Items related to From Algorithms to Evidence (Comparative Policy Evaluation)
Synopsis
From Algorithms to Evidence: Using GenAI in Evaluation Practice offers a timely, practice-grounded guide for evaluators and development professionals navigating the fast-moving world of generative AI. Building on the foundations laid in Artificial Intelligence and Evaluation (2025), this volume moves decisively from theory to application. It documents how evaluators across the globe are already using GenAI in real projects, showing not only what worked but also what failed, why, and under what conditions. The result is a clear, practitioner-centered resource that cuts through hype and provides grounded, real-world insight.
Structured around the seven phases of the evaluation lifecycle (design, structuring and inception, data collection, data analysis, reporting, judgment, and utilization), this book offers concrete examples of how GenAI is being integrated into everyday evaluation tasks. Contributors explain their rationale for using AI tools, the steps they took, and the results they achieved. Crosscutting chapters synthesize lessons on methodological adaptation, evolving evaluator competencies, and the ethical and professional standards needed to use GenAI responsibly. Throughout, this volume emphasizes ‘hybrid intelligence,’ showing how human expertise and AI-enabled methods can work together to strengthen evaluative reasoning.
Clear, accessible, and grounded in real practice, From Algorithms to Evidence fills a critical gap in the literature. It provides evaluators, policymakers, and organizational leaders with practical guidance for building more adaptive, data-informed, and future-ready evaluation systems while keeping equity, transparency, and human judgment at the center of their work.
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About the Author
Kerry Bruce (DrPH) is a global health and evaluation practitioner working to support both practical monitoring, evaluation, and learning projects and training. She is the CEO of ClearUp Consulting and is a member of INTEVAL.
Valentine Joseph Gandhi (PhD) wears multi-disciplinary hats as a Policy Advisor, MEL specialist, and AI, Data Science and Cybersecurity expert. He is the founder of the think tank The Development CAFE, the host of the EvalEdge Podcast for the European Evaluation Society and a member of INTEVAL.
Steffen Bohni Nielsen (PhD) is Director General at the Danish National Research Centre for the Working Environment (NFA), a member of the Danish National Research and Innovation Council, and chairman of the Partnership for European Research in Occupational Safety and Health (PERSOH). He is also a member of INTEVAL and has published extensively in the field of evaluation.
"About this title" may belong to another edition of this title.
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From Algorithms to Evidence (Hardcover)
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Hardcover. Condition: new. Hardcover. From Algorithms to Evidence: Using GenAI in Evaluation Practice offers a timely, practice-grounded guide for evaluators and development professionals navigating the fast-moving world of generative AI. Building on the foundations laid in Artificial Intelligence and Evaluation (2025), this volume moves decisively from theory to application. It documents how evaluators across the globe are already using GenAI in real projects, showing not only what worked but also what failed, why, and under what conditions. The result is a clear, practitioner-centered resource that cuts through hype and provides grounded, real-world insight.Structured around the seven phases of the evaluation lifecycle (design, structuring and inception, data collection, data analysis, reporting, judgment, and utilization), this book offers concrete examples of how GenAI is being integrated into everyday evaluation tasks. Contributors explain their rationale for using AI tools, the steps they took, and the results they achieved. Crosscutting chapters synthesize lessons on methodological adaptation, evolving evaluator competencies, and the ethical and professional standards needed to use GenAI responsibly. Throughout, this volume emphasizes hybrid intelligence, showing how human expertise and AI-enabled methods can work together to strengthen evaluative reasoning.Clear, accessible, and grounded in real practice, From Algorithms to Evidence fills a critical gap in the literature. It provides evaluators, policymakers, and organizational leaders with practical guidance for building more adaptive, data-informed, and future-ready evaluation systems while keeping equity, transparency, and human judgment at the center of their work. This book offers a timely, practicegrounded guide for evaluators and development professionals navigating the fastmoving world of generative AI. It documents how evaluators across the globe are already using GenAI in real projects, showing not only what worked, but also what failed, why, and under what conditions. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9781041357483
