Human intuition, when combined with algorithmic assistance, can outperform both individual algorithms and teams of human experts in complex decision-making tasks. This finding is the result of an experiment conducted by researchers at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL). The study involved a task called ‘guessing games,’ where participants had to predict the pattern of a series of numbers.

The results showed that human participants, when supported by algorithms, made more accurate predictions than either humans or algorithms alone. The combination of human intuition and algorithmic assistance resulted in a 21.3% improvement in accuracy over the best-performing algorithms, and a 24.2% improvement over the best-performing human teams.

The researchers believe this approach, termed ‘human-in-the-loop optimisation,’ could be applied to various fields, such as data analysis, medical diagnosis, or any area where pattern recognition and decision-making are crucial. This study highlights the potential of combining human intuition with technology to solve complex problems more effectively.

Despite the success of this approach, the researchers acknowledge that it may not be suitable for all tasks. They emphasise that the effectiveness of the human-algorithm partnership depends on the complexity of the task and the quality of the human intuition involved.

Go to source article: