Recent advances in generative AI have introduced AI-extended characters, which refer to AI-generated personas grounded in pre-existing human or fictional referents. While prior research focuses on direct social interaction, their capacity to foster parasocial interaction (PSI) in media remains underexplored. We analyzed 1,460 audience comments from 299 AI talk show videos to investigate this gap. Our findings identify three distinct objects of PSI within AI-extended characters: referents, AI proxies, and blended characters. Although referents remain the primary focus, PSI toward AI proxies and blended characters suggests that audience engagement with AI media may extend beyond the original referents. We further found that humanlikeness and AI awareness appeared as recurring themes in how audiences interpreted these relationships. This work provides a preliminary understanding of human engagement with AI-extended characters and offers design implications for future AI-mediated creative media content.

AI has been increasingly integrated into screenwriting practice. In refinement, screenwriters expect AI to provide feedback that supports reflection across the internal perspective of characters and the external perspective of the overall story. However, existing AI tools cannot sufficiently coordinate the two perspectives to meet screenwriters’ needs. To address this gap, we present DuoDrama, an AI system that generates feedback to assist screenwriters’ reflection in refinement. To enable DuoDrama, based on performance theories and a formative study with nine professional screenwriters, we design the Experience-Grounded Feedback Generation Workflow for Human Reflection (ExReflect). In ExReflect, an AI agent adopts an experience role to generate experience and then shifts to an evaluation role to generate feedback based on the experience. A study with fourteen professional screenwriters shows that DuoDrama improves feedback quality and alignment and enhances the effectiveness, depth, and richness of reflection. We conclude by discussing broader implications and future directions.

Generative AI has greatly transformed creative work in various domains, such as screenwriting. To understand this transformation, prior research often focused on capturing a snapshot of human-AI co-creation practice at a specific moment, with less attention to how humans mobilize, regulate, and reflect to form the practice gradually. Motivated by Bandura’s theory of human agency, we conducted a two-week study with 19 professional screenwriters to investigate how they embraced AI in their creation process. Our findings revealed that screenwriters not only mindfully planned, foresaw, and responded to AI usage, but, more importantly, through reflections on practice, they developed themselves and human-AI co-creation paradigms, such as cognition, strategies, and workflows. They also expressed various expectations for how future AI should better support their agency. Based on our findings, we conclude this paper with extensive discussion and actionable suggestions to screenwriters, tool developers, and researchers for sustainable human-AI co-creation.

With the rise of AI technologies and their growing influence in the screenwriting field, understanding the opportunities and concerns related to AI's role in screenwriting is essential for enhancing human-AI co-creation. Through semi-structured interviews with 23 screenwriters, we explored their creative practices, attitudes, and expectations in collaborating with AI for screenwriting. Based on participants' responses, we identified the key stages in which they commonly integrated AI, including story structure & plot development, screenplay text, goal & idea generation, and dialogue. Then, we examined how different attitudes toward AI integration influence screenwriters' practices across various workflow stages and their broader impact on the industry. Additionally, we categorized their expected assistance using four distinct roles of AI: actor, audience, expert, and executor. Our findings provide insights into AI's impact on screenwriting practices and offer suggestions on how AI can benefit the future of screenwriting.

Researchers frequently need to synthesize their own publications into coherent narratives that demonstrate their scholarly contributions.To suit diverse communication contexts, exploring alternative ways to organize one's work while maintaining coherence is particularly challenging, especially in interdisciplinary fields like HCI where individual researchers' publications may span diverse domains and methodologies.In this paper, we present PaperBridge, a human-AI co-exploration system informed by a formative study and content analysis.PaperBridge assists researchers in exploring diverse perspectives for organizing their publications into coherent narratives.At its core is a bi-directional analysis engine powered by large language models, supporting iterative exploration through both top-down user intent (e.g., determining organization structure) and bottom-up refinement on narrative components (e.g., thematic paper groupings).Our user study (N=12) demonstrated PaperBridge's usability and effectiveness in facilitating the exploration of alternative research narratives.Our findings also provided empirical insights into how interactive systems can scaffold academic communication tasks.

Cultural Heritage is not just about tangible artifacts; it also includes intangible elements such as personal memories, community ties, and envisioned futures. Traditional museums and archives often emphasize physical items like architectural pieces and photos, while overlooking people’s personal and emotional connections to cultural heritage. To illustrate the personal connections people have with cultural heritage sites, we designed an exhibition that displayed images created by participants, which represent their perspectives and future visions of cultural heritage sites. The exhibition’s images, generated through GenAI, helped participants narratively describe cultural heritage locations, allowing them to express their visions of future threats like over-tourism and climate change on these sites. Contrary to constraints, co-creating with Generative AI associates participants with personal memories of cultural heritage, stimulating personal narratives and promoting deep reflection on cultural heritage preservation. The dissemination strategies we designed illustrate the use of GenAI to empower the expression of matters of cultural value beyond the physical.