Ethics and Law in Data Analytics

Analytics and AI are powerful tools that have real-word outcomes. Learn how to the practical, ethical, and legal frameworks to be an effective analytics professional.

Welcome

• Welcome

Module 1: Data, Ethics, and Law

• Data, ethics, and law
• Designing the data revolution
• The age of big data
• Ethical foundations: Part 1
• Ethical foundations: Part 2
• Ethical foundations: Part 3
• Law, analytics, and society
• Different types of law
• IRAC analysis
• Subjective to objective
• A Data oath
• IRAC application
• Explore the compassions data set: Part 1
• Explore the compassions data set: Part 2
• Explore the compassions data set: Part 3

Module 2: Data, Individuals, and Society

• Data, individuals, and society
• Bias in data processing: Part 1
• Bias in data processing: Part 2
• Legal concerns for equality
• Bias and legal challenges
• Consumers and policy
• Employment and policy
• Education and policy
• Policing and policy
• Best practices to remove bias
• Descriptive analytics and identity
• Privacy, privilege, or right
• Privacy law and analytics
• Negligence law and analytics
• Power imbalances
• IRAC application

Module 3: Data Ethics and Law in Business

• Data ethics and law in business
• Handling consumer data
• Handling employee data
• Ethics in hiring with big data
• Digital market manipulation
• The evolution of privacy and technology
• Data privacy and security best practices
• GDPR
• GDPR, big data, and AI
• IRAC application
• The ethics and variables of recidivism

Module 4: Artificial Intelligence and Future Opportunities

• AI and future opportunities
• From analytics to AI
• AI design principles
• Example autonomous cars
• Values like ours
• Why XAI
• XAI the issues
• XAI complex algorithms
• XAI or GAI
• Algorithms and accountability

Conclusion

• Wrap up