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TECH 113 W — Ethical Data and AI: Concepts and Tools for Responsible Decision-Making

Quarter: Fall
Course Format: Flex Online (About Formats)
Duration: 10 weeks
Date(s): Sep 26—Dec 8
Refund Deadline: Sep 29
Units: 2
Grade Restriction: No letter grade
Tuition: $840
Instructor(s): Angel Evan
Limit: 30
Class Recording Available: Yes
Status: Closed
Please Note: No class the week of November 20
ACCESS THE SYLLABUS » (subject to change)
Flex Online(About Formats)
Sep 26—Dec 8
10 weeks
Refund Date
Sep 29
2 Units
Grade Restriction
No letter grade
Angel Evan
Please Note: No class the week of November 20
ACCESS THE SYLLABUS » (subject to change)
How do we maintain ethics in a world awash in data? Problem-solving has grown increasingly complex as people, technology, and cultural events often blur the line between what is fair and what is violative. Society now confronts never before seen challenges that require new thinking and thoughtful answers to the questions that will invariably shape the future role of data and technology in our lives. These questions challenge our conventional thinking, moral ideologies, and professional agendas. For example:

  • Should self-driving cars be allowed on public roads if they are potentially harmful to humans?
  • Is using grade-predicting algorithms to predict students’ test scores potentially harmful if students cannot sit for the exam?
  • Should large language models be government regulated to protect personal data and intellectual property?
  • Is there an ethical boundary between automating a job task for the sake of efficiency versus eliminating a job altogether?
Questions such as these illustrate the danger of data-driven initiatives that go unchecked and are allowed to operate without ethical frameworks to help guide decision-making and outcomes.

This course goes beyond creating high-level awareness of data-related issues. It focuses on making decisions in ethically ambiguous situations. It will provide current leaders and business professionals charged with making data decisions with a set of tools and decision-making capabilities for dealing with data-related ethical problems in real-world scenarios.

Students in the class are stratified into cohorts that tackle four unique case studies: data governance and surveillance for the public good, questionable data encoded into machine learning models, data privacy and transparency issues for consumers, and ethics-related issues involving machines and robots. Each case study requires careful examination by the cohort and a commitment to a set of decisions based on a predetermined set of questions. By the end of the course, students will have learned how to make decisions in ethically complex situations involving data, which they can apply to their own organizations.

No prior technical or statistical background is required.

Data Science and AI Ethics Leader

Angel Evan is an emerging leader in the field of ethical data and responsible AI. With a career in data science spanning over 10 years, he has a deep, technical knowledge of large-scale machine learning systems paired with a real-world understanding of how to implement these technologies safely and ethically. He is dedicated to helping others understand and use AI conscientiously by ensuring responsible innovation and protecting vulnerable constituencies from potential harm. Evan studied data mining and analytics at UC San Diego, graphic design at Suffolk University, and is currently an MSc candidate in the data and AI ethics program at the University of Edinburgh.

Textbooks for this course:

There are no required textbooks; however, some fee-based online readings may be assigned.