
arXiv: 2502.16740
This paper investigates the task delegation trends of digital comic authors to generative AIs during the creation process. We observed 16 digital comic authors using generative AIs during the drafting stage. We categorized authors delegation levels and examined the extent of delegation, variations in AI usage, and calibration of delegation in co-creation. Our findings show that most authors delegate significant tasks to AI, with higher delegation linked to less time spent on creation and more detailed questions to AI. After co-creation, about 60% of authors adjusted their delegation levels, mostly calibrating to less delegation due to loss of agency and AIs unoriginal outputs. We suggest strategies for calibrating delegation to an appropriate level, redefine trust in human-AI co-creation, and propose novel measurements for trust in these contexts. Our study provides insights into how authors can effectively collaborate with generative AIs, balance delegation, and navigate AIs role in the creative process.
11pages
FOS: Computer and information sciences, Computer Science - Human-Computer Interaction, Human-Computer Interaction (cs.HC)
FOS: Computer and information sciences, Computer Science - Human-Computer Interaction, Human-Computer Interaction (cs.HC)
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
