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Research Ethics in Applied Economics

Emphasizing the new challenges posed by the data science revolution, digital media, and changing norms, Research Ethics in Applied Economics examines the ethical issues faced by quantitative social scientists at each stage of the research process. The first section of the book considers project development, including issues of project management, selection bias in asking research questions, and political incentives in the development and funding of research ideas. The second section addresses data collection and analysis, discussing concerns about participant rights, data falsification, data management, specification search, p-hacking, and replicability. The final section focuses on sharing results with academic audiences and beyond, with an emphasis on self-plagiarism, social media, and the importance of achieving policy impact. The discussion and related recommendations highlight emergent issues in research ethics. Featuring perspectives from experienced researchers on how they address ethical issues, this book provides practical guidance to both students and experienced practitioners seeking to navigate ethical issues in their applied economics research.

Doing AI

Artificial intelligence (AI) has captured our imaginations—and become a distraction. Too many leaders embrace the oversized narratives of artificial minds outpacing human intelligence and lose sight of the original problems they were meant to solve. When businesses try to “do AI,” they place an abstract solution before problems and customers without fully considering whether it is wise, whether the hype is true, or how AI will impact their organization in the long term. Often absent is sound reasoning for why they should go down this path in the first place. Doing AI explores AI for what it actually is—and what it is not— and the problems it can truly solve. In these pages, author Richard Heimann unravels the tricky relationship between problems and high-tech solutions, exploring the pitfalls in solution-centric thinking and explaining how businesses should rethink AI in a way that aligns with their cultures, goals, and values. As the Chief AI Officer at Cybraics Inc., Richard Heimann knows from experience that AI-specific strategies are often bad for business. Doing AI is his comprehensive guide that will help readers understand AI, avoid common pitfalls, and identify beneficial applications for their companies. This book is a must-read for anyone looking for clarity and practical guidance for identifying problems and effectively solving them, rather than getting sidetracked by a shiny new “solution” that doesn’t solve anything.

Genetic Control of Insect Pest Species – Achievements, Challenges, and Perspectives