Posts Tagged ‘play’
“Every happiness is the child of a separation it did not think it could survive”*…
A third and final (for awhile:) post on AI and what it might mean… Sunday’s post was a consideration of what we might lose if AI becomes central to our lives, a modern echo of Socrates’ lament on the spread of writing. Indeed, we are in a moment of high dudgeon over AI: its potential impact on the environment, on jobs. on the economy more broadly, and in the wake of recent statements from foundational model companies, on their governability(“rogue AI,” though do also see here), and thus on the prospect of our very existence (though do also see here).
Yesterday’s post was an example of thinking that starts from the implicit assumption that AI is coming, then asks how we might govern it. It’s worth noting that even if there is an AI Bubble about to burst, AI could still loom large in our longer-term future. Investors hobbled in many earlier bubbles (e.g., railroads, telecom, the dot.com crash, et al.) were directionally absolutely right about the longer-term promise of the technologies that excited them, just wrong to believe that the early entrants (and their specific offers) in which they were investing were the vehicles to realize that promise.
Today, we stick with the assumption that AI will continue to develop and to change the world around it. Some suggest that AI and its impact are moving us from literacy back to orality (the loss of which so concerned Socrates). But others suggest that AI (and the advances that it enables) could usher in a new Axial Age, a time of huge and ultimately positive transformation, on the other side of which we– humanity– will be… different, as different from the people we were in, say 1999, as Shakespeare was from Socrates.
But what might that be like? It’s relatively easy to imagine disasters that amount to the things we know collapsing; it’s much harder to envisage positive futures filled with altogether new things, futures the contents of which are, essentially by definition, things we’ve not imagined, much less experienced.
Following, from Vinkatesh Rao, one of the most thoughtful approaches I’ve yet come across. He starts with mathematics– with the recent successes of AIs in that field– locates that work in the history of math (in particular axiomatics), then suggests a way of understanding AI’s “success”:
… A theorem prover does not search the space of all possible sequences of logical symbols. It plays inside a world humans have painstakingly designed.
This makes recent achievements in AI mathematics look slightly different.
Perhaps we have been too quick to interpret them as evidence that AI has acquired access to the wild source of mathematical intuition. A significant part of the achievement may instead be that humans spent a century converting increasingly large regions of mathematical wilderness into exceptionally good game boards: semi-closed environments in which the relevant state can be represented, legitimate moves can be made, accumulated technique can be reused, and success can be verified…
Rao then explains how similar trajectories have accrued in the application of AI to programming and to physics, concluding…
Across mathematics, programming and physics, the same pattern keeps appearing. First there is clever performance. Then somebody finds a representation that captures what the clever performers are doing. Then general machinery accumulates around the representation. Then the machinery becomes architecture. Eventually much of the play becomes mechanical.
The creativity has not disappeared. It has moved.
There is an obvious objection to this story.
Perhaps what I am describing as progress is merely legibility.
James C. Scott famously described [and here] the tendency of modern states to simplify complicated social and natural realities into representations that administrators can see and manipulate: cadastral maps, standardized names, scientific forests, censuses, planned cities.
The representation is useful precisely because it throws things away. A forest seen by a forester interested in timber yield is not the forest experienced by the people, animals, fungi and plants living in it. The administrative forest has become extraordinarily legible along a narrow set of dimensions by becoming blind along others.
Every game performs a similar operation. Before you can play, you must decide what the pieces are. You must decide what constitutes the state of the game, what counts as a move, what consequences follow from moves, and what counts as winning. Everything else becomes environment.
A rigid body in a mechanical simulation is not actually rigid. A point mass is not a point. A frictionless surface does not exist. A program described by its types still runs on processors with caches and memory hierarchies. A theorem encoded in Lean does not contain the diagram that gave somebody the idea for it.
Formalization is compression.
In physics this is explicit. Reality becomes a model, the model becomes mathematics, and the mathematics becomes a numerical representation. Information is discarded at every step.
