Human-generative AI collaboration enhances task performance but undermines human's intrinsic motivation

Abstract

In a series of four online experimental studies (total N = 3,562), we investigated the performance augmentation effect and psychological deprivation effect of human-generative AI (GenAI) collaboration in professional settings. Our findings consistently demonstrated that collaboration with GenAI enhanced immediate task performance. However, this performance augmentation effect did not persist in subsequent tasks performed independently by humans. Importantly, transitioning from collaboration with GenAI to solo work led to an increased sense of control of human workers, and was also accompanied by significant decreases in intrinsic motivation and increases in feelings of boredom. These results highlight the complex dual effects of human-GenAI collaboration: It enhances immediate task performance but can undermine long-term psychological experiences of human workers.

Fig. 1

Overview of Studies 1 to 3. This figure illustrates the experimental setup across Studies 1 to 3. For each study, participants in the Collab-Solo condition (top flow) worked with ChatGPT on Task 1, then proceeded to work alone on Task 2, whereas participants in the Solo-Solo condition (bottom flow) independently completed both Task 1 and Task 2. Measures taken after each task assessed participants’ sense of control, intrinsic motivation, and feelings of boredom. Each study adopted different tasks.

Fig. 2

Study 4 experiment design.

Fig. 3

Augmentation effect of collaboration with ChatGPT for Study 1, Task 1 performance. Independent raters assessed how engaging and informative the posts created by participants were. The overall quality score was computed as the means of these two ratings. In contrast to individuals who created Facebook posts on their own, those who collaborated with ChatGPT produced posts that were more engaging and of higher overall quality. Nevertheless, there was no significant difference between the two participant groups in terms of post informativeness. N = 352. ^* p < .05. Error bars indicate ± 1 SEM.

Fig. 4

Study 1, Task 2 performance across two conditions. Independent raters counted the number of ideas; and assessed the quality of these ideas on a five-point scale with endpoints 1 for “poor” and 5 for “excellent” in Task 2 (Alternative Uses Test; AUT). Participants who collaborated with GenAI in Task 1 generated ideas of higher quality in the subsequent human-solo work in Task 2, compared to participants who worked solo in both tasks. No significant difference was found between the two groups in terms of the number of ideas generated in Task 2. N = 352. ^** p < .01. Error bars indicate ± 1 SEM.

Fig. 5

Study 1, Deprivation effect of collaboration with ChatGPT on psychological experiences. Participants reported their sense of control, intrinsic motivation, and feelings of boredom on 7-point scales after Task 1 and Task 2, respectively. For participants who shifted from collaboration with ChatGPT to solo work, we observed a significant change in their sense of control (increased), intrinsic motivation (decreased), and feelings of boredom (increased). Such within-person changes were also significantly different from participants who consistently worked on two tasks alone. N = 352. ^* p < .05; ^** p < .01; ^*** p < .001. Error bars indicate ± 1 SEM.

Fig. 6

Augmentation effect of collaboration with ChatGPT for Study 2, Task 1 performance. We analyzed the quality of performance review reports across three dimensions—word count, analytical content, and prosocial orientation—using the LIWC tool. Results suggest collaborating with ChatGPT augments participants’ Task 1 performance. Participants collaborating with ChatGPT produced outputs of higher quality across all three dimensions: They had greater word counts, exhibited more analytical content, and demonstrated enhanced prosocial orientation compared to those working without ChatGPT’s assistance. N = 793. ^** p < .01; ^*** p < .001. Error bars indicate ± 1 SEM.

Fig. 7

Study 2, Task 2 performance across two conditions. Independent raters counted the number of ideas and assessed their novelty and usefulness on a five-point scale (1 = “poor”, 5 = “excellent”) in Task 2, where participants brainstormed ideas for improving a product. Analysis of data showed no significant differences between the two conditions in terms of idea quantity, novelty, or usefulness, suggesting that collaboration with ChatGPT did not significantly augment performance in the subsequent solo task. N = 793. ^* p < .05; ^** p < .01; ^*** p < .001. Error bars indicate ± 1 SEM.

