Surgent's AI and Data Ethics in Accounting

Overview

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.

Prerequisites

None

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

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