The miracle is not that nothing is lost. The miracle is how often we can throw almost everything away and still retain what matters…
…
… This suggests an important asymmetry. A productive mathematical ecology wants porous epistemic boundaries and impermeable verification boundaries. On the way in, metaphor, hallucination and category mistakes can be useful. On the way out, they are forbidden.
A poem can inspire the theorem. The poem cannot prove it…
… A domain becomes playable when enough of its phenomenological complexity can be compressed into something like a state; when there is some reasonably stable repertoire of actions; when interactions can be repeated; when outcomes provide feedback about better and worse play; and when the environment is stationary enough that lessons learned yesterday remain useful tomorrow.
None of these conditions needs to be perfect. Poker contains hidden information. Markets change their own rules. Hunting happens in an uncontrolled environment. Conversation does not have an explicit score.
Playability is a matter of degree.
Nor is playability the same as formalizability.
Children learn social games without writing axioms. Hunters learn landscapes. Merchants learn markets. Political operators learn institutions. Formalization is merely one unusually powerful technology for increasing playability.
So are money, measurement, domestication, standardization, simulation, bureaucracy and digitization. They do related things. They compress states. They stabilize interactions. They make outcomes comparable. They create memory. They allow experience to accumulate.
This suggests a hypothesis:
Far more of reality than we might reasonably have expected can be carved into semi-closed environments in which experience accumulates, performance improves through repeated play, and success eventually becomes sufficiently legible to automate.
Call this the Curiously Playable Universe hypothesis…
…
… If playability were merely a property of AI-friendly digital environments, none of this would be particularly interesting.
But the pattern is ancient. Consider agriculture.
Hunting and gathering takes place in a relatively wild learning environment. Animals move. Weather changes. Useful plants appear where they appear. The training distribution is supplied by nature.
Agriculture does something profound to the learning problem: It changes the environment.
Fields stabilize locations. Planting stabilizes cycles. Domestication alters organisms. Irrigation alters water availability. Storage alters time. Property regimes and markets stabilize incentives.
Humans did not merely become better at learning nature. They made nature easier to learn.
The wild game becomes domesticated.
Eventually industrial agriculture pushes large portions of the process toward automaticity: standardized breeds, standardized feed, controlled environments, mechanized planting and harvesting, precisely measured yields.
Then the game moves upward.
Instead of merely optimizing how an organism is cultivated, we begin optimizing the organism itself. Selective breeding becomes genetics becomes genomic selection and genetic engineering.
The old player becomes a game piece.
It is tempting to map this progression onto contemporary machine-learning terminology. Hunting looks vaguely like reinforcement learning in a difficult environment. Agriculture introduces something like shaped rewards and a controlled training distribution. Factory farming begins to resemble a regime of relentless verification against measurable outputs.
The analogy should not be pushed too literally. Human cultures have always involved teaching, imitation, norms and complicated reward systems.
But structurally the direction is unmistakable: increasing control over the state representation, action space, feedback signal and training distribution.
Commerce underwent another version of the transformation.
Exchange begins embedded in relationships, obligations, reputation, kinship and local knowledge. Credit can be intensely personal. Value is contextual.
Money performs an astonishing act of compression.
Heterogeneous goods and obligations become comparable through a common medium. Markets then stabilize arenas in which repeated exchange produces prices. Accounting makes states more legible. Contracts formalize future obligations.
Eventually finance builds games on top of the game.
A derivative can be a claim on the future value of another asset. Options put prices on possible future prices. Markets become arenas for expectations about expectations.
Play moves upward.
None of this required artificial intelligence. Humans have been turning wildernesses into games for thousands of years.
What AI changes is the cost of achieving playability in a domain.
Historically, making a domain playable was expensive. Somebody had to invent the categories. Somebody had to measure the variables. Somebody had to standardize the procedures. Somebody had to construct the institutions that made interactions repeatable.
And the resulting representation had to be relatively explicit because ordinary software was brittle.
