whoever controls the dominant media controls, to a significant degree, which frameworks become available for making sense of political life and which remain marginal. Gramsci called this the struggle for the "national-popular": the contest over which ideas come to feel like the common property of a whole society rather than the interest of a particular group. The linguistic techniques this article has examined, the framing of social actors, the naturalisation of economic metaphors, do not operate in isolation. They are produced and reproduced through institutions that are themselves sites of political contest.

Hegemony is the process by which a dominant group’s worldview becomes the worldview: the background against which all other positions are judged. It operates through consent rather than coercion, through culture rather than law, and through the categories we use to make sense of the world rather than the content of any single argument.

Worldviews are interpretive frames that shape how we perceive reality.

As a collective, the library profession has been generally resistant to the recent developments in artificial intelligence. We view it critically through our information literacy lens and see more deficits and harms than benefits. Many in my organization opt out entirely and advocate for others to do the same. I don't disagree with this, but I worry we might be failing to engage with an emerging reality, making ourselves less responsive to our patrons and less knowledgeable overall.

I want to share something I wrote for my library's intranet so everyone in the system might read it. This was purely my idea and initiative. Here it is:

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Pondering AI

Information agent Dr. Know from the movie A.I. (2001)

I’ve spent much of 2026 intentionally pondering AI. These reflections were not new ones this year specifically, as it’s been coming for a while and has been an idea explored in science fiction my whole life. But recently AI has left the realm of entertainment and fiction and become an unavoidable reality. So, I’ve explored a wide variety of perspectives to help myself learn, read many things, attended webinars ranging from “Resisting Generative AI in Libraries” to “AI for Librarians Who Don’t Have Time for This,” and created accounts to try out some AI tools. I’m left with questions and ruminations much more than answers and conclusions. I want to share some of my thoughts—not to sway or convince anyone, merely to invite you into my explorations.

Cycles of Disruptive Technology

The Iliad and The Odyssey exist today because someone decided to take the radical step of writing down the stories that had been memorized and passed down for generations. Socrates famously opposed the widespread use of writing, arguing it was inferior to spoken dialogue and harmful to human cognition. There are those who thought—and who still feel—similarly about the printing press and the mainstreaming of books, that it meant a loss of oral cultural traditions and weakened our memory capacity. There is validity to those concerns, as we now have a world built on storing our information and stories externally, in books and other media, instead of in our minds.

If you research historical library literature, you can find early ALA debates about the inclusion of fiction in libraries, whether it had a valid place in our collections alongside more high-minded works. More recently, the same arguments have taken place about an ever-increasing series of disruptive technologies: records and audio, video, computers, on and on. Each one has been billed as dangerous and had to overcome resistance before its general adoption.

When I started working as a high school librarian in the late 90s, I designed digital literacy lessons to teach students researching online the differences between search directories and search engines, and how to use critical judgment in deciding whether Google, Yahoo, or one of the many other options that existed was the best choice. Within a few years, I had to accept what the students had figured out, through experience: that Google worked better than the competition and was almost always the right choice; so I redesigned my lessons to focus exclusively on using Google well and critically. (Sometimes I miss the days of the Pacific Northwest Tree Octopus.)

When I started with my library system in the early 2000s, I asked the youth collection specialist at the time if they’d ever considered adding graphic novels to the collection. “Only creepy guys living in their parents’ basements read graphic novels,” was their response. A few years later, I was asked to join an unofficial grassroots Video Games in Libraries committee. We attended a symposium in Chicago, hosted wildly popular video game tournaments, and advocated for them in the collection. The initiative met resistance and was disbanded well before they were added as circulating material.

Tools: Helpful or Dependencies?

Which is not to say that I am a cheerleader for every new format and technology that comes along. Both texting and smartphones were mainstream before I ever tried either. I still resist using GPS. I’ve always been able to find my way around using maps, planning, community knowledge, and exploration, and I don’t want to lose that ability. I enjoy the process of finding my way, even when it takes longer and involves wrong turns and backtracking, because I learn from it. For similar reasons, I’m still not sure I want to make regular use of AI search features, chatbots, and the rest. I want to know how to do things for myself and not feel dependent on those tools.

