Designed for researchers, educators, and students, this series provides a comprehensive introduction to artificial intelligence and its applications in academic health sciences environments. Participants will explore AI technologies, research tools, ethical issues, citation requirements, and data governance considerations. Registration automatically enrolls you in all sessions in the series.

Fundamentals of AI - 8/27/2026 | 1:00 - 2:00 PM (60 min)

This session provides a foundational introduction to artificial intelligence (AI). Participants will explore key AI concepts, including machine learning, deep learning, large language models, generative AI, retrieval-augmented generation (RAG), and prompt engineering, while examining how these technologies are transforming knowledge creation and decision-making. The session also highlights current applications of AI in research and healthcare, as well as introduce important limitations, ethical considerations, and risks associated with its utilization.

AI Prompt Engineering - 9/3/2026 | 1:00 - 2:30 PM (90 min)

Generative AI tools can be powerful research assistants, but the quality of their outputs depends heavily on the quality of the prompts they receive. This interactive session introduces the fundamentals of prompt engineering, including practical frameworks for crafting more effective prompts and strategies for refining outputs through an iterative process. Participants will gain hands-on experience using AI tools for research tasks such as keyword generation and background exploration while learning how to recognize common pitfalls and verify AI-generated information.

AI Research Tools - 9/10/2026 | 1:00 - 2:30 PM (90 min)

The growing ecosystem of AI-powered research tools offers new ways to discover, organize, and understand scholarly literature. In this hands-on session, participants will explore the differences between generative AI tools and AI-assisted research tools, as well as the strengths and limitations of each. Through demonstrations and an interactive activity, learners will explore AI search engines, academic discovery tools, and citation mapping platforms to support literature searching while considering appropriate and responsible use in academic and clinical research.

Citing AI - 9/17/2026 | 1:00 - 2:00 PM (60 min)

As artificial intelligence tools become increasingly common, understanding how to properly cite AI-generated content is essential. This presentation explores the importance of transparency, academic integrity, and ethical use of AI tools such as Microsoft Copilot, ChatGPT, and other generative AI platforms. Participants will learn when AI citations are necessary, how citation requirements vary by style guide, and best practices for documenting AI-assisted work. Also discussed will be limits to the use of AI sources in submissions to academic journals.

Ethical Concerns of AI - 9/24/2026 | 1:00 - 2:30 PM (90 min)

Artificial Intelligence (AI) is transforming medical research by accelerating data analysis, improving disease prediction, supporting drug discovery, and enabling personalized medicine. However, the use of AI in healthcare research raises important ethical questions related to patient privacy, informed consent, algorithmic bias, transparency, accountability, and equitable access to healthcare innovations. This workshop explores the ethical challenges and responsibilities associated with implementing AI in medical research.

AI & Data Integrity - 10/1/2026 | 1:00 - 2:30 PM (90 min)

AI systems are only as reliable as the data they learn from, access, and generate. This session explores how data quality, bias, missing information, and other data integrity challenges can influence AI-generated outputs and affect trust in those results. Participants will also examine important considerations related to privacy, confidentiality, and data security when using AI tools, and learn the foundational principles of AI-ready data, including data governance, metadata, standardization, and stewardship practices that support effective and responsible AI use in research and organizational settings.