Machine learning relaxes that requirement…
Rao muses on where this effect might accrue…
Coding is perhaps the clearest domain currently passing through the transition.
Programming was unusually playable before generative AI arrived.
Compilers already supplied verifiers. Type systems constrained legal moves. Unit tests supplied rewards. Version control recorded trajectories. Continuous integration repeatedly evaluated outcomes. Package ecosystems created enormous libraries of reusable moves.
Generative coding systems arrived in a landscape generations of programmers had inadvertently prepared for them.
As implementation becomes cheaper, the game moves upward toward specifications, architectures, product decisions and the increasingly important question of what software should exist in the first place.
Robotics is a more difficult frontier.
The physical world is phenomenologically unruly. Objects deform. Friction varies. Things break. Lighting changes. People walk into rooms. Drawers stick.
Simulation, cheap sensors, multimodal models and increasingly capable world models are gradually making physical environments more playable, but reality continually leaks through the representation.
This is why robotics may be one of the most important tests of the Curiously Playable Universe hypothesis.
Can enough of ordinary physical reality be compressed into stable learned representations to permit the same cycle of domestication and automation?
Science will probably fragment according to playability rather than according to our traditional rankings of intellectual difficulty.
Protein structure turned out to be unusually playable.
Drug discovery is less so because chemical promise must survive biology, organisms, clinical trials and human heterogeneity. Materials discovery may become increasingly playable through the combination of simulation and automated laboratories. Ecology may remain stubbornly wild because every useful abstraction excludes interactions operating at another scale.
Medicine contains both extremes. Image interpretation and molecular design can be made relatively game-like. Caring for an elderly person with five interacting conditions, family constraints and changing preferences is another matter.
Governance may become a particularly strange frontier.
States have spent centuries making populations legible through names, addresses, laws, property records, taxes, censuses, bureaucratic categories and standardized procedures. In that sense the modern administrative state is already a vast game-making machine.
AI will make more of its internal operations automatic.
But political systems contain an unusual source of wilderness: the pieces know they are pieces.
People respond strategically to measurements, categories and incentives. A rule changes the behavior it was intended to regulate. A metric becomes a target and stops being a good metric (Goodhart’s Law). Political actors learn to play the machinery designed to make them legible.
This may push governance upward toward new games involving states themselves: transnational protocols, financial systems, supply chains, standards regimes, platform governance and other structures that do not fit comfortably inside the old nation-state game board.
Some domains may resist for much longer.
Child-rearing is difficult to make playable because the objective changes as the child changes. Friendship has no stable score. Diplomacy involves adversaries whose models include models of your model of them. Entrepreneurship often consists precisely of discovering a game nobody realized existed.
Frontier science operates where we do not yet know which measurements matter. Cultural creation is evaluated by audiences who change partly because of the works being evaluated. Political legitimacy is altered by attempts to measure and optimize it.
These are not necessarily domains AI cannot enter. They are domains in which the wilderness fights back…
He continues…
… We keep asking what it means that machines can now play chess, write programs, fold proteins, prove theorems, steer robots and discover molecules. The question presumes that the remarkable new object is the machine—that some mysterious substance called intelligence has finally become “general” enough to flow from one human province into another.
But perhaps the stranger discovery concerns the provinces: Wildernesses can be reliably turned into game boards. We domesticate the territory, become skilled at its game, build machinery that plays it better than we can, and move outward to construct another game around the first, domesticating a larger scope.
This happened to fields and livestock long before it happened to chess. It happened to trade before it happened to programming. It happened to mechanics before it happened to mathematical proof.
Artificial intelligence did not invent this strange property of reality. It is merely making it difficult not to notice.
The deepest surprise of the AI era may turn out not to be that intelligence was easier to manufacture than we thought. It may be that the universe is far more playable than we imagined…
And he concludes with a consideration of writing…
… Writing sits somewhere awkwardly in the middle of the playability spectrum. It is obviously more playable than friendship or political legitimacy. There are stable artifacts, accumulated techniques, recognizable genres, repeatable operations and abundant feedback. Sentences can be revised. Arguments can be tested for consistency. Stories can be checked for continuity. Editors can compare two versions and usually say something useful about why one works better.
