The ambiguity of intelligent algorithms: job killer or supporting assistant

The history of industrialisation shows how new technologies triggered social and economic revolutions, and how traditional jobs were replaced or changed by the use of machines. There are signs of highly dynamic changes in the learning and working environment of the 21st century, with serious global social consequences similar to the industrial revolution. In the working environment, computers assist people and reduce their workload in a variety of ways. With increasing computing power and advanced memory technologies, they master the basics of autonomous machine learning. Intelligent algorithms are increasingly taking control, with the result that in many occupations, decisions are already routinely taken by software systems and not by people any more. Within just a few decades, information technology and its associated technological requirements have become the catalyst for a highly industrialised society. Developments in microelectronics are progressing at exponential speed, which will also have far-reaching social consequences for vocational fields outside of the information and communication technologies. Impacts of the knowledge and information society include changes in the nature of work towards an increasingly important service sector and a significant increase in knowledge work. This is accompanied by a decline in the working population (demographic change) and the need for a modified workplace design in context of the changed age structure of the workforce. This Paper intends to explore on basis of the findings from the most recent German Foresight Exercise (BMBF Foresight Cycle II), how technological innovations in the field of ICT will dramatically change structures and ways of communication, collaboration and work. Some alternative development paths and implications for the areas job, career, production and work are scrutinized and discussed. Possible developments depend on the degree of autonomy of computer systems and the extent to which humans lose control over these systems; while - of course - the boundaries between conceivable scenarios are fluid.