The Best Australian Science Writing 2015 by Heidi Norman Read Free Book Online

exceeds our own – often feels more like speculative fiction than reality. Sentient machines, which would exhibit consciousness, curiosity and emotions, remain a long way off. Human–robot relations are stilted; anyone who’s ever shouted at Apple’s Siri will know such interactions are not yet seamless.
    Simulating human traits remains the principal bugbear of artificial intelligence developers. But an increasing number of them believe they can design sophisticated and intelligent machines by going back to first principles – that is, by replicating the neural circuitry of simple organisms. Timothy Busbice is one such developer keen to fuse the knowledge of the neural circuitry of a worm with the aim of building intelligent, autonomous robots.
    Late in 2014, Busbice and a team of scientists uploaded a simulation of the nematode worm’s neural networks into a small programmable Lego robot. A video of the result is on YouTube, and it shows the three-wheeled robot skating jerkily around on the floor – if you didn’t know the project’s background you might think it is simply being controlled, somewhat clumsily, with a remote.
    Busbice claims the robot’s movements had not been preprogrammed, and its behaviour was directed by the simulation of the worm’s brain. For example, touching the robot’s ‘nose’ resulted in the machine beating a spontaneous and hasty retreat, while activating a ‘food sensor’ made the robot advance. The video has elicited vociferous debate about the project’s validity and accuracy, as well as the metaphysical implications.
    Busbice emphasises that although his simulation aims for a high degree of biological fidelity, it inevitably lacks the mess and noise of a real-life central nervous system. And this would seem to be the overarching flaw in computational simulations of neural activity, which play a central role in the nascent disciplineknown as ‘executable biology’. Monash University associate professor and bioethicist Robert Sparrow believes such simulations are destined to be incomplete portraits of brain activity. ‘There is still some uncertainty over whether we are capable of characterising all the behaviour of neurons,’ he says. ‘It’s not clear to me that just capturing the neuronal activity is enough to capture consciousness.’
    The simulation of multicellular organisms is no easy feat. No scientist has yet managed to create a comprehensive model of a bacterial cell, let alone a living organism with a brain. It’s no surprise that at about 100 billion neurons, the human brain remains something of a black box for neuroscientists; even a mouse has one million neurons. Making a computational simulation of these nervous systems would be an arduous task, but as researchers such as Busbice have proposed, there are simpler places to start: at present, the focus is on the microscopic, soil-inhabiting nematode (roundworm), otherwise known as the Caenorhadbitis elegans.
    The C. elegans worm has been the organism of choice for biologists for decades, for reasons that are practical and scientific. It is transparent, which permits scientists to observe each one of its 959 somatic cells and 302 of its neurons under a microscope; its size (one millimetre in length) allows it to be bred in large quantities in a Petri dish; and it shares physiological traits – muscles, a central nervous system, reproductive capabilities – with animals much higher up the food chain.
    28 years ago, a team of scientists led by John White and Sydney Brenner published a map of the C. elegans ’ neural connections, otherwise known as a connectome. Tracing cross-sections of the worm’s anatomy and figuring out where the neurons connected was a painstaking process that had taken close to 13 years.
    Today, an open-source science project named OpenWorm, of which Busbice is a co-founder and former member, is