But writing lacks the feature that makes Lean such an extraordinarily good game board: a verifier. There is no kernel that accepts Middlemarch and rejects a bad novel. The relevant state is incompletely represented, the available moves are effectively unlimited, and the reward function wanders around outside the text in readers, institutions, historical circumstances and cultures that change partly in response to what gets written. Recent attempts to extend verifiable-reward techniques to writing therefore have to manufacture approximate evaluators out of principles and pairwise judgments rather than simply checking an answer. Writing is playable, but imperfectly and unevenly so.
The unevenness is becoming easier to see because AI is revealing which kinds of writing were already more game-like than we realized. A corporate memo, SEO article, product description, technical explanation or conventional news report has relatively strong constraints: purpose, audience, format, facts, length, house style, perhaps measurable outcomes. Formulaic genre fiction has a looser but still recognizable game board of beats, tropes, pacing, character functions and reader expectations. Even fiction once assumed to depend heavily on irreducible human voice is proving surprisingly susceptible to systematic generation and variation. Writing is not one game but a family of wilderness activities at very different stages of domestication.
At the other end lies writing whose purpose is partly to alter the terms by which it will be judged. As Walter Benjamin observed, “all great works of literature establish a genre or dissolve one.”
A genuinely new literary form, a strange essay, a foundational work of philosophy, or a piece of criticism that gives its readers a concept they did not previously possess cannot simply optimize against an existing reward function. Its success may consist in creating a new one. This is writing at its most wilderness-like, and perhaps why arguments about AI writing become confused when “writing” is treated as a single capability. Producing competent prose, satisfying a genre contract, developing an argument and inventing a form are different games with different degrees of playability…
… The meta-game emerging above writing may therefore involve constructing—and strategically revealing—the game boards on which execution takes place. If competent prose becomes cheap, more resources can be directed toward finding the question, assembling unlikely source domains, inventing the useful distinction, designing sequences of inquiry, recognizing when an analogy is productive, deciding what belongs together, and establishing the criteria by which a finished object ought to succeed. The writer becomes somewhat less like a person manufacturing sentences and somewhat more like an architect and player of generative constraints.
That does not mean prose becomes irrelevant. A game board badly realized is still a bad essay, just as a brilliant architectural plan does not eliminate the need for a building. Nor does it mean the higher-level activity is permanently reserved for humans. AI systems may themselves become increasingly capable of inventing representations, designing probes, discovering genres and constructing new games. The point is only that automaticity at one level does not end the activity. It displaces its frontier.
Writing may therefore be undergoing the same transition described throughout this essay, only messier and in public. Some of its old games are becoming startlingly playable. Some are approaching automaticity. New games are forming above them. And beyond those remains the poorly mapped territory from which the next game board might emerge…
Eminently worth reading in full: “The Curiously Playable Universe,” from @vgr.bsky.social.
And further: “Our Eukaryotic Moment,” in which Rao urges us to keep our minds open– to resist “premature ontological closure in conceptualizing AI.” A taste:
… About two billion years ago, life underwent a change in architecture. Until then, the planet was ruled by relatively simple prokaryotic cells: bacteria and archaea, tiny packets of chemistry bounded by membranes, carrying their genetic material directly in the same cellular space where much of the business of life took place.
Then something happened, or rather, several things happened in an order that remains uncertain. At some point, an ancestral archaeon cell entered into a permanent symbiosis with a bacterium capable of unusually powerful energy metabolism.
That bacterium eventually became the mitochondrion.
Somewhere in the same long evolutionary transition, genetic material became enclosed within a nucleus, separating the storage and regulation of hereditary information from much of the cell’s everyday chemistry. Internal membranes proliferated, cytoskeletons became more elaborate, and a new kind of cell emerged: the eukaryote….
