Day 053 - What survival machines want and what they get

Submitted by Sam on 12 July, 2011 - 22:35

Bodies are the vehicles of survival for genes, which programme proteins to make systems which will live long enough to reproduce, ensuring that the genes themselves continue to replicate. Whilst genes obviously have no conscious purpose or desire to replicate, it is their natural propensity to create organisms that do exhibit such behavioural characterstics, whether consciously or otherwise. Following in Dawkins' tradition then, it is convenient to refer to the effects of genes with the compressed language of intention, imagining what they might 'want' as a short-hand way of referring to the behaviour their interrelated effects tend to produce in their host organisms to benefit their genes' own propagation. What a gene 'wants', in short, is to ensure its own survival, by replicating as widely as possible throughout a population.

To this end, genes are 'selfish', largely seeing other survival machines either as impediments or as resources to be exploited. The important exception to this indifference is when those other machines are close relatives to the first, when they will likely be vehicles for the same genes as it carries itself. If they are not genetically closely related, other survival machines represent a threat, potentially competing for mating partners or other resources. The logical policy to adopt against this threat might seem to be for each organism to murder all of its rivals, and perhaps even then eat them for food. However, this policy does not necessarily always work, as removing one rival from the complex system of many rivals may benefit yet another rival more than it benefits oneself.

What tends to happen therefore, is that various survival machines adopt various pre-programmed behavioural policies, perhaps of the form 'if rival is smaller, attack; otherwise flee'. Some strategies be more effective than others, and will therefore tend to spread throughout the population. What is crucial is that the behaviour of each individual depends largely on what the majority of the other members of the group are doing – if the majority of other genes are encoding the behavioural pattern 'if rival is smaller, run away; if larger, attack', then clearly a selective advantage is shown to those that exhibit the reverse trait. After a period of oscillation, an evolutionarily stable strategy will be adopted; a pre-programmed behavioural policy which cannot be bettered by any alternative strategy if most members of the group follow it. It may not necessarily represent the optimum efficiency for the group were they to conspire together to create a perfect strategy, but instead gains its persistence from being 'immune to treachery from within' – once such a strategy has evolved through the testing of many other forms, a deviant individual cannot, on average, out-perform it. If it can, and has evolved a newly successful strategy, then another period of oscillation will occur until this is selected as the new evolutionarily stable strategy for the group to adopt.

Day 052 - Where bodies came from

Submitted by Sam on 11 July, 2011 - 23:07

Intelligence arises from a society of unintelligent agents working together in very complex ways, emerging from a group of neurons that can, individually, be represented algorithmically. But where do neurons themselves come from? Where do all biological structures come from? How can evolution produce something so complex as an electrically-gated logic circuit from raw materials like carbon and hydrogen, insensibly pulling together groups of molecules to create structures as intricate as the organic computers that power the human brain?

In his seminal book The Selfish Gene, Richard Dawkins extends Darwin's theory of natural selection backwards in time to the inorganic precursors to life, lensing Darwin's principle of 'survival of the fittest' into the more general 'survival of the stable' to show how complex yet stable molecules 'evolve' from their constituent elements.

Chemists have shown how a sea of simple substances, like those that would have been found in the earliest environments on earth, can be stimulated with a source of energy, such as sparks (representing primordial lightning) or ultraviolet light, to produce molecules more complex than those originally present in the mix. Typically, after a few weeks, a 'soup' containing amino acids is created. Amino acids are the basic components of proteins, which are in turn the basic components of biological organisms. Dawkins saw that the earliest form of natural selection was therefore a selection of such stable molecular forms against a rejection of unstable ones, which would rapidly and automatically degenerate to be replaced by more robust forms.

Such a 'primeval soup' is believed to have constituted the seas thousands of millions of years ago, where clumps of organic molecules could become locally concentrated, perhaps combining into even larger molecules under the influence of energy from the sun or lightning. Through countless iterations of this process, Dawkins theorized that a singularly remarkable molecule was formed by accident – a molecule able to create copies of itself which he termed tht replicator.

A replicator could have acted as a mould or a template built from smaller building block molecules derived from the abundant soup, arranged in such a way that each building block had an affinity for its own kind. With this chemical propensity to draw together and bond, the building blocks would automatically join together into a sequence that would mimic (or inversely mirror) the shape of the replicator itself. If the chain ever split, there would be two replicators, and they would spread rapidly through the soup of building-blocks, making further copies of themselves.