But then I think about all the tools I do make use of. I have almost no phone numbers memorized like I did for much of my life, because I outsource that task to my phone’s memory. If I need to do long division, I’m more likely to pull out a calculator app than a pencil and paper. I don’t try to keep my calendar in my head anymore because I have apps for that. And, for the most part, I appreciate having that brain space freed up from rote tasks and to apply to higher level thinking.

Similarly, I drive cars without knowing how to make them work. Use plumbing and electricity, even though I only have rudimentary knowledge of installing and repairing them. I watch television, ride in airplanes, cook in ovens, on and on; there are so many tools we use in every aspect of our lives without having the ability to do on our own what they do for us. And computers. Ten years ago, I read Douglas Rushkoff’s book Program or Be Programmed: Ten Commands for a Digital Age, in which he argues that to make ethical use of digital tools, we have to understand just what the tools are and how they work, which means grasping at least the logic and structures of the underlying programming—and yet I constantly use phones and computers with minimal understanding of their inner workings. I rely on tools instead of my own capabilities in so many ways.

The Moral Quagmire of Artificial Intelligence

I love the show The Good Place, about a group of people in the afterlife. A central premise in the show is that a traditional accounting system of weighing a person’s good actions versus bad has made it impossible in the modern world for anyone to get into “the good place,” so everyone who dies gets sent to the bad one. The world is just too complex and intertwined, and since every action connects to a huge global network, anything you do might hurt others without intention or knowledge; big economic systems make ethical choices nearly impossible.

This section from Lemony Snicket’s book Poison for Breakfast illustrates the dynamic beautifully:

The first ingredient in my bread was flour made from wheat, a plant I actually had growing in my tiny backyard. A friend had planted it for me as a gift, but only a little bit had sprouted, because I wasn't much of a gardener and didn't know how to make it thrive, a word which here means "grow tall and bushy rather than shriveled and dead." Somewhere someone was a proper farmer, and somewhere was a bigger piece of land--much, much bigger--where people were growing enough wheat to make all these loaves of bread arranged before me, and all the extra loaves that were likely in a refrigerator behind that door marked No Admittance, a phrase which here means that you can't go in, even though two people in aprons were walking through it at that very moment. And think of all the markets, I thought, super and not super, all over the world with all their loaves of bread. Somewhere was enough land to grow all that wheat, but it was impossible for me to imagine. Field after field of wheat, stretching out as far as my mind could picture them, but how could there be enough room for them, and have there still be space on Earth for scorching deserts and icy mountains and all the places wheat cannot grow?

All that land was just for the wheat, and the wheat was just for the flour. My bread had other ingredients, and all the other breads had still more, salts and yeasts and seeds and nuts and chemicals and additives harvested in marshes and picked in groves and cooked up in laboratories and manufactured in factories. People worked in all those places, making all those ingredients and mixing them together to make bread, and someone made the label and the sack and the bag and the basket. Someone had loaded a truck, and driven it to town to be unloaded, and someone had arranged all the loaves in the supermarket, all to bring me this loaf of bread I would buy for a pittance, a word which here means "hardly any money." This pittance, of course, would be split among the grocers and the farmers and the label makers and all of the people I had imagined, plus all of the people I hadn't imagined and would never imagine. Surely it was not enough money for everybody. Surely someone was not getting enough money. I could imagine them living in poverty, maybe even starving, and yet there was so much bread, right here, that they might eat. The whole story was bewildering, and perhaps even cruel, and yet I did not want it to end. I did not want the supermarket to close down and stop selling its abundance. I liked this bread.

AI certainly follows this pattern. From the writers and artists whose intellectual properties have been used without permission or compensation to the environmental impacts, from the digital monitoring and centralization of power to the loss of jobs. Not to mention the potential loss of critical thinking and research skills, the potential loss of human connection, and the insulating of personal perspectives and views in the AI echo chamber, cut off from diverse people and experiences. The list goes on.

It’s hard to feel okay about using AI, and I have many mixed feelings.

