The Best Australian Science Writing 2015 (6 page)

It's time to head back. The day is getting on and my fellow explorer wants lunch. We leave without finding the adult moth, though I didn't expect to given its reputation for being furtive and so profoundly small. Its body is only 2 millimetres long. Its wingspan is 10–12 millimetres, if that. Yet what it has written, and left behind, is larger than it will ever be itself.

And I think there's poetry in that.

Love bug

Field guide to the future

Lost in a floral desert

I, wormbot:
The next step in artificial intelligence

Gillian Terzis

Even before they began to stake a claim on our jobs, our boardrooms, our battlefields and our bedrooms, robots have long activated our existential anxieties, forcing us mortals to ponder our own planned obsolescence. Advances in artificial intelligence deepen these feelings.

Supercomputers with artificial intelligence, such as IBM's Watson and Deep Blue, have declared emphatic victories on
Jeopardy!
and against world chess champion Garry Kasparov. And earlier this year, it was announced that a program created by scientists at the University of Alberta is invincible at heads-up limit Texas hold 'em poker. Not only can the program bluff – a seemingly cognitive trait – but it is said to ‘learn' from its mistakes through an algorithmic process known as ‘counterfactual regret minimisation'.

For all these developments, artificial intelligence systems are still fairly primitive. Yet Ray Kurzweil, futurist, Google engineering director and prominent AI hype-man, believes machines could surpass human intelligence in 15 years. Still, the dawn of the so-called ‘technological singularity' – the point at which the
intellectual capacity of machines 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 discipline
known 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 trying
to create a 3D computer simulation of the
C. elegans.
From this similar initiatives have also spawned: scientists are also trying to create simulations of the common fruit fly and the jellyfish.

Another of OpenWorm's founders, Stephen Larson, says that while he thinks the Lego robot was a ‘fun and interesting application of the open science approach', their efforts are concentrated on computer simulations.

‘It's exciting that folks are getting creative,' he says, but adds that he hasn't seen the finer details of Busbice's robot and couldn't speak to its scientific validity. ‘We feel very strongly about peer review. We want to be doing real science.'

A computer simulation may be a simplified model of reality, subject to certain controls, but Larson believes it still has value. He hopes that as computer simulation technology becomes more advanced, physics and chemistry can more closely approximate reality. ‘We now understand enough about living systems to appreciate that they are built on the foundations of physics and chemistry, that they are carrying out physical operations and transformations that are knowable.'

Equally intriguing is what still remains unknowable, and most likely unquantifiable. While these experiments in executable biology explicitly challenge the dichotomy between the living and non-living, the scientists themselves are reluctant to delve into the slippery liminal space in between. Busbice does not believe his robot to be alive in a biological sense, and both he and Larson appear content to leave the task of defining life to philosophers.

‘As a scientist, I don't have any feelings towards it,' Busbice says of his Lego experiment. ‘I do kill it.'

Nonetheless, during the course of our conversation he occasionally speaks about the robot with the sort of fondness one might reserve for a family pet. ‘I liken it to a cat,' he says. ‘You can try to entice it with food and things like that, but a cat pretty
much does what it wants to do.' The robot often scurries about his office, ‘wandering around like an animal, observing and interacting with its environment. It kind of makes you think it is alive to some degree – as much as a worm is alive.'

* * * * *

The degree of the ‘aliveness' of things is surprisingly debatable. Is a worm alive in the same way as a mammal? As Sparrow notes, there are organisms in the natural world for which a binary categorisation of life and non-life seems unsatisfactory. Viruses, for instance, share some characteristics of the living: they can reproduce (albeit within the cells of other living organisms) and they have an evolutionary history.

Perhaps a more pertinent question, Sparrow suggests, is whether virtual organisms are worthy of moral consideration. If a virtual organism were to reach the functional equivalent of a living one, ‘there would be questions about whether it would be wrong to cause it pain'. Most humans would place animals in an ontological category similar to our own, but the same cannot be said for computers or robots.

Many of us would hope that our existence is more than a pneumatic network of neurons, valves and ventricles. Such biological determinism may seem depressing – and has been vigorously contested by critics – but Busbice is unfazed. For him, the ghost is the machine.

‘What I've done with the technology, I guess, reduces humans to a bunch of connections. That scares people, that we're not this benevolent creature, unique in the universe … we're just a bunch of wires connected together.'

Maths explains how lobsters swim

Robots on a roll

Social robots are coming

It's all in your mind:
The feeling of ‘wetness' is an illusion

Jesse Hawley

Everything you experience is an illusion to some extent. The light from your screen, the sound of your breathing, the ambient temperature of a room – you cannot experience these things directly because you are your brain, and your brain is currently housed in a bony isolation chamber with no contact to the outside world.

Your brain is in stark darkness inside your skull, yet you still see the light from your screen because of the light receptors in your eyes. Similarly, hairs in your ears help you to hear, and temperature receptors in your skin help you to detect temperature. Using these types of information, your body has evolved detection kits to help sense the outside world, to feed the brain accurate information about the environment.

There are temperature receptors all over your skin, although they are more common on the hairy parts of your body. And all over your skin there are also ‘movement' receptors to help you detect changes in pressure and texture (these are more concentrated in your hands and feet).

But what about the feeling of wetness? This seems to be a different case entirely, for there are no ‘wet' receptors.

We can all agree on how important wetness/humidity is. Humidity governs the health of our skin, our lungs, and maybe our joints. Being wet can mean a sudden change in body temperature. And being wet is what sweating is all about; that is your body stopping itself from cooking to death.

A recent study published in the
Journal of Neurophysiology
discovered that humans cannot truly feel wetness. Since ‘wet receptors' never evolved along our line in the family tree, our brains must compensate with other clever tricks.

The researchers used cold-wet, cold-dry, warm-wet, and warm-dry treatments on participants who had various receptor nerves blocked. The study found that the brain integrates information about temperature and contact with the skin in order to infer wetness.

They discovered that participants were more likely to feel wet if the liquid was cold than if it were warm. And if participants had nerve blockers reducing movement sensitivity, they could only detect cold liquids as wet, not warm ones.

Once we process these two stimuli (heat and touch), our brains cross-reference those feelings with past experiences to determine that we are indeed getting wet.

Even completely fabricated perceptions such as ‘being wet' can feel so real that we'd never thought to question them before. Researchers point out that a nose-bleed, where the liquid is at body temperature, can go undetected till we are informed. And, dare I say it, the slow compression of hairs can be what alerts us to a pants-wetting incident. Not that any of us can remember what that feels like, right?