AI Governance - Information Matters

October 14, 2026 Ebubechukwu Uba

Should We Audit AI Before We Adopt It?

Whenever we hear AI Audit, what comes to mind is a technology already in use. We examine its outputs for bias, test its accuracy, investigate failures, or study its effects on users. By then, however, an institution may already have purchased the technology, integrated it into existing systems, trained employees to use it, and introduced it to students or community members. What would change if some of this scrutiny occurred earlier? As AI-powered technologies become more common in schools, universities, libraries, and other information environments, there is a case for treating the period before adoption as an important point of inquiry. Since we increasingly audit what AI does, should we also audit what we know about an AI system before we decide to adopt it?

Featured Translation

October 12, 2026 Alexander Richter

Keeping Humans in Practice: What the Quipu and Marshallese Stick Chart Can Teach Us about AI Governance

An organisation can keep humans in the loop and still lose the expertise that makes their oversight meaningful. When AI analyses evidence, frames options and drafts recommendations, it can also displace the work through which experts develop and sustain judgement. People may retain the authority to approve a decision while becoming less able to reconstruct how it was reached, challenge its assumptions or exercise independent judgement. For leaders, the question is not simply whether a human signs off. It is whether the organisation is preserving the expertise that makes that sign-off worth having.

Featured Opinion

September 30, 2026 Bo Hyun Hong

Could We Slow Down AI—Who Gets to Set the Pace and Write the Rules?

As AI companies begin discussing slower development and stronger codes of conduct, a deeper question remains: Who gets to decide? This article examines how power, responsibility, and public participation should shape the rules governing A—and why these questions belong in the technology ethics classroom.

Frontiers

December 9, 2025 Ponego Letswalo

Governance as Code: How AI is Enforcing Information Policies Directly in the Tech Stack

Traditional governance models, reliant on static documents and manual reviews, are fundamentally incompatible with the velocity and complexity of modern AI and software development. This paper examines the paradigm of “Governance as Code” (GaC), a transformative approach that embeds information policies, ethical guidelines, and compliance controls directly into the technology stack. By translating human-readable rules into machine-executable code, GaC enables proactive, automated enforcement within DevOps and AIOps pipelines. We explore practical implementations such as AI guardrails that filter sensitive prompts and automated risk-tiering systems that streamline project oversight.

Frontiers Original

May 1, 2025 Jodie Lobana

Forging a Middle Path: Canada’s Moment to Lead in AI Governance

Today, with the AI landscape evolving rapidly, especially with the explosive advancement of generative AI technologies, Canada finds itself pulled between two global powers: the United States, favouring open innovation, and the European Union, doubling down on strict AI regulation. Canada does have a proposed Artificial Intelligence and Data Act (AIDA), introduced in 2022 as part of Bill C-27, which aims to regulate high-impact AI systems. However, AIDA is still under review and has yet to be finalized, leaving a critical gap in national legislation.