Machine agency and the future of work
The introduction of new technology causes concern for the future of work. What is the role of humans in a work life in which an increasing number of tasks are conducted better and more efficiently by machines than by humans.
In a much cited paper on automation of work through computerization, Frey and Osborne, take a starting point in the premise that new technology makes old jobs redundant faster than new jobs are created. They then move on to claim that advances in machine learning and mobile robotics in the 21st century may render not only manual routine work victim to automation, but also work previously thought of as non-routine such as car driving, medical diagnostics, financial trading, or educational tutoring. Think only of the self-driving cars, entities that are able to perform tasks that only a few years back were considered beyond the computational capacities of machines. Tasks that represents engineering bottlenecks for computerizations, such as those associated with perception and manipulation in highly diverse environments, creativity, or social intelligence, are considered low risk for automation also in the foreseeable future. Hence, workers in work that are at risk for automation may need to acquire skills that are not easily automated.
While there is no doubt that automation will replace human workers, the picture may not be as bleak as sometimes suggested in popular reports on the subject. Autor, in an essay on workplace automation, argue that “journalists and even expert commentators tend to overstate the extent of machine substitution for human labor and ignore the strong complementarities between automation and labor that increase productivity, raise earnings, and augment demand for labor”. One example is the technological improvements in the health sector which lead to increasingly larger shares of income being spent on health. Another, is the value creation in the computer industry itself, where automating machinery spawn myriads of previously non-existing jobs.
In HUMANE, we have used the typology dimensions human agency and machine agency as a framework for discussing the role of automation in the complex systems. While Frey and Osborne, as well as Autor, discuss the effect of automation on work at a societal level, we discuss how automation may affect the work of humans within specific human-machine networks. Through a series of case studies on systems for decision support, crisis management, and evacuation support, we investigate how increasing the range of tasks allocated to computerized machines in such settings may actually strengthen the range of tasks, opportunities for influence, and opportunities for creativity in human operators. In these domains, all characterized by highly procedural work tasks and the need to adhere to regulation and policy, allowing machines to take over procedural decision making, human operators may instead spend their time and resources at the tactical and strategical levels of decision making. Here, automation does not remove the need for human operators, but redefines its purpose, allowing for novel ways of value creation.
We often seem to think of automation in terms similar to that of the self-driving cars, where the role of the human driver simply evaporates. The reality, however, may often be that automation enables new forms of value creation where the combined capabilities of humans and machines provide better outcomes in a more efficient manner than was previously possible. By understanding how to design the networked interaction between humans and machines, as we aim for in the HUMANE project, such an optimistic take on the social challenge of automation may be even more feasible.