Astronomy and Cosmology

14.       Astronomy , Cosmology

Planet Formation

Nobody knows for sure how planets are formed, because we haven’t been around to watch one. But we have a pretty good idea. The driving factor here, as is often the case, is gravity. If you take a large cloud of gas and debris in space, all the bits of the cloud attract all the other bits together; that is what gravity does. The bits will gradually move towards the ‘centre of gravity’ of the cloud, and eventually form a glob of ‘proto planet’ – if it happens to be near a star, that is. And if it is near a star, it will also be orbiting it, or else it will fall into the star, or disappear into inter stellar space. Technically of course, a planet has to be in orbit around a star, but the process I am describing could apply elsewhere – as indeed it does for star formation, only on a larger scale.

 Gravitational attraction depends on two things – the amount of matter, and the distance between them. The closer things are, the stronger the gravitational attraction.

So as the cloud ‘condenses’, the movement gets faster as the bits get closer, the attraction increases, gets faster, and so on until they all come together in a clump. This is our old friend positive feedback. Even when the bits have stuck together, gravity hasn’t quite finished its work. If the planet is big enough, the gravitational forces will cause the inner planet to heat up. This is partly why the centre of the earth is hot. It is not the only reason, though; atomic decay adds a large part to the heating. This caused a lot of confusion in the early days of evolutionary theory. It was thought that the earth was not old enough to provide enough time for evolution to have done its work, until it was realised that the nuclear decay was the key factor that kept the earth’s core hot.

Novas, Supernovas

When a star grows old, and loses its youthful vitality, it gets weak and tired. It just can’t throw off the energy like it used to (you know, like sunlight). Now a large object like a star has a lot of gravitational attraction between all the bits of stuff inside it. When it can’t throw off enough energy, it starts to lose the battle with gravity (a bit like we do when we get old). It starts to collapse under its own gravitational strain.

Now the thing about gravity is that the closer things get, the stronger the gravitational attraction gets. So as the star starts to shrink, the attraction of its own stuff gets stronger. And as it gets stronger, it collapses more quickly. And as it collapses more, the stuff gets closer, and the gravity gets stronger. Sounds familiar? Its that old positive feedback again. The collapsing strengthens the gravitational attraction, and that quickens the collapse, so much so that the final collapse of a huge star can be a matter of seconds. Perhaps its not quite classic feedback, but its close enough. In a way it is similar to thermal runaway, on rather a large scale.

So what happens? Well, when a big star collapses far enough, it starts to heat up under the strain (sounds a bit like me). The heat energy starts to counter balance the gravitation energy, and when it gets hot enough it just explodes. Depending on how big the star is, it is either a huge explosion (a nova) or a ginormous one (a supernova).

If the star isn’t big enough, it just can’t hack being a nova, so it settles down into a sort of quiet old age as a white dwarf, or a neutron star. Though apparently all is not quite so quiet as you might expect. While doing my research, I came across a reference to thermal runaway on the surface of white dwarfs. You may be glad to know that I am not going into that in depth, but it just goes to show how widespread these fundamental processes are.

Goldilocks

I will leave you with one final (possible) example of feedback in the cosmos. Paul Davies has written a book on The Goldilocks Enigma. The title refers to the difficult puzzle of why it is that many things about the Cosmos and the earth are ‘just right’ for life to form. Many physical constants and processes are remarkably ‘fine tuned’ so that stars can form and produce all the other elements, and the earth is also in the right kind of orbit round the right kind of star so that life can form. There is some debate about just how fine the tuning actually is, but all agree that it remains something of a difficult question. There are several attempts to provide answers, and I am not going to go into all of them here. Many are built around something called the ‘Anthropic Principle’, which comes in various flavours, but basically says that things have got to be the way they are for us to be here asking the question. So don’t worry about it.

Davies doesn’t like this answer, and has come up with another one which is a bit tricky to explain, as it depends on quantum physics. It has been said, and oft repeated, that if you think you understand quantum physics, then you haven’t really understood it. Rather fittingly, there seems to be some uncertainty as to who said this; some say Richard Feynman, some Neils Bohr, or even John Wheeler, who seems to get everywhere, like a quantum particle. Maybe they all said it. Quantum physics was developed in the early part of the twentieth century, and a hundred years later, scientists are still unsure of what it really ‘means’. Like the old joke about economists, if you ask five scientists to explain what quantum physics really tells us, you will get six different answers. There are many popular science books that try and explain these problems, such as John Gribbin’s Schrodinger’s Kittens, so I am not going to go into detail.

The hard part of the quantum world is that it seems that on the very small scale, things just do not behave in any sensible way. Particles are not in any exact place (or maybe even time), but are rather fuzzy, or at least that is one way of looking at it.

Quantum physicists explain the difference between this and the ‘real world’ that we are used to by saying that the fuzziness ‘collapses’ at some rather hard to determine point. Others though say that this is the wrong way of looking at it, and that the universe is actually a ‘multiverse’ consisting of a very large (possibly infinite) number of universes in a sort of tangled super universe all running in parallel. People working on quantum cosmology tend to this view, because that is the way the mathematics leads them when you try and do the maths on the whole universe. This viewpoint was originally proposed by Everett, expanded by De Witt, and championed recently by David Deutsch, among others. One of the strange consequences of this view of things is that there is (according to Davies and others) no such thing as a ‘unique past’. This is pretty hard to get hold of, because I can generally remember things in the past, or at least, I used to be able to before I started having senior moments. The point is, that in the multiverse, different universe strands become entangled and unentangled in a way that makes it impossible to completely separate them.

Now what Davies is proposing is that there is some kind of feedback loop that operates on the whole multiverse so that in some sense the future influences the past, as well as the past influencing the future. There is a nice kind of symmetry in this that I quite like, and in fact I had some ideas along these lines, for totally different reasons, a long time ago. Just because an idea looks nice doesn’t make it right though. Anyway, what Davies is saying is that life, and intelligence, form a fundamental part of the whole scheme of things, and so in a way is responsible for tweaking the multiverse in the right direction for life to form. So it all depends on feedback, life the universe and everything. You can’t top that, so I will stop right here.

Ecology

13.       Ecology

The earth’s climate is a highly complex system, as we are increasingly coming to understand in this era of global climate change.

For one thing, there are ice ages, and within each ice age, alternating cold and warm glacials and interglacials brought about by a number of factors including three cyclic changes in the earth’s orbit.

Firstly, there is the eccentricity cycle of about 93,000 years, secondly there is the change in the tilt of the Earth's equatorial plane roughly every 41,000 years, and thirdly there is the 26,000 year precession cycle.

These cycles do not (for once) involve feedback, but there are a huge number of feedback mechanisms which do influence the earth’s climate and ecology.

Just to give one example, there has been considerable interest of late in the possibility that marine plankton may contribute to global climate control by the production of DMS (Dimethylsulphide), which can influence cloud formation and hence sunlight falling on the oceans (and the plankton).

We are still learning about these mechanisms, and all of them are not fully understood. We do, however, know enough to be confident that increased carbon emission from human activities are responsible for increasing global warming.

Fires and Oxygen

I have already talked about fires in Thermal Runaway, but now I want to take that to the global picture.

One of the facts that I recall best from James Lovelock’s book Gaia was the remarkable control over the earth’s oxygen level. It has remained at a very constant level, as a percentage of the earth’s atmosphere, for millions of years. How is this so? Well, as Lovelock so nicely describes, there are feedback mechanisms that keep it there.

