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In the midst of the fourth industrial revolution, big data is weighed in gold, placing enormous power in the hands of data scientists – the modern AI alchemists. But great power comes with greater responsibility. This book seeks to shape, in a practical, diverse, and inclusive way, the ethical compass of those entrusted with big data.

Being practical, this book provides seven real-world case studies dealing with big data abuse. These cases span a range of topics from the statistical manipulation of research in the Cornell food lab through the Facebook user data abuse done by Cambridge Analytica to the abuse of farm animals by AI in a chapter co-authored by renowned philosophers Peter Singer and Yip Fai Tse. Diverse and inclusive, given the global nature of this revolution, this book provides case-by-case commentary on the cases by scholars representing non-Western ethical approaches (Buddhist, Jewish, Indigenous, and African) as well as Western approaches (consequentialism, deontology, and virtue).

We hope this book will be a lighthouse for those debating ethical dilemmas in this challenging and ever-evolving field.



In the midst of the 4th industrial revolution, big data is weighed in gold, placing enormous power in the hands of data scientists - the modern AI alchemists. This book seeks to shape, in a practical, diverse and inclusive way, the ethical compass of those entrusted with big data.

1. Introduction: Moral Machines,
2. Introduction to Ethical Approaches in Data Science,
3. Research Ethics and the Scientific Method,
4. Machine Models in Court,
5. Synthetic Media and Political Violence,
6. Biometrics and Facial Recognition,
7. Content Moderation: Hate Speech and Genocide in Myanmar,
8. Mental Malware: Algorithms and Choice Architecture,
9. AI and Nonhuman Animals

Nachshon (Sean) Goltz is an academic, entrepreneur and lawyer. His main interest is in the intersection of ethics, technology and history.

Tracey Dowdeswell is a Professor of criminology and legal studies at Douglas College. Her research interests focus on the intersection between law and data science.