“Who would want the future to be the endless repetition of the past?” Some new level of machine-biology evolution is coming, suggests Karen Bakker and Mark C. Taylor
We admire Noema magazine (from the Berggruen Institute in LA) for crossing boundaries and binaries with persistence and rigour. Two recent pieces there try and weave the digital and the ecological/natural together.
The first is a threnody to the late Karen Bakker, a scientist who was trying to use AI to decode the speech patterns of whales and other creatures, in order to communicate with them in their own language (see her TED talk bel0w). Noema has posthumously published a prose-poem of hers, reprinted here:
Parable Of Tree And Stone
Long before dinosaurs roamed our planet, in a time called the Carboniferous, a tree was born.
A seed fell to Earth, rooted in swampy soil, grew over a hundred feet tall and a hundred years long. When the tree died, its body became home to cockroaches as big as house cats, and dragonflies with wings as wide as hawks.
Bacteria fed on the rotting wood, and mosses grew. Covered by Earth’s blanket, the tree’s body sunk deep, compressing into coal, a slow-motion burial.
Millenia later, the coal was unearthed, heated, deprived of oxygen, splintered into plastic pellets, liquified and poured into molds, and polished into small black jewels. Tree, reborn: the keys on my computer.
The stone is even older than the tree.
In Precambrian time a volcano rift opened, and lava flowed from Earth’s core. Cooled by rain, the lava sunk deep, compressing into stone. Millennia later, the stone was lifted from a mine shaft, crushed and bathed in caustic fluid, liquefied and poured into molds, and polished to a shine as sharp as a knife. Stone, recast: the casing for my computer, cradle for the keys.
In deep time, trees and stones are descended from stars.
Tree once drank sunlight and mixed it with air, storing energy for future generations. Stone was forged in the furnace of a long-ago star which — with the cosmic clap of a supernova — dispersed itself as stellar dust, the raw ingredient of our planet. These are the ancestors of our digital devices:
Mother Tree, Father Stone, Grandmother Star, Grandfather Time.
Our computers, then, are made of stardust and tree flesh. Their memories live on machines whose breath warms the sky. Our digital devices are ecological, our ecologies are growing digital.
The second Noema piece, deliberately and provocatively blurring the ecological and the digital, comes from the professor of religion, Mark C. Taylor, titled ‘After The Human’. He suggests “four trajectories that will be increasingly important for the symbiotic relationship between humans and machines: neuroprosthetics, biobots, synthetic biology and organic-relational AI.”
Neuroprosthetics: “Neither neuroprosthetics nor cognitive augmentation is new. Writing, after all, is a mnemonic technology that enhances the mind. In modern times, we have been enabled to archive and access memories through personal devices.” Yet do we need to go down the Musk route of neuro-linking ourselves to machinery? What of empathy being fired by mirror neurons? Or mindfulness and therapy enhancing compassion for others, based on a more accurate accounting for memory and trauma?
Biobots: robots may seem like the crank in the attic of AI - less agile, autonomous and problem-solving than a human four-year-old. But Taylor reports on Google’s latest robot RT-2, which can:
…interpret images and analyze the surrounding world. It does so by translating the robot’s movements into a series of numbers — a process called tokenizing — and incorporating those tokens into the same training data as the language model. Eventually, just as ChatGPT or Bard learns to guess what words should come next in a poem or a history essay, RT-2 can learn to guess how a robot’s arm should move to pick up a ball or throw an empty soda can into the recycling bin. Thus, rather than programming a robot to perform a specific task, it is possible to give the robot instructions for the task to be performed and to let the machine figure out how to do it.
Synthetic biology: Quite the most challenging, even scary, of the bio-machine cross over. We hear of Micheal Levin’s xenobots, explained as “a scalable pipeline for creating functional novel lifeforms…AI methods automatically design diverse candidate lifeforms in silico to perform some desired function. Transferable designs are then created, using a cell-based construction toolkit, to realize living systems with predicted behaviour.”
Eva Jablonka, who is an evolutionary biologist at Tel Aviv University, believes that xenobots are a new type of organism, one “defined by what it does rather than to what it belongs developmentally or evolutionarily.” The good/bad, sane/mad intent of who is designing/”defining” the function of these bots is, as ever, paramount. A god-like tool, in the hands of palaeolithic emotions?
Organic-relationial AI: a difficult section. But Taylor seems to be suggesting a new kind of artificial intelligence. Not an AI that advances by crunching knowledge and then simulating our thoughts. But one whose code operates like a brain in relation to its proteins, where experiences trigger biochemical developments, assembling its neural structures moment by moment.
“The brain doesn’t come into being fully wired with an ‘empty network,’ all ready to run, just without information,” Hiesinger writes. “As the brain grows, the wiring precision develops.” This creates a feedback loop that never stops and, therefore, the algorithmic growth of biological networks is continuous. Continues Taylor:
Hiesinger proposes that the self-assembly of the brain’s neural network provides a more promising model for AI than either symbolic AI or ANNs. The successful creation of evolving networks and algorithms would create an even closer symbiotic relationship between the biosphere and the technosphere.
One of the concerns about developing “organic” AI is its unpredictability and the uncertainty it creates. Human control of natural, social and cultural processes is, however, an illusion created by the seemingly insatiable will to mastery that has turned destructive.
As Hiesinger correctly claims, “An artificial intelligence need not be humanlike, to be as smart (or smarter than) a human.” Non-anthropocentric AI would not be merely an imitation of human intelligence, but would be as different from our thinking as fungi, dog and crow cognition is from human cognition.
Taylor lays down a final challenge:
Machines are becoming more like people and people are becoming more like machines. Organism and machine? Organism or machine? Neither organism nor machine? Evolution is not over; something new, something different, perhaps infinitely and qualitatively different, is emerging. Who would want the future to be the endless repetition of the past?
More here. And all of this is open, of course, to the entirely justified charge: That religion and spiritual traditions, in all their global diversity, have imagined an animate and evolving universe, with consciousness and intent penetrating the material and the biological, for many millenia…