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Chapters

This textbook is organized into 8 chapters covering 250 concepts from the learning graph.

Chapter Overview

  1. Introduction to Data-Driven Ethics - Covers foundational concepts including ethics, data-driven approaches, critical thinking, research methods, bias recognition, and evidence-based reasoning.

  2. Measuring Harm - Covers harm quantification frameworks including DALYs, QALYs, social cost accounting, externalities, life-cycle analysis, environmental and health impact assessment, and normalized metrics.

  3. Ethical Data Gathering - Covers ethical data collection methods, informed consent, sampling, bias detection, peer review, data quality assessment, transparency, and reproducibility.

  4. Systems Thinking for Impact - Covers complex systems, feedback loops, stocks and flows, dynamic equilibrium, tipping points, causal loop diagrams, system dynamics models, and mental models.

  5. System Archetypes and Root Cause Analysis - Covers system archetypes (Tragedy of the Commons, Shifting the Burden, etc.), the iceberg model, root cause analysis, five whys technique, and unintended consequences.

  6. Finding Leverage - Meadows' leverage points framework, intervention hierarchy, behavioral economics, nudge theory, choice architecture, and advocacy strategies. We look at market failures, power dynamics, stakeholder analysis, game theory, plus all industry case studies including tobacco, fossil fuels, ultra-processed foods, fast fashion, and more.

  7. The Neurobiology of Moral Decision-Making - , intervention hierarchy, behavioral economics, nudge theory, choice architecture, and advocacy strategies.

  8. Reform, Corporate Responsibility, and Capstone - Covers communication strategies, data visualization, reform proposals, corporate responsibility, ESG metrics, sustainability reporting, and capstone project implementation.

How to Use This Textbook

This textbook follows a logical progression where concepts build upon each other. Start with Chapter 1 to establish foundational knowledge, then proceed sequentially through subsequent chapters. Each chapter lists the specific concepts covered and their prerequisites from earlier chapters. The learning graph visualization can help you explore concept dependencies interactively.

Note: Each chapter includes a list of concepts covered from the learning graph. Make sure to complete prerequisites before moving to advanced chapters.