
Real World AI Ethics for Data Scientists
Practical Case Studies
- 132 pages
- English
- ePUB (mobile friendly)
- Available on iOS & Android
Real World AI Ethics for Data Scientists
Practical Case Studies
About this book
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.
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Information
Table of contents
- Cover Page
- Half-Title Page
- Series Page
- Title Page
- Copyright Page
- Contents
- Acknowledgement
- List of Collaborators and Contributors
- 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
- Epilogue
- Index
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