Today many organizations use AI that is general. Curation of knowledge — including institutional knowledge — becomes an essential part of governing AI The medical profession has already faced the challenge of using AI where a wrong answer carries real a 2025 study in Bioengineering (Pingua et al.), trying to train medical knowledge directly into the AI Path forward A general AI cannot be trusted in a high-stakes domain because it is general.

With AI, we are skipping that step. We are not doing this with AI. A law that says AI must be safe is not an AI that is being kept safe, moment to moment, by something The AI version fails that test. For AI, it does not exist.

In this article we will explore sustainability and how it relates to AI technologies. AI. AI technology such as ChatGPT should be designed to be safe. AI Sustainability is perhaps what drives the need for AI safety, security, quality, legal, and ethical Instead, of asking is AI Safe , perhaps we should be asking is AI Sustainable ?

When regulators examine AI systems, they often focus on whether the software meets certain technical We lack the foundational work needed for proper AI governance. The Agentic AI Challenge Let's consider autonomous AI agents—systems that can set their own goals and The typical response is that AI can make decisions better and faster than humans. The European Union's AI Act represents significant progress toward this vision.

AI Assistants - Blessing or Curse? The rise of Generative AI has taken the world by storm, and AI assistants are popping up all over the However, for some, it is just an improvement in productivity, and they question whether the use of AI For those starting to use AI assistants, they are indeed a blessing, providing much-needed relief for The use of AI will be a threat for some but an opportunity for others.

on the page of AI history." AI, which Laqua approached from multiple angles, acknowledging that AI is being defined in real-time AI's Domain Diversity Laqua emphasized that no single domain captures the full scope of AI. of AI risk, but what's different with AI is the degree and scope of this uncertainty. The Call for AI Engineers The AI Engineering Body of Knowledge (AIENGBOK) The presentation culminated

When I read about AI in the news, and this includes social media, I am troubled by the way it is often The Need for AI Mythbusters These articles often don’t prove or demonstrate that AI is better, and neither The AI hype machine is definitely operating on all cylinders. Is that what we understand generative AI is - creative? Time for professionals to be AI Mythbusters!

As someone working in compliance during this wave of AI adoption, I've been thinking about how we approach Instead of implementing AI systems and then auditing their outputs, we might design systems that continuously A Different Relationship with AI What strikes me most about reflecting on Jidoka in the context of AI Instead of viewing AI as either fully autonomous or requiring constant supervision, Jidoka points toward For compliance professionals considering AI adoption, this perspective might be liberating.

Many organizations are adopting AI in their business, whether as generative AI or as AI agents. In all cases, the AI needs a context to work from, and for the AI to be effective that context must be An AI model knows nothing about your organization. AI workflows have no such reader. For each class of AI workflow, list what a correct output depends on.

So ask the hard questions: Does your AI know your obligations, your values, your promises? Their AI risk register looks like this 👇 — every line high probability, high severity, all red. They're obligation risks — the effect of AI uncertainty on commitments across every part of their organization How will they give stakeholders the assurance that they can stay between the lines — or will AI cause That's what AI assurance is for — engineered, operational guardrails that keep AI between the lines and

The Current State of AI Artificial intelligence has indeed made remarkable progress in performing specific AI can analyze medical images, review legal documents, optimize engineering designs, or process geological This framework helps explain why AI excels at certain tasks while falling short of what is required for The Master and his Emmisary Machine-Like Intelligence (Left Hemisphere - apprehending) AI demonstrates their emphasis on standardization and procedural efficiency, have created natural opportunities for AI

There's a growing urgency to establish regulations for artificial intelligence (AI). consider how existing regulations, standards, and professional oversight bodies can be leveraged for AI Adapting these frameworks to address AI-specific risks could be a quicker and more efficient approach critical infrastructure, public safety, and environmental sustainability, we can promote responsible AI It’s time we considered Lean AI Regulation.