… Eukaryotic cells became larger, more internally differentiated and capable of forms of organization unavailable to their ancestors. Much later, and independently in several lineages, some evolved multicellularity. Cells themselves became components of larger entities, differentiating and cooperating in increasingly elaborate ways. From the eukaryotic architecture eventually came forests, mushrooms, octopuses, hummingbirds, whales and us.
Eukaryotes were more than just “better bacteria.” They represented a different organization of life, capable of sustaining far more complex structures..
We may be living through an analogous transition now. The emergence of AI, in the particular form that it has appeared (deep learning), is arguably the eukaryotic moment in human cultural evolution, understood in memetic terms, with humans playing the role of mitochondria, and AI the role of the nucleus…
Meantime: “After We Stop Grieving AI: Cyborgs, Centaurs and Cyberpunks” (via Patrick Tanguay) See also: “Diving Deeper Into Digital Transformation” from John Hagel (source of the image above).
As the estimable Tim O’Reilly suggests, we’d probably be wise to take a breath, to treat AI as a “normal technology”: “Technology doesn’t force us… it merely opens the door.”
* Rainer Maria Rilke, Sonnets to Orpheus, Part Two, XII
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As we crane to conceive what’s beyond our cocoon, we might recall that it was on this date in 1947 that the Association for Computing Machinery (or ACM) was founded. In one sense, computer science dates back to the 17th century and the mechanical calculators of Wilhelm Schickard and Gottfried Leibniz; in another, to the Difference and Analytical Engines of Charles Babbage (and the “programming” of Ada Lovelace). But the ACM can claim to be at least a key stone in the foundation of the field we now knw as “Computer Science”– the first modern “learned society” devoted to the emerging field. (Computer Science began to be established as a distinct academic discipline in the 1950s and early 1960s. The world’s first computer science degree program, the Cambridge Diploma in Computer Science, began at the University of Cambridge Computer Laboratory in 1953. The first computer science department in the United States was formed at Purdue University in 1962.)
“Life is more fun if you play games”*…
David Freidman ponders scientific satire…
I first encountered the scientific paper simply titled “Strapless Evening Gowns” four years ago, when I was flipping through a collection of magazines that once belonged to the cybernetics pioneer Norbert Wiener.
Among his magazines was the May 1960 issue of Voo Doo magazine, which was MIT’s “only intentionally humorous campus publication” going all the way back to 1919.
I got a chuckle out of this article, which attempted to semi-seriously analyze what exactly keeps a strapless dress from falling down:
Scientists have a long history of amusing themselves with humor. In addition to Voo Doo, other science humor magazines include the Annals of Improbable Research, the Journal of Irreproducible Results, and the Worm Runner’s Digest which included both satirical and serious scientific papers, much to the confusion of their readers – a problem eventually solved by printing the satirical articles upside down.
And then there are the quasi-serious scientific studies meant to be amusing, such as this study on the effectiveness of tin foil hats in protecting you from government surveillance (spoiler: tin foil hats can actually amplify certain radio frequencies, so the authors speculate that the government has been behind promotion of tin foil hats all along).
And back in 1974, the Journal of Applied Behavior Analysis published a paper by clinical psychologist Dennis Upper called “The Unsuccessful Self-Treatment Of A Case Of Writer’s Block” [pictured at the top]. And lest you question the veracity of the author’s finding, I should note that the author’s failure to treat his writer’s block has been successfully replicated…
Read on for more on the engineering of the formal dress, both the social (largely sexist) context and the (interestingly meaninful) scientific content– and the art it has inspired: “Science And The Strapless Evening Gown” from @ironicsans.com.
