Part IV
The Ethical Tightrope:
Balancing AI’s Power with Accountability in Auditing

Mary Breslin, CFE, CIA

As AI becomes more integrated into the auditing process, it brings with it a host of ethical considerations that auditors must navigate carefully. While tools like ChatGPT offer unprecedented power and efficiency, they also raise questions about accountability, transparency, and the potential for bias. It’s crucial for auditors to understand these challenges and take steps to ensure that the use of AI enhances, rather than undermines, the integrity of their work.

Reliability and Data Integrity Concerns

One of the primary ethical concerns with AI is its reliability. AI tools, including ChatGPT, are based on algorithms that process vast amounts of data to generate insights. However, these insights are only as good as the data they’re based on. If the data is biased, incomplete, or outdated, the AI’s recommendations could be flawed, leading to potentially significant errors in the audit. For instance, if an AI model has been trained on data that reflects historical biases, it might perpetuate those biases in its analysis, leading to unfair or inaccurate outcomes.

Transparency and the “Black Box” Problem

Transparency is another critical issue. AI systems, especially those based on deep learning, often operate as “black boxes” where the decision-making process is not easily understood even by experts. In auditing, where transparency and accountability are paramount, this can be problematic. Auditors must be able to explain how they arrived at their conclusions, and this includes understanding how AI tools like ChatGPT generated the insights they’re using. Without this understanding, there’s a risk that auditors could place too much trust in AI, leading to decisions that are not fully informed or that overlook potential issues.

Accountability in AI-Driven Audits

Moreover, there’s the question of accountability. If an AI tool makes a mistake—such as failing to flag a critical risk or misidentifying a pattern—who is responsible? The software developer? The auditor who used the tool? The firm that deployed it? Navigating these questions is crucial, especially as AI becomes more prevalent in the auditing field. Auditors must ensure that there are clear protocols in place to address these issues, including maintaining human oversight over AI-driven processes and validating AI’s outputs against traditional methods.

Mitigating Risks with Professional Judgment

To mitigate these risks, it’s essential for auditors to approach AI with a healthy dose of skepticism. While AI can provide valuable insights, it should not replace the need for professional judgment. Auditors should verify AI-generated findings, cross-check them with other data, and be transparent with stakeholders about the role AI played in the audit process. By doing so, they can harness the power of AI while maintaining the trust and integrity that are the cornerstones of the auditing profession.

Responsible Use of AI in Auditing

In conclusion, while AI has the potential to transform auditing, it also poses significant ethical challenges. By understanding these challenges and taking proactive steps to address them, auditors can ensure that AI is used responsibly, enhancing the quality and credibility of their work.

Mary Breslin, CFE, CIA, is president and founder of Verracy, a training and consulting company. Contact her at mbreslin@verracy.com.