Artificial Intelligence and Evaluation is a groundbreaking exploration of how the landscape of program evaluation will be redefined by artificial intelligence and other emerging digital technologies. This book presents a pivotal resource for evaluators navigating the transformative intersection of their practice and cutting-edge technology.
Artificial Intelligence and Evaluation is a groundbreaking exploration of how the landscape of program evaluation will be redefined by artificial intelligence and other emerging digital technologies. This book presents a pivotal resource for evaluators navigating the transformative intersection of their practice and cutting-edge technology.
Steffen Bohni Nielsen (PhD) is Director General at the Danish National Research Centre for the Working Environment, NFA and a member of the Danish National research and Innovation Council. He is a member of INTEVAL and has published extensively in the field of evaluation. Francesco Mazzeo Rinaldi (PhD) is professor at the University of Catania, Italy, and affiliate professor at the Royal Institute of Technology (KTH) Stockholm. In recent years, his research interest has revolved around program and policy evaluation and Big Data analytics in several regional, national, and international public organizations. He is a member of INTEVAL. Gustav Jakob Petersson (PhD) is Senior Analyst at the Swedish Research Council. He is a member of INTEVAL and has co-edited one of its volumes on cyber society, Big Data and evaluation in 2017.
Inhaltsangabe
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 & 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 an Evaluation 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
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 & 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 an Evaluation 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
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