ABSTRACT

Artificial Intelligence and Evaluation: Emerging Technologies and Their Implications for Evaluation is a groundbreaking exploration of how the landscape of program evaluation will be redefined by artificial intelligence and other emerging digital technologies.

In an era where digital technologies and artificial intelligence (AI) are rapidly evolving, this book presents a pivotal resource for evaluators navigating the transformative intersection of their practice and cutting-edge technology. Addressing the dual dimensions of how evaluations are conducted and what is evaluated, a roster of distinguished contributors illuminate the impact of AI on program evaluation methodologies. Offering a discerning overview of various digital technologies, their promises and perils, they carefully dissect the implications for evaluative processes and debate how evaluators must be equipped with the requisite skills to harness the full potential of AI tools. Further, the book includes a number of compelling use cases, demonstrating the tangible applications of AI in diverse evaluation scenarios. The use cases range from the application of GIS data to advanced text analytics. As such, this book provides evaluators with inspirational cases on how to apply AI in their practice as well as what pitfalls one must look out for.

Artificial Intelligence and Evaluation is an indispensable guide for evaluators seeking to not only adapt to but thrive in the dynamic landscape of evaluation practices reshaped by the advent of artificial intelligence.

The Open Access version of this book, available at https://www.taylorfrancis.com, has been made available under a Creative Commons Attribution-Non Commercial-No Derivatives 4.0 license.

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chapter 5|25 pages

Extracting Meaning from Textual Data for Evaluation

Title
Lessons from Recent Practice at the Independent Evaluation Group of the World Bank
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chapter 7|24 pages

Big Data for Big Investments

Title
Making Responsible and Effective Use of Data Science and AI in Research Councils
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chapter 11|23 pages

The Future of Evaluation Analytics

Title
Case Studies of Structural Causal Modeling in Action
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chapter 12|24 pages

The Algorithmization of Policy and Society

Title
The Need for a Realist Evaluation Approach
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chapter 14|22 pages

Artificial Intelligence

Title
Challenges for Evaluators
Size: 0.79 MB