It comes, at least to those of us in temperate climates, as something of a surprise to realise how many thunderstorms there are in the world. I have seen different estimates of 1000 and 10,000 present at any one time. Anyway, its a lot. And these storms start a lot of fires, of course many of them are never seen by many of us, as they are deep in forests. The likelihood of lightning starting a fire depends on two things, how dry is the wood, and how much oxygen there is in the atmosphere.

If the oxygen level were to rise by even a small amount, then a great many more fires would start. These fires would consume more oxygen, but also reduce the oxygen producing plants, and thus reduce the level of oxygen. The sensitivity to the oxygen level is acute; a 1% rise in oxygen level increases the probability of starting a fire by 70%. If the oxygen level were 25%, even damp grass would ignite. Conversely, at the current oxygen level, even a 20% moisture content reduces the probability of ignition to only 1%.

The whole control mechanism of oxygen level in the atmosphere is very complex and not yet fully understood, involving the oxidation of rocks and animal life (which consume oxygen),  plants, bacteria and sea life (which produce it). Burial of carbon and its release through the production of methane comes into it too. In fact, forest fires are a pretty small part of the equation, which makes it convenient that the level is kept where it is.

It seems a reasonable assumption that, if you find any variable in a complex dynamic system that is staying at a constant level, then there must be some negative feedback mechanics that are keeping it in place. In a modification of the ‘If it ain’t broke, don’t fix it’ slogan, I guess you could say ‘If it don’t move, it must be fixed’.

Forests and Deserts

Another feedback loop involves forests and deserts. Forests do not reflect a lot of sunlight, and so absorb a lot of heat. This leads to higher evaporation, cloud formation and rainfall. The rain enables forest growth to be sustained. If the forest is reduced from some cause (logging, clearance, insects, fires), then the amount of rainfall is reduced, which can lead to an increasing loss of forest and a process of desertification.

Forests also are involved in global climate change because they are a major carbon store. Deforestation from burning leads to more carbon in the atmosphere, which leads to global warming, which may also lead to disruption of tropical rainforests. This is yet another potentially dangerous feedback loop, with global warming and loss of forest chasing each other in a vicious spiral.

Its actually more complex, because deforestation can also involve changing patterns of land use, such as cattle ranching, which itself can lead to increased methane in the atmosphere.

These global feedback mechanisms can unfortunately be very sensitive things. It has been recently estimated (well, using a model) that the Sahara desert could be eliminated by planting vegetation to just above 18 degrees north of the present rain forests. A small distance less than that would result in the vegetation dying back to desert again.

Clouds

Now this is where you are going to have to remember that stuff about the water cycle that you learnt in school – come, on you must have done. My kids did it about three or four times.

Water falls as rain, then evaporates with heat from the sun, forms clouds, clouds make rain, OK?

Clouds reduce the amount of heat from the sun reaching the earths surface. So an increase in clouds could reduce the surface temperature of the earth. This reduction would reduce the amount of water evaporation, and so reduce the amount of clouds. Likewise a reduction in clouds would lead to an increase in earth temperature, and so more evaporation, and more clouds. This is our old friend negative feedback keeping things nice and stable – we hope.

As usual, the earth is a bit more complex than that, and we also need to consider things like ocean currents and wind systems which move the heat round a bit.

Snow

Snow reflects sunlight pretty well, so if snow starts to melt in one of the snow covered regions, more sunlight is absorbed because the ground is now darker. This causes the ground to heat up and melt more snow in a postive feedback loop. Remember, positive feedback – bad.

Once again, this process also works in reverse, so an increase in snow can lead to the earth to get colder, and colder, and colder. There is currently an idea doing the rounds that once there was a ‘snowball earth’. Actually, it would have been more of an iceball, but that doesn’t sound so good. The idea is that the earth went through a bad positive feedback loop that ended up with the whole earth covered in ice.

The idea was originally rejected, becase it seemed there was no way of escaping from this rather unpleasant state (temperature even at the equator would have been around -20°C). Now there are suggestions that the process could be reversed, either by a slow process of heat convection, or by a rapid heating up from a volcano blitz. Or maybe something else. The fact is, no one really knows yet if this ever happened, but it makes a good story.

Gaia

As I mentioned earlier, James Lovelock brought all our attention to the many complex ways in which the earth’s systems are kept in balance in his book Gaia, which has now become a byword for the earth’s eco system.

Something as big and complex as the earth has got to have a lot of feedback going on to keep things in balance. Lovelock pointed out that the fact that the earth was not in the state of balance of a lump of rock was sufficient evidence that life existed. If there was no life on earth, the oxygen level would very rapidly fall to zero, as oxygen is a highly reactive element that would combine with others until there was none left. Just think of how quickly iron can rust if unprotected. In fact, oxygen was effectively poisonous to early life forms; we can live in it because we have complex mechanisms to stop us becoming rusty (like skin).

I already mentioned oxygen balance, but the whole atmosphere is kept in a remarkably steady balance, with levels of gases from Nitrogen, Nitrous Oxide,  Ozone and Carbon Dioxide all being maintained. Whoops, did I say Carbon Dioxide? Well, of course that opens up the whole greenhouse gas, global warming Pandoras box. The danger here is that the earth’s feedback mechanisms cannot cope with the rapid increase in Carbon in the atmosphere that has been caused by man’s activities.

Evolution

12.               Evolution

In an essay sent to Darwin, A.R.Wallace wrote comparing evolution with the action of a steam engine governor, and how any imbalance in the animal kingdom would be reduced ‘by rendering existence difficult and extinction almost sure to follow’.

Feedback operates at different levels (as it often does) in the process of evolution.

Right down at the gene level, feedback loops were identified by Francois Jacob and Jacques Monod in 1962. Some genes are controlled by activator and repressor proteins, which are themselves the product of other genes.

At the other end of the process, the rise and fall of populations is another case of a balance between positive and negative feedback. A rise in population leads to an increase in births, which leads to a further increase in population. This can lead to a population explosion, as in the famous case of Australia and the rabbits. Normally the growth will be limited by a shortage of food supply, and/or an increase in the number of predators, parasites or diseases. In Australia, none of these were present to limit the growth until a disease (myxamatosis) was ‘imported’ especially for the purpose. The reduction in food supply is a negative feedback opposing the positive feedback of population growth. As the population grows, the food supply is reduced, and this reduces the birth rate.

Likewise when a tasty animal increases in numbers, so its predators will have an increased food supply, and their numbers will grow, and hence reduce the numbers of tasty critters. These population swings will often run in cycles of increase and decrease. Sometimes however, they will stabilise at an ‘evolutionary stable state’.  Other times, as famously discovered relatively recently in the 1980’s, they can fluctuate seemingly at random between high and low levels. This is now called ‘chaotic’ behaviour, and has led to a whole new subject area in the study of chaos and chaotic systems (see James Gleick’s book Chaos).

Arms Races

The term ‘Arms Race’ was originally coined to explain the propensity of human societies to engage in a continual battle between developing methods of attack and defence. As soon as a new weapon is developed, others try and invent defences against it. So the sword produced the shield and helmet, shrapnel produced the flak jacket, radar produced ‘smooth’ profiles, and so on. The development of defence is a kind of negative feedback as human kind tries to reduce the effect of weapons of attack. And the new methods of defence provoke further developments of new weapons. So there is a kind of see-saw effect which is reminiscent of the Flip Flops described in the electronics section.

The term Arms Race has been hijacked by evolutionary theorists to describe the process of two species evolving in competition with each other. So one perhaps develops a poisonous toxin to kill or paralyse its prey, then the other develops an antidote to defend against it.