Fig. 8

Study 2, Deprivation effect of collaboration with ChatGPT on psychological experiences. Participants transitioning from collaboration with ChatGPT to solo work reported a significant increase in their sense of control, while those who worked independently on both tasks reported a significant decrease. Additionally, participants in both conditions experienced a notable decrease in intrinsic motivation and an increase in feelings of boredom. However, the differences in these changes between the two conditions were non-significant for intrinsic motivation and only marginally significant for feelings of boredom. N = 793. ^† p < .10,^* p < .05; ^** p < .01; ^*** p < .001. Error bars indicate ± 1 SEM.

Fig. 9

Augmentation effect of collaboration with ChatGPT for Study 3, Task 1 performance. We analyzed the quality of welcoming emails using LIWC across three dimensions: Word count, affiliation content, and social orientation. Results indicated that collaboration with ChatGPT enhanced Task 1 performance, with participants who used ChatGPT producing outputs that were not only longer but also demonstrated greater affiliation content and higher social orientation compared to those who worked independently. N = 793. ^* p < .05; ^** p < .01; ^*** p < .001. Error bars indicate ± 1 SEM.

Fig. 10

Study 3, Task 2 performance across two conditions. Independent raters counted the number of ideas; and evaluated their novelty and usefulness on a five-point scale (1 = “poor”, 5 = “excellent”) in Task 2, where participants brainstormed promotional strategies for a product. The analysis revealed no significant differences between the two conditions in terms of the quantity, novelty, or usefulness of the ideas, indicating that collaboration with ChatGPT did not significantly enhance performance in the subsequent human-solo task. N = 793. ^* p < .05; ^** p < .01; ^*** p < .001. Error bars indicate ± 1 SEM.

Fig. 11

Study 3, Deprivation effect of collaboration with ChatGPT on psychological experiences. Participants reported their sense of control, intrinsic motivation, and feelings of boredom on 7-point scales after Task 1 and Task 2, respectively. Those who transitioned from collaboration with ChatGPT to human-solo work showed a marginally significant increase in their sense of control. In contrast, participants who worked solo in both tasks experienced a significant decrease in their sense of control. Additionally, those shifting from collaboration to human-solo work reported significantly decreased intrinsic motivation and increased feelings of boredom, with these changes being significantly different from those who consistently worked solo on both tasks. N = 352. ^* p < .05; ^** p < .01; ^*** p < .001. Error bars indicate ± 1 SEM.

Fig. 12

Performance augmentation of ChatGPT of Study 4, Task 1. We analyzed Task 1 performance using LIWC across three dimensions: Word count, analytical content, and positive tone. Results indicated that collaboration with ChatGPT (i.e., the Collab-Solo and Collab-Collab conditions, N = 801) enhanced Task 1 performance significantly, with participants who used ChatGPT producing outputs that were longer, more analytical, and more positive in tone compared to those who worked solo in Task 2 (i.e., the Solo-Solo and Solo-Collab conditions, N = 823). ^* p < .05, ^*** p < .001. Error bars indicate ± 1 SEM.

Fig. 13

Study 4, Task 3 performance across Collab-Solo and Solo-Solo conditions. Task 2 performance was evaluated based on text length, analytical content, and positive tone of participants’ outputs, analyzed using the LIWC software. Results showed no significant differences between the two conditions in analytical content or positive tone, but a slight difference in text length, with the Solo-Solo condition producing longer texts. These findings suggest that prior collaboration with ChatGPT does not significantly enhance performance in subsequent solo tasks. N = 773. ^* p < .05. Error bars indicate ± 1 SEM.

Fig. 14

Study 4, Changes of psychological experiences from Task 1 to Task 2 across four conditions. Participants rated their sense of control, intrinsic motivation, and feelings of boredom on 7-point scales after completing each task. Those who transitioned from collaboration with ChatGPT to solo work (N = 345) reported an increased sense of control, decreased intrinsic motivation, and increased feelings of boredom. Participants who worked solo in both tasks (N = 428) experienced a decrease in sense of control and intrinsic motivation, and an increase in feelings of boredom, similar to those in the Solo-Collab condition (N = 395), who transitioned from solo work to collaboration with ChatGPT, and those in the Collab-Collab condition (N = 456), who collaborated with ChatGPT in both tasks. Comparisons between the Collab-Solo condition and the other three conditions are illustrated in the figure. ^* p < .05, ^** p < .01, ^*** p < .001. Error bars indicate ± 1 SEM.