The Real Story of What Got Us to the Top of the Food Chain
Natural "narrative selection" was key to turning insignificant apes (who had tools for 2 million years) into the species that now dominates the bio-sphere.
1. What got us to the top of the food chain? Yuval Harari says it wasn’t bigger brains and tools. His view of what mattered will surprise fans of evolution’s red-in-tooth-and-claw story.
2. Going from “stone-tipped spears to… spaceships” took us ~20,000 years; meanwhile, our brains have shrunk ~10% (note: Neanderthal brains were bigger).
3. But we’ve had tools for ~2 million years (intelligently designed tools have long shaped our genes).
4. Harari says the “crucial factor” was our unique capacity “to cooperate flexibly in large numbers.”
5. Cooperation is critical for both types of what biologist E. O. Wilson calls “the social conquest of Earth.” Humans and social insects dominate the biosphere (because, organized groups can always outperform individuals, in combat, and in peacetime productivity).
6. Ants and bees were doing large-scale cooperation millions of years before us. But their cooperation is kin-based and inflexible (adapting genetically = slowly).
7. David Sloan Wilson calls teamwork humanity’s “signature adaptation,” but Harari describes how scaling beyond team-level cooperation was key.
8. This “large-scale human cooperation” requires shared stories, because “The human mind is a story processor, not a logic processor." Stories transmit what matters in a culture, and configure our “emotional grammar” (aside: Harari usefully calls emotions “biochemical algorithms”).
10. We live in a “web of stories” about what matters. In that sense artists and “storytellers run the world,” and a culture’s storytelling resources shape its politics and moralities (Alasdair MacIntyre).
11. Languages, stories, the arts, religions, moralities, politics, and economics are all social tools for organizing cooperation.
12. We’d be wiser to call ourselves “Homo Storius” or “Homo Narratus” or "Homo Socius" rather than Homo Sapiens (sapiens derives from judgement or taste). Our wisdom is story-driven and deeply social.
13. Stories, like all meaning, are relational (intrinsically social, not individual). We’re likely the most other-dependent species ever (inalienably self-deficient by nature). Those with life-structuring stories that are fittest for cooperation, win.
14. Our innate story-hunger enables what Rebecca Goldstein calls our “mattering instinct.” We’re driven to connect to cooperative projects greater than ourselves. If a community’s life-shaping stories don’t connect mattering to collective survival (and related needs), that community, and those stories, won’t survive.
15. The story that evolution is all about competition, overlooks widespread cooperation. Symbiosis isn’t rare, it’s the rule. Every “selfish gene” must cooperate. Every animal cooperates with billions of microbiome mates. Trees run redistributive social safety nets.
16. These cooperation-and-competition-mixing strategies face natural selection, and the most sustainably productive wins. Internal competition that hinders sustainable cooperation becomes self-defeating. Humans are how evolution exceeds the limits of individual competition and slow-changing genes.
17. A narrative-level natural selection is at work. Communities with story norms that help suppress destructive internal competition, survive better. History shows victory goes to those who “cooperated better.”
18. It’s clear we can’t live without tools. But it also took large teams and large tales to enable our cooperative survival and dominance. That’s the bigger story. That’s what matters.
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Illustration by Julia Suits, The New Yorker cartoonist & author of The Extraordinary Catalog of Peculiar Inventions
Science And Poetry Both Depend On Metaphors
Science's signature moves share something with good poetry. Good metaphor-making can make geniuses of both kinds. But bad metaphors can mislead whole fields.
1. Science, like poetry, depends on metaphors*. They can hide, sometimes causing mischief.
2. Science’s signature moves deploy two or more metaphors. Pythagoras’s “All things are number.” Plus at least one other, framing what the numbers mean (often tacitly, through tools or models).
3. Scientists should “think like poets and work like accountants,” E. O. Wilson advises. Useful number crunching builds on the poet's rarer skill of making good metaphors.
4. Good metaphor-making can make geniuses: Energy conservation is like balancing account-books (Joule). Evolution’s “struggle for existence” is like humanity’s economic struggles (Darwin).
5. But bad metaphors can mislead entire fields: People ≠ biological billiard balls. Economies ≠ gases. (Alarmingly, “economic poet” Gary Beck metaphorized—>family = “little firm,” kids = “durable goods,” heroin = bowling.)
6. Let the “data do the talking” (preach Freakonomics folk)? Alfred Marshall noted that can be “treacherous.”
7. You can’t always count on Pythagoras’s number-world move. For example many concepts in biology, economics, and social science (e.g., fitness, utility, happiness) don’t have the mathematical properties of mass or length. They don’t fit a ratio scale and aren’t as measurable (=weakens the utility of math).
8. Many are confused about how quantitative and qualitative relate; e.g., Nate Silver says that those not "quantitatively inclined” risk creating "a lot of bullshit."
9. But fruitful quantification requires sound qualitative distinctions, otherwise it risks increasing bullshit—>e.g., the average human has ~1 ovary + ~1 testicle. Mixed-types math can be fruitless (≠ apples-to-apples comparison).
10. Statistical methods are especially slippery number-world tools. They require that underlying phenomena have sufficiently stable representative patterns—valid for physical traits like height variation, but often not for behaviors (different kinds of variability).
11. Stats harbor new versions of old logic woes, like the fallacy of composition—projecting properties of parts onto wholes (e.g., apples are made of atoms, all atoms are invisible, therefore apples are invisible). And its opposite the fallacy of division (ascribes properties of wholes onto parts).
12. Consider data on shootings by police. Sendhil Mullainathan blunders in claiming that police racial bias has “little effect.” That’s a fallacy of division, assuming national data represent localities well. Conversely, Rajiv Sethi notes a statistical “fallacy of composition,” can stats from one city be of any use in any differently composed city?
13. Top researchers often mishandle stats, e.g. p-value cherry-picking (in medicine, economics, psychology), multiple regression (social sciences, randomized trials). And standard stats moves can’t always help. Randomization still drops the ball on average testicle counts, and more data doesn’t automatically overcome lumpiness (Mullainathan’s misstep).
14. Three distinct pattern types exist with intrinsically increasing levels of variability: see Newton vs. Darwin vs. Berlin patterns. And tools like statistics and algebraic equations yield more in physics than in social sciences.
15. For example, Diane Coyle calls the seemingly objective GDP a tarnished measure. It’s a badly built number, it doesn’t distinguish “bads” from genuine goods, and it omits all that isn’t sold (marry your housekeeper—>GDP declines).
16. The cult of calculation and data is seductive. And I’m no quantiphobe. But number crunching has no monopoly on precision or truth. Words, metaphors, non-numerical logic, images, and patterns can be exact and can exceed what numbers can do.
17. A desire to jump to “the numbers” isn’t always wise. We often shouldn’t ignore unquantifiable factors, or the metaphoric or qualitative weaknesses hidden in the number-world mindset.
*—Deep conceptual metaphors structure most of our thinking (George Lakoff).
Illustration by Julia Suits, author of The Extraordinary Catalog of Peculiar Inventions, and The New Yorker cartoonist.
