Genetic Economics 0. Abstract When reflecting on the possible changes the coming decades may bring, technological inventions and discoveries readily come to our imagination. Cloning, robotics, human-computer interfaces, IT- and space-technology are only some examples. The following essay, however, suggests how some slight additions to the rules governing multiple store companies and investment trusts may eventually change economics at large. Applying basic genetic principles like encoding of traits, duplication instead of growth and variation of traits may lead to whole populations of companies optimizing themselves according to the laws of evolution. If this principle should be successful, it will effect two major changes: Firstly, economics will mainly deal with „customizing“ genetic principles to certain branches. Instead of thinking about how a certain company should be improved, the overriding question will be how best to filter out the influence certain traits have on economic success. And secondly, politicians will have to reconcile themselves to the fact that economic developments will be even further ahead of social and political awareness than they are today. Yet, the full force of these changes is only hinted at as the main focus of the essay lies on the comparative ease with which a genetic economy could be realized within our lifetime. 1. The genetic principle The history of life on earth is the story of a never ending stream of ingenious inventions. The creation of living cells out of dead matter is still seen by many as a miracle. The chemistry of photosynthesis, easily mastered by almost all plants, can give headaches to even clever students. And albeit all advances in IT-technology, the living tissue we call the brain is still the most powerful information processing unit we know so far. There is a widespread belief that the theory of evolution can account for many, if not all, of these marvels. No single cell of a bird’s brain did ever concern itself with optimizing the shape of the bird’s wings. It was brainless mechanisms like „meiosis“, „recombination“, „mutations“, „selection“ and so on that shaped living organisms towards perfection over many generations. Yet, although text-books of genetics are often full of mathematics, complicated figures and scientific jargon the basic principle behind it all can be boiled down to three fundamental rules applicable to any sufficiently large number of individuals competing against one another for limited ressources.
An example will illustrate the effect of these principles before we go on to extend them to economic companies. Suppose some hypothetic arctic forest is populated by a large population of foxes. A limited ressource they compete for is prey. An important trait of the foxes is the colour of their fur, which is biologically encoded in genes. Up to now, the foxes were rather whitish to make them indistinguishable against the prevalent background of snow. Being thus well camouflaged, they could stealthily approach hares and fowl near enough to hunt them down in a short sprint. Suppose, however, that in recent years, a change in climate has made the green and grey of plants and stones the predominant colour of the landscape. A fox having perchance a gene for grey and green fur will probably enjoy an advantage in hunting over its competitors. This new fox will be able to produce and nurture more offspring than the white foxes. Owing to the rules of sexual reproduction, the fox hands on its genes to its offspring. Over a number of generations, the gene for grey and green fur will automatically spread within the population of foxes. As a result, the whole population of arctic foxes has become more successful. It is important to bear in mind, that no individual fox need to have any understanding of the whole matter. Let us now turn our attention to economics. Although the idea of economic evolution is often conjured up, it usually exhausts itself in allusions to competition and selection. Quite rightfully so. Instead of reproducing themselves on the basis of encoded traits, most companies aim at growth. Growth, however, implies a change in structure and organisation. A company with 15.000 employees, for instance, cannot be based on the principle of a familiy-like community. With a small company, this principle may well be a main contributor to the overall success. Therefore, a growth in size may be identical with the renunciation or perversion of formerly successful traits. Biological evolution has gone a different way. Successful bacteria do not grow to the size of an elephant. They do not even try to do so. Instead, they duplicate themselves and thereby give their successful genes a chance to statistically prove their worth under more or less similar conditions. We will now proceed to see how the basic principles of genetic evolution could be implemented in an economic environment. Most of the raw-material exists already. 2. Building a genetic company: multiple store companies Multiple store enterprises come very close to the principles of genetic evolution. Consider any of the well known fast food chains. Profits are (at least partly) used to set up new restaurants. And all restaurants are built and organised along the same line which is most likely laid out in some sort of blueprint. Enforcing two simple additional rules would transform such a multiple store enterprise into a genetic algorithm. Firstly, each restaurant is allowed to have its own blueprint to encode its traits. And these traits can be modified by the restaurant`s management, thus providing for mutations. Secondly, the more profit a restaurant contributes to the overall company, the more likely it is to have its traits passed on to new restaurants. This could be implemented by a formula like the following: the most profitable restaurant contributes half of its genes, selected at random, to a new restaurant. The second most profitalbe restaurant contributes a quarter of its... Suppose a fast-food chain called „Bülent’s“ specializes on Mediterranean cookery. It has restaurants all over the world. The following list is an extract of a hypothetical blueprint of a single restaurant. Italics indicate where restaurants are allowed the freedom of their own choice:
