Dedoctive grounds outputs in trusted evidence, provides full source-level provenance, and governs workflows with human-in-the-loop guardrails.

Author: Keith Harrison-Broninski


  • AI IPOs are War Bonds

    AI may be leading the world’s greatest nations into a death spiral of unchecked spending on technology that improves productivity only for assurance work about which no-one really cares – even if they should.

  • Safer AI for a Safer World

    When safety becomes a primary design concern from the start, the result is not just lower risk. It is better systems that require less rework, resulting in more effective innovation with less cost and in less time. Safety is not a constraint. It is a way of seeing more clearly.

  • Why do we need AI at all?

    In previous centuries, new sources of economic value emerged from sources that are no longer acceptable – extracting resources from colonies (e.g., silver mined in South America), gunboat diplomacy (e.g., forcing China to accept the opium trade), and large-scale human exploitation (e.g., Lancashire cotton mills). So where can we now look for the massive injection…

  • How Cities, Regions, and Responders can bring their risks to life

    The risk management challenge is to help humans make best use of their knowledge, skills, and experience. We must help risk professionals process all this information easily, when funds are limited, risk responses cross boundaries, and every action must be as effective as possible. We must make documents and data work harder – not by…

  • Trust is a Sustainability Issue

    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. We often talk about AI as if it were a neutral tool that just happens to consume electricity. In reality,…

  • The Most Energy Efficient Machine Ever Created

    The real framing of the AI sustainability question is this: “Does AI reduce the total energy required to achieve meaningful outcomes?” To answer this question, we need to look at more than server racks, and take a systems perspective. The total energy cost must take into account human labour, organisational processes, and the physical world…

  • AI’s Real Footprint

    You can assess the impact of data centre construction in square footage, GPUs burning in megawatts (or more commonly now, gigawatts), and cooling systems in running costs. But there’s another kind of energy footprint, one that is far harder to measure, potentially far larger, and fundamentally dependent on the reliability issues discussed in earlier articles…

  • Lambs to the Slaughter

    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 interface, like others later on, said so right up front. And there was no shortage of social media posts illustrating…

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

    Successful people are dangerous. They treat their past triumph as evidence for always being right, when in fact it simply means they were lucky enough to get it right once. They may have just been lucky enough to be in the right place at the right time – and to get out before the limitations…

  • Building the Platforms We Once Dreamed Of

    Do you have an idea for a transformative digital platform, and suspect AI could help, but don’t know where to begin? Dedoctive AgenticFlow is designed for exactly that situation. You don’t need to be an AI expert, or have any AI knowledge at all. You just need to know what you want. The system does…