This course explores the ethical considerations of AI in accounting. Participants will examine the principles of AI data ethics, regulatory requirements, and strategies for ethical AI use.
Learning Objectives
- Understand the fundamental principles of AI and data ethics and their relevance to accounting
- Analyze the ethical implications of AI adoption in auditing and accounting with a focus on independence, objectivity, and professional skepticism
- Describe the concepts of algorithmic bias and fairness in AI systems and develop strategies to mitigate these issues
- Evaluate the regulatory requirements and guidelines from national and international bodies regarding AI and data ethics
- Develop strategies for ensuring ethical use of AI in accounting practices
Major Topics
- Fundamental principles of AI and data ethics
- Importance of ethics in AI adoption
- Relevance of data ethics in accounting practices
- Frameworks for ethical AI implementation
- Ethical implications of AI in auditing and accounting
- Maintaining independence and objectivity
- Ensuring professional skepticism with AI tools
- Addressing ethical dilemmas in AI-driven audits
- Algorithmic bias and fairness in AI systems
- Identifying and understanding algorithmic bias
- Strategies to ensure fairness in AI models
- Case studies on bias and fairness issues in accounting
- Regulatory requirements and guidelines
- Overview of national and international regulations (e.g., GDPR, HIPAA)
- Compliance with ethical standards in AI use
- Emerging guidelines from accounting bodies on AI ethics
- Strategies for ethical AI use in accounting
- Implementing ethical AI frameworks and tools
- Promoting transparency, accountability, and fairness
- Developing a culture of ethics in AI-enhanced accounting practices
