How do we deliver safe AI? LLMs), as if AI exists in a vacuum. Example 2: AI Used Within the MOC Process Itself More subtly, when an organization uses AI to automate We now understand that different categories of AI systems present different risk profiles: Narrow AI AI, organizations can move beyond the hype and fear that too often characterize AI discussions.

This integration requires understanding that AI challenges span multiple dimensions. At its core, AI is simultaneously a technical, organizational, and social problem. As we build AI systems, we should continuously ask: where can AI best complement human work, and which We need breakthroughs in AI safety just as much as we need advances in AI capabilities. Through all of this, remember the simplest principle: be good with AI.

Canada's sovereign AI infrastructure is being built right now. Environmental scrutiny of AI energy consumption is intensifying. AI governance frameworks are formalizing.

to "How do we enable AI to reliably meet obligations?" Consider an AI agent managing customer service operations. Unlike current AI systems that respond to prompts, agentic AI agents must serve as the reliable fulfillment AI Agents Enabling Human Promise Fulfillment Understanding AI agents through Promise Theory also helps Rather than asking "Is the AI agent following the rules?"

The rapid proliferation of AI across critical sectors—from healthcare diagnostics to financial trading Yet most current AI governance efforts remain trapped in conventional compliance paradigms: reactive It reflects a deeper challenge rooted in the nature of AI systems themselves. Unlike traditional engineered systems with predictable inputs and outputs, AI systems exhibit emergent What regulatory approaches have you seen that effectively address AI's unique challenges?

this is important, it will not be enough to handle concerns associated with Artificial Intelligence (AI When decisions are made to proceed with a course of action (for example, to use or not use AI, in the That's why I believe our upcoming micro program, "Ethical Decision Making Involving AI" is so important You will learn how to make ethical choices supporting responsible and safe AI along with your other compliance

In this post we take a look at a new AI technology called ChatGPT from OpenAI. I am sure that AI will continue to develop and so will ChatGPT.

the concept of manufacturers' integrity and the significance of self-regulation with application for AI Principles of Ethical Use of AI for Ontario Countries across the world are actively looking at how best Regular peer review of AI systems is also important. These principles aim to ensure that AI systems respect the rule of law, human rights, civil liberties framework for responsible AI practice and use.

exposure resulting from adverse effects of AI. This week the Responsible AI Institute as part of their work (which I support) released an AI tool that AI systems are self-referencing. Clearly, AI is still in the experimental stage. You need to understand what AI can and cannot do.

. - Eliyahu Goldratt Achieving Breakthrough Benefits Artificial Intelligence (AI) holds the promise of Some organizations will adopt AI and receive incremental benefits associated with increased efficiencies of Constraints) offers 4 questions to help you transform your operations using technology including AI why we recommend organizations consider the following three questions with respect to their use of AI policies, standards or guidelines should be established or amended to ensure our responsible use of AI

This predicament has led many to seek technological solutions, with artificial intelligence (AI) emerging According to Gartner's research, AI is poised to transform project management across six key domains: Optimized project planning and reporting: AI-driven systems aim to automate time-consuming tasks, improve change requires empathy and leadership that AI cannot yet replicate. Can AI save your project from failure?

Customers don't just want AI – they want AI they can trust. Many professionals are moving into AI governance roles, but fewer are pursuing AI engineering due to now face "shadow AI" – people using AI tools without official approval. In practice, it appears that AI governance cannot be effectively separated from AI engineering, yet many As AI systems become more sophisticated, there are legitimate concerns that certain types of AI agents