Course HighlightsCOURSE
Ethics and Law in Data and Analytics

Ethics and Law in Data and Analytics

Analytics and AI are powerful tools that have real-word outcomes. Learn how to apply practical, ethical, and legal constructs and scenarios so that you can be an effective analytics professional.

Ethics and Law in Data and Analytics Highlights

Course Enrollment

Starts on

01 January 2019

Enrollment closes on
30 September 2019

  Course duration

Duration

  • Total 12 to 18 hours
  Course Fee

Fee

US$89 - US$149

Course Enrollment

Starts on

01 January 2019

Enrollment closes on
30 September 2019

Course duration

Duration

  • Total 12 to 18 hours
Course Fee

Fee

US$89 - US$149

Enrollment is Closed

About this course

Corporations, governments, and individuals have powerful tools in Analytics and AI to create real-world outcomes, for good or for ill.

Data professionals today need both the frameworks and the methods in their job to achieve optimal results while being good stewards of their critical role in society today.

In this course, you'll learn to apply ethical and legal frameworks to initiatives in the data profession. You'll explore practical approaches to data and analytics problems posed by work in Big Data, Data Science, and AI. You'll also investigate applied data methods for ethical and legal work in Analytics and AI.

What you'll learn

  • Foundational abilities in applying ethical and legal frameworks for the data profession
  • Practical approaches to data and analytics problems, including Big Data and Data Science and AI
  • Applied data methods for ethical and legal work in Analytics and AI

Meet the instructors

Ben Olsen

Ben Olsen

Sr. Content Developer

Microsoft

Ben is a Sr. Content Developer for Microsoft's Learning and Readiness team, and is an analytics professional and educator with over 8 years of industry and managerial experience. Prior to joining Microsoft, Ben ran and directed multiple consulting firms, where he also held critical analytics roles in companies as diverse as Juniper Networks, Costco, and T-Mobile. He has taught Data Visualization at The University of Washington, and recently founded Seattle Pacific University's Analytics Certificate Program.

Geneva Lasprogata

Geneva Lasprogata

Endowed Chair in Business

Seattle University

Geneva ("Eva") Anne Lasprogata is a professor of law at Seattle University, where she is tenured in the Albers School of Business and Economics. Profiting from her unique position as a law professor in a business school environment, Eva has been creatively bridging and integrating law and business for over fifteen years.

Eva’s teaching, research and consulting interests rest at the intersection of human rights and entrepreneurial business models. She has been recognized for her scholarly work in the areas of employee privacy law and social entrepreneurship, and is published in such journals as the Stanford Technology Law Review and the American Business Law Journal.

Nathan Colaner

Nathan Colaner

Instructor of Management and Philosophy

Seattle University

Teaching, writing, and mentoring in business ethics have been the greatest joys of my professional life. Although I have realized, as many academics before me have, that there is a kind of satisfaction you can find only by directly impacting your community for good. So in addition to my role as Instructor at Seattle University, I have co-founded Digital Dignity Consulting, which addresses what will become one of the most important questions of the 21st century: what are the ethical and legal issues that businesses should consider when managing big data and machine learning?

Course Outline

Enrollment is Closed
Before You Start
Welcome to the Course!
Instructor and Course Introduction
Prerequisites
Module Objectives
Grading
Pre-Course Survey
Try Office 365 for Free
Introduce Yourself
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
Further Reading
Law, Analytics, and Society
Different Types of Law
IRAC Analysis
IRAC Continued
Further Reading
Subjective to Objective
A Data Oath
Ethical Data Use Cheat Sheet
Further Reading
Assignment
IRAC Application
Data Set Instructions
Explore the Compas Data Set
Exploration Prompt
Validation
Module 01 Assessment
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
Further Reading
Privacy, Privilege or Right
Privacy Law and Analytics
Negligence Law and Analytics
Power Imbalances
Personal Data and Privacy
Masking Personal Data
Further Reading
Assignment
IRAC Application
Personal Data Exercise
Validation
Moduele 02 Assessment
Data Ethics and Law in Business
Handling Consumer Data
Handling Employee Data
Ethics in Hiring with Big Data
Digitial Market Manipulation
Further Reading
The Evolution of Privacy and Technology
Data Privacy and Security Best Practices
GDPR
GDPR, Big Data, and AI
Further Reading
Assignment
IRAC Application
The Ethics and Variables of Recidivism
Predictive Variables Instructions
Validation
Module 03 Assessment
AI and Future Opportunities
From Analytics to AI
AI Design Principles
Example - Autonomous Cars
Values Like Ours
Further Reading
Why XAI
XAI - The Issues
XAI - Complex Algorithms
XAI or GAI
Further Reading
Assignment
Algorithms and Accountability
IRAC Case Study
IRAC Suggested Answers
Predicting Recidivism without Using Protected Classes
Validation
Module 04 Assessment
Module 05 Assessment
Wrap Up
Post-Course Survey
Course Certificate

Earn your certificate

Once you have completed this course, you will earn your certificate.

Ethics and Law in Data and Analytics