About Backyard-AI
Practical AI, grounded in real public-health work
Backyard-AI was created to help organizations move beyond vague excitement about AI and toward thoughtful, useful implementation. The focus is on practical systems that improve communication, synthesis, learning, and workflow efficiency while keeping people, judgment, and trust at the center.
About Nick Swope
Nick Swope is a public health professional and AI educator focused on practical, responsible uses of AI in public health practice. Through Backyard-AI, he helps teams translate AI from a broad idea into usable workflows for communication, reporting, training, and evidence synthesis. His work emphasizes implementation, clarity, human review, and real-world usefulness.
Nicholas Swope is a public health educator and applied AI practitioner focused on practical uses of artificial intelligence in research, teaching, and community health practice. He has over a decade of experience as a public health practitioner. He is a DrPH student at East Tennessee State University, where he founded the AI interest group and has developed AI tools to support faculty, researchers, and community organizations. His work includes building Jessie AI, a substance-use recovery chatbot for Recovery Resources TN, creating multi-platform AI research workflows, and developing custom tools for social-media data extraction and qualitative analysis. Swope also partners with organizations to streamline large-scale analytic workflows, reducing weeks of manual review to hours. He previously served as a manager over three public health teams, health promotions, epidemiology, and immunizations in Northern Idaho, and as a faculty member for half a decade, teaching in an MPH program.
What matters here
Practicality
The work should be usable in the real world, not just interesting in theory.
Clarity
AI should make communication and systems easier to understand, not more confusing.
Oversight
Human review, judgment, and accountability remain essential.
Mission fit
The best uses of AI support public-service work rather than distract from it.
How Backyard-AI works
Backyard-AI focuses on specific, high-value use cases rather than broad promises. Every engagement starts by identifying a real task, understanding who does it, what slows it down, where errors matter, and where AI can provide support without replacing expert judgment.
The result is a more practical form of AI adoption. Instead of asking teams to redesign everything, Backyard-AI helps them improve a workflow, train staff, add guardrails, and learn what works in their actual environment.