This course explores the ethical, legal, and societal implications of Artificial Intelligence, emphasizing responsible AI development and governance. Students will examine key concepts such as fairness, transparency, accountability, and ethical decision-making in AI systems. Through case studies, regulatory frameworks, and hands-on discussions, this course equips learners with the knowledge and tools to design, deploy, and assess AI technologies responsibly in real-world applications.
Number of Units: 2.0 graduate level extension credits in semester hours
Who Should Attend: Chief Executive Officers (CEOs); Chief Information Officers (CIOs) and Chief Technology Officers (CTOs); Chief Data Officers (CDOs) and Chief Analytics Officers (CAOs); Chief Operating Officers (COOs); Vice Presidents and Directors of Strategy, Innovation, or Operations; Senior Managers and Consultants in Technology, Data, and Business Transformation; Business Unit Leaders and Functional Managers (e.g., Marketing, Finance, HR, Supply Chain); and Board Members and Senior Advisors.
Required Textbook: Dignum, V. (2019).Responsible Artificial Intelligence: How to Develop and Use AI in a Responsible Way. Springer. ISBN 978-3030303709. It may be found at Amazon.com or your local bookstore.
Technical Requirements
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Online fixed-date courses are delivered virtually but follow a predetermined schedule, requiring students to complete assignments, participate in discussions, and take assessments by specific deadlines—much like a traditional classroom. The key difference is that while traditional courses are conducted in person at set times and locations, online fixed-date courses allow students to engage remotely, offering more flexibility in where they learn while preserving structure and accountability through fixed timelines. (Note: Any scheduled Zoom sessions will be outlined on the class schedule.) These courses have fixed start and finish dates, but as an online student you will have 24/7 online access to your classroom assignments, syllabus and course resources. Instructor feedback is shared along with the graded assignments.
How is the learning structured? Each online fixed-date course is asynchronous, meaning that you can work on your assignments anytime, although you are required to complete the assignments by specific dates. The course is designed with learning modules where all of the content is grouped into weekly assignments. Each module covers one or more topics. Within each of the learning modules, you can expect the following components:
• Module introduction that outlines what you can expect to learn in the module.
• Required readings (textbook, articles, journals, etc.) and presentations (audio and/or video).
• Assignments with due dates (which may include: written assignments, journal entries, research, blogs, etc.) based on the readings and presentations.
• Discussion forum where you answer prompts from the instructor and interact with your classmates.
• Module conclusion to review the topics and what you should have learned.
Typically, there is a final project, paper, or exam due in the last module that culminates all of the topics covered in each of the learning modules. You’ll find that the design of the learning modules has a rhythm to help you manage your time in the course.
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