It is now commonly accepted that the likelihood of AI causing human extinction is significantly greater than zero. While technologists scramble to mitigate this threat by improving AI itself (which, some might argue, brings us ever closer to the brink), the world appears to have lost sight of how we could apply well-proven systems engineering…

The Internet of Communities could create trusted online identities based on visible commitments, community contribution, and verifiable social value.

Putting a human in the loop does not automatically make AI safe. It may even make it more dangerous. To address the cognitive, practical and governance challenges, you need more than technology – you need a socio-technical process. Dedoctive enables you to create, quickly and easily, AI-enabled systems that do more than drop a human…

AI for disaster logistics and supply chain risk reduction.

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.

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.

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…

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…

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 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…