I’ve looked previously at the rise of so-called automated leadership, with the scheduling and appraisal of employees largely done via algorithm, with researchers exploring just how people feel working under this kind of leadership.
That is but one part of the infusion of automation into leadership, however, with things like forecasting and other forms of data analysis handed over to computers for a while now.
A team from the University of York and software company MooD International are teaming up to use a mixture of AI and gaming technology to help management decision making.
The work revolves around the so-called Monte Carlo Tree Search, which is a commonly used algorithm for decision-making in video games. The aim is to make a similar algorithm for use in the workplace.
This will involve a visualization the kind of impact a decision will have, thus hopefully making it easier for managers to ensure they make the right choices.
“Despite huge developments in AI research and gaming intelligence in recent years, there is still a big gulf between such techniques and how they can be applied to real-life situations,” the researchers say.
The partnership will see the academic thinking being put through the rigors of commercial life, with the results of this exposure then feeding back into making the algorithms smarter. Hopefully, it’s a feedback look that will bring managers a significant amount of support in making the best decisions.
Suffice to say, decision support systems have been around in some guise or other for many years, but there’s much to suggest that the convergence of big data and AI can really deliver on what has largely been promised up until now.
Editor's note: For more on algorithms and machine learning in video games, watch the following video about Super Mario: