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" "Plainly stated, I believe consciousness is an instinct. Many organisms, not just humans, come with it, ready-made. That is what instincts are, something organisms come with. Living things have an organization that allows life and ultimately consciousness to exist, even though they are made from the same materials as the non-living natural world that surrounds them. And instincts envelop organisms from bacteria to humans. Survival, sex, resilience, and walking are commonly thought to be instincts, but so, too, are more complex capacities such as language and sociality — all are instincts. The list is long, and we humans seem to have more instincts than other creatures. Yet there is something special about the consciousness instinct. It is no ordinary instinct. In fact, it seems so extraordinary that many think only we humans can lay claim to it. Even if that’s not the case, we want to know more about it. And because we all have it, we all think we have insight into it. As we will see, it is a slippery, complex instinct situated in the universe’s most impenetrable organ, the brain.
Michael S. Gazzaniga (born December 12, 1939) is an American neuroscientist, author and professor of psychology at the University of California, Santa Barbara, where he heads the new SAGE Center for the Study of the Mind.
Biography information from Wikiquote
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The computer scientists Jeff Clune, Jean-Baptiste Mouret, and Hod Lipson did what computer scientists do: they designed computer simulations.23 They used well-studied networks that had sensory inputs and produced outputs. What those outputs were determined how well the network performed when faced with environmental problems. They simulated twenty-five thousand generations of evolution, programming in a direct selection pressure to either maximize performance alone or maximize performance and minimize connection costs. And voilà! Once wiring-cost-minimization was added, in both changing and unchanging environments, modules immediately began to appear, whereas without the stipulation of minimizing costs, they didn’t. And when the three looked at the highest-performing networks that evolved, those networks were modular. Among that group, they found that the lower the costs were, the greater the modularity that resulted. These networks also evolved much quicker — in markedly fewer generations — whether in stable or changing environments. These simulation experiments provide strong evidence that selection pressures to maximize network performance and minimize connection costs will yield networks that are significantly more modular and more evolvable.
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