There are similar but mores subtle examples of this kind of thing, which have been collectively called the ‘Red Queen’ effect, and Matt Ridley has written an excellent book with this title. The idea is that some genetically determined characteristic is selected, not because it has any actual benefit, but because it is ‘fashionable’. A typical example, quoted because it exemplifies a ‘useless’ feature, is the Peacock’s tail. The length and strength of a large tail is selected because it gives males the benefit of pleasing the females, who are themselves selected for a preference for large tails. These two selection processes drive each other in a positive feedback loop. Just like in our first example of positive feedback, the whistling sound system, there does not have to be any significant starting point (why tails for instance?). The feedback loop causes some such feature to be driven more and more once it is started. This is reminiscent of human fashion, as described previously.

There is still considerable debate on some of these issues in evolution – some people give more emphasis on the fact that a large tail could act as a signal of strong health for example. And the whole issue of why sex evolved at all is still an open question, though there are many good ideas. The whole ‘Red Queen’ method depends on having different sexes, so the feedback loop can involve both of them. The Red Queen name comes from Alice in Wonderland, where the Queen tells Alice that you have to run faster and faster to stay in the same place. This sounds tiring, and it has been argued that the whole arms race idea is pretty wasteful. It causes species (or countries) to expend a lot of effort to try and stay ahead of the competition, rather like ‘keeping up with the Joneses’. I suppose that is one of the snags with the free market competitive model, but then it does have advantages. Cooperation rather than competition can lead to stagnation, and who wants that? It can all too easily lead, in the wonderful words of Tom Lehrer, to ‘A sense of futility’.

You could argue that the whole mechanism of evolution is a feedback process. Each species (or its genome) evolves changes that are successful in being reproduced in its environment. So there is a constant feedback between the species and its environment. And the whole thing is driven by energy, ultimately from the sun. So evolution is quite simple really, it is a kind of heat pump, which extracts energy from the sun, and builds an ever more complex system of life. (Some people would argue about the ‘ever more complex’ bit, but I am pretty confident in it).

Actually, there is an alternative theory that life on earth was driven by energy from the earth, not from the sun. Energy is present in chemical energy in rocks, and in thermal energy below the earth’s surface (think of hot springs and volcanoes). There are some good reasons to suppose that life may have started from these energy sources rather than sunlight, though this is by no means established. Personally, I prefer sunlight, but then I was born in the Mediterranean.

Of course, it is not true that evolution is simple. The more we learn about it, the more complex it gets. For one thing ‘the environment’ against which a species evolves includes all other species, as well as the geographical local one. Some species will affect it more than others, but they are all woven together in such a global tangled web that it is impossible to extract out a part of it. And it is not only the local geography that is involved, as we are only too aware these days with the advent of man made global warming, which is already having an impact on the distribution of other species.

And as I have already indicated, evolution takes place at a number of levels. Evolutionary methods themselves evolve. They have to when you think about it – the earth wasn’t born with DNA lying around. It evolved, and so did all the enzyme mechanisms for copying, cutting, extracting, joining and correcting that form part of the incredibly complex DNA toolkit. Chromosomes also evolved, as did cells and mitochondria (the cells power plants). Cells evolved into organs and organisms, and organisms evolved groups, tribes, nation states.

And now we are evolving ever more complex systems of economics, government and (especially) technology. The growth of all this complexity shows a characteristic exponential nature that is the hallmark of positive feedback. This is best illustrated by looking at figures on a log scale, where an exponential curves show up as straight lines. Anyone can see if a line is roughly straight, but it is harder to tell if a curve is a true exponential. For example, the growth in GDP per head in the USA over the last 100 years looks pretty much a straight line on a log scale, and even large events such as the great depression and WW II show up as blips on the line.

There has been a lot written in the past few decades about a ‘singularity’ in the evolution of human life, which is predicated around the year 2020 (this is not a precise figure). The growth curve of many long term demographic trends, such as global population, energy consumption, materials extraction, GDP, all look like hitting some kind of wall around 2020.

There are other trends, too that are predicted to reach some kind of threshold around this time. Ray Kurzweil, in his book ‘The Singularity is Near’ lists some of these, such as the possibility of having computers that are as intelligent as humans. In case you think this is pie in the sky, IBM recently announce that by 2012 they expect to have a computer with the raw processing power roughly equivalent to the human brain. Of course that does not mean that it can lean to read, cook, and sew. But still, it is food for thought, and an indication of the rapidity of change now taking place.

There are other examples, too. I believe it is no coincidence that the current global economic mess is happening now. It is simply an example of things that are more likely to happen when the rate of overall complexity is changing so rapidly. Attack always evolves before defence, and the economic banking and trading systems have evolved too far too fast for them to be in control.

Games and Music

11.   Feedback in Games and Music

Computer games rely heavily on feedback to make the game playing exerience enjoyable, and also, importantly, playable. Immediate feedback is given by audio sounds – gun shots, explosions, splats, screeches and so on. And of course, the visual control of the car, robot, or other avatar relies on the feedback from the screen motion in response to the players movements of keys, mouse, joystick or other controller.

Feedback can also be used, though, to affect the game play in other ways like keeping the difficulty level appropriate for the player. Sometimes this can be negative feedback, keeping the skill level of the computer controlled players similar to the live player. Other times, this can be positive feedback, giving the human player greater skills and resources as he achieves certain goals.

And in the all action world of computer games, these mechanisms are often combined together, so that rapid feedback is happening all the time in a cacophony of screen effects, sound effects, score indicators, colour changes and motion effects.

Of course, it isn’t always that rapid, in sport games like cricket or golf. Here feedback is sometimes given, as in real life, in the physcs of controlling the ball, or maybe by some tutorial from a computer training session.

There is a distinction to be made here between ‘obvious’ feedback, such as a score indicator, and ‘low-key feedback’, which is the kind of background which we hardly notice, such as the engine noise made by a car. Computer games have to make use of both to make them more life like and playable.

Virtual Reality

The idea of virtual reality has been changing a bit recently. The original thrust was to enclose the user in some kind of headgear, body suit, or a complete room. The user experience is then to see, hear, and maybe feel and touch a virtual world created by the computer game or simulator.

A new trend, largely driven by the Nintendo Wii, has been to all the user to move and see freely, but to use his body movements to control the virtual ‘person’ or avatar within the virtual environment. The Wii uses a hand held controller which senses position, orientation and acceleration, but recently Microsoft has demonstrated a concept system called Natal which uses video cameras to track the user’s position and movement. Somewhat alarmingly, it recognises people as they approach the camera, and greets them by name.

This isn’t true virtual reality, but is an interesting development in game technology.

In traditional VR, the user wears a head-mounted display (HMD) that presents a picture to each eye. It also measures the location of the user's head and the direction in which he is looking. This enables a computer to show the virtual world with a slightly different view for each eye.

Users can also hear sounds in a virtual world through earphones contained in the HMD. The position information is used to make the sounds appear to come from the right position.

And all this stuff relies on feedback just as we rely on feedback to use our muscles, joints and limbs. The VR kit provides feedback to the computer software, which in turn gives feedback to the user or game player via the VR kit.

So the Nintendo Wii not only senses where your hand is, and uses that to tell the computer where to position your virtual hand, it also can vibrate the hand uinit to give you sensory feedback. It does this, for example, when you hit the golf ball too hard, to simulate the shock you would feel through the club shaft if you did this in real life.

The term “haptics” refers to the sense of touch in a person's skin and muscles. Haptic feedback is tricky to implement, but some progress is being made using gloves and body suits to ‘touch’ virtual objects.