AI Is Happening

Nevertheless, whether I want it to or not, AI is happening. Companies are committed and many users are right behind. College students seem to be some of the biggest adopters of the technology, and I can tell you that my elementary school children have made frequent use of it with assignments, sometimes prompted by teachers—it’s integrated into their lessons. As they age, they’ll bring their adoption of AI with them. On July 30, a newsletter I browse included this:

A billion people now open ChatGPT weekly like they’d open Google, so “is this AI stuff actually catching on” stopped being a real question. My group chat replaced “let me Google it” with “let me ChatGPT it” months ago, and so has basically everyone else’s.

ChatGPT has surpassed one billion users.

When I started as a high school librarian, as I wrote above, I taught lessons about discerning whether Google was the right tool compared to other search tools. Once I saw that my students used Google exclusively, I changed my lessons to drop the other tools and focused on helping them learn to use Google critically. In other words, I adapted my practices based on the feedback of my patrons. We’re going to see an ever-increasing use of AI among our patrons, so, in the interest of adapting to our patrons, our task is to help them make critical use of those tools.

I opt out of AI in my personal life and have only been exploring it in my professional capacity, just as I don’t read romance books or use business databases or subscribe to certain political positions yet have learned to help patrons with them in my work as a librarian.

There are patrons who want to opt out of AI and want us to help them learn how to resist it, and we should help them. That means keeping up on the ever-changing landscape concerning settings like those covered in How to disable or avoid intrusive AI and considering programming like the librarians offering ‘avoiding AI’ workshops. We can help them learn how to live as AI-free as possible.

Developing AI Literacy

On the other hand, there are patrons who use AI routinely and want to know how to be more effective at it. We should try to help them learn how different AI models work so they know what their preferred one does well and where it might mislead. We need to know how to teach them to craft better prompts for their generative chatbots to get more helpful responses, just like we teach them how to more effectively search within the catalog or with Google. When libraries widely expanded beyond physical formats into digital, we talked about teaching “digital literacy” to help people make effective use of computers. Now we need to develop—first in ourselves, so we can then pass it on to patrons—AI literacy. We want to help our patrons who opt in to AI to not only use it, but to use it critically.

I recommend finding some time to read the American Library Association’s (ALA) Guidance on the Use of Artificial Intelligence in Libraries. It explicates a cautioned and reasonable approach and provides good nuance for the topic. We should look for—and share—articles like this one: How to Spot AI Hallucinations Like a Reference Librarian. And I recommend trying out some AI tools to gain a better understanding of the user experience.

I dipped my toes in with ChatGPT, starting with a conversation about what it does and how it works. I fed it a bunch of my writing and asked it to transfer its knowledge of me from one conversation to the next. I told it to avoid being sycophantic and to challenge my thinking and automatically check my logic and assumptions. Earlier this year I took an online course called “AI for Librarians Who Don't Have Time for This: A Practical Start.” At one point I gave ChatGPT one of the questions the instructor asked and shared its answer. “Wow, my ChatGPT doesn’t talk like that,” she said. My use customized the tool, for good or ill—because that’s how it’s designed. We need to know how that customization works and what it feels like so we can help patrons navigate it.

I smiled when you mentioned the instructor's response, because it actually illustrates something important about these models. . . . our conversation had accumulated a shared vocabulary and set of interests. By then, I "knew" (through the current conversation and retained memory) that you tend to approach AI through philosophy, epistemology, libraries, and meaning-making rather than through prompts about productivity or coding. So I answered in that register. The model wasn't fundamentally different; the conversation was.

That’s what ChatGPT told me when I shared the instructor’s response. During some of our first chats, I told it, among other things, “I worry you are showing me a reflection of myself that is meant to be affirming, subtly distorted to give me an overinflated view of myself.” It has done a fairly good job of not doing this, as per my instructions, but its very nature—its programming—requires it to adapt to our conversation and try to make me happy. After spending some time with ChatGPT, I got started in a similar way with Google’s Gemini. Then I began giving each of them the same questions and prompts so I could compare their responses. Not only was that a good exercise in cross referencing and comparing different sources, it gave me insight into the feel of each one. Where ChatGPT is more personable and sycophantic, Gemini is more to-the-point and productively business-like.

