Course Description

This course examines the founding and evolution of OpenAI as an ethics case study in mission drift. It opens with the origins of artificial intelligence at the 1956 Dartmouth Summer Research Project and the two competing definitions of intelligence that still shape AI safety debates, then traces how a company founded as a non-profit, expressly to keep advanced AI out of any single corporation's hands, became a commercial enterprise racing its competitors to market. Participants follow the decisions that produced that transformation: the compute problem that forced a change in structure, the self-interest threat created by placing a for-profit branch inside a non-profit, the charter revisions that preceded that move, the safety evaluations that were compressed or skipped, and the governance breakdown that led a board to remove and then reinstate its chief executive in five days. For CPAs, finance professionals, and company leaders, the case offers a detailed look at how commercial pressure erodes stated ethical commitments over time, why a written charter is not a safeguard on its own, and how an ethical framework such as the IESBA Code is designed to guard against mission drift, conflicts of interest, and failures of candor with those charged with governance.

Learning Objectives

Upon completing the course, the participant will be able to:

  1. Identify the origins of the term artificial intelligence, the two competing definitions of intelligence that emerged in early AI research, and the AGI benchmark, and recognize how those competing definitions continue to shape AI safety and ethics debates today.
  2. Explain how Symbolic AI was designed to work and analyze the four limitations that caused the AI research community to lose confidence in it.
  3. Describe how connectionism differs from Symbolic AI and identify the breakthroughs that ended the AI winter and made deep learning the dominant approach.
  4. Recognize the technical milestones, the personal rivalry, and the ethical convictions that together led Elon Musk and Sam Altman to found OpenAI as a non-profit positioned against Google.
  5. Explain why OpenAI's founders chose an open, non-profit structure and identify the commitments the 2015 founding letter placed on record.
  6. Analyze how funding pressure and a leadership vacuum led to Elon Musk's departure and to the creation of OpenAI's capped-profit structure.
  7. Evaluate the self-interest threat created by OpenAI's move to a for-profit structure and identify the specific changes made to the company's charter.
  8. Explain what a large language model does and analyze OpenAI's decision to withhold GPT-2 on safety grounds, the Microsoft partnership that funded what followed, and the release of ChatGPT without comparable safety evaluation.
  9. Identify the safety principles at stake inside OpenAI and the governance failures that led its board to remove Sam Altman in November 2023.
  10. Evaluate the five days that reversed the board's decision and what OpenAI's evolution demonstrates about mission drift, and apply the role of an ethical framework such as the IESBA Code in guarding against it.

Instructors

Garth Sheriff, CPA, CA, CPA (Illinois), CIA, CGMA, MAcc, is the founder of Sheriff Consulting. Sheriff Consulting provides continuing professional education (CPE) courses in leadership, communication, and assurance. Garth has worked as an assurance professional and learning provider for over 20 years. Garth has also acted in various stage and film productions. He is a graduate in improvisation from The Second City and a member of ACTRA (the Alliance of Canadian Cinema, Television and Radio Artists).

Course Information

Course Title: Professional Ethics: The OpenAI Story

Estimated Total CPE: 4.0

Field(s) of Study: Behavioral Ethics

Delivery Method: Self-Study

Program Level: Basic

Prerequisites/Advanced Preparation: None

Enrollment Period/Expiration Date: One year from date of purchase

Date of Last Program Review/Update: August 18, 2026

Refund Policy/Complaint Resolution Policy: Our policies can be found in our FAQ

Assessment Requirements:

To earn CPE credit, participants must successfully complete the qualified assessment with the following minimum passing grades:

Self-Study (0.5 CPE or higher): 70% cumulative passing grade

Nano Learning (0.2 CPE): 100% passing grade

Participants who do not achieve the required passing grade may retake the assessment in accordance with sponsor policy.

Course curriculum

    1. Instructions for QAS Self Study

    2. Course Overview

    3. Glossary of Key Terms

    1. The Holy Grail of AI

      FREE PREVIEW

    2. Review Question

    1. The First Order of AI

    2. Review Question

    1. The Rise of Connectionism

    2. Review Question

    1. Elon Musk and Sam Altman Team Up

    2. Review Question

    1. If You Build It They Will Come

    2. Review Question

About this course

  • $150.00
  • 24 lessons
  • 2 hours of video content

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