  

Music

Popular music changed in the 1960s. I know, I was there. When I was at school, my peer group all became keenly interested in jazz and blues in the light of the new music scene from the likes of Elvis and Buddy Holly. We listened to all the old names like John Lee Hooker, Lightning Hopkins, Muddy Waters, Bo Diddley, Jimmy Reed and many others. A local group started playing quite good blues, and I went to see them a few times at a pub called the Wooden Bridge near Guildford. They were called the Rolling Stones, and became quite popular after that. In fact, the pub rapidly became too small to hold the crowds, and I saw them later in some ramshackle buildings on Eel Pie Island, which, I seem to remember, burnt down not long afterwards.

Other rock guitarists were experimenting with using feedback to produce distorted ‘howl’ like sounds – notably of course, Hendrix, but also others like Eric Clapton, Jeff Beck and Pete Townshend of The Who. Even before that, guitarists like Guitar Slim had played around with feedback in the 1950s. And later on other groups like  Velvet Underground , Jefferson Airplane and The Grateful Dead experimented with  feedback effects.

The sound produced by this excessive feedback actually makes use of the limitations of the amplification system. As the feedback tries to make the sound ever louder, it is limited by the power of the amplifier, and can drive it into distortion, where the sound is no longer being amplified as it should be, but changed into a different, harsher sound. The extent of the feedback can be varied by moving the guitar closer or further from the loudspeaker, and so increasing or decreasing the amount of feedback. So Pete Townshend would wave his guitar around in front of the speaker, creating a kind of wobble effect.

Long before the swinging sixties, feedback had been utilized in two new musical instruments - the Theremin and Onde Martinot. These were invented in the 1920s, and used capacitance effects between the player and the instrument. They both involve the player moving his hand to change the pitch. The change in capacitance is used to control the frequency of an oscillator which mixes with another fixed frequency oscillator to produce a wide range of notes. Feedback is used by the player to control the movement of his hand and hence the music.

These instruments have been used in classical, film and pop music such as the Beachboys Good Vibrations.

Design and Production

10.           Design and Production

Design means many different things to different folks. To a clothes designer, it means sketching styles that might appeal to their target market. To a car designer or aircraft designer, it means (nowadays) building a model on a computer that can be evaluated for strength, speed and efficiency by using simulation tools. More and more, design methods are involving computers, for electronics, cars, buildings, and yes, even clothes.

Computers are not being used because they are good at designing things. In fact, they are pretty useless – as yet. Virtually all of the creative design comes from the person using the computer. What the computer is good at is storing the design in great detail, analysing it in various ways, and producing data for machines that can automatically produce the finished product when the design is complete.

People have always used models for designing, either in the form of drawings and sketches, to fabricated prototypes built using anything from string and sealing wax to steel and cement. The point of building models is that they can be used to test ideas, and gain feedback. That’s the old kind of feedback that everyone understands – comments from potential users, from marketing staff, or from production engineers, or anyone else who might have an input to the design process.

Software designers have found a new way of getting feedback – it is difficult (though not impossible) to model software. Instead, new software systems are produced in Beta form and distributed to selected potential customers for them to try and give feedback. A more cynical view of this process is that is product testing by users rather than by designers. Very early (and hence possibly problematic) Alpha systems are sometimes used in this way. Alpha and Beta prototypes have been used for a long time in engineering, where they represent early ‘hand crafted’ models made in the design and development departments, before being refined into something that can be built in mass production departments.

There is a big difference in designing and making something that works, and something that can be repeatedly produced with the right quality and price. Production engineers will often be pretty scornful of the efforts of the development department; ‘how do you expect us to produce that’ is not uncommon. So there is feedback all the way through the process; in fact continuous feedback is necessary for continuous product improvement.

In the actual production, monitoring and feedback is used to keep the product line quality acceptable. Products can be tested for dimensions, weight, colour and any other important characteristics so that any deviation from the desired standard can be fed back to the production method to adjust and correct.

One of the neatest examples of this can be found in the manufacture of metal balls, as found for example in ball bearings. These can be bounced off a number of flat surfaces into a final collecting bin. If the ball deviates from being accurately round, it will not bounce correctly, and will thus automatically end up in a ‘scrap’ collector rather than the collecting bin. The feedback and selection is achieved here by the product itself, rather than any complex measuring equipment.

Economics and Organisation

9.             Economics

David Hume was evidently aware of the action of feedback as a self correcting mechanism, although he did not perhaps recognise it as such. In his Political Discourses of 1752, he surmised that if Great Britain were to lose a large part of its money supply, then the price of goods and wages would fall, but it would not take long for this to be corrected because of the impact on the balance of trade with other countries. Likewise, if the country received a quantity of money, this would drive up prices, and imports, which would then send more money to other countries. In fact, Hume compared this mechanism with the balancing of fluids in interconnected chambers

Not long after, Adam Smith, in his Wealth of Nations, explained how social feedback mechanism were involved in the control of wages, population and supply and demand.

For example, when wages fall, then profits rise. This leads to a general rise in wealth of industrialist / capitalists/ share owners, and hence eventually to a rise in wages. Of course, many factors come into play here, such as the rate of unemployment and the strength of labour unions, but the point is that negative feedback will limit runaway trends.

Sometimes, though, that doesn’t happen, and you get runaway hyperinflation as in the Weimar republic, or to a lesser extent in South America, or even Turkey recently. This is a classic case of positive feedback causing a runaway condition. As money loses value, confidence is weakened, and more money is printed, leading to a further decrease in the value of money, and so on.

I remember in Britain in the 1970’s, wage inflation caused a rapid increase in inflation to around 25%, when labour wages and money value chased each other up in a spiral. This process was fuelled by a wage policy that automatically linked wages to the RPI (retail price index), effectively building in a positive feedback loop. One wonders if the then political leaders had ever heard of positive feedback. Of course inflation is not a bad thing for some people. I you own property with a large mortgage, inflation can reduce the value of the mortgage rapidly. But for those with cash savings, it can be disastrous. Inflation effectively redistributes wealth from cash holders to debt owners, often in fact from the (relatively) poor to the better off

The stock market is another place where feedback is evident, both positive and negative. Rising share prices lead people to expect that times are good, and that they will keep on rising, so they buy shares. This leads the price to increase further, and so creates positive feedback. This type of behaviour is known in the trade as momentum buying, and is not something to be recommended. In other words, do not buy shares just because other people are buying them. Why not? Well, eventually someone will decide that the shares have become too expensive, and are overpriced, so they will start selling. Then the price will start to fall, and before you can say ‘crash’, other people will join in and make the price fall further. This is known as momentum selling, or less kindly, behaving like headless chickens. The fall in prices is again positive feedback, but the whole process of changing from rise to fall is negative feedback. And eventually, negative feedback will persuade some people that the shares have once again become cheap, and start buying.

Probably the most extreme example of momentum buying was in Holland around 1636. A fashion for tulip bulbs got rather out of hand, so much so in fact that the price of bulbs went up by 20 times in just one month. At the peak of the madness, one bulb could cost more than a good house in Amsterdamn. This might seem crazy – lets face it, it was crazy, but the point is that people were speculating. They did not intend to keep the bulbs, they were simply buying in the expectation that the price would increase. We are not immune to this kind of thinking even today; not that long ago you could hear some people say that house prices (in the UK anyway) were bound to keep on rising. All sorts of arguments could be used to support this – ever increasing demand, immigrant workers, split families etc. The thing to remember is that when everyone is saying that the price of something must go up, then that is the point of maximum danger, and time to steer well clear.