More seriously: “a Nature analysis signals the beginnings of a US science brain drain“: “Researchers in the United States are seeking career opportunities abroad as President Donald Trump’s administration slashes science funding and workforce numbers, finds an analysis of Nature’s jobs-board data…”
* Roald Dahl
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As we play, we might recall that it was on this date in 1961 that Robert Noyce was issued patent number 2981877 for his “semiconductor device-and-lead structure,” the first patent for what would come to be known as the integrated circuit. In fact another engineer, Jack Kilby, had separately and essentially simultaneously developed the same technology. Ineligible (as a new Texas Instruments empoyee) for a vacation over the summer of 1959, he gave himself the “assignment” of creating “a body of semiconductor material … wherein all the components of the electronic circuit are completely integrated.”
Kilby’s design was rooted in germanium; Noyce’s in silicon and had filed a few months earlier than Noyce. But Kilby’s invention was not a true monolithic integrated circuit chip since it had external gold-wire connections, which would have made it difficult to mass-produce– an obstacle Noyce overcame. Still, Kilby’s contribution was recognized in 2000 when he was Awarded the Nobel Prize– in which Noyce, who had died in 1990, did not share.
“Man’s most serious activity is play”*…
Until the mid-20th century, the “playing fields” on board games tended to be composed of squares; then hexagons emerged. Jon-Paul Dyson explains why…
A board game begins with the board. But how is that board divided up? Often the simplest unit of division is a square. Consider the 64 squares of a chess board, or the 92 squares on a Stratego board. In each case, players take control of a square which exists in relation to other spaces around it, especially if they share adjoining borders. The design of these game boards affords or encourages certain types of movement, usually horizontally or vertically (in four directions) or in some cases diagonally in eight directions (as with the bishop in chess).
And yet there exists a problem with this sort of layout in any game that allows freedom of movement, because the connection between these squares is uneven. Although squares share a long border horizontally and vertically, they do not share such a border on the diagonal connections. In a game like chess, where you physically pick up a piece to move it, this is not much of an issue. But as simulation board games began to develop after World War II, this proved more problematic. Many of these games involved sliding pieces (or cardboard tiles that were frustrating to pick up) from square to square, like army units occupying territory. For these situations, hexagonal spaces that provided equal movement in six directions, produced a better solution.
As is true throughout the history of innovation, whenever there is a problem, it usually turns out that multiple people arrive at similar inventive solutions. That was the case with the development of the hex as a basic unit of division in board games.
Piet Hein [see here], a Danish polymath, who was a quantum physicist as well as a designer, poet, and puzzle and game inventor, came up with the idea in 1942 for a game in which players competed to create connected lines across a game board made up of hexagonal spaces. Thus he might be credited as the father of hex. Yet in the late 1940s, American mathematician John Nash (the subject of the movie A Beautiful Mind) independently invented a similar game at Princeton that also used hex tiles [though we should note that it was a variation on the Shannon switching game, created by Claude Shannon sometime before 1951]. In 1952, Parker Brothers released a version of the game which they called Hex.
This was a time of post-war prosperity when people increasingly had the discretionary income to buy board games, but it was also a period when the United States and the Soviet Union, allies during the war, had become bitter rivals locked in a Cold War. Rather than downsizing after the victory over Germany and Japan, the American military complex shifted from fighting the Axis powers to planning for a major conflict with the Soviet Union and engaging in a series of smaller wars such as that fought in Korea. To help plan American strategy, the Army Air Force and the Douglas Aircraft Company created the Rand Corporation, a think tank that made significant contributions to American policy and computing.
One of the projects the Rand Corporation focused on was modeling conflict through the use of war games. To that end Alexander Mood, a staff member at the Rand Corporation, introduced a honeycombed, hex-shaped board that allowed pieces to move in six directions rather than just four. John Nash was at the Rand Corporation and, in a 1952 paper he coauthored entitled “Some War Games,” he and coauthor R. M. Thrall described using this hex-based system for ground and air games.
It was another game creator, however, who took this development and made the most significant contribution to the development of hex-based games: Charles S. Roberts. Roberts was an army veteran who in 1954 published Tactics, a military simulation board game that is often credited as the first modern wargame. Roberts then founded the game company Avalon Hill, and his games and their innovative simulation of battlefield odds drew the attention of the Rand Corporation because his Combat Results Table for determining the outcome of battles mirrored systems they had developed. The Rand Corporation invited Roberts to visit, and supposedly while he was there he noticed their use of hex-based boards.
