In December 2023, American regulators approved a medicine called Casgevy, the first therapy to treat a genetic disease by editing a patient’s own DNA. It rested on a laboratory technique that didn’t exist two decades earlier, and it pointed to something larger than a single cure: biology had become a technology that can be engineered, deliberately, to a specification. It’s a capability that has led to biology’s inclusion in a very select list.
The list is the set of civilization-level technologies, the handful of capabilities so foundational that whole societies come to depend on them. Economists have kept a similar tally for years under the name «general-purpose technologies,» and for two centuries it ran to steam, electricity, the internal combustion engine and, more recently, information technology.
Biology was not on that list. For most of its history, the field was observational, a matter of describing life rather than building with it. But it is on the list now, and, with the ability to directly impact the nature and health of living organisms, it may be the most consequential entry of them all.
Why Biology Was Left Off
Biology’s historical absence from the discussion of civilization-level technologies followed from how the field’s power was structured, not from any failure of imagination. Biology has produced applied triumphs for a century, from vaccines and antibiotics to the first recombinant-DNA drugs, such as synthetic insulin, around 1980, and those advances saved millions of lives. But most of them came from discovering and harnessing what living systems already did, or from slow, one-off feats of engineering, rather than from a general ability to design and rewrite genetic code.
A civilization-level technology has to be something many other industries can build on cheaply and reliably, and for most of the twentieth century biology offered profound discovery and specific cures more than that kind of programmable infrastructure.
The pattern held even through the field’s celebrated breakthroughs. The structure of DNA was solved in 1953, and the human genome was mapped by 2003, yet for decades reading and understanding life ran well ahead of the ability to rewrite it for the greater good. Genetic engineering existed, but it was narrow, slow, and expensive. Understanding a system, and even tinkering with it, is not the same as being able to design and build with it at scale and with a controlled, safe approach.
From Reading Life to Writing It
Three curves crossed within a single generation. The cost to sequence a human genome collapsed from about $95 million in 2001 to a few hundred dollars. Genetic reading went from a national project to a routine lab expense. In 2012, researchers showed that the bacterial system CRISPR-Cas9 could be programmed to cut DNA at chosen locations. Precise gene editing came within reach of ordinary laboratories.
And artificial intelligence became biology’s force multiplier: DeepMind’s AlphaFold predicted the shapes of some 200 million proteins, nearly every one known to science, work that won the 2024 Nobel Prize in Chemistry and compressed years of experiments into afternoons. Reading, writing, and modeling life all became relatively inexpensive at once.
| General-purpose technology vs. civilization-level technology. General-purpose technology is an established concept in economics, describing a technology (the steam engine, electricity, the computer) marked by broad applicability across industries, steady technical improvement, and innovation complementarities, meaning progress in it drives progress everywhere else. Civilization-level technology is the broader, less formal category this series uses. It includes what a general-purpose technology does economically, but also takes in a technology’s effect on institutions, geopolitics, infrastructure, and daily life. Every general-purpose technology is civilization-level; not every civilization-level technology fits the stricter economic definition. |
Artificial Intelligence Meets the Genome
The convergence runs deeper than prediction. David Baker, who shared the 2024 chemistry prize, develops computational methods for designing proteins that don’t exist in nature. His lab has used those methods to create novel enzymes, molecular binders and protein components for experimental vaccines, although the resulting designs still require extensive laboratory testing and refinement.
Pharmaceutical companies now use machine-learning models to screen and even generate candidate drugs, work that once took years. The same computational methods that taught AlphaFold to read a protein’s shape are being turned toward writing new ones. Two of the five pillars, biology and computing, are increasingly the same project when it comes to revolutionary medicine, and each accelerates the other. Drug discovery can run on a continuously improving loop: a model proposes a molecule, a lab builds and tests it, and the results train the next model.
The Reach of Engineered Biology
What makes biology civilization-level is the sheer breadth of what those tools touch. In medicine, gene and cell therapies built on CRISPR have moved from theory to approved treatments, with companies such as Vertex and CRISPR Therapeutics turning edits into cures.
Casgevy alone offers a potential functional cure to some of the roughly 100,000 Americans living with sickle cell disease, an option that did not exist a decade ago. In manufacturing, firms are programming cells to make chemicals, fuels, and materials that were once refined from petroleum: Ginkgo Bioworks runs an automated foundry for cell programming, while Twist Bioscience manufactures synthetic DNA the way a fab prints chips. Agriculture is being rewritten through gene-edited crops that resist disease and drought and through microbes engineered to fix nitrogen, which cuts the need for synthetic fertilizer. Materials from plastics to leather and textiles are increasingly grown in vats from engineered cells rather than drilled or farmed for.
The economic weight of that shift is hard to overstate. McKinsey estimates that biological methods could eventually account for as much as 60% of the physical inputs to the global economy, and generate up to $4 trillion a year in direct economic impact over the next decade or two. A capability that reaches medicine, food, materials, energy, and the climate at the same time behaves less like an industry than like infrastructure.
In the United States alone, biomanufacturing already accounts for hundreds of billions of dollars in annual output, and the industry is still in early stages. Each civilization-level technology has had a moment when its central capability crossed from demonstration into dependency. The evidence suggests biology is crossing that line now.
The biological toolkit responsible for medical and environmental advances is also being applied to animal conservation. Colossal Biosciences combines gene editing, computational biology and reproductive technology to read, write and restore genomes, and applies them to conservation: it is helping build a national genetic biobank for endangered species and working to rebuild populations that are threatened or already lost. Biological technology now stretches from curing a child’s blood disorder to banking the genome of a vanishing species.
The Living Pillar
What put biology on the list is the way several capabilities arrived together: it now works at the scale of whole economies, other industries are starting to build on it, and cheap reading, cheap writing and machine learning keep compounding one another. Health, food, materials and energy are beginning to route through biological methods rather than chemical or mechanical ones. The same toolkit turns up in a medicine, a material, a crop, and a threatened species alike, and few technologies reach into so many parts of life at once.
Energy, space, computing, and artificial intelligence reshaped what societies could do to the industrial world around them. Biology reshapes the living world itself, including us.
The first CRISPR cure and the first billion-dollar conservation platform are early markers, not endpoints. If the twentieth century was built on steel, silicon and code, a growing share of the twenty-first could be grown through the design of life itself.
