Real World AI Ethics for Data Scientists: Practical Case Studies

Description

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. Cover Half Title Series Page Title Page Copyright Page Contents Acknowledgement List of Collaborators and Contributors 1. Introduction: Moral Machines Introduction: Moral Machines What Is Data Science? The Case Studies Case 1 – Research Ethics and the Scientific Method Case 2 – Machine Models in Court Case 3 – Synthetic Media and Political Violence Case 4 – Biometrics and Facial Recognition Case 5 – Content Moderation: Dangerous Speech and Ethnic Cleansing in Myanmar Case 6 – Mental Malware: Algorithms and Choice Architecture Case 7 – AI and Nonhuman Animals Notes 2. Introduction to Ethical Approaches in Data Science Introduction Consequentialism and Utilitarianism Common Objections to Utilitarianism Advice for Properly Applying Utilitarian Principles Think Broader and Longer Use Expected Values to Make Decisions In Choosing Charitable Projects, Choose Effective Ones Deontological Ethics Virtue Ethics A Provisional Perspective on African Ethics Buddhist Ethics Jewish Ethics Indigenous Ethics: Actions as Interactions Notes 3. Research Ethics and the Scientif ic Method ‘One Simple Trick’: The Cornell Food & Brand Lab Commentary Utilitarian Ethics Notes 4. Machine Models in Court The Trials of Oral Nicholas Hillary The ‘Most Dangerous Prosecutor in New York’ The DNA Evidence Commentary Jewish Ethics Deontological Ethics Notes 5. Synthetic Media and Political Violence The Coup in Gabon ‘Bulli Bai’: Selling Women Synthetically in India Commentary Utilitarian Ethics The Key Consideration – The Value of Truth Is It All About Deepfake? African Ethics Indigenous Ethics Notes 6. Biometrics and Facial Recognition Clearview AI Biometrics and Facial Recognition Technology Facial Recognition and Privacy Commentary Indigenous Ethics Humanitarianism and the Laws of Armed Conflict Notes 7. Content Moderation: Hate Speech and Genocide in Myanmar Facebook and Ethnic Cleansing in Burma Old Hate and New Tech Commentary Buddhist Ethics Virtue Ethics Indigenous Ethics Notes 8. Mental Malware: Algorithms and Choice Architecture The Cambridge Analytica Data Scandal Choice Architecture and Persuasive Technology: A ‘Skinner Box for the Modern Human’ ‘Popular’ Politicians, ‘Inauthentic’ Activity and the Mathew Effect The Nuremberg Code of Medical Ethics Commentary Buddhist Ethics Virtue Ethics Deontological Ethics Notes 9. AI and Nonhuman Animals Algorithmic Bias Language Models and Databases Bias in Search Engine Algorithms AI in Factory Farming Commentary Jewish Ethics Deontological Ethics African Ethics Notes Epilogue Index