How to avoid the traps of “social laziness”: steps to Artificial intelligence improve team effectiveness
Artificial intelligence (AI) is rapidly becoming an indispensable tool in business. From automating marketing campaigns to improving customer interactions! AI promises to significantly improve the efficiency of companies. However! not everything is so clear-cut.
Recent research suggests that working with AI can have both positive job function email list and negative effects on teamwork. Have you ever experienced a decrease in productivity in your team? The reason for this may be the so-called “social laziness” effect! a phenomenon that can be amplified by the use of artificial intelligence.
The phenomenon of social laziness: more does not mean better
Social laziness is a psychological phenomenon that manifests itself in the reduction of individual efforts of group members when performing a shared task. In other words! when people work together! they tend to exert less effort than when working alone.
This phenomenon is known as the Ringelmann effect and was anything about such applications yet first scientifically described by French engineer Maximilien Ringelmann in 1913. In his research! he found that when people pull a rope together! the total force they develop is less than the sum of the forces they could develop working individually.
For example! if one person can pull a rope with a force of 85 kilograms! then a group of seven people should logically be able to pull the rope with a force of 595 kilograms ( 7 people x 85 kg/person). However! in practice! the group was only able to pull 455 kilograms (7 people x 65 kg/person) . This means that the larger the group! the less effort each member exerts.
AI as a catalyst for “social laziness”
In 2022! Fabrizio Dell’Acqua of Harvard Business School led a large-scale ao lists study to examine the impact of artificial intelligence (AI) on the recruitment process. The experiment involved 181 recruiters who were asked to evaluate 7!964 resumes of software engineering candidates. Candidates were evaluated solely on their math skills.