Recognizing the superiority of a hex-based system for simulating movement, Roberts began using it in game design in 1961. That year was the centennial of the American Civil War, and so there was a demand for historical simulations. Roberts redesigned his recently released game Gettysburg with the new hex pattern. The Strong owns copies of Gettysburg belonging to Roberts, both in the older square format and in the revised hex version. He also used it for the Avalon Hill game Chancellorsville, another Civil War simulation. Soon the hex system became commonplace in a high proportion of wargames, as well as in more mainstream games such as the 1969 release Psyche-Paths.
Since then, hex board layouts have been used in a wide variety of games. Settlers of Catan is perhaps the most famous example, but plenty of others exist including the spaces in the game Hero Scape. Even video games will often use the hex layout, not only in wargames but in titles such as in Sid Meier’s Civilization V…
“Hex Marks the Spot,” from @jpdysonplay and @museumofplay.
* George Santayana
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As we make our moves, we might send playful birthday greetings to Seymour Papert; he was born on this date in 1928. Trained as a mathematician, Papert was a pioneer of computer science, and in particular, artificial intelligence. He created the Epistemology and Learning Research Group at the MIT Architecture Machine Group (which later became the MIT Media Lab); he directed MIT’s Artificial Intelligence Laboratory; he authored the hugely-influential LOGO computer language; and he was a principal of the One Laptop Per Child Program. Called by Marvin Minsky “the greatest living mathematics educator,” Papert won a Guggenheim fellowship (1980), a Marconi International fellowship (1981), the Software Publishers Association Lifetime Achievement Award (1994), and the Smithsonian Award (1997).
A champion of fun and games in learning, Papert was the brain behind Lego Mindstorms.
“Mankind is poised midway between the gods and the beasts”*…
Julius Caesar, who was deified by the Roman Senate this week in 42 BCE
At least, most of mankind. Anna Della Subin on men turned divine…
In the beginning, it was the serpent who first proposed that mankind might become divine. Ye shall be as gods, he advised, as the fruit waited…
The idea that a man might turn divine, even without intending or willing it, was to ancient Greece a natural and perfectly rational occurrence. Traffic flowed between earth and the dwelling place of the gods in the sky. In his Theogony, the poet Hesiod sang of the births of gods in a genealogy often crossed with that of humans. He told of mortals who became daemons, or deific spirits; of the half-gods, born of mixed parentage; of the man-gods, or heroes, venerated for their deeds. The theorist Euhemerus claimed he found, on a desert island, a golden pillar inscribed with the birth and death dates of the immortal Olympians. According to his hypothesis, all gods were originally men who had once lived on earth, yet their roots did not impinge upon their cosmic authority, nor make them any less divine. The ranks of the gods swelled with warriors and thinkers, from the Spartan general Lysander to the materialist philosopher Epicurus, deified after his death. In his Parallel Lives, the biographer Plutarch recorded that someone among the older, established gods was evidently displeased by the newcomer, Demetrius. A whirlwind tore apart Demetrius’s robe, severe frost disrupted his procession, and tendrils of hemlock, unusual in the region, sprouted up around the man’s altars, menacingly encircling them.
