Films from the Future - Andrew Maynard

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turns out to be about as useful as trying to starve someone by locking them in a grocery store.

      There’s a pretty high chance that the movie’s scriptwriters didn’t know that this safety feature wouldn’t work, or that they didn’t care. Either way, it’s a salutary tale of scientists who are trying to be responsible—at least their version of “responsible”—but are tripped up by what they don’t know, and what they don’t care to find out.

      In the movie, not much is made of the lysine contingency, unlike in Michael Crichton’s book that the movie’s based on, where this basic oversight leads to the eventual escape of the dinosaurs from the island and onto the mainland. There is another oversight, though, that features strongly in the movie, and is a second strike against the short-sightedness of the scientists involved. This is the assumption that InGen’s dinosaurs couldn’t breed.

      This is another part of the storyline where scientific plausibility isn’t allowed to stand in the way of a good story. But, as with the lysine, it flags the dangers of thinking you’re smart enough to have every eventuality covered. In the movie, InGen’s scientists design all of their dinosaurs to be females. Their thinking: no males, no breeding, no babies, no problem. Apart from one small issue: When stitching together their fragments of dinosaur DNA with that of living species, they filled some of the holes with frog DNA.

      This is where we need to suspend scientific skepticism somewhat, as designing a functional genome isn’t as straightforward as cutting and pasting from one animal to another. In fact, this is so far from how things work that it would be like an architect, on losing a few pages from the plans of a multi-million dollar skyscraper, slipping in a few random pages from a cookie-cutter duplex and hoping for the best. The result would be a disaster. But stick with the story for the moment, because in the world of Jurassic Park, this naïve mistake led to a tipping point that the scientists didn’t anticipate. Just as some species of frog can switch from female to male with the right environmental stimuli, the DNA borrowed from frogs inadvertently gave the dinosaurs the same ability. And this brings us back to the real world, or at least the near-real world, of de-extinction. As scientists and others begin to recreate extinct species, or redesign animals based on long-gone relatives, how do we ensure that, in their cleverness, they’re not missing something important?

      Some of this comes down to what responsible science means, which, as we’ll discover in later chapters, is about more than just having good intentions. It also means having the humility to recognize your limitations, and the willingness to listen to and work with others who bring different types of expertise and knowledge to the table.

      This possibility of unanticipated outcomes shines a bright spotlight on the question of whether some lines of research or technological development should be pursued, even if they could. Jurassic Park explores this through genetic engineering and de-extinction, but the same questions apply to many other areas of technological advancement, where new knowledge has the potential to have a substantial impact on society. And the more complex the science and technology we begin to play with is, the more pressing this distinction between “could” and “should” becomes.

      Unfortunately, there are no easy guidelines or rules of thumb that help decide what is probably okay and what is probably not, although much of this book is devoted to ways of thinking that reduce the chances of making a mess of things. Even when we do have a sense of how to decide between great ideas and really bad ones, though, there’s one aspect of reality we can’t escape from: Complex systems behave in unpredictable ways.

      Michael Crichton started playing with the ideas behind Jurassic Park in the 1980s, when “chaos” was becoming trendy. I was an undergraduate at the time, studying physics, and it was nearly impossible to avoid the world of “strange attractors” and “fractals.” These were the years of the “Mandelbrot Set” and computers that were powerful enough to calculate the numbers it contained and display them as stunningly psychedelic images. The recursive complexity in the resulting fractals became the poster child for a growing field of mathematics that grappled with systems where, beyond certain limits, their behavior was impossible to predict. The field came to be known informally as chaos theory.

      Chaos theory grew out of the work of the American meteorologist Edward Lorenz. When he started his career, it was assumed that the solution to more accurate weather prediction was better data and better models. But in the 1950s, Lorenz began to challenge this idea. What he found was that, in some cases, minute changes in atmospheric conditions could lead to dramatically different outcomes down the line, so much so that, in sufficiently complex systems, it was impossible to predict the results of seemingly insignificant changes.

      In 1963, when he published the paper that established chaos theory,14 it was a revolutionary idea—at least to scientists who still hung onto the assumption that we live in a predictable world. Much as quantum physics challenged scientists’ ideas of how predictable physical processes are in the invisible world of atoms and subatomic particles, chaos theory challenged their belief that, if we have enough information, we can predict the outcomes of our actions in our everyday lives.

      At the core of Lorenz’s ideas was the observation that, in a sufficiently complex system, the smallest variation could lead to profound differences in outcomes. In 1969, he coined the term “the Butterfly Effect,” suggesting that the world’s weather systems are so complex and interconnected that a butterfly flapping its wings on one side of the world could initiate a chain of events that ultimately led to a tornado on the other.

      Lorenz wasn’t the first to suggest that small changes in complex systems can have large and unpredictable effects. But he was perhaps the first to pull the idea into mainstream science. And this is where chaos theory might have stayed, were it not for the discovery of the “Mandelbrot Set” by mathematician Benoit Mandelbrot.

      In 1979, Mandelbrot demonstrated how a seemingly simple equation could lead to images of infinite complexity. The more you zoomed in to the images his equation produced, the more detail became visible. As with Lorentz’s work, Mandelbrot’s research showed that very simple beginnings could lead to complex, unpredictable, and chaotic outcomes. But Lorentz, Mandelbrot, and others also revealed another intriguing aspect of chaos theory, and this was that complex systems can lead to predictable chaos. This may seem counterintuitive, but what their work showed was that, even where chaotic unpredictability reigns, there are always limits to what the outcomes might be.

      Mandelbrot fractals became all the rage in the 1980s. As a new generation of computer geeks got their hands on the latest personal computers, kids began to replicate the Mandelbrot fractal and revel in its complexity. Reproducing it became a test of one’s coding expertise and the power of one’s hardware. In one memorable guest lecture on parallel processing I attended, the lecturer even demonstrated the power of a new chip by showing how fast it could produce Mandelbrot fractals.

      This growing excitement around chaos theory and the idea that the world is ultimately unpredictable was admirably captured in James Gleick’s 1987 book Chaos: Making a New Science.15 Gleick pulled chaos theory out of the realm of scientists and computer geeks and placed it firmly in the public domain, and also into the hands of novelists and moviemakers. In Jurassic Park, Ian Malcolm captures the essence of the chaos zeitgeist, and uses this to drive along a narrative of naïve human arrogance versus the triumphal dominance of chaotic, unpredictable nature. Naturally, there’s a lot of hokum here, including the rather silly idea that chaos theory means being able to predict when chaos will occur (it doesn’t). But the concept that we cannot wield perfect control over complex technologies within a complex world is nevertheless an important one.

      Chaos theory suggests that, in a complex system, immeasurably small actions or events can profoundly affect what happens over the course of time, making accurate predictions of the future well-nigh impossible. This is important as we develop and deploy highly complex technologies. However, it also suggests that there are boundaries to what might happen and what will not as we do this. And these boundaries become highly relevant in separating out plausible futures from sheer fantasy.

      Chaos theory also indicates that, within complex systems, there are points of stability. In the context of technological

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