Some post modern economists have poured cold water on the Tulip Mania theory, though their arguments sound rather like someone trying to persuade you that the Titanic was not exactly sunk. In any event, there have been other notable examples of speculative bubbles such as the South Sea Bubble, and more recently the dot.com bubble.

Wise old investors like Warren Buffet will advise you (amongst other things) to indulge in contrary investing; in other words to do the opposite of what most people are doing. This is worth considering, but don’t overdo it. But here again, the point is that ‘contrary’ behaviour is a form of negative feedback.

Economics is, or course, a tricky business. The old joke that, if you ask five economists a question, you will get six different answers is actually not far from the truth. Look at the end of year predictions for next years GDP, inflation, base rates and currency rates, and you will get a large range of different predictions. The only common factor between all of them is that they will all be wrong. Or if any of them is exactly right, it will be by chance.

The early economic models of balanced supply and demand depend on feedback to keep them in balance. If the market value of something rises too much, people will stop buying and the price will fall. This is classic negative feedback.

In fact, real life is a bit more complex than that. Many factors intervene in ‘perfect’ market pricing. For one thing, naughty companies can indulge in cartels or price fixing which keeps the price higher than it ‘should’ be. For another, modern market complexities can serve to confuse the consumer so much that the optimum decision can be too difficult to take, too time consuming, too costly in itself. Watch a busy shopper in a supermarket, and they will often make more or less random decisions, without much regard to pricing. And the power of global brands can lead consumers to stick to tried and tested names rather than try new ones to see if they offer better value.

In recent times, there has been a rise in applying ideas from Chaos Theory to economics, with the acceptance that such systems are, like much else in life, complex non linear dynamic systems, involving feedback. The trouble is, that this still does not make them any easier to predict. In fact, it tends to bring home the inherent unpredictability.

Feedback in organizations

Organizations come in all shapes and sizes. A small company is one, so is a large company, or a multinational. Villages are too, as are towns and cities. Some living systems are organizations, like ant colonies, or coral reefs. It can be argued that all living things are organizations, in that they are collections of cells organized together.

Let us take city growth as an example. In Field of Dreams, the semi mystic Kevin Costner film, the theme is ‘If you build it, they will come’. There is a lot of truth in that, as anyone who has played Simcity knows. People need somewhere to live, somewhere to work, and somewhere to shop. If you provide all of that, then people will tend to come there. There are a few other factors too, like leisure facilities, policing and crime – all in Simcity as well. There is also a positive feedback effect. If a city grows and attracts more people, then those people create opportunities for yet more people. They need services, hairdressers, decorators, doctors, teachers and so on. Conversely, if a city starts to have inner city problems – violence, graffiti, slums, then people start to move out. As the population falls, the demand for services falls, which leads to further reduction. Of course there are many factors involved here, such as birth and death rates,  which also impact the population levels. The huge growth in third world cities like Mexico City, Sao Paolo, owe as much to high birth rates as to inward migration.

Now let us take a look at companies, which use feedback in all sorts of ways to try and control and improve the company’s growth and share price. The internal accounting system monitors the incoming and outgoing cash, and provides feedback to the directors as to the ongoing situation, and allows them to take steps to correct problems. Likewise, sales forecasts from the sales and marketing department give an indication of the likely income for the near future, and again allows for steps to be taken to increase sales, or cut costs.

Customer surveys and meetings give feedback on how customers view the company, share price monitoring indicates how the stock market is feeling about the company, and staff appraisals give two way feedback between the company and its employees. Running a business involves continuous feedback at all levels, and any company that neglects this even for a short time is in danger of heading downhill fast.

Education and Learning

8.    Education Learning and Communication

Education

You can’t teach someone without feedback. Well you can, but the results are somewhat unpredictable. That’s the whole point of the feedback. It tells you how much has been learnt, and how well, and what problems remain.

That is why schools have tests. They are often seen as just a means of judging how good a pupil is, and if he or she is a candidate for further education, or a scholarship. But really, they are just as much a marker of how well the education process is going. They tell the teacher what the student has learnt, and what still remains to be learnt.

If you have ever taken a golf lesson, you will know that the whole process is one of constant feedback. You hit a shot, and the pro tells you what was wrong with it (usually). He shows you how to make and adjustment, and you try again. This goes on (in my case at least) for a long time. Lots of feedback, and there is no short cut.

In fact feedback is perhaps the biggest difference between a real live teacher and a teaching machine. You can program a computer quite easily to impart information, but it is not so easy to give feedback. A lot of progress has been made in this direction since the first days of teaching machines, but it is still something that a human can usually do better. The problem is that the teacher needs to have an understanding of the individual student, and a model of his learning method, to best give ‘formative’ feedback. And more than that, enthusiastic encouragement is a benefit which is sometimes hard to take from a computer, however much they try.

Learning

Learning is what happens when you don’t have education (only joking). Animals and humans are all capable of learning by experience. Although some animal behaviour that looks so ‘intelligent’ that one would think it involves learning is, in fact, built in pre-programmed instinctive behaviour.

Courtship dances of fish and insects, pecking, nest building and egg rolling by birds are all examples of built in ‘motor programs’. These actions are innate, although they do allow for adjustment to deal with specific circumstances. And naturally, these adjustments require feedback from position sensors and vision.

Other motor programs, though, can be learned. In humans, activities such as walking, swimming and bicycle riding are learned behaviour. But once the learning process has been gone through repeatedly (a lot of times in some cases), it becomes almost automatic. Feedback is essential in the early learning stages, but becomes less important as the process becomes more automatic. Anyone who drives a car for a while is familiar with the ‘automatic pilot’ syndrome, where it is possible to drive back home from work and hardly be aware of making any conscious effort. Mind you, even then there is still feedback going on, otherwise it would be too easy to drive off the road.

In fact, driving involves a lot of feedback. Not only must you keep your eyes on the road, you also have to be aware of other traffic, pedestrians, obstacles, traffic lights, traffic signs and lane markings. Then you have to monitor the pressure of your foot on the accelerator, and sometimes the brake (and clutch if you insist on a manual gear change). When you watch speed up film of dense traffic, it sometimes amazes me that there are not a lot more accidents than there are.

Speech also requires feedback in the early stages, which is why deaf people have difficulty in learning to speak. But once speech is learnt, deafness later has little effect. The feedback is no longer needed.

Sometimes feedback like this can actually cause problems. Stutterers, for example, can sometimes benefit from an electronic device that prevents them hearing their own voice. It seems that the feedback can be part of the problem.

And indeed, stuttering can be induced by delaying the audio feedback to someone who is speaking. If you have ever tried to speak while listening via headphones to your own voice delayed by a second or two, you will know how difficult this makes it.

So all learning involves some kind of feedback to inform the learner about the effects of their actions. The other key aspect of learning is reinforcement, where desired behaviour is reinforced positively, and undesired negatively (gold stars or black marks – or, in my day, sometimes a ruler over your knuckles).

So feedback in learning is used both to adjust actions (such as motion, or pressure), and also to adjust the ‘world model’ that is being used to learn the behaviour. We learn, for instance, that some objects are hard, others are soft. Some are heavy, others light. We can only do this by taking action, and monitoring the feedback.

In the wider sense of the whole learning system, reinforcement itself is a kind of feedback. It provides positive or negative signals to the learning system to tell it when to repeat behaviour, and when to adjust it.

Some feedback is external - such as that provided by a teacher, and some is internal – such as neural signals fed back into the nervous system as part of learning movements.

