There are lots of genes we'd like to inhibit. One exciting example is the fat insulin receptor gene, which basically says “hold on to every calorie, because the next hunting season may not work out so well.” You have to remember that our genes evolved tens of thousands of years ago, when conditions were very different than they are today. There wasn't any evolutionary reason for people to live very long, because once you were done with child rearing, which was generally maybe age thirty, you were using up the limited resources of the clan. And so longevity was not selected for. But there were genes that were appropriate for the time, like holding on to every calorie, because calories were few and far between—unlike today, with our super-sized meals. Now when scientists inhibited that gene in mice, those mice ate ravenously and remained slim—and they got the health benefits of being slim. They didn't get diabetes; they didn't get heart disease; they lived twenty percent longer. A number of pharmaceutical companies took notice and are now pursuing inhibiting the fat insulin receptor gene in fat cells, which would be quite a blockbuster concept. And that's just one of our twenty-three thousand genes.

So bridge two is already under construction, but in ten or fifteen years, we'll have the full fruition of that revolution, where we can really reprogram these information processes underlying our biology. And then twenty-five years from now, bridge three, the nanotechnology revolution, will enable us to go far beyond the limitations of our biology.

WIE: So even with all of the biotechnological innovation you're predicting, are there some limitations inherent in our biology that we won't be able to overcome without going beyond it?

RK: Biology, while remarkably intricate, clever, and complex, is far from optimal, because biological evolution made various early design decisions that everything else has to be based on. For example, everything is built out of proteins, and although proteins are three-dimensional molecules, they're a very limited class of materials with very limited properties. And we find time and again, as we actually reverse-engineer the methods of biology, that we can reengineer biological processes to be far more capable. For instance, our thinking takes place in the interneuronal connections in our brains. We have a hundred trillion of them, and they process information at chemical switching speeds of a few hundred feet per second, which is a million times slower than contemporary electronics. And that's based on the current speeds of today, when chips are still flat. Once electronics goes into the third dimension, they will be far more powerful. For instance, a one-inch cube of nanotube circuitry would be a million times more powerful than the human brain.

Or take our red blood cells, which are actually very simple devices—they just store and release oxygen in a certain fashion. There are already nanorobotic designs for robotic red blood cells that would do that hundreds of times more efficiently. If you replaced ten percent of your red blood cells with these respirocites, as they're called, you could do an Olympic sprint for fifteen minutes without taking a breath or sit at the bottom of your pool for four hours. Our biological systems are very sluggish. Take our white blood cells. I actually watched my own white blood cell in a microscope attack and destroy a bacterium, and it showed a measure of intelligence. It was very clever, but very slow; it was a boring thing to watch. It took about an hour and a half to complete that mission. Robert Frietas has nano-engineered designs that are fifteen to twenty years in the future, but once perfected, these designs would be hundreds of times more capable, would be able to download software from the internet that destroys specific pathogens including cancer cells, and would perform their mission in seconds rather than hours.

Now even though nanotechnology is largely in the future, there are already early adopter applications. For example, there's a blood-cell-sized capsule that's nano-engineered with seven animated pores that can successfully cure type 1 diabetes in rats; there are already sensors using nanotechnology that will be used in artificial pancreases to detect glucose levels with tiny computers embedded in the skin and to control the feedback loop. But the golden era of nanotechnology and the ubiquitous use of nanobots to augment the immune system and things like that will be more like twenty to twenty-five years away. Once we have the full fruition of biotech and nanotech, we really will have the means to indefinitely forestall disease, aging, and death.

WIE: Leonard Hayflick, one of today's leading authorities on aging, has said that he thinks that people who believe we can engineer our own immortality don't understand what aging really is, that deterioration and decay are universal processes that apply to everything, biological or otherwise.

RK: What am I? What is a person? I'm a pattern of matter and energy. I'm not this stuff that I'm looking at, because these particular particles were all different six months ago. We know that our cells turn over pretty quickly, and although our neurons persist longer, their constituent parts, the tubules and filaments, actually get turned over in days or weeks. Within a matter of months, all of the cells, or at least all of the systems within the cells, are changed. What persists is a pattern. I'd like to compare it to the pattern that water makes in a stream. When it's cascading around a rock, you can see a certain pattern, and that pattern can stay the same for hours or even months or years. But the water molecules that make up the pattern are changing within milliseconds. The pattern itself gradually changes as well—both the pattern of water in a stream and the pattern in our own bodies and brains—but there's a continuity even in this gradual change.

Now, Hayflick is correct that, left to their own devices, complex systems will eventually decay. On the other hand, you can intervene and modify those processes to maintain them. And it's not just a matter of fixing discrete problems, like saying, “Okay, there's a hole here. We'll plug the hole. There's a wound here, we'll plug the wound. There's a disease, we'll fix the disease.” We do have to have more pervasive systemic interventions that maintain the integrity of this complex system. But that is something that can be done. We can do it with complex information systems, and we can do it with our bodies and brains.

One example will be DNA errors. If you examine the cells of an elderly person, you'll see there's a very high rate of DNA errors that have occurred. And that is the type of process that Hayflick is referring to, because over time, those DNA errors cause a lack of integrity in this complex system. However, there are things you can do now to slow down DNA errors, and there will be biotech-based therapies to correct them. For example, I could take my skin cells and convert them into heart cells by manipulating the proteins in the cell body. I would discard those that had DNA errors or correct the DNA errors, extend the telomeres, multiply them in vitro and reinject them, and a good portion would ultimately work their way into my heart. If I did this therapy repeatedly, every day and every week, then after a year, my heart would be ninety-nine percent rejuvenated cells. Even if I was seventy, I'd have the heart of a twenty- or twenty-five-year-old, and I would have corrected the DNA errors.

So there are many ways to restore the integrity of a complex system. And yes, we do notice the sort of gradual blurring of the integrity of the information in a complex system if it's left to its own chaotic devices. But that's precisely what we're going to address.

WIE: Our current life expectancy is less than one hundred years. And our current life extension technology is nowhere near being able to do what you're speaking about. In light of this fact, what you're predicting sounds like an enormous leap in an extremely short time. What gives you the confidence that things will unfold in the way you predict?

RK: We don't have all the tools we need to extend longevity indefinitely at this moment, and if all science and technology were to stop, we wouldn't be able to do it. But science and technology are not stopping, they're accelerating. The future is always much more different than people anticipate because it grows not linearly but exponentially.

About thirty years ago, I became an ardent student of technology trends, and I began to gather data in many different fields and build mathematical models to predict future trends. And it turns out that certain things are hard to predict. If you asked me, “Will Google stock be higher or lower than it is today three years from now?” I could give you a guess, but that's all it would be. If you asked me, “What will the next wireless standard be?” that's also hard to predict. But if you asked, “What would one MIPS [million instructions per second] of computing cost in 2010?” or “How much will it cost to sequence a base pair of DNA in 2012?” or “What's the spatial and temporal resolution of noninvasive brain scanning in 2014?” I could give you a figure that will be remarkably accurate. I have a track record of predictions based on these models, because these types of measures of information technology track in very smooth exponential progressions. We're doubling the price/performance of information technologies each year—a factor of a thousand in ten years or a million in twenty years, which is really quite daunting. For example, whereas it took us fifteen years to sequence HIV, we sequenced SARS in thirty-one days. It cost twelve dollars to sequence one base pair of DNA in 1990, a penny in 2000, and it's under a tenth of a cent now.

Another important observation is that we're now at a point where we have the intersection of information technology and biology. We're understanding life and death, disease and aging as information processes, and we're also gaining the tools to change those processes—to reprogram the little software programs called genes that affect our lives.