Ai and Biology

In this episode

The connection

Writing just days apart this August, two authors watch computer code collide with physical biology. In *Knowable Magazine*, Ben Deighton observes automated laboratories treating algorithms as a factory tool, turning the creation of new drugs into a pure software problem. But look at the same technology through another lens, and it stops being a factory and becomes a mirror. In *Noema*, Daniel Freeman shows how the arrival of thinking machines is pushing neuroscientists to hunt for human consciousness deep inside ancient brain structures. Side by side, a sharp contrast emerges—using artificial intelligence to manufacture new cells and molecules, versus using it to figure out the minds that built the machines in the first place.

Daniel Freeman leaves you in that fluorescent-lit office, staring at a chatbot and realizing that reasoning and language do not actually require a biological brain. By separating the mechanics of intelligence from the physical reality of human feeling, his argument changes how you look at a silicon chip. Then you turn to Ben Deighton. If Freeman treats artificial intelligence as a philosophical mirror to rethink human biology, Deighton watches it operate as a literal factory tool to manufacture it. Deighton takes you inside a former brewery in London where algorithms are doing something entirely different. They are designing cancer-killing molecules and programming yeast cells. Notice what happens when you put the two side by side. Freeman pulls cognition out of the biological brain to show that intelligence is just signal processing. Deighton takes that exact same signal processing and uses it to hack back into biology, turning the creation of living cells and medicines into an automated software loop. Read alongside Freeman, Deighton’s report from the biofoundry feels less like a standard technology update and more like the closing of a circle. Code is no longer just imitating biological life. It is actively engineering it.

What lingers after these pieces is the sharp contrast between a robotic arm mixing synthetic molecules and the ancient, soft tissue inside a human skull. In the automated lab, biology is treated as just another line of code waiting to be optimized. Yet in the brain, the rise of those same algorithms is forcing a search for the raw, unprogrammable ability to feel. The collision leaves a quiet uncertainty behind. If the physical body can be mastered as a software problem, what happens to the parts of a living mind that refuse to be engineered?