Namaste Yogis. Welcome to the Blockchain & AI Forum, where your blockchain and artificial intelligence technology questions are answered! Here no question is too mundane. As a bonus, a proverb is also included. Today’s question, was submitted by Rolando from Panama City, and he wants to know about artificial intelligence (AI) governance?
Rolando, you came to the right place. Plenty of people are asking the same question. Recently I came across an KPMG article titled, “The Shape of AI Governance to Come”, in which KPMG explored fundamental questions related to AI governance. KPMG is a major business consultancy firm and recognized thought leader in the field of AI. Let’s see what KPMG said, beginning with the notion of trust.
According to KPMG research, for AI to become transformative, four critical trust factors must be addressed: integrity; explainability, fairness, and resiliency. These four trust factors make sense and are not surprising. The newsworthy discovery is that 87% of IT decision makers advocate regulations to achieve trustworthy AI governance. If regulations are the solution, what is the current state of regulations? KPMG spotted several trends.
First, the most advanced AI markets are putting in place regulations to protect and promote domestic research and development. Second, governments are establishing advisory committees consisting of industry, academic, and government officials to produce guidelines, regulations, etc. For example, Austria passed an AI ethics law, Singapore adopted a 5-year AI plan, and Japan also approved an AI technology strategy. Laws and regulations are a third trend. The implications of these trends could be far reaching and hence worth an examination.
Clearly, governments hope to realize long-term benefits through increased overall operational efficiency for both the public and private sectors. Second, governments expect to create intellectual property related to AI, and thus obtain patents, copyrights, and trademarks for various AI intellectual property. Attracting and keeping talent is a third implication. People will want to work in a country leading the way in AI, thus setting the stage for tax and immigration policy debates.
KPMG acknowledges AI moves faster than politics, hence KMPG provides six AI governance ideas businesses can deploy now until politics catches up.
- 1. Develop AI principles, policies and design criteria, and improve controls within an environment that fosters innovation, flexibility, and trust while identifying unique risks. Inventory AI capabilities and use cases by understanding the AI footprint within the organization.
- 2. Design, implement, and operationalize an end-to-end AI governance and operating model across the entire AI development life cycle, including strategy, building, training, evaluating deploying, operating, and monitoring AI. Establish separate governance committees and councils to discuss the unique risks and complexities associated with AI.
- 3. Assess the current governance and risk framework and do a gap analysis to identify opportunities and areas that need to be addressed.
- 4. Design a cross-functional governance to deliver AI solutions and innovation through guidelines, templates, tooling, and accelerators to deliver AI solutions quickly, but responsibly.
- 5. Integrate a risk management framework to find and prioritize business-critical algorithms, and incorporate an agile risk mitigation strategy to address cybersecurity, integrity, fairness, and resiliency considerations during design and operation.
Time to go, but first a proverb from Suriname, where they say: You don’t need to see the top of the river to know which way the current is flowing.
Until Next Time,
Yogi Nelson
Blockchain & AI Forum 