The use of AI in business is continually expanding, but understanding the risks it brings and the need to ensure operational reliability are equally critical.
Security risks associated with AI aren’t always identified at sufficient levels. Auditing plays a pivotal role in ensuring that AI solutions are efficient, ethical, and safe. Here’s a step-by-step guide to auditing AI solutions and ensuring related controls.
For instance, can an organization with an ISO27001 certification leverage AI in its operations? ISO27001 requirements include assessing and ensuring adequate controls, responsibilities, and impact evaluation. This responsibility cannot be shifted to the organization’s customers or stakeholders without clearly defined agreements.
Insurance liabilities also demand a framework where an organization identifies operational risks, devises contingency plans, and ensures comprehensive controls are in place.
Risk portfolio management (e.g., Thinking Portfolio Risk Portfolio) can be utilized to identify, evaluate, and analyze these risks, assess their impact and probability, and manage them. If necessary, it can also aid in managing realized risks and planning corrective actions.
Practical aspects to consider in AI-related Risk Management:
- Outline objectives and use cases
Precisely define what the AI solution should achieve and how it will be used. This helps understand the necessary risks and controls. Enhance understanding of risks and required controls.
- Identify ethics and compliance
Ensure the AI solution complies with local laws and regulations. Additionally, verify that the solution respects ethical principles such as transparency and fairness. It’s important to note that this responsibility cannot be shifted from the organization to its stakeholders or customers.
- Assess AI functionality
Examine the AI algorithm’s operation and its outcomes. Is it predictable and explainable? Test the solution’s performance in different scenarios. How are the recommendations, analyses, or summaries provided by AI ensured? Using AI does not eliminate or externalize risks in decision-making or actions taken based on AI recommendations. Ensure that AI algorithms are understood, and their limitations and deficiencies are identified.
- Security and privacy matters
Check the AI solution’s security and ensure it appropriately protects users’ data. Identifying and safeguarding vulnerabilities are crucial steps. If there’s a risk that AI might process or transfer data in a way not permitted in, for example, a personal register, separate permission must be requested. It’s important to note that individuals in the register have the right to know how their personal data has been processed and to refuse the use of AI in analyzing and further processing their data.
- Document and report
Record all information and findings related to AI auditing. Compile a comprehensive report including audit results, recommendations, and potential improvement suggestions. Ensure that before deploying AI, sufficient technical and operational checks and independent audits are conducted.
- Continuous monitoring and updates
AI auditing is not a one-time event but an ongoing process. Monitor the performance of the AI solution and update controls as needed to address evolving needs and risks. Note that the AI field is evolving, and information within AI solutions cannot be conclusively erased even if the companies behind AI solutions change their home countries.
AI auditing requires multidisciplinary expertise and continuous attention. Collaboration between different teams, such as business, cybersecurity, and legal, is essential. In effective risk management, proactive and detecting controls are particularly crucial, and Risk Portfolio Management is precisely such a control.
Risk portfolio management is an important proactive and detecting control.
Ultimately, the use of AI in business offers tremendous opportunities, but the responsibility for its ethical, legal, and safe use is paramount and always falls on the organization employing AI. Through Risk Portfolio Management, AI auditing, and continuous monitoring, it’s ensured that AI solutions serve their purpose efficiently and responsibly.
Read more about Thinking Portfolio’s Risk Portfolio Management SaaS Service
