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PRIM&R AI Programs

Webinar, Seminar, Symposium

Webinar

Building Confidence in AI: Strategies for Transparent and Responsible Data Use

Time: 60 minutes This webinar will explore the concept of data nutrition labels, designed to provide users with essential information about datasets, including their context, strengths, and limitations. Participants will be introduced to AI data structures, construct approaches to overcome AI intimidation in research settings, and critically evaluate AI use in research protocols. The session will also include strategies to mitigate bias in AI research and provide an overview of current and proposed AI regulations affecting research. Don’t miss this opportunity to empower your data practices and engage with key public policy guidelines relevant to AI!

Learning Objectives

  • Understand the purpose and importance of data nutrition labels in promoting transparency and informed data use.
  • Analyze AI training datasets for potential biases and develop strategies to mitigate these biases in research.
  • Interpret key public policy guidelines relevant to AI in research and apply skills to critically evaluate AI use in research protocols.

Seminar

A Comprehensive Guide of What We’ve Learned in the IRB Review of AI Research 
Time: 90 minutes   The rapid growth of artificial intelligence (AI) in research presents unique challenges for Institutional Review Boards (IRBs), often leaving them without the necessary tools and knowledge to conduct thorough reviews. This introductory session will provide participants with an overview of common AI applications in research, clarify essential terminology, and offer strategies for effectively reviewing AI-related studies. Through interactive discussions, attendees will explore the implications of AI research on human subjects, including the potential impacts and ethical considerations outlined in the Belmont Report. This seminar aims to equip IRB professionals with the foundational knowledge required to navigate the evolving landscape of AI in research. 

Learning Objectives:

  • Define key AI terms and understand their applications in various research settings. 
  • Examine the hidden impacts of AI research on individuals and communities. 
  • Identify ethical implications of AI research in relation to the Belmont Report's principles. 

Symposium

Balancing Innovation and Ethics: Artificial Intelligence in Research
Time: 2–3 hours Explore the multifaceted ethical challenges posed by AI-driven research with this PRIM&R symposium that features experts who will examine the impact of AI across various research domains. Attendees will analyze emerging ethical dilemmas and evaluate current regulatory frameworks. Furthermore, the discussions will synthesize practical approaches for balancing innovation with ethical considerations. Participants will be equipped with insights and strategies to assist them as they navigate the evolving landscape of AI ethics in research effectively.

Learning Objectives:

  • Analyze emerging ethical challenges associated with AI-driven research and their implications.
  • Evaluate the impact of AI across various research domains and critique current regulatory frameworks.
  • Synthesize strategies for effective AI governance in research settings