Why is AI governance important?

AI governance will become increasingly important in parallel to its widespread commercial adaptation. Organizations will need to create, maintain, update, and follow an AI governance framework that will dictate and determine how ethically and operationally feasible their usage of AI capabilities is. More importantly, as identified earlier, several critical challenges go in tandem with using AI. An AI governance framework represents the best operational practice to ensure organizations strike a critical balance between the perceived risks and benefits of AI usage.

How does AI Governance impact different sectors?

Various sectors that may leverage AI will need to view and adapt to AI governance depending on various considerations. One critical consideration will be how intimately leveraging AI capabilities affects humans. For instance, within the healthcare sector, AI is used to determine the best course of action, and treatments for patients are already being discussed as one example of its healthcare uses. At the same time, compared to its usage in healthcare, AI may not pose quite the degree of challenge when being used within theme parks as a way for individuals or families to determine the best schedule to follow to make the best use of their time. More importantly, its effect will become clearer and subject to less ambiguity once various industries begin activity leveraging AI capabilities.

What is the future outlook for AI Governance?

There are quite a number of directions AI may turn out. It is considered a matter of time until AI capabilities are leveraged within corporate and government decision-making processes. If and when that happens, there will likely be a coherent set of guidelines, processes, mechanisms, and several fail-safes in place to ensure that all AI capabilities are leveraged within a defined set. AI governance at such a point will be an established discipline, likely being enforced by regulatory obligations.

What is AI Model Governance?

AI model governance involves triangulation of policies, frameworks, and processes that ensure an organization continues its responsible use of AI internally while managing all associated risks, such as bias, privacy breaches, and ethical concerns. Some regulations have specific requirements for specific types of AI models, so AI model governance can be useful for organizations in adhering to such requirements while maintaining accountability, transparency, and reliability in their AI deployments.

What regulations require AI governance?

AI is a fairly dynamic domain, with consistent developments leading to consistent changes in both AI capabilities and their potential risks. However, almost all major data privacy regulations globally, such as the GDPR, CPRA, the Privacy Act of 1988, and PIPEDA, have some form of requirements related to instances where AI is used within the context of data processing activities. Moreover, most countries are well into developing AI-specific regulations, such as the EU’s AI Act, that would require dedicated AI management frameworks from organizations to ensure AI use aligns with social and ethical standards and values.

How should organizations approach AI governance?

While most organizations may view AI governance as simply a regulatory requirement, it can be highly beneficial if viewed as a vital tool as any other. A clear set of policies that govern the development, deployment, and continuous monitoring of AI systems can ensure a dependable governance structure where each personnel is both aware and accountable for their role and responsibilities. Moreover, regular audits and assessments can also ensure compliance with regulatory requirements while taking into account the needs, expectations, and input from all major stakeholders, such as legal, technical, and ethical experts.

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November 14, 2023

Understanding AI Governance: A Strategic Approach for Businesses

AI Governance refers to a defined set of policies, practices, guidelines, processes, and rules an organization establishes to govern its internal use.

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