D6.01 - Skill-building Workshop: Using Ai-driven Tools to Empower Public Health Practitioners in the Age of AI

Brief Abstract Summary: Learn how AI-based tools are transforming graduate research training in an era of disruption, using the Chisquares platform as a case study. Discover how this innovative tool blends analysis-as-visualization with a risk-based AI framework, enabling students to perform rigorous analyses and generate publication-ready manuscripts—without writing code. Gain insight into how rules-based algorithms ensure accuracy while AI is limited to low-risk narrative tasks, preserving both speed and ethics. Recognize how this approach levels the playing field for students new to statistics or coding, accelerates time to publication, and embeds ethical decision-making into research. See how AI tools, when designed intentionally, provide a scalable, equitable model for graduate programs to adapt to AI-driven change while equipping students with enduring, real-world research skills.

Detailed abstract description: Research is being reshaped by continuous disruption—from the rapid adoption of AI to shifting learner needs and widening equity gaps. Traditional models of research training, especially in data analysis and manuscript writing, often depend on coding proficiency, long learning curves, and extended timelines. These barriers leave many students—particularly those from non-technical or under-resourced backgrounds—struggling to fully participate in research.

This session invites attendees to experience a new, inclusive model for research training using the Chisquares platform, a technology designed to democratize research by merging analysis-as-visualization with a risk-based AI framework. Participants will see firsthand how students can conduct robust, reproducible analyses and generate structured, publication-ready manuscripts—sometimes in as little as one hour—without writing a single line of code.

Attendees will:

Discover how rules-based algorithms maintain 100% analytical accuracy, while AI is used ethically and safely for low-risk tasks such as paraphrasing or summarizing narrative sections.

Gain practical strategies for accelerating time to publication without compromising quality or rigor.

Recognize how this approach embeds ethical decision-making and transparency throughout the research process.

Explore how AI can be used to improve student engagement and reduce equity gaps in research training.

The presentation will showcase case examples illustrating how graduate students, even those with limited statistical or programming experience, have successfully used the platform to analyze data, produce manuscripts, and contribute to academic knowledge. Faculty will learn how this model can enhance mentoring, streamline the supervision of theses or capstones, and foster confidence in research competence among diverse learners.

In an era where disruption has become the new normal, this session demonstrates how technology can be both a stabilizer and an equalizer. By reducing dependency on coding and introducing automation responsibly, well designed AI tools can empower researchers to focus on critical thinking, interpretation, and ethical reasoning—the hallmarks of good science.

Attendees will leave with a concrete understanding of how this innovation bridges gaps in digital readiness, expands research participation, and strengthens institutional resilience. They will also gain access to a framework for integrating emerging technology into research education without compromising academic standards.

Ultimately, this session will inspire educators, administrators, and researchers to reimagine graduate education—not as a casualty of disruption, but as a laboratory for innovation. Through responsible AI use, institutions can train the next generation of scholars to produce faster, more ethical, and more equitable research, ensuring that no capable student is left behind simply because they cannot code.