If the feedback is reduced or hampered in some way, then learning is slower. Likewise, if it is enhanced or amplified, then learning can be improved. Good learning depends on good feedback; the clearer, and more specific is the feedback, the better the learning. Feedback also needs to be timely to be effective, delayed feedback is bad feedback. Practice makes perfect only if there is feedback. Practice without it leads to poorer performance and increased errors.

Feedback can also improve task activity that has already been learned. If a task required constant vigilance, it has been found that providing feedback to give knowledge of actions taken will improve the performance. It seems that the feedback stimulates the performer to better monitor his actions and so improve his vigilance.

Humans also learn how to behave (or not) by using feedback. Encouraging words, hugs, sweets and other desirable actions tend to lead to repeating the behaviour, while similar negative feedback tends to inhibit it. This does not mean, however that all behaviour is learnt. We are not ‘blank slates’ as Steven Pinker so ably demonstrates in his book of that name. Humans have a propensity for certain kinds of behaviour, but of course their subsequent path is hugely influenced by what they learn after birth.

Learning is actually a pretty tricky business. In Gregory Bateson’s book Steps towards an Ecology of Mind, he shows that people don’t just learn; they learn to learn. In fact, they also learn to learn to learn, and maybe that goes on further, depending on how smart you are. Some computer programs can learn, but getting them to learn to learn is a lot harder. When they start to do that, we may see really intelligent computers. But in any case, there has to be some feedback to make sure the learning process is doing any good.

Animal Learning

Animals also learn, though sometimes it can be difficult to distinguish learning from instinctive behaviour. For instance, Jackdaws learn what objects to use when making nests by trial and error (so using feedback). They will start off by grabbing just about anything, but learn that some things just don’t make good nests. Other birds, though, apparently have built in knowledge of what constitutes a good nest.

Bird song is an example of a combination of instinctive behaviour and learning. Birds that do not hear other birds have only a poor and limited repertoire of songs, but those exposed to bird society learn to develop a richer range.

And any pet owner knows that they can be trained to learn what kind of behaviour is acceptable, and what is not (well, some of them can).

Communication

Hey you, are you talking to me? Well obviously not, you are reading this, so in a sense I am talking to you. In the age of the media, communication is taking place in a variety of guises – printed media, TV, radio, web sites, podcasts, CDs, DVDs. And there are still the art galleries and concerts and books that have long been a source of communication.

Theoretical approaches to communication stem mainly from the 1940s, with the well known work of Claude Shannon. Shannon described communication channels between a transmitter and a receiver, and went on to explore the properties and limits of sending messages through these channels.

This kind of communication is obviously demonstrated by telephony or radio, but also by data signals between computers through modems or data networks.

Essentially though, this is a one way system. The message is sent and received, and that’s about it. Of course, there may be a message in reply, but that is separate and distinct from the first message.

Often though, communication is more complex than that. When we talk to someone, we are observing them while we talk, and we may be adjusting the tone or content of our ‘message’ by the way in which we see them reacting. So there is feedback here. We us the ‘signal’ from them as feedback to modify the way in which we are communicating.

Feedback is also used to overcome another feature of communication that Shannon explored – noise. In communication theory, noise is an unwanted signal that can interfere with the intended message and cause distortion and errors. We come across similar problems when talking to someone in a noisy room, or over a bad phone line. Often we overcome this by checking that the other person has heard us correctly. Did you get that?

This is also feedback, at the ‘message’ level. Similar techniques are used in data communications, by using additional error correcting bits to check the message, and even correct it if possible. This is an example of redundancy in communication, which we use all the time. Written text contains a large amount of redundancy, something that can easily be seen by omitting say vwls frm sm mssg. A technique that has received a large fillip from texting in mobile phones. It is also surprising that you can often read a piece of text by observing only the top half of a line.

 Modern mobile phones use huge amounts of digital signal processing to continuously monitor and correct the transmitted voice signal. Clever techniques are used to transmit a ‘training’ signal in each voice packet that contains known data, and can hence be used to adjust the parameters of processing algorithms that optimise the accuracy of the voice signal. This is all feedback, using information from the received signal to change the way in which the transmitter is sending the signal.

These are simple examples of communication (though the message may be far from simple). The modern world is rapidly becoming more diverse in its modes of communication. Newspapers, TV and radio are mainly a one way street. Someone writes an article, or transmits a program, and people read it or listen or watch. That model is changing. Of course, there has always been some feedback in this process – letters to the editor, viewers comments, but these have been limited in speed and quantity. Now, with the increased use of blogging, instant messageing, chat rooms and social networking the aim of the broadcaster is often to engage the end user as much as possible.

I am a regular listener to Podcasts from both TWIT (This Week in Tech) and Science Friday. As they are broadcast in the U.S., I am limited to listening to them from downloads, but both shows take live feedback from listeners (or viewers) via a variety of means – phone calls, Twitter, chat rooms, second life, email.

 

 

Humans

7. Feedback in Humans

We have already looked at various biochemical mechanisms in humans, as well as in other organisms. This chapter looks more generally at how feedback mechanisms are involved in various aspects of human behaviour.

Human Motor control

It is one of the frustrating things about trying to make robots that tasks which appear very simple to us, like drinking a glass of water, brushing our teeth or tying shoelaces are actually incredibly difficult to automate. The movements involve a lot of ‘degrees of freedom’ – basically movements that are independent of each other. They also need precise control in holding and releasing objects, and an overall understanding of the task, and a lot more smarts such as object recognition.

Something as ‘simple’ as eating - chewing and swallowing, is in fact fiendishly complicated. Large numbers of muscles and sensors are in play to taste, filter, manipulate, crush and masticate a mouthful. No one (as far as I know) has even tried to automate this process accurately.

Understanding exactly what goes on when we do these simple things is still a work in progress, as is trying to get robots to do them, although good progress is being made with the large amounts of processing power now available.

But fundamentally, any motor control (such as picking up an object) has to involve negative feedback. Without any, we would be back to the ‘blind driving’ problem. Try picking up something with your eyes closed and wearing thick gloves. When we reach for an object, we are getting feedback from a variety of means. Firstly we can see our hand and arm in relation to the object. We are getting a continuous message from or brain as to how far a way we are, and what direction we are moving in. If we overshoot (as babies do when learning) we can see that too, and make necessary corrections. Then we have proprioceptors in our muscles to tell us where they are, even if our eyes are closed. Finally we have touch as we close in on the object (and maybe smell and sound can help us sometimes).

So everything we do, from getting out of bed, walking, eating, drinking, driving, fighting (well, some people do), all involve feedback. We simply could not exist without it.

And if all of us use feedback, some of us use more than others. Sports involve this kind of feedback all the time. Recent research has shown that talented sports people have built in ‘maps’ that tell them where they are in relation to, say, a football. We all have them to some extent, but gifted sports people have better maps of the kind that, well, make them good at ball games. Of course, we have always known that something like this must be going on – we call it ‘ball sense’.

Biofeedback

This is a technique that can be learnt to control body functions which are normally considered to be under involuntary control. The most common example is blood pressure, along with the closely connect pulse rate.

The feedback is provided by some monitoring equipment, such as a screen display of blood pressure. The feedback can then be seen and used by the patient to try and lower the pressure displayed. Any action he takes which reduces it can be reinforced, and those that increase it can be avoided.

Although the degree of control that can be acquired is limited, it can be used to treat several problems such as tension and migraine headaches, tics, and muscle tension. It has even shown promise in helping patients to recover the use of paralysed limbs.

Human behaviour

Epidemics

When someone gets an infectious disease, he can pass it on to someone else (obviously). That person can pass it to another, and so on. If the rate at which this passing on is fast enough, it leads to an epidemic. Epidemiology is (as usual) pretty complicated, but the basic process is fairly simple.

