Buch, Englisch, 330 Seiten, Format (B × H): 152 mm x 229 mm, Gewicht: 608 g
Emerging Technologies and Their Implications for Evaluation
Buch, Englisch, 330 Seiten, Format (B × H): 152 mm x 229 mm, Gewicht: 608 g
Reihe: Comparative Policy Evaluation
ISBN: 978-1-032-84389-6
Verlag: Taylor & Francis
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 http://www.taylorfrancis.com, has been made available under a Creative Commons Attribution-Non Commercial-No Derivatives 4.0 license.
Zielgruppe
Postgraduate and Undergraduate Advanced
Autoren/Hrsg.
Fachgebiete
Weitere Infos & Material
1. Evaluation in the Era of Artificial Intelligence
2. Emerging Technology and Evaluation in International Development
3. The Applications of Big Data to Strengthen Evaluation
4. Ethics and Equity in Data Science for Evaluators
5. Extracting Meaning from Textual Data for Evaluation: Lessons from Recent Practice at the Independent Evaluation Group of the World Bank
6. Text Mining and Machine Learning in a Performance Audit of Police Handling of Cybercrime in Norway
7. Big Data for Big Investments: Making Responsible and Effective Use of Data Science and AI in Research Councils
8. The Use of Quantitative Text Analysis in Evaluations
9. Artificial Intelligence and Text Analysis in Evaluating Complex Social Phenomena: The Russia-Ukraine Conflict
10. Harnessing Geospatial Approaches to Strengthen Evaluative Evidence
11. The Future of Evaluation Analytics: Case Studies of Structural Causal Modeling in Action
12. The Algorithmization of Policy and Society: The Need for a Realist Evaluation Approach
13. The Evaluation Industry and Emerging Technologies
14. Artificial Intelligence: Challenges for Evaluators