Courses

Objective

• 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

Highlights

• 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

Designed For

Prerequisite

Advanced Preparation