This is another example of the ‘avalanche’ effect. Each passing of the infection is not an example of feedback, but the way in which the epidemic as a whole grows is a kind of positive feedback. The more people that get infected, then the more possibilities there are of further infections. This is similar to the kind of thing in ‘explosions’, which is whey we sometimes use that term to describe a very rapid epidemic.

Social Networks

There has been a lot of interest in social networks recently. A lot of it has centred around the ‘six steps to anyone’ idea – the discovery that you can reach almost anyone in the world through a chain of six contacts who know each other. There is also the ‘Kevin Bacon’ index – a measure of how busy an actor has been by measuring how many contacts with other actors is need to reach a film in which Kevin Bacon appears. These ideas are covered in detail in such books as Malcolm Gladwell’s The Tipping Point, and Philip Ball’s Critical Mass.

And now we have web based social networks such as Myspace, Facebook and Twitter, though other web based groups have been around since the early days of Compuserve, Aol, the Well and others. In some ways social networks can behave like crowds, which in a sense they are – only distributed over a wide area. And of course, they are more diffuse in both time and space, so do not tend to exhibit behaviour quite like hysteria.

Recent research however has shown that they can produce surprising results. Behaviour patterns such as happiness, depression and even obesity, can be spread through social networks like Facebook. Studies have shown that there is a greater correlation in these behaviours between people who are closely linked on Facebook than those who are not. The linkage acts up to three degrees of separation, so person A who is a ‘friend’ of person B who is a friend of C who is a friend of D shows some correlation between himself and D. Though naturally the correlation is stronger between immediate contacts. And, as in all social contacts, there is always some feedback going on.

Crowds and social networks are both similar to swarms that I discussed in the section on Biology. Behaviour is adapted according to the observed behaviour of close neighbours. Because humans have complex minds, and complex technology, the observation and adaptation in these networks can be more complex than in swarms, and closeness does not have to imply physical closeness, but close connectivity.

The Wisdom of Crowds

There has also been a lot of interest in ‘the wisdom of crowds’ in the light of social networks and other internet connectivity. The point is that, especially these days, no one person can possess more than a minute fraction of all the knowledge in the world. But if you can access in an integrated fashion the knowledge, talent, experience and wisdom of a large group of people, then you could have something potentially more powerful and wise than any one person. You have, in fact, some kind of composite mind.

The wisdom of crowds has been with us for a long time, since Adam Smith and his ‘invisible hand’ of market forces, as I shall discuss in Economics. And ever since democracy was invented, there has been some kind of trust in the wisdom shown by a widely based franchise.

But the internet has increased the number of ways in which this effect can be observed. Public opinion can be tested more or less immediately, and perhaps more reliably than by asking people questions. Opinion polls are always subject to the problem that people may give answers that they think that they should give, rather than that which they actually hold. Recent use of Google’s search data has shown that you can observe changes in the public’s economic activity more accurately than by any other means, and can be used to modify economic models. It shows what people are actually thinking by the questions they ask, including how they are thinking of spending their money. The net can also be used to quickly hold tests of public opinion, and to form pressure groups and create petitions. These can now be global in scope, and can form powerful lobbies which are capable of causing change to take place. Look at Avaaz for example.

There are also an increasing number of efforts to form internet groups that can combine together to do useful work. Some such efforts have been going on for a while, such as the search for extra terrestrial life (SETI), and simulating protein molecule folding. These have centred around the ability to link large numbers of PCs around the world to perform very heavy duty processing. I am rather fond of this trend because I wrote an essay some years back called ‘The Global Computer’ which discussed the general idea (and it is still on my web site atiyah.plus.com).

These efforts involved little input from the network group other than providing computer power. More recently there has been an increased emphasis on actually getting the group to contribute their personal skills and effort. For example, there is a Facebook ‘crowd source’ of 56,000 people in 101 countries working on an animation film by both producing short animation clips and voting on them to see which the crowd thinks best (see www.massanimation.com).

Hysteria and the Media

Mass hysteria and crowd behaviour spreads something like an epidemic. The more people who behave hysterically, or in some extreme way, the more likely that others will follow them. Mob violence can spread like a fire.

The media plays a part in this kind of spreading. A classic example was the death of Princess Diana. A natural expression of sympathy was magnified into an astonishing outburst of public mourning, and was hugely magnified by continuous coverage by the media. After a point, the media was no longer covering the original event, but the reaction to it, and other media coverage. In other words, the media was covering the media, which is a classic example of a feedback loop.

In fact, these days it hardly needs any interest from the public in an event for the media to get itself stuck in a positive feedback loop. If it is a ‘quiet news week’ then any event that the media perceives as being important (to the media) can spiral into a continuous coverage frenzy, with the mere fact that lots of media people are covering it becomes a reason in itself for others to follow. An example of this in the UK was in December 2004, when the media spent most of its time and newsprint on two fairly trivial (and unrelated) events involving the Queen’s butler, and Cherie Blair. These have now been forgotten, but at the time they occupied the entire attention of the media, to an extent which puzzled most viewers and readers, as many people had little interest in them.

Which all goes to show how deceptively dangerous positive feedback can be

 

Biology

6.               Feedback in Biological Systems

Feedback is so prevalent in Biology that I can only cover a small sample of the mechanisms involved. In fact it is hardly an exaggeration to say that all Biology is concerned with feedback.

The point is that in any biological system things need to be kept under control, so that the system can operate in a manner that is suitable, or even near optimal. So for a simple instance, our body temperature is kept remarkably under control in a variety of external conditions. This can only be done with a feedback mechanism, or more likely, numerous such mechanisms.

It is worth pointing out straight away that a biological system can be at many levels. It can be a single cell, an organism, a complete ecosystem, or indeed, even the whole biosphere.

Exponential growth

One of the most basic examples of feedback in living systems is growth. Living things start off small, and grow bigger. The amount of growth depends on how big the thing is. So as it gets bigger, it grows faster (up to a point). This is classic positive feedback, and is called exponential growth, because the mathematical expression is exp(x). The same thing can be observed in the growth of human population, and many other growth mechanisms.

Positive feedback is also used in organisms when they want to do things in a hurry – the ‘flight’ syndrome; making an escape from something nasty is a good example. To get things going quickly, positive feedback is used to pump up the systems needed for rapid motion.

An example of a positive feedback loop is the production of an impulse in a nerve: the depolarization of the nerve cell increases sodium flowing into the cell, which increases depolarization, which increases sodium flow, and so on. This positive feedback continues until a threshold is reached and the sodium channels are closed. So ultimately the positive feedback is limited  by a negative feedback to stop it getting out of control.

On the other hand, negative feedback is used to keep things under control, such as the level of a substance inside a cell. If too much gets made, one of the enzymes used in its production is inhibited, and production is reduced.

The general tendency of living things to maintain themselves in a suitable condition is called homeostasis.

Feedback mechanisms in Human Biology

In human beings, homeostasis controls such things as the total volume of blood, blood pressure, blood sugar, temperature, fluid intake, food intake, body clocks and sleep.

The Hypothalamus is important in many of these control mechanisms by controlling the hormones produced by the pituitary gland, which themselves control the different body functions. The hypothalamus itself receives information from the brain, nervous system, and the endocrine system and this enables it to control the temperature, energy balance, and fluid regulation of the body. It partly does this by influencing behaviour - for example by feelings of hunger, and partly by outputs of the endocrine and the nervous system.

