<p>A growing number of studies have compared human and AI creative performance. These studies differ in AI chatbots, human populations, creativity tasks, and creativity indicators (e.g., originality, usefulness, elaboration). They mostly neglect psychological research on determinants of creative performance such as instructions or processing time. The present study contributes to the theoretical foundation and replicates a study comparing humans’ and AI’s creative output in the Alternate Uses Task. Building on established knowledge of creativity determinants, we modified the Alternate Uses Task’s instructions (call for quality AND quantity), provided more time for the human participants, and added a second task (Remote Associates Task). The Alternate Uses Task output was scored in two ways: the mean and maximum scores of each Alternate Uses Task item, both in terms of semantic distances and in terms of human rating scores. The result shows that AI’s mean scores were significantly higher in the original and modified Alternate Uses Task condition, maximum scores in the original Alternate Uses Task condition, and in the Remote Associates Task. No significant differences between humans and AI were found for the maximum scores in the modified Alternate Uses Task. We mainly replicated the original studies’ findings. Our study provides initial clues that the evaluation of creative performances depends on creativity indicators and approaches (instructions and time).</p>

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Time-on-task and instructions help humans to keep up with AI: replication and extension of a comparison of creative performances

  • Astrid Carolus,
  • Martin J. Koch,
  • Shuyan Feng

摘要

A growing number of studies have compared human and AI creative performance. These studies differ in AI chatbots, human populations, creativity tasks, and creativity indicators (e.g., originality, usefulness, elaboration). They mostly neglect psychological research on determinants of creative performance such as instructions or processing time. The present study contributes to the theoretical foundation and replicates a study comparing humans’ and AI’s creative output in the Alternate Uses Task. Building on established knowledge of creativity determinants, we modified the Alternate Uses Task’s instructions (call for quality AND quantity), provided more time for the human participants, and added a second task (Remote Associates Task). The Alternate Uses Task output was scored in two ways: the mean and maximum scores of each Alternate Uses Task item, both in terms of semantic distances and in terms of human rating scores. The result shows that AI’s mean scores were significantly higher in the original and modified Alternate Uses Task condition, maximum scores in the original Alternate Uses Task condition, and in the Remote Associates Task. No significant differences between humans and AI were found for the maximum scores in the modified Alternate Uses Task. We mainly replicated the original studies’ findings. Our study provides initial clues that the evaluation of creative performances depends on creativity indicators and approaches (instructions and time).