This process would continue until the smaller molecular components in the soup became a 'contested' resource, placing a selection pressure on replicators which would favour any which might happen to form that used even larger molecules as building blocks. Non-identical replicators may have been created through copying errors in their 'parent' replicators, and these cumulative mistakes could have created molecules even more stable in the new environment than the old replicators. Perhaps new replicators formed by accident which were able to cannibalistically break down other replicators, decreasing their stabillity in order to obtain 'food' to fuel their own replication. In response to these 'proto-carnivores', other replicators may have been selectively favoured if their copying mistakes afforded them chemical or physical protection from their rivals, perhaps through a physical wall of protein which shielded them from chemical assimilation.

Dawkins shows that the replicators which would survive in this soup would be the ones that built 'survival machines' for themselves to live in, which would gradually get stronger and more elaborate as the competition for resources grew closer, and the competition itself grew more advanced. The culmination of these survival machines, and the marvellous conclusion to Dawkins' argument, is that genes are descended from the original replicators, and we are their survival machines.

Day 051 - Defining things

Submitted by Sam on 10 July, 2011 - 23:22

In order to have a notion of a “thing” we first have to be able to distinguish a group of properties which seem to stay the same whilst other things change, or that change in ways that we can predict. Our 'thing-recognition' processes have evolved to isolate an integral constellation of properties to accurately define an entity, whether a spoken word or a physical object or anything that can have a name. This ability is so elementary to us that we hardly ever consider how marvellously complex it is, given that we never see (or hear, or feel, or taste) the same thing in exactly the same way twice – invariably we always experience it from a slightly different perspective, perhaps against a different background, from a higher perspective, or under a different shade of light. Whilst our ability to differentiate things seems simple because it is 'second nature' to us, this is only because we are unconscious of the great network of processes in our brain that make the fantastically intricate computations that allow us to make such distinctions possible.

Even the most advanced robots today lack the visual object-recognition capabilities that a two year-old child possesses, and fail to attain the language capabilities of a four year old child. A two-year old child can recognize classes of objects, and can classify a black shoe as a shoe, despite never having seen a black shoe of that exact style, colour or size before, but yet our robots cannot reliably classify because we have yet to be able to replicate the complex object-identification processes in our brains. A four year-old child can understand language in noisy environments and in a variety of accents, whilst our voice-recognition algorithms break down under such conditions.

Humans are able to discard a great deal of sensory information in order to perceive only what is most essential to each scene – without this ability we would be unable to learn because our memories would never sufficiently correlate with current appearances.

Day 050 - Expressing yourself

Submitted by Sam on 10 July, 2011 - 01:36

We can never verbally express exactly what we are thinking at any given moment, because to do so would require articulating the states of agencies that we are not actually conscious of, let alone able to describe using language agencies. 'What I am currently thinking' can therefore only ever be an expression of higher-level agencies, and therefore only a partial indication of the global brain state, leaving out a description of its non-verbal emotions and thought-processes. In endeavouring to translate the states of the brain that we are consciously aware of into language, there is also an inevitable time delay, implying that any expression of the 'current' state is either an anticipation of what higher-level agencies will be doing by the time the description is vocalized, or a reflection as to what they were doing 'just now'. By the time you have expressed what you were thinking, your state of mind has changed, and new thoughts have been formed as a result of this attempt at introspection and expression.

The same problems occur when we try to express an idea to someone else; we often end up not entirely saying what we 'meant'. This is because if the idea pre-exists in our brain as some kind of structure, it is not necessarily going to be a definite, fixed structure that language agents can easily reformulate into an easily transmittable description – not least because some parts of the idea may be reliant on interactions with a rapidly changing network of agencies whose subtle interactions are not accessible to conscious thought or linguistic expression. In order to try to express the idea then, the language agencies in the brain must hypothesize about the states of these linguistically-inaccessible states, attempting to reformulate them into words. This process inevitably oversimplifies the transmission of the mental state necessary to recreate the idea in its true essence, perhaps leading to a loss of nuance and full comprehension.

The best descriptions work by using words which decompress in the mind of the reader or the listener, activating a whole series of networks and associations, both conscious and unconscious, which expand into a recreation of the original 'meaning' in its purest sense, activating both the language areas associated with the original idea and those attendant agents which were not expressed verbally. Through the reassembly of the words using the listener or reader's own personal lexicon of inferences and definitions, a similar structure to that of the original idea can be rebuilt in the 'receiving' mind, even though it is only ever a representation or reformulation of the original neuronal activity that constituted the first idea.