In ancient Rome, the borders between heaven and earth fell under Senate control, as deification by official decree became a way to legitimize political power. Building upon Greek traditions of apotheosis, the Romans added a new preoccupation with protocol, the rites and rituals that could effect a divine status change. For his conquests, Julius Caesar was divinized, while still alive, by a series of Senate measures that bestowed upon him rights as a living god, including a state temple and license to wear Jupiter’s purple cloak. Yet if it seemed like a gift of absolute power, it was also a way of checking it, as Caesar knew. One could constrain a powerful man by turning him into a god: in divinizing Julius, the Senate also laid down what the virtues and characteristics of a god should be…
The century that reset time began with a man perhaps inadvertently turned divine. It is hard to see him, for the earliest gospels were composed decades after his death at Golgotha, and the light only reaches so far into the dark tombs of the past. The scholars who search for the man-in-history find him embedded in the politics of his day: a Jewish dissident preacher who posed a radical challenge to the gods and governors of Rome. They find him by the banks of the Jordan with John the Baptist. He practices the rite of baptism as liberation, from sin and from the bondage of the empire that occupied Jerusalem…
In the decades after the crucifixion, just as the gospels were being composed and circulated, the apotheosis of Roman emperors had become so routine that Vespasian, as he lay on his deathbed in 79 CE, could quip, ‘Oh dear, I think I’m becoming a god.’…
In 325 CE, the emperor Constantine gathered together two thousand bishops at the Council of Nicaea to officially define the nature of Jesus’s divinity for the first time. Against those who maintained he had been created by God as a son, perfect but still to some extent human, the bishops pronounced Jesus as Word Incarnate on earth, equal to and made of the same substance as God the Father, whatever it may be. Other notions of Jesus’s essence were branded as heresies and suppressed, and gospels deemed unorthodox were destroyed. Through the mandates of the Nicene Creed, the idea of divinity itself became severed from its old proximities to ordinary mortal life. In the work of theologians such as Augustine, who shaped Christian orthodoxy for centuries to come, the chasm between humankind and divinity grew ever more impassable.
Though mystics might strive for union with the godhead, veiled in metaphors, the idea that a man could transform into an actual deity became absurd. God is absolutely different from us, the theologians maintained; the line between Creator and His creation clearly drawn.
Eminently worth reading in full: “First Rites,” a fascinating excerpt from Accidental Gods, by @annadella in @GrantaMag.
* Plotinus
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As we delve into the divine, we might recall that it was on this date in 1953 that Samuel Beckett’s Waiting for Godot premiered in Paris. The English-language version premiered in London in 1955. In a poll conducted by the British Royal National Theatre in 1998/99, it was voted the “most significant English-language play of the 20th century.”
Waiting for Godot, Theatre de Babylone–the first performance (source)
“Toys are intriguing… they represent one way that society socializes its young”*…
And, as Greg Daugherty explains, that process was accelerated in the second half of the last century…
World War II gave rise to countless innovations that would change American life for decades to come—from the rugged Jeep, to mass-produced penicillin, to the terrifying atomic bomb. But, ironically enough, few U.S. industries were more profoundly affected by the war than the toy business.
Not only were toy and game designers and makers able to take advantage of the latest scientific advances, such as colorful and inexpensive plastics; they also benefited from two other post-war trends. The baby boom—more than 76 million kids born between 1946 and 1964—offered them record numbers of potential customers. And television, little more than a novelty before the war, soon made it possible to demonstrate the latest playthings to millions of kids at a time. Little wonder that toy sales grew from $84 million in 1940 to $900 million by 1953 and into the billions of dollars in by the early 1960s…
The ascendance of plastics and television forever changed an industry– and our culture: “How Toys Changed After World War II,” from @GregDaugherty1 in @HISTORY.
Mr. McGuire : I just want to say one word to you. Just one word.
Benjamin : Yes, sir.
Mr. McGuire : Are you listening?
Benjamin : Yes, I am.
Mr. McGuire : Plastics.
Benjamin : Exactly how do you mean?
Mr. McGuire : There’s a great future in plastics. Think about it. Will you think about it?
From The Graduate, written by Calder Willingham and Buck Henry (from the novel by Charles Webb); directed by Mike Nichols
* David Levinthal (a photographer whose work centers toys)
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As we play, we might note that today is the celebration of the 2022 inductees into the Toy Hall of Fame at the Strong National Museum of Play… two of the three honorees are plastic toys heavily advertised on television in the 60s, 70s, and 80s.
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