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2021 AER Conference

Research Conducted in the Digital World Track

B09 - Explaining Explainable Machine Learning (XML)—What Research Review Boards Need to Know

Wednesday, November 17, 2021
1:45 PM – 2:45 PM ET
Location: Livestreamed
New for 2020 CSP Icon Livestreaming Session Icon CIP Accredited
Sophisticated uses of machine learning can be a challenge for research review boards to evaluate. Savvy researchers know to use XML or explainable artificial intelligence (XAI) tools and terminology, but how do research reviewers know whether an XML or XAI tool accomplished the regulatory and ethical objectives of explanation, such as for risk-benefit assessment or informed consent forms?

Learning Objectives:

  • Provide an overview of XML and XAI, and how these differ from Machine Intelligence and Artificial Intelligence
  • Identify when XML tools should be included in research proposals
  • Pair proposed machine learning methods with appropriate XML metrics and tools
  • Respond to gaps in machine learning-based research proposals and request appropriate amendments