Lilly Tech Systems
AI Ethics & Governance
Master AI ethics and governance end-to-end. 50 deep dives across 300 lessons covering foundational ethics, bias & fairness, privacy & data rights, transparency, accountability, safety & alignment, regulation worldwide (EU AI Act, US, NIST, ISO 42001, Singapore, UK, China, UNESCO), and sectoral ethics (healthcare, criminal justice, hiring, education, warfare).
All Topics
50 ethics and governance topics organized into 8 categories. Each has 6 detailed lessons with frameworks, code, and policy references.
Foundational Ethics
AI Ethics Foundations
Master the foundational concepts of AI ethics. Learn the difference between AI ethics, AI safety, and AI governance, plus the core ethical questions every AI engineer should answer.
6 LessonsUtilitarianism vs Deontology in AI
Understand how utilitarian and deontological ethics shape AI design. Learn why the choice of ethical framework determines what 'good' AI even means.
6 LessonsVirtue Ethics for AI
Apply virtue ethics to AI design. Learn how the question 'What kind of AI should this be?' differs from 'What should this AI do?' and why it matters.
6 LessonsAI Moral Agency & Personhood
Wrestle with whether AI systems can be moral agents. Learn the philosophical, legal, and practical implications of attributing agency to AI.
6 LessonsCross-Cultural AI Ethics
AI ethics is not universal. Learn how cultural context shapes AI ethics in the US, EU, China, India, the Middle East, and Africa, and the implications for global products.
6 LessonsMajor AI Ethics Frameworks
Master the major AI ethics frameworks: NIST AI RMF, IEEE Ethically Aligned Design, OECD AI Principles, EU Ethics Guidelines, and how to apply them.
6 LessonsBias & Fairness
AI Bias Sources
Understand where AI bias comes from. Learn the seven types of bias (historical, representation, measurement, aggregation, evaluation, deployment, feedback loop) and how to spot them.
6 LessonsAlgorithmic Fairness Metrics
Master the math of algorithmic fairness. Learn demographic parity, equalized odds, predictive parity, calibration, and the impossibility theorems.
6 LessonsBias Auditing
Audit AI systems for bias. Learn the audit process, tooling (Fairlearn, AIF360), test set design, audit reporting, and how to defend audits to stakeholders.
6 LessonsBBQ & Bias Benchmarks
Use established bias benchmarks to evaluate models. Learn BBQ, StereoSet, CrowS-Pairs, RealToxicityPrompts, ToxiGen, and what each measures.
6 LessonsBias Mitigation Techniques
Reduce bias in AI systems. Learn pre-processing (data reweighting), in-processing (constrained optimization), and post-processing (threshold adjustment) techniques.
6 LessonsFairness in Hiring AI
Apply fairness to hiring AI. Learn NYC Local Law 144, EEOC guidance, the four-fifths rule, audit requirements, and the patterns for compliant hiring AI.
6 LessonsFairness in Credit & Lending
Apply fairness to credit & lending AI. Learn ECOA, Fair Lending laws, adverse action notices, the disparate impact framework, and CFPB enforcement.
6 LessonsFairness in Criminal Justice AI
Apply fairness to criminal justice AI. Learn the COMPAS controversy, predictive policing ethics, risk assessment fairness, and the ProPublica analysis.
6 LessonsPrivacy & Data Rights
Privacy in AI Systems
Master privacy in AI systems. Learn the privacy threat model, training data privacy, inference-time privacy, model inversion attacks, and membership inference.
6 LessonsGDPR for AI
Apply GDPR to AI systems. Learn lawful basis, automated decision-making (Article 22), DPIAs for AI, the right to explanation, and data subject rights.
6 LessonsCCPA & US Privacy Laws
Navigate CCPA, CPRA, state privacy laws (CO, VA, CT, UT), and emerging federal privacy laws. Learn how each applies to AI systems and training data.
6 LessonsDifferential Privacy
Master differential privacy for AI. Learn the math (epsilon, delta), DP-SGD for training, the privacy budget, and practical implementations (Apple, Google, US Census).
6 LessonsFederated Learning Ethics
Apply ethics to federated learning. Learn what FL solves and what it doesn't, secure aggregation, gradient leakage attacks, and FL deployment patterns.
6 LessonsRight to Explanation
Implement the right to explanation. Learn the legal basis (GDPR Article 22), what counts as a meaningful explanation, technical implementation, and edge cases.
6 LessonsTransparency & Explainability
The Black Box Problem
Understand the black box problem in AI. Learn why deep learning is opaque, why traditional ML is more transparent, and the practical implications for trust.
6 LessonsExplainable AI (XAI)
Master XAI methods. Learn the taxonomy (model-specific vs model-agnostic, local vs global), key methods (SHAP, LIME, attention visualization), and limitations.
6 LessonsSHAP, LIME & Interpretability Tools
Master SHAP, LIME, and modern interpretability tools. Learn the math, how to use them in practice, when each is the right tool, and how to communicate explanations.
6 LessonsModel Cards & Datasheets
Author model cards and datasheets for AI systems. Learn the Mitchell et al. format, what to include, when to publish, and how regulators use them.
6 LessonsAI Transparency Standards
Adopt AI transparency standards. Learn ISO/IEC 23894, EU AI Act transparency rules, IEEE 7001, and the emerging norms around AI disclosure.
6 LessonsAccountability & Liability
AI Liability Frameworks
Master AI liability frameworks. Learn product liability, professional malpractice, EU AI Liability Directive, and the open questions in AI tort law.
6 LessonsAlgorithmic Accountability
Build algorithmic accountability into AI systems. Learn the Algorithmic Accountability Act, audit standards, public-sector AI accountability, and accountability without explainability.
