Most of Stuart McClure's AI writing addresses the security domain directly — where AI is being used to attack systems, where it is being used to defend them, and what organizations need to understand about both sides of that equation. "A.I. for Good" steps back from the immediate security context to ask a broader question: what does the positive-sum version of AI development look like, and how do we get there?
The essay reflects Stuart's conviction, developed across decades of working at the intersection of technology and organizations, that the most consequential applications of AI are not the ones that replace human capability but the ones that amplify it. Security is one domain where this plays out: a human analyst augmented by AI that surfaces the most relevant signals from a vast event stream is more capable than either the human alone or the AI system operating without human judgment on the hard edge cases.
The same logic applies more broadly. AI for good means AI that is designed to extend what humans can do — to give individuals and teams access to the kind of pattern recognition, synthesis, and prediction that were previously available only at institutional scale. The question Stuart returns to is whether the design choices being made in AI development are genuinely oriented toward that goal, or whether they are oriented toward replacement and concentration of capability in ways that ultimately reduce human agency.
Written during the period when Stuart was developing the Wethos AI platform for human performance, the essay reflects the same core conviction: technology built to understand and amplify human potential produces better outcomes than technology built to bypass it.