The 22nd IEEE International Conference on Ubiquitous Intelligence and Computing (Hybrid)

The revolutionary advancements of AI capabilities, especially in large scale generative models, advanced learning frameworks, and automated data mining pipelines, is catalyzing a fundamental transformation in how knowledge is produced, validated, and shared across disciplines. AI is now reshaping the way we do research, from speeding up literature reviews and data cleaning to inspiring new ideas and even helping draft papers However, this revolution also raises critical concerns about methodological transparency, reproducibility of AI assisted results, and recognition of contributions in human-AI collaborations. These emerging shifts demand a dedicated forum for the research community to explore both the benefits and the risks of embedding AI into scholarly workflows.

This panel aims to brings together researchers who have integrated AI into their daily research practices and responsible for guiding publication processes and upholding scholarly standards. The objectives are threefold:

1. Map the impact of AI on research affairs by distinguishing between early-stage prototypes and fully deployed systems in tasks such as manuscript drafting, data manipulation, and project resource organization.
2. Assess the procedural and potential ethical challenges introduced by AI tools at every stage of the research lifecycle, from conceptual design and data analysis to publication, peer review, and post-publication monitoring.
3. Develop institutional recommendations for embedding AI oversight, training, and accountability into research processes, ensuring that policies on authorship, integrity, and compliance respond to the realities of AI-enhanced practices.

Through case-study presentations, interactive tool demonstrations, and guided discussions, panelists will illuminate both real world successes and cautionary lessons, and further reflect on questions of trust, accountability, and academic credit.

By the end of this panel, attendees will have contributed to a blueprint for AI's role in scholarship—recognizing both its transformative power and the responsibilities it entails. They are expected to leave with practical insights on how to harness AI's speed without undermining scholarly rigor, learn concrete methods to manage AI risks, and a clearer understanding of promoting responsible AI-driven innovation in their work. By laying this foundation, this panel seeks not only to set a direction for today's AI-empowered research but also to spark an ongoing conversation that will shape the future of academic work.