6 LessonsAudit Trails for AI
Build comprehensive AI audit trails. Learn what to log, retention policies, log integrity (immutability, hashing), and audit log analysis tools.
6 LessonsAI Insurance & Risk Transfer
Transfer AI risk through insurance. Learn the emerging AI insurance market, what's covered (and not), how AI changes existing E&O and product liability policies.
6 LessonsSafety & Alignment
The AI Alignment Problem
Master the AI alignment problem. Learn the difference between capability and alignment, inner vs outer alignment, instrumental convergence, and the orthogonality thesis.
6 LessonsRLHF & Constitutional AI
Master RLHF and Constitutional AI. Learn how human feedback shapes models, the limitations, Constitutional AI from Anthropic, and the emerging alignment techniques.
6 LessonsAI Safety Research
Survey AI safety research. Learn the major labs (Anthropic, DeepMind, OpenAI, ARC, Redwood, MIRI), key research agendas, and how to follow the field.
6 LessonsExistential Risk from AI
Engage with the AI x-risk debate. Learn the main arguments (Bostrom, Russell, Yudkowsky), the skeptical responses, and the practical implications today.
6 LessonsMesa-Optimization
Understand mesa-optimization. Learn how learned optimizers can emerge, mesa vs base objectives, deceptive alignment, and the implications for ML safety.
6 LessonsReward Hacking & Goodhart's Law
Understand reward hacking and Goodhart's Law in AI. Learn the canonical examples, why optimization always breaks proxies, and design patterns to mitigate.
6 LessonsSpecification Gaming
Defend against specification gaming. Learn the DeepMind specification gaming examples, root causes, and engineering practices to write less gameable specs.
6 LessonsMechanistic Interpretability
Get into mechanistic interpretability research. Learn the goal (reverse-engineer neural networks), key results (induction heads, circuits, sparse autoencoders), and tools.
6 LessonsRegulation & Compliance
EU AI Act Deep Dive
Master the EU AI Act. Learn the risk categories, prohibited practices, high-risk AI obligations, GPAI rules, timelines, penalties, and compliance roadmap.
6 LessonsUS AI Executive Order & Federal Policy
Master US federal AI policy. Learn the AI Executive Order, NIST guidance, OMB AI memo, Bipartisan AI roadmap, and federal agency-specific AI rules.
6 LessonsNIST AI Risk Management Framework
Implement NIST AI RMF. Learn the four functions (Govern, Map, Measure, Manage), the AI RMF Playbook, GenAI Profile, and how to operationalize NIST in your org.
6 LessonsISO 42001 (AI Management Systems)
Implement ISO/IEC 42001. Learn the AI management system standard, certification process, gap analysis, and how it complements other ISO standards.
6 LessonsSingapore AI Governance Framework
Apply Singapore's Model AI Governance Framework. Learn the second edition framework, AI Verify toolkit, GenAI Framework, and Singapore's pragmatic governance approach.
6 LessonsUK AI Regulation
Navigate UK AI regulation. Learn the UK AI White Paper, sectoral regulator approach (CMA, ICO, FCA, Ofcom), AISI, and the post-Brexit divergence from EU AI Act.
6 LessonsChina's AI Regulations
Understand China's AI regulatory landscape. Learn the Generative AI Measures, Algorithm Filing System, Deep Synthesis rules, security review, and CAC enforcement.
6 LessonsUNESCO AI Ethics & Global Governance
Map global AI governance. Learn UNESCO AI ethics recommendation, G7 Hiroshima AI Process, GPAI, UN AI advisory body, and the path to global coordination.
6 LessonsSectoral Ethics
AI in Healthcare Ethics
Apply ethics to healthcare AI. Learn the principles of medical AI ethics, FDA SaMD framework, clinical validation, AI hallucination risks in clinical use.
6 LessonsAI in Criminal Justice Ethics
Apply ethics to criminal justice AI. Learn risk assessment ethics, predictive policing ethics, facial recognition, evidence admissibility, and due process implications.
6 LessonsAI in Hiring & HR Ethics
Apply ethics to hiring/HR AI. Learn EEOC guidance, NYC Local Law 144 in practice, video interview AI ethics, AI screeners, candidate disclosure rules.
6 LessonsAI in Education Ethics
Apply ethics to education AI. Learn FERPA, AI tutors, AI proctoring, AI grading, plagiarism vs AI use, and the equity question in EdTech AI.
6 LessonsAI in Warfare & Autonomous Weapons
Engage with the LAWS debate. Learn the lethal autonomous weapons debate, IHL implications, the campaign to stop killer robots, US DoD policy, and dual-use considerations.
6 LessonsWhy an AI Ethics & Governance Track?
Ethics + governance is now load-bearing infrastructure for AI products. This track gives you a single comprehensive map.
Foundations + Bias + Privacy
20 topics: AI ethics foundations, utilitarianism vs deontology, virtue ethics, moral agency, cross-cultural ethics, frameworks; bias sources, fairness metrics, auditing, benchmarks, mitigation, hiring/credit/CJ fairness; GDPR, CCPA, differential privacy, federated learning, right to explanation.
Transparency + Accountability
9 topics: black box problem, XAI, SHAP/LIME, model cards, transparency standards; AI liability, algorithmic accountability, audit trails, AI insurance.
Safety + Alignment
8 topics: alignment problem, RLHF & Constitutional AI, AI safety research, x-risk, mesa-optimization, reward hacking, specification gaming, mechanistic interpretability.
Regulation + Sectoral
13 topics: EU AI Act, US AI Executive Order, NIST AI RMF, ISO 42001, Singapore, UK, China, UNESCO; healthcare, criminal justice, hiring, education, warfare ethics.