Recent research from ESMT Berlin delves into the intersection of artificial intelligence (AI) and large-scale research projects, demonstrating AI’s potential to manage human participants by handling tasks such as coordination, motivation, and task allocation.

The study reframes AI’s role from that of a mere “worker” executing specific tasks to that of a “manager” overseeing human workers engaged in research activities. This shift, known as algorithmic management (AM), marks a significant departure in research methodology, promising increased efficiency and scalability.

Growing complexity

As scientific research becomes more complex, AI’s ability to swiftly and comprehensively manage tasks suggests it could outperform human managers. The study focuses on algorithmic management in crowd and citizen science, illustrating how AI effectively handles managerial functions such as task division, direction, coordination, motivation, and facilitating learning.

Using a combination of online document analysis, interviews with project stakeholders, and firsthand participation in projects, the researchers identify instances of algorithmic management and explore its effectiveness.

The increasing adoption of algorithmic management in various research domains suggests it could play a crucial role in enhancing research productivity.

Enhancing research

“The capabilities of artificial intelligence have reached a point where AI can now significantly enhance the scope and efficiency of scientific research by managing complex, large-scale projects,” the researchers explain.

They found that those using additive manufacturing (AM) tend to be bigger and often linked with platforms offering shared AI tools. This hints that AM might help projects grow, but they need solid technical support that solo projects might lack. These findings show how research advantages are changing and could affect funding, digital platforms, and big research institutions like universities and corporate R&D labs.

While AI can assume critical management roles, it doesn’t imply that principal investigators or human managers will become redundant.

“If AI can take over some of the more algorithmic and mundane functions of management, human leaders could shift their attention to more strategic and social tasks such as identifying high-value research targets, raising funding, or building an effective organizational culture,” the researchers conclude.