How should organisations approach AI governance?

As artificial intelligence gains prevalence in the enterprise, it has become exceedingly important for businesses to outline their AI governance frameworks

Today, fewer people are shuddering at the thought of an artificial intelligence (AI)-driven world. With a cyber uprising/revenge of the robots seeming less likely, organisations are embracing AI to bolster their business performance. In fact, AI has something to offer every industry, making for an exciting time to be alive.

However, the cyber uprising fears have left behind a different niggling feeling. Increasingly, organisations are becoming aware that they need, and I mean need, an AI governance framework. In particular, businesses want to know how to use AI and how to validate its results. AI governance also makes a good implication for standards to follow, as well as outlines how to take corrective measures.

Organisations should strive to implement safeguards to ensure their AI is delivering valid outcomes. Even though these efforts are only in-house, as an industry-wide endeavour, different fields can move forward with more uniform ideals.

Getting your governance together

Firstly, it’s important to understand the weight of why having an AI governance framework is necessary. With AI governance, organisations can create policies to combat the negative aspects associated with AI. This includes AI bias and discrimination. Organisations must outline these policies as early as possible to create the best possible foundation to move forward with.

As per Gartner’s suggestion, data and analytics leaders and CIOs need to zero in on three things: trust, transparency, and diversity. This means identifying transparency requirements for data sources and algorithms, reducing risks in turn. To tackle bias and uphold ethics, organisations need to ensure data, algorithm, and viewpoint diversity too.

To further aid you in transparency, you need to consider your AI’s traceability. Since GDPR especially, organisations need to be able to disclose their machines’ decision-making process and logic journey. Beyond just meeting regulations, it will give you a more comprehensive understanding of your machines’ thought process.

Fundamentally, AI governance is all about trust. On the one hand, your clients and governing bodies are trusting you to be governing your AI properly. On the other, you need to have confidence in your AI machines and be able to trust them too. AI is a very exciting asset for the industry, but the consequences of misconduct could cause the demise of your business.

Want to know more about AI? Check out our Ask the Expert with antifuturist, Theo Priestley.