Day 049 - Artificial intelligence and reverse cyborgs

Submitted by Sam on 8 July, 2011 - 20:52

A cyborg is a fully integrated man-machine system, where a human's natural tolerances or capabilities are extended beyond their normal capacity through machine augmentation. Various existing neural and physical prosthetics have given glimpses of the potentialities for such biological -machine syntheses, but we are objectively a very long way away from creating a perfect man-machine hybrid. The recent phenomenon of internet crowdsourcing, however, has already created hybrid intelligences which outperform our current artificial intelligent agents in a number of ways. Indeed, it has been speculated that perhaps the most intelligent machines in the near future may be “reverse cyborgs”, or artificial intelligences augmented by us 1.

Crowdsourcing allows companies or individuals to outsource work to an open, undefined community, rather than tasking specific employees or contractors with it. Web-based crowdsourcing has lead to the phenomenon of ubiquitous human computing, which is where a task is broken down into smaller, much more basic sub-tasks, which are then parcelled out around the world for completion by anyone with an internet connection. In theory, this allows computers to turn to the human crowd to assist when a problem is encountered that cannot be solved.

In 2005, Amazon launched Mechanical Turk, an online service which has made possible such reverse-cyborg-like systems. Mechanical Turk co-ordinates human intelligence from a crowd of “Workers” with HITs (Human Intelligence Tasks) posed by “Requesters”, who are typically corporations or researchers. Tasks like transcription can now be crowdsourced extremely cheaply, and with great rapidity – the crowd of workers is often thousands-strong, and so jobs can get completed in seconds.

One example of a human-computer hybrid built on Amazon's crowdsourcing platform is IQ Engine's oMoby smartphone app, which joins the company's “visual intelligence” image recognition software with human intelligence. Users take a picture with their mobile phone using the app, which then tries to identify the image with conventional image recognition algorithms. If it's attempts at categorization are unssucessful, the software will upload the image to the crowd on Mechanical Turk, or the company's own pool of workers. Their Director of research, Pierre Garrigues, claims around half of all queries are able to be answered by this hybridised method in under 25 seconds.

  • 1. Giles, Jim. "Brain Donors." New Scientist 2818 (2011). Print.

Day 048 - Imprinting

Submitted by Sam on 8 July, 2011 - 00:33

As genes cannot possibly encode a human's complete value system, our brains have evolved general purpose machinery, such as mirror-neurons, as a means to acquire and transmit goals and values from one person to another. A child therefore not only has to learn about causes and effects itself, but has also to internalize a coherent system of values, and there is no way for it to do so without basing it on a pre-existing model. The child therefore typically constructs its value system from those models expressed by older individuals, and most typically the ideals, values and goals provided by its parents.

Strong bonds of childhood attachment have therefore evolved in order to keep children within the protective and didactic sphere of its parents, giving the child every opportunity to learn and construct an understanding of what should be classed as good and bad. The strength of these filial bonds also ensure that the child isn't exposed to too large a number of close adult role-models, which could potentially result in a fragmentary pastiche of influence that would not result in a coherent personality. Instead, the attachment mechanism restricts the child's attention to only a few very close (genetically) models, simplifying the child's task.

Marvin Minsky has suggested that the strong attachment-bonds between human children and parents could be based on memories which are rapid to form but extremely slow to degrade, perhaps using memory structures descended from the forms of learning called “imprinting”, which is where some very young animals such as chicks, ducklings and goslings quickly 'imprint' a recognition of their parents in the early days of their life. Minsky reasons that whilst primates and humans don't actually imprint in this way, infants and parents do develop an analogous bond serving the same evolutionary purpose of providing offspring with a strong role-model as the basis of their personalities, and the foundation of their value system.

Minsky's postulation draws attention to a spectrum of behavioural patterns, ranging from the purely innate to the fully-learned. In many animals, innate behavioural mechanisms provide the methods to learn new behaviours, just as a kitten has the instinct to hunt a rat, but must learn how to follow it from its mother. The brain's innate actions facilitate the learning process, and help to maintain a proximity to the object of its attachment, affording the infant a good chance of survival.

