Hey there, fellow internal auditors!
So you’re interested in AI? Well, these days who isn’t?
But, let’s face it…
Auditing AI can feel a bit too overwhelming telling its complex concepts and ever-changing technology.
But fear not! We’ve got your back.
In this article, we break down essential components of AI auditing in a way that’s as easy as chatting with a friend over coffee. From understanding governance to ensuring data quality and measuring performance, we’ve got all the insights you need to level up your auditing game in the fast-paced realm of AI. Let’s dive in!
1. AI Governance:
Think of AI governance as the rulebook for how an organization uses AI. Therefore, the auditor’s responsibility on an AI Governance level is to make sure that AI activities are in line with overall company goals and values. Additionally, clear rules are set to monitor AI uses within the organization and the people in charge know what they’re doing.
2. Data Architecture and Infrastructure:
Just like a building needs a strong foundation, AI needs reliable data. Auditors need to check that the data AI uses is accurate and safe, additionally to checking if proper systems are set for storing and managing this data.
3. Data Quality:
Consider AI as an architect designing a building. Just as a strong building needs sturdy materials, AI requires reliable data to construct accurate insights. Auditors ensure that the data AI utilizes is solid and consistent. This ensures that AI’s conclusions stand firm, just like a well-built structure.
4. Measuring Performance of AI:
We want AI to do a good job, right? Auditors help measure how well AI is performing and if it’s helping the organization achieve its goals. They check if AI is actually doing what it’s supposed to do.
5. The Human Factor:
Even though AI is smart, humans still play a big role. Sometimes humans make mistakes, and that can affect AI too. Auditors help make sure that AI is used correctly and ethically, and they keep an eye out for any human errors that could cause problems.
6. The Black Box Factor:
Ever heard of a black box in a plane? It’s something mysterious that we don’t really understand. AI can be a bit like that sometimes. Auditors need to figure out how AI works, even if it seems like a mystery. This helps ensure that AI is trustworthy and that we know what it’s doing.
In a nutshell, auditing AI is about making sure that it’s being used in the right way and that it’s doing what it’s supposed to do. By understanding these six components, you can now help organizations use AI safely and effectively!
