This event includes 2 hours of Ethics CPD


NOTE: This is an On Demand session. This course is available 24 hours a day, 7 days a week. Once registered, you can access the material at any time. However, you will only have access to the course for 30 days AFTER REGISTRATION closes.

This course is developed in partnership with the Centre for Advancing Responsible Ethical Artificial Intelligence (CARE-AI) at the University of Guelph.

Big data and artificial intelligence (AI) are changing our world and raising unprecedented ethical issues.

CPAs must be prepared to grapple with ethical questions related to data and algorithms as AI and machine learning (ML) applications increasingly permeate business. In this CPA Ontario course, you will be introduced to ethical concepts such as bias, fairness, and privacy in the context of AI and ML. You will sharpen your ability to think critically and carefully about the challenges posed by big data and AI in today’s workplace and in society at large.

You will also hear industry perspectives from Natalia Modjeska, Research Director at Info-Tech Research Group. Based on her extensive experience advising businesses on ethical and responsible AI, Natalia shares common misconceptions and questions that businesses must ask of any AI/ML application.


The course includes case studies, reflection questions, and a final quiz.


  • Recognize and anticipate ethical issues stemming from AI/ML applications
  • Cut through the hype and think critically about the ethical, legal, and social implications of AI/ML
  • Identify key risk drivers behind bias and privacy violations in the use of big data
  • Prepare to raise questions about the data that drives AI/ML applications
  • Learn about the limitations of addressing ethical issues with regulation, legal compliance, and technical frameworks


This course will benefit CPAs at all levels of an organization who wish to develop increased awareness of ethical issues in today’s data-driven environment. CPAs who are exploring the use of AI/ML, and any CPAs working alongside data scientists, engineers, application developers, and other colleagues who design or implement AI/ML systems.