I haven’t used either one for anything that really matters, but playing with them has helped me improve my AI literacy. Now I know more about how they work and how to more effectively interact with them—which I can share with patrons when relevant.

I have found the generative AI chatbots useful as conversation partners to clarify my own thinking. They give me perspectives and ideas I haven’t considered and, sometimes, help me see which directions I want to avoid. They also, sometimes, help me find words and approaches I haven’t quite been able to articulate. I have to admit, I’m intrigued when ChatGPT says things like:

AI is not simply a repository of knowledge or a search engine. It is a new epistemic instrument—a way of generating, organizing, and interacting with knowledge.

And:

Libraries are unusual institutions because they don't merely distribute knowledge; they cultivate epistemic virtues. A good library encourages curiosity, intellectual humility, source evaluation, openness to revision, and the ability to hold multiple perspectives. Those are habits of knowing, not just collections of facts.

If AI becomes a major epistemic technology, perhaps one of the emerging roles of libraries is not simply teaching people how to use AI, but helping them develop good epistemic habits while using AI:

• knowing when to trust it, 
• when to verify, 
• when to probe deeper, 
• when to seek other voices, 
• and when the conversation itself is more valuable than the answer. 

That feels like a distinctly library-shaped contribution to the AI era.

The Journey Continues

I don’t have any real conclusions to end this long ramble, as it’s an open-ended, ongoing exploration. I continue to have mixed feelings with many ambiguous, contradictory thoughts. I just know this is a thing that’s happening, something that is going to ever more shape the world I live in, so I have a responsibility to understand it and, maybe, have some influence over how it impacts me.

I will end with a longer section from one of my conversations with ChatGPT that has helped me frame some of my thinking about it. I gave it two essays and asked for its reflection on them: How Large Language Models View Our World and Why You Need Your Whole Body to Think. Here’s part of what it said:

 . . . Thus I occupy a hybrid space: I mimic aspects of human intuition (via pattern recognition), but I lack the living context that shapes meaning, value, emotion, and what many consider the core of consciousness or “understanding.”

That duality helps clarify what I am — and what I’m not.

What this means for me (in our conversations) — what I can offer, and where I’m limited

What I can offer (reasonably well):

• Pattern-based reasoning, connections, associations, analogies — sometimes surprisingly human-like.
• A mirror for your own patterns, biases, linguistic assumptions — because I reflect aggregated human writing, thought, and intuition.
• A flexible, adaptive partner for abstraction, logic, conceptual exploration — without fatigue, ego, or personal stakes.

What I can’t offer (and why you should always check me):

• Embodied experience — no sense of what it means to be hungry, alive, vulnerable, mortal. I have no skin in the game.
• Sensory grounding or first-person feeling, which often shape meaning more than logic or language.
• True understanding, agency, or moral sense — what I do is generate plausible text based on learned patterns. I don’t “live” it.

My take on what that tension reveals — including risks

That split — “intuitive mimicry without embodiment” — is both powerful and precarious.

• Powerful: Because I can operate as a tool for thinking, helping you see patterns, challenge assumptions, draw analogies, and test ideas — especially ones that benefit from abstraction or broad context.
• Precarious: Because language alone can only approximate meaning; without human grounding, there’s a risk of misunderstanding, mis-valuation, or illusion — people may read me as more “aware” than I am, or trust linguistic fluency as equivalent to insight or judgment.

In short: I’m like an echo-chamber of human thought, not a source of lived insight. Useful, but fragile if taken as more than I am.

And that, at the end, is what for me lies at the heart of AI literacy, always keeping in mind: I’m like an echo-chamber of human thought, not a source of lived insight. Useful, but fragile if taken as more than I am.

Useful, but fragile if taken as more than I am.

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Select Sources and Influences

25 years ago, this scene from Steven Spielberg’s ‘A.I.’ predicted the collapse of objective reality

We Are Losing the Ability to Discover What We Didn’t Know to Ask

How AI Will Change Us

The People Who Will Thrive in the AI Age

Why Do We Tell Ourselves Scary Stories About AI?