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From Algorithms to Evidence (Hardcover)
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Hardcover. Condition: new. Hardcover. From Algorithms to Evidence: Using GenAI in Evaluation Practice offers a timely, practice-grounded guide for evaluators and development professionals navigating the fast-moving world of generative AI. Building on the foundations laid in Artificial Intelligence and Evaluation (2025), this volume moves decisively from theory to application. It documents how evaluators across the globe are already using GenAI in real projects, showing not only what worked but also what failed, why, and under what conditions. The result is a clear, practitioner-centered resource that cuts through hype and provides grounded, real-world insight.Structured around the seven phases of the evaluation lifecycle (design, structuring and inception, data collection, data analysis, reporting, judgment, and utilization), this book offers concrete examples of how GenAI is being integrated into everyday evaluation tasks. Contributors explain their rationale for using AI tools, the steps they took, and the results they achieved. Crosscutting chapters synthesize lessons on methodological adaptation, evolving evaluator competencies, and the ethical and professional standards needed to use GenAI responsibly. Throughout, this volume emphasizes hybrid intelligence, showing how human expertise and AI-enabled methods can work together to strengthen evaluative reasoning.Clear, accessible, and grounded in real practice, From Algorithms to Evidence fills a critical gap in the literature. It provides evaluators, policymakers, and organizational leaders with practical guidance for building more adaptive, data-informed, and future-ready evaluation systems while keeping equity, transparency, and human judgment at the center of their work. This book offers a timely, practicegrounded guide for evaluators and development professionals navigating the fastmoving world of generative AI. It documents how evaluators across the globe are already using GenAI in real projects, showing not only what worked, but also what failed, why, and under what conditions. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. Seller Inventory # 9781041357483
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Condition: New. Kerry Bruce (DrPH) is a global health and evaluation practitioner working to support both practical monitoring, evaluation, and learning projects and training. She is the CEO of ClearUp Consulting and is a member of INTEVAL.Valentine Jos. Seller Inventory # 3178623129
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From Algorithms to Evidence (Hardcover)
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ISBN 10: 1041357486
ISBN 13: 9781041357483
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Hardcover. Condition: new. Hardcover. From Algorithms to Evidence: Using GenAI in Evaluation Practice offers a timely, practice-grounded guide for evaluators and development professionals navigating the fast-moving world of generative AI. Building on the foundations laid in Artificial Intelligence and Evaluation (2025), this volume moves decisively from theory to application. It documents how evaluators across the globe are already using GenAI in real projects, showing not only what worked but also what failed, why, and under what conditions. The result is a clear, practitioner-centered resource that cuts through hype and provides grounded, real-world insight.Structured around the seven phases of the evaluation lifecycle (design, structuring and inception, data collection, data analysis, reporting, judgment, and utilization), this book offers concrete examples of how GenAI is being integrated into everyday evaluation tasks. Contributors explain their rationale for using AI tools, the steps they took, and the results they achieved. Crosscutting chapters synthesize lessons on methodological adaptation, evolving evaluator competencies, and the ethical and professional standards needed to use GenAI responsibly. Throughout, this volume emphasizes hybrid intelligence, showing how human expertise and AI-enabled methods can work together to strengthen evaluative reasoning.Clear, accessible, and grounded in real practice, From Algorithms to Evidence fills a critical gap in the literature. It provides evaluators, policymakers, and organizational leaders with practical guidance for building more adaptive, data-informed, and future-ready evaluation systems while keeping equity, transparency, and human judgment at the center of their work. This book offers a timely, practicegrounded guide for evaluators and development professionals navigating the fastmoving world of generative AI. It documents how evaluators across the globe are already using GenAI in real projects, showing not only what worked, but also what failed, why, and under what conditions. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9781041357483
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