In less complex animals, the hard-wired ability to rapidly imprint usually leads to an immediate recognition of the animal's parent, helping to protect the child from potentially threatening events that the adult can help protect against. However, as Austrian naturalist Konrad Lorenz showed in the mid-20th century, imprinting is a very rigid mechanism for forging filial bonds, and is vulnerable to attribution errors. Lorenz discovered that the greylag geese he reared right from hatching would treat him like the parent, imprinting him as the first sensory object that they met. The geese would follow him around, and as adults would court him in preference to other greylag geese. Mammals have a much more robust method of forming parental bonds, which are more complex and generate bonds which are strong and long-lasting, ensuring that children are likely to see their parents (and often their mother) as the ultimate protector and provider; a ready-made consolidated value machine ripe for emulation.

Day 047 - Male and female brains

Submitted by Sam on 6 July, 2011 - 23:25

In 2001, Simon Baron-Cohen and other researchers from the University of Cambridge published a paper exploring whether human sexual dimorphism in sociability (i.e. anecdotal and scientifically observed differences in behaviour between men and women) is a result of biological or socio-cultural differences between the two sexes. The study examined 102 new-born babies (only a day old so that they would not have had time to be influenced by social and cultural factors), testing whether there was a difference in the amount of time the boys and girls spent looking at a face compared to a mechanical mobile. Averaged over the group, their results showed that the male infants spent longer looking at mechanical objects whilst the females showed a stronger interest in the faces 1 , suggesting that the sex differences arise from a biological (i.e. innate neurological) difference, rather than through the social environment.

The male preference for systems is supported by other psychological tests, including the on-average better performance of males at mental rotation tests, where the task is to identify whether a shape is a rotation or a mirror of another. Males are generally both quicker and more accurate at such tests than females, who score more highly in tests measuring empathy. Twelve-month old baby girls, for example, expressively signal more emotional concern through facial expressions and vocalizations than boys of a similar age when confronted with the distress of other people. Women, in general, are more sensitive to facial expressions, and tend to score higher than men when asked to identify what expression a particular image depicts.

These differences, which emerge as statistical trends when groups are compared, have lead Simon Baron-Cohen to create the 'empathizing-systemizing theory', which identifies three common brain types. In this scheme, the 'male' brain is predisposed towards understanding and building of systems; the 'female' brain is hard-wired for empathy, and the 'balanced' brain is equally attuned to both systemizing and empathizing. Crucial to the theory is that your sex doesn't necessarily determine which type of brain you have, as men can have the female brain and women can have the male brain, but trends suggest that men are more likely to have 'male' brains and women more likely to have 'female' brains.

Neurologically, it could be suggested that each brain type is determined by the number or efficiency of its mirror neurons, and thus that male brains have fewer mirror-neurons than female brains.

The BBC has a comprehensive set of six online tests which help identify the 'sex' of your brain, whilst an adaptation of Baron-Cohen's emotional empathy image test is available online here.

I scored 30/36 on the emotional empathy image test, and the BBC test tells me I have a male brain, as I can't spot the difference, and have a preference for more feminine faces.

  • 1. Connellan, Jennifer, Simon Baron-Cohen, Sally Wheelwright, Anna Batki, and Jag Ahluwalia. "Sex Differences in Human Neonatal Social Perception." Infant Behavior and Development 23 (2001): 113-18. Print.

Day 046 - Mirror-touch synaesthesia

Submitted by Sam on 6 July, 2011 - 02:20

The hypothesis that we emphasize with others through a process of simulation enabled by our mirror-neurons is supported by a rare and recently discovered form of synaesthesia called mirror-touch synaesthesia. People with this condition are considered to be hyper-empathetic and actually feel tactile sensations in their own body when observing other humans being touched.

The somatosensory cortex of the brain receives inputs from the body when it is touched, with subregions corresponding to each part of the body becoming active in a systematic response to each stimulus. Neuroimaging studies have shown that people with mirror-touch synaesthesia have a hyperactivated somatosensory cortex when they observe other people being touched, personally feeling the sensation themselves. The synaesthetes' sensations of observed touches are indistinguishable from those produced when they themselves are actually touched, making the usual empathetic simulation a very real reality for them.

Synaesthetes with hyperactive mirror-neurons consistently score higher in questionnaires designed to measure empathy, correlating the relationship between mirror neurons and understanding of others. In her article for the Guardian earlier this year, synaesthete Fiona Torrance described herself as “hugely considerate of other people”, feeling as though she knew “exactly what it feels like to be them”. However, like the people at the other end of the empathetic scale (such as those autism spectrum disorders – a much more common condition), Fiona's extreme level of empathy carries with it a great many difficulties. She has struggled with weight loss through always feeling full by seeing other people eat, constantly crying because she felt someone else's pain, and suffering sleep deprivation as other people's feelings permeate and invade her own.