The management of the specific restaurant thought it a good to idea to attract families by installing a TV box for the children. But even after the installation, it will be difficult to assess the influence of this feature on the restaurant’s profit (or loss). A rise or fall of profit may be attributable to any other feature or even external influences like a change in the purchasing power of consumers. This is where genetic evolution plays out its trump. If the gene for a TV box was beneficial to restaurants, it will have a good chance of spreading to new restaurants and ultimately over the whole population. The more beneficial the gene, the more profitable the restaurant, the more likely the gene is to spread. There is no need for analysing a certain gene’s influence on profit. No money need to be wasted on studies, polling, benchmarking or expensive advisors. Traits which are suspected of having an influence on profit but which are at the same time difficult to assess should be considered for definition as genes on restaurant blueprints. Over a sufficiently long time, the statistical filtering of the genetic principle will select the more successful genes. To make the fast food company work as a genetic algorithm, the rate of mutations must be limited. A gene must have a fair chance to express itself in a number of restaurants before it is „mutated away“. Therefore, some rule is needed to prevent the management from changing the blueprints of their restaurants at too high a rate. This consideration, however, is a matter of optimization rather than principle. Also, some rules must be defined for when to close down less profitable restaurants. „Any restaurant making losses in three successive years will be closed“ may be as good a rule as „the least profitable two percent of restaurants will be closed down“. Again, this is a matter of optimization and not one of principle. What has been outlined so far may easily be implemented by any multiple store company adventurous enough to invest some capital on an idea which cannot do much harm if not successful. If it does work, however, it may well usher in a new era of economics. 3. Building a genetic company: extending the idea to investment trusts Large investment trusts, too, could be turned into genetic algorithms. Each trust would have to specialize on companies that would be more or less comparable. And the trust would have to aquire enough shares to have a say in its companies’ management. Something which is not so uncommon today. A sufficient amount of encoding could then be effected by enforcing the application of norms such as ISO 900X (quality managment), for example, or ISO 1400X (environmental management). These norms can be interpreted as guidelines on how to make blueprints of key traits of the companies. A fully applied norm may be regarded as part of the companies` genectic code. The use of computerized workflow engines may also be a good way of encoding important company features. The investment trust might then go on to enforce an advanced form of compulsory bench-marking. The benchmark is defined in terms of shareholder value, for instance. The genes of the best in class are perforce transferred to those companies which are worst in class. Surplus dividend is used to set up new companies, the blueprint of which, of course, includes the best companies` genetic code. 4. Genetic management A genetic trust is self-learning. No one need worry about trying to predict the influence a certain change in company structure or decision making processes may have. Populations of companies will automatically adapt to changes in their environment. A change of consumer behaviour, for instance, will be reflected by a rise or fall of certain genes. The management of genetic trusts will be less occupied with questions concerning company structure or politics. Instead, they will try to optimize the genetic algorithms. The one fundamental question will be how best to mix and modify the genes of all companies taking part in the game. Should companies be arranged in groups which are to change genes? These would correspond to biological species. Should genes only be mixed when creating new individual companies? This would mean that other individuals might have to „die“. Is there an optimum life-span for single companies for the whole population to be optimized? What is the best rate of mutation? Should it, in some way, be related to the rate the environment changes? Should genes be exchanged amongst living individuals, as is the case with many bacteria? Many questions geneticists put to nature, may soon be applied to companies. Indeed, the whole theory of evolution and genetics may be applied to economics wholesale. The far-reaching implications of this may be appreciated by reading any standard textbook on the topic. 5. Outlook: political and social implications Ours is a time of high expectations. The capital markets are booming, eager to give any new technology a fair chance. Computer sciences, robotics, artifial intelligence and the life sciences are only a few fields of research that compete for capital while at the same time spurring one another on to ever new discoveries. So, it’s only a question of time until some large company or investment trust will define some filling stations, some food markets or some hotels as a genetic algorithms. If the idea is worth anything, it will have a good chance of radically transforming economics within a few decades. The pace of progress will be much increased, even if measured against the staggering rate we have already. Successful innovations will have spread before political life has taken notice of them. The history of the Internet gives a faint idea of this phenomenon. Genetic economics will bring the phenomenon of companies spreading across the earth in full career without anybody knowing why. Long before politics have formed an opinion on the desirability of a certain trait in companies, the trait may have spread and be a fact. If politics are not to succumb to economics, as was the case with Laissez-Faire policies in the 19th century, they will themselves have to think about how to become adaptive. Adaptivity of companies as well as social and economic systems will be a key-issue of the 21st century. Evolution on our planet will soon have taken another leap.
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