He hired 181 professional recruiters and gave them a tricky task: to evaluate 44 job applications based on their math ability. The data came from an international test of adult skills, so the math scores were not obvious from the résumés. Recruiters were given different levels of AI assistance: some had good or bad AI support, and some had none. He measured how accurate, how fast, how hardworking, and how confident they were. Recruiters with higher-quality AI were worse than recruiters with lower-qualitnd ower-qualy AI. They spent less time and effort on each résumé, and blindly followed the AI recommendations. They also did not improve over time. On the other hand, recruiters with lower-quality AI were more alert, more critical, and more independent. They improved their interaction with the AI and their own skills. Dell’Acqua developed a mathematical model to explain the trade-off between AI quality and human effort. When the AI is very good, humans have no reason to work hard and pay attention. They let the AI take over instead of using it as a tool, which can hurt human learning, skill development, and productivity. He called this “falling asleep at the wheel.” Dell’Acqua’s study points to what happened in our study with the BCG consultants.
