Digital Humanity

  Before my current role, I was leading performance marketing for a global healthcare company—a quiet giant in the pharma world. The work was complex: multiple product lines, strict compliance, and highly targeted campaigns across markets. We used Google Analytics, CRM data, and a lot of hands-on optimization to drive results. Over the years, I’ve seen digital marketing shift from gut-based decisions and spreadsheets to data-driven planning. Now, we’re entering the next phase—where AI doesn’t just support campaigns, it actively shapes them. Whether it’s automated bidding, predictive audiences, or creative generation, the tools are evolving fast—and so is the way we work. 1. From Manual Analytics to Predictive Insights In the past, Universal Analytics was our go-to. We manually set up goals, configured event tags, and pulled weekly reports. GA4 changed that with its event-based tracking model and built-in machine learning. Real example – McDonald’s Hong Kong They used GA4’s predict...

The European Accessibility Act: What It Means and Why It Matters (Now) If you work in tech, digital product development, or compliance, you've probably started hearing more about the European Accessibility Act (EAA). And if you haven’t yet, it’s time to tune in — because this is one of those laws that doesn’t just apply to “someone else.” It affects nearly every company doing business in the EU, whether you're based in Berlin or Bangalore. What is the EAA? The European Accessibility Act is a major EU directive that requires a wide range of digital products and services to be accessible to people with disabilities. That includes things like websites, banking apps, transport booking systems, smart devices, and even eBooks. By June 28, 2025, any organization offering services in the EU must comply. And “compliance” doesn’t just mean checking a few boxes — it means your digital experiences need to work for people with vision, hearing, motor, or cognitive impairments. What's Cov...

The Illusion of Thinking: Why Even the Smartest AI Models Struggle to Truly Reason In June 2025, Apple published a research paper titled The Illusion of Thinking, and it couldn’t be more aptly named. In this study, Apple’s researchers pulled back the curtain on what we often assume about Large Language Models (LLMs): that their convincing chain-of-thought answers reflect actual reasoning. Spoiler alert—they don’t. Or at least, not reliably. This post breaks down what Apple discovered, how it compares with tools like ChatGPT, GitHub Copilot, DeepSeek, and Claude, and what it all means for the future of “thinking” machines. What Apple Found: Simulated Thinking Falls Apart Apple coined the term Large Reasoning Models (LRMs) for LLMs explicitly trained or prompted to reason step-by-step—like how ChatGPT uses “Let’s think step by step.” These models were tested on logical puzzles like Tower of Hanoi, River Crossing, and Blocks World, where complexity can be scaled in measurable ...

Last week, the technology world witnessed a strategic pivot that could reshape the future of personal computing. OpenAI acquired Jony Ive’s AI hardware venture io for a reported $6.5 billion. This isn’t just a play for sleek devices—it’s an ambitious move to define what comes after smartphones. The implications were immediate: market reactions included a notable drop in share prices for major device and ecosystem players, signaling concern about a potential paradigm shift. But this isn’t about one company overtaking another. It’s about an emerging platform that could redefine how humans interact with technology. 🔁 From Apps to Agents: A New Computing Paradigm At the heart of this move is the idea of AI-native hardware —devices built from the ground up to operate as intelligent companions, not just tools. Unlike traditional phones or smart speakers, these devices aim to deliver context-aware, proactive assistance through powerful AI models like GPT. This new wave of devices may...