Why is AI governance important?

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Dr Rachel Finn | Director, Data Protection & Cyber-risk Services / Head of Irish Operations

Date: 3 May 2024

AI governance is a crucial – and ongoing – practice that can help you deploy and maintain responsible AI solutions.  

Here, we answer the question why is AI governance important? 

AI governance can help you mitigate AI risks  

When we talk about the risks associated with AI, it is important to remember that AI isn’t inherently good or bad. It can simply have positive and negative outcomes, depending on how it is built, used, and maintained. As we say in this blog, “if you feed AI models with ‘garbage’, ‘garbage’ is what they will produce.”  

Imagine that you deploy an AI screening tool to help you review candidates’ job applications. It uses real-world data to assess the best candidates for the role, and learns from historical hiring data that people of a certain age, race, and economic background are most likely to be hired. In doing so, it disadvantages the candidates who don’t fit this profile. We have seen this happen in real life already, with Amazon’s AI hiring tool found to prioritise men for technical roles 

This is just one example of how AI could cause harm to your organisation, and to wider society, even though it was used with positive intentions. 

Following a robust AI governance framework can help you mitigate risks like these. By regularly conducting risk assessments – such as with an AI governance platform like STRIAD:AI Assurance – you can make sure that your AI solutions are not perpetuating bias, infringing on people’s privacy, spreading misinformation, or having any other unintended outcomes. 

AI governance can help you build and use responsible AI  

AI has the potential to truly change not just individual organisations, but society as a whole. However, to make effective changes, these tools need to evolve following responsible, trustworthy, and safe frameworks. 

With responsibility principles at their core, you can make sure that your AI systems are ready to use appropriately for their intended use cases. You can also make sure that AI solutions align with your internal best practices and any regulatory obligations that you are bound by. 

The exact building blocks of your AI solutions will depend on how you plan to use them. However, the following six principles are core to responsible and trustworthy AI (RTAI): 

  1. Transparency and explainability 
  2. Safety, security and robustness 
  3. Non-maleficence 
  4. Privacy 
  5. Fairness and justice 
  6. Accountability 

Our Report on the Core Principles and Opportunities for Responsible and Trustworthy AI, commissioned by Innovate UK and BridgeAI, dives into these principles in more detail, exploring what they entail and why they are so important. 

AI governance can help you stay compliant  

Governance practices can help you adhere to emerging AI regulations and avoid the repercussions of non-compliance, from legal issues to financial setbacks to reputational damage.  

The recently passed EU AI Act, for example, puts AI solutions into a series of risk categories, each of which has its own rules to follow. The organisations that don’t abide by these could face fines upwards of €35 million, which highlights the very real importance of staying compliant.  

To learn more about the AI Act’s regulatory framework, who it applies to, and how you can prepare for it, check out EU AI Act: A guide to the first artificial intelligence act. 

By prioritising AI governance – and investing in the development and deployment of responsible AI technologies – organisations can also make sure that future regulations don’t become a blocker to innovation. This is something that our CEO Kush explores in his article on responsible AI, and how it can ultimately help you carve out an innovative (and competitive) edge. 

What is the AI Governance Alliance? 

You may have come across the AI Governance Alliance in your search to better understand why AI governance is so important. 

Created by the World Economic Forum, the AI Governance Alliance brings together some of the global key players in AI to encourage innovation while ensuring that it upholds ethical and inclusivity standards.  

Ensure ongoing AI governance with Trilateral Research 

Effective AI governance isn’t just something that you can do once and never again. As AI evolves, new regulations emerge, and your data changes, new risks can present themselves. 

To help you stay up to date with responsible AI and governance requirements, we regularly share resources in our Knowledge Library and newsletter. You might find this blog valuable next, as it dives into four key strategies for building RTAI, including how to create the right accountability and governance structures.  

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