Introduction: From intelligent machines to self-driven organisations

Abstract

One of the sources of human ‘competitive advantage’ over other animals stems from our capacity for communication and abstract thought. This allows us not only to collectively perform certain tasks but also to transfer years’ worth of cumulative experience and knowledge to our children and other members of the community. This knowledge constitutes a key factor in our development: the more we acquire and learn to utilise, the faster we are able to grow. Thousands of years of history allowed humans to develop many effective methods of transferring knowledge, particularly by teaching it to others. Still, those methods are not without certain inherent limitations: they are time-consuming and highly dependent on the aptitude and motivation of the respective people involved. But even despite this fact, the dynamics of societal development, be it in the technological, economic (welfare) or social dimension (level of education, health, value systems) remains staggeringly high. But let us imagine structures that would (1) have the ability to gather and process considerably larger amounts of information from a far broader spectrum of stimuli than that available to humans, (2) be able to extract knowledge therefrom and learn from the experiences gained and (3) have the capacity to instantaneously and reliably transfer the same to all members of their community. As soon as any one of the thousands of elements comprising such a structure were to learn a certain skill, all other members thereof would also gain access to the same. And if a certain mistake were made and then successfully remedied in a given situation, all members would learn the ability to avoid it in the future. How quickly would such a structure be able to develop? And what would be the direction of its evolution? For years, artificial intelligence (AI) has excited the imaginations of science fiction writers and business managers alike. On the one hand, there are many hopes for potential future benefits, and on the other, exaggerated fears of less than welcome repercussions. Optimists see it as a chance for accelerated growth, lower production costs or improved safety. Pessimists fear the expected disappearance of job opportunities, excessive dependence on technology, deterioration of human cognitive abilities, a world controlled by elites with exclusive access to intelligent technologies and ultimately ripped from our grasp by AI itself. Meanwhile, researchers are busy looking for new