Category: Dedoctive


  • Why do we need AI at all?

    In previous articles, I argued that for AI to be green, it needs to be trustworthy (which is why Dedoctive exists). But why do we even need AI? Would the world be greener, and perhaps better off altogether, if AI didn’t exist? Shown below are current estimates of world population growth, showing how it’s slowing…

  • How Cities and Regions can bring their risks to life

    Strengthening Municipal Preparedness Cities and regions have always faced risks, and always needed to prepare. But now that climate change is generating such an increase in threat levels, and in threat frequency, is it time to take a fresh look at municipal risk management? The challenge is not to create adequate documentation. If anything, there…

  • How to unlock trustworthy, transparent, standards-compliant AI

    While AI continues to evolve rapidly, developers and enterprises face a common challenge: maintaining control and transparency without sacrificing the power of generative agents. At Collaboration Tools, we are bridging this gap with a hybrid approach based on our unique Dedoctive technology. 1. Dedoctive Developer Edition: The Power of Hybrid Workflows Dedoctive Developer Edition is…

  • Trust is a Sustainability Issue

    Part 5 of 5 in a blog series looking at AI’s journey since the release of ChatGPT in November 2022. In the working world, there’s a secret sauce to sustainability: trust. Without it, every decision has to be verified, safeguarded, and hedged. That takes time, costs money, and burns energy. This matters enormously for AI.…

  • The Most Energy Efficient Machine Ever Created

    Part 4 of 5 in a blog series looking at AI’s journey since the release of ChatGPT in November 2022. In the last instalment of this blog series, we saw how the real framing of the AI sustainability question is this: “Does AI reduce the total energy required to achieve meaningful outcomes?” To answer this…

  • AI’s Real Footprint

    Part 3 of 5 in a blog series looking at AI’s journey since the release of ChatGPT in November 2022. In this article, I’ll start looking at another issue with modern AI: the electricity it consumes. The part of the story that’s easy to grasp is huge data centre facilities. You can assess the impact…

  • Lambs to the Slaughter

    Part 2 of 5 in a blog series looking at AI’s journey since the release of ChatGPT in November 2022. After November 2022, many people who normally acted with care and caution seemed to lose the plot. It was clear that Large Language Models (LLMs) were often misleading or just plain wrong. The ChatGPT user…

  • The biggest threat to AI? It’s own success.

    Part 1 of 5 in a blog series looking at AI’s journey since the release of ChatGPT in November 2022. In the noughties, I started blogging about the action research into collaboration I had been conducting for over a decade. Following an approach from a US publisher, my first book, “Human Interactions”, was published in…

  • From Months to Hours: The Power of Dynamic Risk Management

    Think of traditional safety analysis like a paper map; it’s static, hard to read, and quickly becomes out of date. Dedoctive is like a live GPS system. It takes all the raw data (the roads), understands the connections (the routes), and updates in real-time as the situation on the ground changes, always showing you exactly…

  • Show Your Working: Trusting AI with Your Safety

    Think of traditional safety analysis like a paper map; it’s static, hard to read, and quickly becomes out of date. Dedoctive is like a live GPS system. It takes all the raw data (the roads), understands the connections (the routes), and updates in real-time as the situation on the ground changes, always showing you exactly…