Research & Projects

Generative AI is rapidly becoming part of everyday creative practice, influencing how people generate ideas, solve problems, collaborate, and learn across domains such as art, writing, design, and game development. While much of the existing research has focused on AI as a tool for improving productivity or assisting with creative tasks, I argue that its impact extends far beyond efficiency. My research examines generative AI as a sociotechnical actor that shapes not only individual creative workflows but also the social relationships, collaborative processes, and community practices that underpin creative work. I am particularly interested in understanding how AI changes the ways creative practitioners make decisions, develop expertise, exchange feedback, and negotiate creative values.

I investigate these questions through the context of independent (indie) game development, where creativity emerges through interdisciplinary collaboration, strong community networks, and a high degree of creative autonomy. My research combines computational analyses of large-scale online discussions with qualitative interviews and participatory design methods to examine both the experiences of creative practitioners and the perspectives of AI developers who build these systems. By connecting these perspectives, I seek to uncover how assumptions about creativity become embedded in AI design and how future generative AI systems can better support human creativity in ways that are ethical, collaborative, and aligned with the values and needs of creative communities.

Publications

Ruchi Panchanadikar, Yang Hu & Guo Freeman (2026). A Dual Role Collision: How Generative AI’s Intertwining Productivity Support and Social Support Reshape Indie Game Developers’ Creative Work. In The 2026 ACM Conference on Fairness, Accountability, and Transparency (pp. 1098-1119) [Best Paper Honorable Mention Award: Top 1.5%]. [PDF]

Ruchi Panchanadikar & Guo Freeman (2026). A Potential Teammate?: Understanding How Indie Game Developers Approach Generative AI’s Involvement in Their Small-Scale Creative Teamwork. In Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems (CHI '25). Association for Computing Machinery, New York, NY, USA, 18 pages. Acceptance rate: 23% [PDF]

Ruchi Panchanadikar & Guo Freeman (2024). “I’m a Solo Developer but AI is My New Ill‑Informed Co‑Worker”: Envisioning and Designing Generative AI to Support Indie Game Development. In ACM SIGCHI Conference on Computer‑Human Interaction in Play (CHI PLAY 2024 ), Oct 14‑17 2024, Tampere, Finland [Best Paper Honorable Mention Award: Top 5%] [PDF]

Ruchi Panchanadikar, Guo Freeman, Kelsea Schulenberg, Lingyuan Li, & Yang Hu (2024). ”A New Golden Era” or ”Slap Comps”: How Non‑Profit Driven Indie Game Developers Perceive the Emerging Role of Generative AI in Game Development. In Extended Abstracts of the CHI Conference on Human Factors in Computing Systems (CHI EA ’24), May 11–16, 2024, Honolulu, HI, USA. (Acceptance rate: 33.88%) [PDF]

| Poster CHI 2024 | Presentation CHI PLAY 2024 | Presentation CHI 2026 | 

Social Virtual Reality (VR) platforms (e.g., VRChat, Meta’s Horizon Worlds, and RecRoom) are spaces where multiple users can interact with one another typically through VR head-mounted displays and immersive 360-degree virtual content in 3D virtual spaces. There has been a steady growth of streamed VR content on popular streaming platforms like YouTube and Twitch.

In this project, with comprehensive user interviews with 17 social VR streamers, we explore their unique strategies to engage with their audiences and their perceived potential limitations of these strategies.

Publications

Yang Hu*, Ruchi Panchanadikar*, Guo Freeman (2025). Beyond Traditional Gaming: Understanding How Social VR Streaming Creates New Forms of Play. In Companion Proceedings of the Annual Symposium on Computer-Human Interaction in Play (CHI Play Companion 2025) [PDF]

Yang Hu, Guo Freeman & Ruchi Panchanadikar (2025). "Grab the Chat and Stick It to My Wall": Understanding How Social VR Streamers Bridge Immersive VR Experiences with Streaming Audiences Outside VR. In The 2025 ACM Conference on Human Factors in Computing Systems (CHI'25) [PDF].

Guo Freeman, Yang Hu, Ruchi Panchanadikar, Amelia L Hall, Kelsea Schulenberg, & Lingyuan Li (2024). "My Audience Gets to Know Me on a More Realistic Level": Exploring Social VR Streamers’ Unique Strategies to Engage with Their Audiences. In Extended Abstracts of the CHI Conference on Human Factors in Computing Systems (CHI EA ’24), May 11–16, 2024, Honolulu, HI, USA. (Acceptance rate: 33.88%) [PDF]

| Poster CHI 2024 | Poster CHI Play 2025 |

Large Language Models (LLMs) have rapidly become a significant part of various everyday applications, from customer support to content generation. However, their widespread use has highlighted issues of bias and fairness, particularly in sensitive tasks like resume evaluation. In this project, we investigate these concerns by focusing on nationality bias in LLMs, specifically examining how GPT-2 may exhibit such biases.

Publications

Venkit, P., Gautam, S., Panchanadikar, R., Huang, K., Wilson, S. (2023). Unmasking Nationality Bias: A Study of Human Perception of Nationalities in AI‑Generated Articles. AAAI/ACM Conference on AI, Ethics, and Society‑ AIES ’23 [PDF]

Venkit, P., Gautam, S., Panchanadikar, R., Huang, K., Wilson, S. (2023).Nationality Bias in Text Generation. Conference of the European Chapter of the Association for Computational Linguistics‑ EACL ’23 [PDF]

The Creativity Assessment Platform (CAP) is a free, web-based tool for designing, administering, and scoring creativity assessments (cap.ist.psu.edu). With multilingual support, machine learning–based scoring, and an easy point-and-click interface, CAP makes creativity measurement accessible to educators, researchers, and beyond. The design and development of the initial design and development of the website was a part of my Master's scholarly paper.

Publications

John D Patterson, Jimmy Pronchick, Ruchi Panchanadikar, Mark Fuge, Janet G van Hell, Scarlett R Miller, Dan R Johnson, Roger E Beaty (2025). CAP: The creativity assessment platform for online testing and automated scoring. Behavior Research Methods, 57(9), 264 [PDF].