The blood circulatory system is the ‘maintenance highway’ for homeostasis. It provides tissues with what they need, and removes waste products. But the levels of substances within the blood are actually under the control of other organs: the lungs and the nervous system control carbon dioxide, the liver and pancreas control glucose, the kidneys sodium and potassium, and the endocrine glands control hormones.

The whole system of control in humans is hugely complex, with many different interacting negative feedback loops involving different organs and hormone systems.

For example, when a certain amount of thyroid hormone is present in the bloodstream, the pituitary ceases production of thyroid-stimulating hormone until the level of thyroid hormone is reduced.

Similarly, a low level of blood calcium stimulates the parathyroid hormone (parathormone), which raises the calcium level. A high blood calcium level stimulates release of calcitonin from the thyroid, which then stops the parathormone production.

The thyroid picture is actually a bit more complicated. Thyrotropin (thyroid-stimulating hormone, or TSH) is produced by the pituitary gland by the action of thyrotropin-releasing hormone (TRH). TSH then stimulates the production of a thyroid hormone, thyroxine. There is then a three component feedback among TRH, TSH, and thyroxine: if the thyroid gland makes too much thyroxine, then this acts on the pituitary gland to slow down the secretion of TSH and TRH.

To give perhaps the most complex example, blood glucose level is stimulated by five different hormones: growth hormone, glucagon, glucocorticoids, adrenaline, and thyroxine. It is inhibited by just one - insulin which is produced by the pancreas High levels of glucose in the blood stimulate the production of insulin, whereas low blood-sugar levels stimulate the adrenal glands to produce adrenaline and glucagons. And of course if this control mechanism goes wrong, it leads to Diabetes.

The amount of glucocorticoid secreted by the adrenal cortex is controlled by the levels of adrenocorticotrophic hormone (ACTH), which itself  is produced by the anterior pituitary gland.

The endocrine system consists of the pituitary gland, the adrenal gland, the pancreas, the gonads, and the thyroid and the parathyroid glands. All these glands produce hormones.

If the homeostatic systems were simple feedback loops, all body systems would be kept in balance, but not be able to respond to sudden threats. So the endocrines are also regulated by the nervous system. This allows such things as sudden changes in adrenaline levels in response to stress. This is where things get really complicated, with two or three different feedback loops involving the hypothalamus in addition to the endocrine glands. In fact, endocrine glands can be controlled in various ways; by other hormones, by chemicals such as glucose, or by simple elements like potassium or calcium.

Actually, it turns out that different cell types within one endocrine gland also produce some control mechanisms, without involving circulating hormones. But it is still all negative feedback.

And just to make things more difficult, there are also other control characters such as neurotransmitters, growth factors and pheromones. But that is another story.

Homeostasis at the Cellular level.

All organisms perform homeostasis at a cellular level as the components of a cell must be held in a fairly stable concentration. The cell membrane is responsible for controlling which substances can enter and leave the cell. Waste products must be able to leave the cell so that they do not build up to toxic levels, and substances essential to metabolism must also be allowed in.

The same kind of negative feedback loops play an important role in regulating the rate at which enzymes act with a cell. If an enzyme acts upon a protein by breaking it down into separate molecules, these new molecules can inhibit the enzyme from breaking down more protein. This sort of control can extend to long pathways of enzyme reactions, with the start being controlled by the final end product.

Homeostasis in other Organisms

Organisms which do not have watertight skins, have to control of the amount of water which is gained or lost by absorption or evaporation. For example, bacteria have a high surface area to volume ratio, so they are prone to drying out. They try and deal with this by having an internal pressure which is greater than the outside, and so reduce water loss. The pressure is controlled by Osmosis – the effect caused by more water crossing a membrane in one direction than another. This is the reason, for instance, why dried fruit will plump up if left in a basin of water. They let in more water than they let out.

Other single celled organisms, like amoebas, gain water from their surrounding environment by osmosis. If this carried on without any control, they would die. So the water is kept in a separate compartment which occasionally ‘leaks’ it back outside the cell.

Fish have even more complex mechanisms to control their water content. Freshwater fish absorb water and lose salt by osmosis, so they have to take salt from the water through their gills, and also produce large amounts of urine.

On the other hand, sea fish lose water and gain salts by osmosis. So they have to swallow salt from the sea, and produce small amounts of urine.

Slime Moulds

Everyone likes to mention slime moulds sooner or later, so why should I be the exception. These fascinating creatures are part way between individuals and a composite being. They live in sort of colonies where they behave as amoebas mooching around feeding and dividing. Then sometimes – typically when the food gets scarce – they change tack, and gather together in clumps. They do this by following chemical attractants towards a centre. The more of them in a given centre, the more attractive the centre becomes, until all of the little fellows are tightly clumped. This is positive feedback, and we will come across something very similar in Astronomy.

When they have clumped, the whole lot behaves like one creature, moving around until it forms a little peak in the middle, which then produces spores that float off and land some distance away, where perhaps the feeding is better.

Swarms

Swarms are quite fashionable these days being an example of emergent behaviour which has only been understood relatively recently (and was mentioned in control systems). In fact swarm is a general term that refers to any large group of individuals who are behaving in some kind of related fashion. So a flock of birds is also a swarm, as is a shoal of fish, or a herd of bison. It saves having to remember all those group terms that come up in things like trivial pursuits. Ant colonies, bee hives and bacterial growth are also examples of swarms. The individuals in a swarm are referred to as agents or boids.

It can seem incredible watching a flock of tens of thousands of starlings, as I have done on some evenings over Tewkesbury (they seem to have gone elsewhere now sadly). They swoop, wheel and shift almost as one creature. How can they do this when it would take maybe several seconds for a ‘message’ to travel across the whole group?

Well, it turns out that they do this by following some very simple rules. The rules just relate to watching the nearest neighbours, and acting according to how they are moving. This is very similar to the rules in cellular automata that I talked about in control systems, which is one reason why this stuff has been of interest. Its possible to model this kind of group behaviour quite easily on computers by having an ensemble of ‘agents’ who each have associated values like physical position, and who all follow a set of rules or procedures. Luckily, this is easy to do in ‘object oriented’ computer programming which has become commonplace now. I first came across this method myself about twenty years ago or so when I was working in computer aided design. At the time it was very new in major software projects, although its roots date back to the sixties at Xerox Parc.

The rapid composite movement can be thought of as a sort of feedback, because each actor is getting feedback from its neighbours, and modifying its own behaviour as a result. Which behaviour is also being observed by other adjacent actors, and so on.

This kind of group movement is also of interest in road traffic engineering, because it has been shown that drivers modify their speed by observing the relative speed between them and the car in front (makes sense). The resultant behaviour of traffic emerges from individuals following their own simple rules.

One of the reasons that swarms are now popular is that these methods can be used quite successfully on a range of difficult problems around Optimisation.

This refers to a common example of trying to find the best or optimum solution for a given problem. Often quoted is the ‘Travelling Salesman’ problem, which involves finding the best (shortest) route to follow in order to visit a number of towns. The problems are hard because they typically involve potentially huge numbers of possibilities. Many methods have been used to tackle these problems, and swarms are showing promise as they involve a kind of parallel approach with multiple agents all ‘working’ on the problem at once. Interestingly, the precise methods used can be based on the observed behaviour of ant colonies or bee hives, with communication between agents based on the actual way ants or bees communicate.

There are many other possible applications of swarm ideas, such as unmanned military vehicles, planetary mapping by NASA, and medical nanobots in the human body. Swarm techniques have already been used in crowd scenes in films such as Lord of the Rings and Batman Returns.