Aging Is an Engineering Problem | David Wood, LEV Foundation

What we talked about.

Sunny Ray talks with David Wood, a futurist and catalyst who chairs London Futurists and advocates for the LEV Foundation, about treating aging as an engineering problem rather than fate. Wood explains longevity escape velocity through a rocket analogy, where successive rounds of rejuvenation treatments buy enough healthy time for the next round to arrive. He traces his path from helping build the Symbian phone operating system to activism after encountering the ideas of Aubrey de Grey, Eric Drexler, Ray Kurzweil, and James Hughes. He argues that aging involves many types of damage, so combinations of therapies are needed, and describes the foundation's robust mouse rejuvenation experiments, including lessons from the first study and plans for the second. He also pushes back on the idea that death gives life meaning, calls for a war on aging modeled on the COVID response, and discusses where AI helps science and where it creates risk. He favors narrow AI without independent agency, and democratic rather than elite decisions about advanced AI. The episode closes with where listeners can follow his work.

David Wood argues aging is repairable damage, not destiny, and explains how stacked rejuvenation treatments could outrun it within a generation.

The questions, and the answers.

What is longevity escape velocity, and what problem is LEV solving?

I use the analogy of a rocket escaping gravity. Aging pulls us down toward weakness and disability, but a sequence of boosts to our health can carry us away from it. The first treatments might give three to five healthy years, and in that time new treatments arrive. Eventually we could return to the health of our 30s or 40s if we wish.

What first convinced a smartphone software engineer that aging was worth solving?

Most people make peace with aging, but what changed my mind was Dr. Aubrey de Grey, who framed it as engineering rather than pure science. Our cells and molecules accumulate damage, and we could undo it like maintaining a vintage car, with rust removed and oil changed. With rejuvenation and detox treatments, we could each live indefinitely if we wished.

What did hosting London Futurists since 2008 teach you about changing minds?

Narrative is fundamental. People rise above the ordinary when they see themselves as part of a grand story, such as abolishing aging and transcending human limits. I also learned my role is catalyst, not just chair or futurist. A catalyst brings out energy latent in the group, because conversations create things, not one person speaking.

How do you respond when people say death is what gives life meaning?

I hear it all the time, because we are in denial. A young child jumps out of bed fascinated by toys and friends, not because they fear dying in 75 years. So I say what gives life meaning is life. Accepting death was wise when nothing could be done, but now we have the science to change it.

Why test combinations of repair treatments instead of one at a time?

Aging is not a single thing. It is like a car with scores of parts that can fail. De Grey's analysis points to about seven types of damage, such as zombie senescent cells and depleted stem cells, and probably more. Single treatments extend mouse lives maybe 20 to 30 percent, so we must address many types of damage in parallel.

What did the first mouse rejuvenation study teach you about designing the next one?

RMR1 was small, with four treatments. Mice receiving all four lived longer on average, but the gain was smaller than hoped, partly because we had not fully duplicated earlier researchers' individual results. For RMR2 we are running more pilots first to replicate best practice, and more treatments now have experimental backing, so we expect more dramatic results.

Where do AI safety and longevity meet?

AI can accelerate science, as AlphaFold showed, but it relied on decades of painstaking data. General AI also risks cyber hacking and bioweapons, and we could die faster from misaligned AI than from aging. I advocate narrow AI without independent agency, and not rushing ahead until it is safe, with democratic decisions rather than elite ones.