Over the past few years, we have gained a growing appreciation for what technology can and cannot do. As a result, we have gradually moved away from fears that machines will take all of our jobs to an understanding that we are likely to be working alongside technology in new ways.
A recent paper from INSEAD explores four ways in which the division of labor between man and machine may emerge. The four ways operate in a kind of matrix, with specialization along one axis and operating in either sequence or in parallel along the other axis.
The paper suggests that specialization is the optimal approach when there is a clear advantage for either us or the machine. For instance, the author suggests humans are best place to conduct a sales call or lead a meeting, but analysis of financial results may be best left to computers.
Humans can also come to the fore even if they offer no clear advantage over algorithms, simply because of the additional thought diversity they bring to the task. This is commonly used in areas such as medical diagnoses, where algorithms do a lot of the work, but humans always check and sign-off on the suggestions.
Working well
Of course, working effectively with technology is not simply a matter of finding the ideal combination, especially if humans don’t trust the technology they’re working alongside. In such a scenario, the author suggests that working in parallel may be the better approach, even if it overlooks the benefits provided by specialization.
The author further examined the kinds of cooperation that may enhance trust between man and machine in a second study, which they hope will act as a first step towards helping us to work more effectively with technologies such as AI.
The survey provides a degree of insight into the kind of configurations that people seem to both like and dislike. The researchers also believe it provides insight into how prepared people are for any potential future working alongside technology.
It’s the kind of analysis they believe managers and organization designers will need to do more and more of as AI and robotics become a more central part of our organizational existence.