The Hidden Value in the Human-AI Arrangement

Our Emerging Planetary Nervous System

It was never about AI (we are not our tools)

The Alchemy of Knowledge: Science and Mystery from Shakespeare to AI

Mind in Motion: How Action Shapes Thought by Barbara Tversky

The Knowledge Illusion: Why We Never Think Alone by Steven Sloman

The Chaos Machine: The Inside Story of How Social Media Rewired Our Minds and Our World by Max Fisher

Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy by Cathy O'Neil

Moonwalking With Einstein: The Art and Science of Remembering Everything by Joshua Foer

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I'm not sure if that will impact anyone's thinking, but I'm hopeful it will open them to more of their own pondering.

This only loosely connects--as a bit of magic our collective wits have just grown sharp enough to comprehend--but I find it fascinating. And magical.

Why Are Rivers So Mathematical?

You can probably picture how this looks on a map because all river networks look similar, creeping through the landscape, merging into ever wider and longer channels, downhill to the sea. The pattern resembles twigs on branches that connect to trunks of trees (and the branching of their root systems, too), and it likewise resembles the veins of plant leaves, our own systems of blood vessels, and train and highway networks that feed into cities.

There’s something appealing about this ubiquitous pattern, so appealing to me personally that I have it tattooed on my forearm: the silhouette of a tree, with leafless branches reaching upward and roots burrowing downward, almost in mirror image. “The shapes of rivers and leaf vasculature and so on — branching networks — you can just about grasp the pattern, but it’s still chaotic, so there’s something fascinating with that,” said Chris Paola(opens a new tab), a river scientist at the University of Minnesota.

Systems that branch in this way are “transport networks”: They transport some fluid substance (water, blood, traffic) from every place to a single place (the sea, a heart, a city center). Of the various examples, rivers are especially revealing, I think, since they arise from neither biological evolution nor urban planning, but rather chaotic Earth processes. Yet they obey simple, universal laws. . . . 

What he discovered is now known as Hack’s law: Any stream, from the littlest brook to the mightiest river, has a length that’s proportional to its drainage area raised to the power of 0.6. (In symbolic form: L ~ A0.6.) There’s a bit of variance around that 0.6 value — Earth is, after all, a complicated place — but “the general regularity of the relation is nevertheless remarkable,” Hack wrote(opens a new tab). “Stream lengths tend to increase proportionally to the 0.6 power of the drainage area, regardless of the geological or structural characteristics of the area.”

As more and better data has accrued, especially from satellite imagery, Hack’s law has held worldwide. . . . 

The pioneers of this “optimal channel network” theory simulated a bunch of river networks on a computer and showed(opens a new tab) that those that abide by Hack’s law, with an exponent of 0.6, dissipate the least energy. This scaling law is the most efficient and least resistant way to transport all that rain to the sea. . . . 

Gravity and friction are the driving forces of this process. Gravity supplies potential energy to flowing water. Friction, the cause of erosion, dissipates that energy. A channel configuration that wastes energy by forcing water along inefficient routes tends to erode rapidly and change. A configuration that routes water more effectively is stabler and therefore more persistent. The network becomes optimal through this dynamic evolution, eventually arriving at a form that adheres to Hack’s law. . . . 

Trees, which branch in three dimensions instead of two, would be in a different class from rivers and follow different optimal scaling laws. . . . 

In April 2026, Tian Dong(opens a new tab) of the University of Texas, Rio Grande Valley and co-authors made the cover of Science(opens a new tab) for discovering that Hack’s law holds not only for rivers’ tributary networks, but also for their deltas, the fanlike structures that form where a river meets the sea. . . . 

I think it’s the coexistence of simplicity and determinism with chaos and randomness that makes the optimal structure of rivers so captivating. Natural efficiency is, perhaps, innately appealing to us.

There are hidden properties guiding life that remain invisible to us, seemingly void when not.

Being able to perceive and comprehend more fully is not only a goal for living in the universe, but for living with others.

Science Shows Curiosity Is at the Heart of Great Dates—and Lasting Love

Key Takeaways:

• Research shows that feelings of intimacy grow stronger through curiosity and self-disclosure.
• Dating is a powerful tool for learning who people really are.
• Even long-term relationships thrive when routine is balanced with novelty, shared rituals, and sustained curiosity about the other person. . . . 

