Technology Life-cycle As I observe the current state of Artificial Intelligence (AI) and the rush surrounding As AI moves beyond pure research, distinct engineering domains are starting to crystallize. Too many organizations and leaders are treating AI as if it were already in the commodity phase—ready have expected the early pioneers of computing to immediately build data centres, we shouldn't expect AI He actively contributes to the profession through his leadership roles, serving as AI Committee Chair

Why AI Is Different: AI presents unique risks because of its ability to operate with minimal human oversight Challenges with AI Regulation: While regulations like the EU AI Act are emerging, they are still new A Program to Govern AI: A comprehensive AI governance program should include four elements: AI Code of AI Design Standards: Technical guidelines for AI development, emphasizing ethical considerations. AI Safety Policies: Measures to prevent harm and ensure robust testing and monitoring of AI systems.

As AI capabilities rapidly advance, a stark prediction is emerging from industry leaders: AI Engineering AI operations (managing and maintaining AI-powered systems at scale). Survival Strategies in an AI-First World AI represents a genuine threat to traditional engineering careers to AI system design; adopt AI engineering knowledge and methods into your practice Specialize in AI reliability and maintenance  - AI systems need monitoring, debugging, and optimization Develop AI model

This is one way to evaluate what is happening with AI.

the European Union's AI Act, the UK National AI Strategy and Proposed AI Act, Canada's Artificial Intelligence AI. AI is safe and ethical. UK National AI Strategy and Proposed AI Act The UK national AI strategy, launched in November 2021, is AI talent.

While this is just one example, I know my experience with AI chat applications is not unique. Many are fond of attributing human qualities to AI which is called anthropomorphism . However, if we are going to anthropomorphize then why not go all the way, and say AI lied . We don’t do this because it applies a standard of morality to the AI system. That's why when it comes to AI systems we need to stop attributing human qualities to them if we hope

Review and Boston Consulting Group (BCG), “The Future of Strategic Management: Enhancing KPIs with AI more than 3,000 managers and interviews with 17 executives to examine how managers and leaders use AI In this report the authors categorize AI-enhanced KPIs in the following way: Smart Descriptive KPIs : Smart Prescriptive KPIs : use AI to recommend actions that optimize performance. (Goodhart’s Law) What steps should be followed when using AI for KPIs?

ladder offers the right level of analysis to further the discussions regarding responsible and safe AI At this level of analysis we are talking about AI Systems (i.e. engineered systems) not about systems that use AI technology (Embedded AI). across the socio-technical system, not just the AI technology. This is where professional AI engineers are most helpful and needed.

Artificial Intelligence (AI) is on a trajectory to revolutionize various industries, from healthcare Ethical AI in Action One notable example of integrating ethics into AI development is the concept of explainable AI (XAI). XAI emphasizes transparency and interpretability in AI systems, ensuring that decisions made by AI models integrity into AI initiatives.

AI governance policies typically describe what organizations intend to do. Seven Elements of Operational AI Governance 1. AI-assisted operational controls where they add value. Periodic alignment with ISO 42001, NIST AI RMF, sector frameworks. Is your AI governance capable of ensuring and protecting Total Value?

Working with AI over the past year opened my eyes to a systemic problem: AI systems are stuck in the It's a blindspot because AI systems literally cannot "see" emerging trends, innovations, or approaches This shift might be the future, but it barely exists in AI's world. The data doesn't show it enough, so the AI rarely mentions it. I've tried everything. Remember that AI shows what was common, not what's becoming common.

AI now presents both the opportunity and the necessity to do so. Here is why. Organizations everywhere are adopting AI. I believe AI is now being used in ways that do exactly that. Much is said today about AI governance. AI will not be the end of Stakeholder Value.