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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.

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

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.

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.

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

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?"

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.