Fiona's condition gives an insight into the neurological basis for empathy, showing how the wiring of the brain can completely control a person's emotional quotient. The implications are profound, particularly for the criminal-justice system. A hard-wired lack of empathy (or the inverse) would act as a determinate of a person's behaviour that they could be totally unaware of, and helpless to override. How can a compassionate and civilized society punish offenders whose actions are determined, at least in part, by neurological machinery totally outside of their own conscious control?

Day 045 - Unpacking subconscious and involuntary social cues

Submitted by Sam on 5 July, 2011 - 00:07

We react to numerous social cues that we give off and perceive during conversation, but often only subconsciously. Unlike the easy-to-fake facial expressions that give indications of our emotional state, many of these signals – such as as variation in the tone and pitch of the voice and gesture mirroring – are transmitted involuntarily, and if we were able to consciously process and analyze them we might have a more holistic understanding of the dynamics of social situations, and perhaps might react more deliberately. Various technologies have been developed to capture and process these signals programmatically, driven by a proven ability to raise group productivity in commercial environments by drawing attention to and elucidating a previously unconscious layer of social interaction.

Vertex Data Science, a multi-million pound private company based in the UK and one of the largest providers of call centre outsourcing in the world deployed such socially-decoding technology in 2006 to analyze the speech patterns of its telephone operators. Alex Pentland and his colleagues from MIT's Media Lab developed the equipment to measure variations in tone and pitch, the physical voice signal, not the semantic content nor the logic of the conversations themselves. After only a few seconds of such audio data the team were able to accurately predict the ultimate success or failure of almost every sales call.

The sensors revealed that people are less susceptible to meaning and reasoning than they are to the unconscious and instinctual aspects of communication, showing in particular the technology’s commercial value by demonstrating how telephone operators could increase their sales performance by consciously controlling previously unconscious aspects of their communication, learning to vary the tone and pitch of their voice in the manner of the most successful callers.

Other work from the team supports this evidence, showing the subtle differences between successful teams and ineffective teams, revealing new ways in which companies can train and support collaboration in order to out-compete rivals using a new type of computer-augmented social awareness. A year before the Vertex Data Science deployment, the team worked with researchers from the MIT Sloan School of Management with similar equipment, recording and analyzing the bodily movements and tone of voice of participants and again ignoring the meaning of the spoken words themselves. The participants were assigned to play a middle manager taking a new job, and another playing the role of a vice president of that division. Their task was to negotiate the middle manager's salary package, with real monetary rewards on offer to motivate the actors. Whilst the negotiations could last for hours, the team's electronic sensor took only a few minutes to predict with 87% accuracy which party would win the negotiation, demonstrating how empirical data can lead not only to a more reliable understanding of how businesses work, but also how the unconscious side of human behaviour may one day be fully soluble through the aid of new technologies.

Day 044 - Mirror neurons and the foundations of civilization

Submitted by Sam on 3 July, 2011 - 21:36

VS Ramachandran identifies a point of significant development in the course of human evolution about 75,000 years ago, when we suddenly and rapidly acquired and spread a great number of skills, which were unique to our species. The development of tool use, the use of fire, shelters, language and the ability to read someone else's expressions and interpret their behaviour can all be traced to the sudden emergence of a sophisticated mirror neuron system, Ramachandran argues.

The very rapid emergence of these skills occurred with no significant change in the size of the human brain, which stabilized almost three or four thousand years ago. Mirror neurons constitute only a very small part of the brain, and so their emergence 75,000 years ago is certainly a possibility in this regard.

As we have seen, mirror neurons allow for virtual simulations of other people's behaviours and emotions, and so their development would have allowed accidental discoveries made by individuals in a group (such as the use of fire) to be emulated and imitated by others, allowing skills to spread throughout the population rather than remaining isolated with their discoverer. In this way skills would rapidly accumulate, propagating vertically across generations, enabling a new kind of social evolution whereby a child can learn complex skills from its parents in ten minutes that otherwise might take hundreds of thousands of years to become evolutionarily encoded.

Below is Ramachandran's TED talk from 2009 in which he discusses the implications of mirror neurons for human development.

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