2025· International Journal of Innovative Research in Humanities & Technology· Vol 8, pp. 01-14· 0 citations
TL;DR
This study examines the ethical challenges of Human–AI co-creation through a literature review and proposes a conceptual framework encompassing fairness, accountability, transparency, privacy, intellectual property protection, trustworthiness, and human oversight.
Abstract
Human–Artificial Intelligence (AI) co-creation refers to the collaborative creation of content, designs, decisions, software, and research outputs by humans and intelligent systems. The rapid advancement of generative AI technologies has transformed creativity and innovation across education, healthcare, business, engineering, media, and scientific research. While AI enhances productivity, creativity, and problem-solving, it also raises significant ethical concerns related to accountability, transparency, fairness, privacy, intellectual property, trust, and human agency. Unlike traditional human–computer interaction, AI actively contributes to ideation and decision-making, making ethical governance increasingly important. This study examines the ethical challenges of Human–AI co-creation through a literature review and proposes a conceptual framework encompassing fairness, accountability, transparency, privacy, intellectual property protection, trustworthiness, and human oversight. The findings indicate that accountability and transparency are the most influential factors for responsible AI collaboration, while bias and intellectual property disputes remain major barriers to adoption. The study highlights the need for ethical governance frameworks, transparent AI systems, regulatory compliance, and human oversight to promote trustworthy and responsible co-creative practices. Overall, the proposed framework supports sustainable Human–AI collaboration by balancing technological innovation with ethical responsibility, ensuring that AI complements rather than replaces human creativity.
The study proposes the Sociotechnical Explainability Alignment (SEA) framework, which conceptualizes ethical XAI as requiring alignment across four levels: design, user, team, and organization.
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