Augmenting Minds or Automating Skills: The Differential Role of Human Capital in Generative AI's Impact on Creative Tasks
Meiling Huang, Ming Jin, Ning Li

TL;DR
This paper investigates how generative AI impacts creative tasks by interacting with different types of human capital, revealing that AI democratizes tools but can also deepen cognitive inequalities and shift creative advantage.
Contribution
It introduces a theoretical framework combining human capital theory with automation-augmentation, highlighting AI's role in reshaping skill valuation and inequalities in creative work.
Findings
AI enhances general cognitive abilities and adaptability.
AI diminishes the value of domain-specific expertise.
AI can exacerbate disparities in skill valuation and workplace hierarchies.
Abstract
Generative AI is rapidly reshaping creative work, raising critical questions about its beneficiaries and societal implications. This study challenges prevailing assumptions by exploring how generative AI interacts with diverse forms of human capital in creative tasks. Through two random controlled experiments in flash fiction writing and song composition, we uncover a paradox: while AI democratizes access to creative tools, it simultaneously amplifies cognitive inequalities. Our findings reveal that AI enhances general human capital (cognitive abilities and education) by facilitating adaptability and idea integration but diminishes the value of domain-specific expertise. We introduce a novel theoretical framework that merges human capital theory with the automation-augmentation perspective, offering a nuanced understanding of human-AI collaboration. This framework elucidates how AI…
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Taxonomy
TopicsExplainable Artificial Intelligence (XAI) · Innovation, Sustainability, Human-Machine Systems · Artificial Intelligence in Healthcare and Education
