Module 1 in this 2-part course sets the stage for understanding the role AI can play in evaluation and the need for organizations to develop AI policies that encourage responsible use. The course starts with a foundational look at what AI-enabled evaluation entails. Participants will assess their current familiarity with the application of AI in evaluation and gain an overview of the state of the field. The module covers essential topics such as the ethical considerations of using AI in evaluation, principles of critical AI literacy, and the competencies needed for AI-literate evaluators and elements of AI-enabled evaluation functions. It concludes with an interactive Q&A session to discuss specific organizational needs and AI’s potential applications in monitoring, evaluation, research, and learning (MERL).

Info on course fees: https://encompassworld.com/elc/course-fees/

Module 2 of this 2 part course begins with an introduction to organizational AI-enabled evaluability, using capacity assessments to identify organizational pain points, and exploring enablers and barriers to AI adoption. Participants will learn the steps involved in developing an AI-enabled evaluation policy using an asset-based, principles-focused approach, and how to manage AI-enabled evaluation tasks with a comprehensive checklist. Examples of policies and small-group work will help participants think through the design and development of AI policies that will support the evaluation life cycle, including inception, data collection, data analysis, and reporting. The instructors will touch on best practices related to launching a policy and overseeing compliance, and conclude with a segment on the role of meta-evaluation in supporting quality assurance.

Info on course fees: https://encompassworld.com/elc/course-fees/