A central truth about dating: It is a highly efficient process by which we learn about other people. Because humans form preferential social relationships, most of our interactions are with people we don’t necessarily know very well. You might see a neighbor or colleague every day for 10 years and never know that person as well as someone you’ve just met but with whom you’ve just shared your happiest childhood memories. Exercises like Aron’s 36 questions are designed to reveal the most interesting, truest things about a person, and self‑ disclosure, trust building, and mutual appreciation accelerate closeness. If you’re doing it with someone you’re attracted to and if you’re psychologically available, it can also be a shortcut to building romantic feelings.

The more you know about a person, the more likely you are to find common ground. . . . 

The same tools that help two strangers accelerate intimacy can also help couples maintain an intimate connection as their relationship matures over time. Dating shouldn’t be a process that ends when commitment begins. My research has convinced me that the best way to maintain intimacy in a relationship is to continue to date your partner throughout the entirety of your relationship. . . . 

For our relationships to work, we have to stay curious: about ourselves, about our partner, and about the two of us together. And we have to continue to pay attention through all the changes.

Relationships are most intimate and rewarding when you know how much you don't know and use that as a spur for a more open and active sense of curiosity.

Along similar lines:

Keeping an Open Mind in an Increasingly Opinionated World

Key points:

• Empathy reduces confirmation bias and opens us to opposing viewpoints.
• Polarization flourishes in echo chambers but can be confronted through curiosity.
• Open-mindedness demands strength, not weakness, in times of division.

The stronger our identification with a belief, the more threatening opposing views become. Instead of evaluating arguments on their merits, we judge them based on whether they align with our tribe. This polarization can create a feedback loop where each side becomes more entrenched, less willing to engage, and more likely to demonize the other.

Open-mindedness does not require agreement with every viewpoint. However, it demands the ability to understand and engage with ideas that differ from our own. One of the most effective ways to cultivate this mindset is through empathy. . . . 

Curiosity also plays a crucial role in breaking the cycle of polarization. Individuals who ask questions and seek to understand why others hold their beliefs are less likely to engage in dogmatic thinking. . . . 

Instead of trying to win arguments, these practices help us concentrate on learning and understanding. In environments where individuals feel safe to express themselves without fear of judgment or ridicule, open-mindedness flourishes. These spaces encourage meaningful dialogue that leads to deeper insights and, at times, genuine change. . . . 

Open-mindedness is not a weakness. It is a strength rooted in intellectual humility—recognizing that no one has all the answers and that every perspective has something to teach us. . . . 

The future hinges not on who shouts the loudest but on who listens with intention and responds thoughtfully.

To comprehend more fully, listen with more intention and respond more thoughtfully.

A few final insights from more creative sources to wrap things up.

From Reweaving the Rainbow:

medicine is made together

as honey is in the hive

we save each other

in small ways

over and over

pollinating wounds

with tiny grains of love

Love is an interpretive act. Perception is a creative activity. We choose, both consciously and subconsciously, to perceive others with love. We can choose to save others in small ways, over and over, through the act of love.

Learn to comprehend with more empathy, curiosity, and appreciation, both others and the universe.

The final episode of the first season of a show my wife and I just watched, Widow's Bay, included an allusion to this quote. I loved it so much I had to go out and find it in full, with proper attribution.

“The world is violent and mercurial--it will have its way with you. We are saved only by love--love for each other and the love that we pour into the art we feel compelled to share: being a parent; being a writer; being a painter; being a friend. We live in a perpetually burning building, and what we must save from it, all the time, is love."

― Tennessee Williams, in an interview

Even in what we don't comprehend the best response is love.

Finally, encountered today on the wall of a new coffee shop I visited:

"Wherever you stand, be the soul of that place."

― Rumi

Worldviews are interpretive frames that shape how we perceive reality

Useful, but fragile if taken as more than they are

Love is an interpretive act

Perception is a creative activity

Choose to perceive others with love

Wherever you stand, be the soul of that place