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Mar 2 •
🤖💻The AI take over...
We know it's coming right? I was just watching the Davos AI summit talks... and we really need to talk about this. AI is transforming the world and it is going to make it radically different in the very near future. Not slowly. Not hypothetically. Rapidly.... Like MEGA MEGA rapidly. Here’s what most people are not fully grasping... We are not just automating tasks.We are automating cognition, COGNITION! 🤯 Writing. Coding. Design. Diagnosis.Customer service.Research.Analysis. Entire categories of intellectual labor are being compressed into seconds. And most labor jobs will be rapidly replaced as well. Even "top ones" This changes everything. When intelligence becomes scalable and near-instant: • The cost of execution collapses. • The barrier to entry drops. • The volume of content explodes. • The speed of business accelerates. • Mediocrity gets exposed fast. Do not be fooled, entire industries will restructure, education will shift and corporate hierarchies will flatten. It is going to look like total collapse for many people. The way that we create, consume, and trust information will evolve dramatically. And MOST people will get absolutely rocked. And here is the deeper layer (most importantly) When intelligence is abundant, judgment becomes scarce. When content is infinite, credibility becomes currency. When automation is everywhere, embodied leadership becomes premium. The future will not belong to people who can “do tasks.” The future will belong to people who can think strategically, decide clearly, and lead powerfully in complexity. ✍🏼 So how do you prepare (this is something I am hyper focused on)? 1. Build ownership, not dependence.Own your brand. Own your audience. Own assets that are not tied to one platform. 2. Master AI instead of fearing it. Learn how to use it to increase output, sharpen thinking, and systemize operations. 3. Develop anti-automation skills.Strategic reasoning. Discernment. Emotional regulation. Negotiation. Systems thinking. High-level synthesis. 4. Strengthen your body and nervous system.Acceleration punishes dysregulation. Clarity becomes a competitive edge, and YOU MUST take care of your physical vessel. 5. Build high-trust networks in a world flooded with synthetic media and infinite information, people will gravitate toward leaders they trust.
0 likes • Mar 2
From: Chara from Ethics & Ink <[email protected], you don’t know yet, do you? Perfect. Neither does most of the nonprofit sector, so don’t feel bad. This is exactly why I wrote this article today. The European Union just passed the most sweeping AI regulation in history — and buried inside it is a definition of bias so precise, so unflinching, and so deeply relevant to your work that it reads like someone transcribed your worst day on the job and turned it into law. Inherent patterns in historical data. Feedback loops that amplify discrimination. Disproportionate harm to vulnerable groups. Sound familiar? It should. You’ve lived it. Now it’s enforceable. In this piece, I’m walking you through exactly how the EU AI Act defines bias ⟶ connecting it to groundbreaking research from USC that proved a single biased training label can flip an AI’s prediction about a real person ⟶ and, breaking down the three specific articles of the legislation that apply directly to the AI tools your organization is already using to screen, score, and serve your communities. This isn’t a legal brief. It’s a wake-up call dressed as a love letter to every nonprofit leader who got into this work because they knew the system was broken — and now has the chance to make sure the technology replacing it doesn’t break in exactly the same ways. But first — let’s start with the word itself. The Word That Costs More Than Your Entire Budget Somewhere in Brussels, a room full of legislators just finished writing 144 pages of binding law around a single word that most nonprofit leaders use in board meetings but couldn’t define under oath. The word is bias. And the European Union didn’t just mention it. They made it load-bearing architecture — the structural pillar holding up the most consequential AI regulation the world has ever seen. Every obligation, every audit requirement, every enforceable penalty in the EU AI Act traces back to this one concept. So here’s an uncomfortable question: if a funder asked you tomorrow — not “do you care about bias,” because of course you do, but “define bias as it applies to the AI systems your organization uses to make decisions about human beings” — could you answer? Could you answer precisely? Could you answer in a way that would survive regulatory scrutiny?
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