Recent Posts
Social•Feb 20, 2026
AI Teaches Us About Bias, Complexity, and Knowledge Fragility
As AI learns from us, we must also learn from it, about bias, complexity, and the fragile nature of knowledge
By Iain Brown
Social•Feb 19, 2026
Embedding AI Requires Culture, Process, Not Just Pilots
From isolated experimentation to embedded capability, culture, process, and incentives as the true transformation levers In boardrooms across industries, the same slide appears with reassuring regularity: a grid of successful AI pilots. A fraud model that lifted detection rates. A marketing...
By Iain Brown
Social•Feb 18, 2026
Data’s Objectivity Is an Illusion; Human Choices Shape It
Data is objective only in appearance. Behind every dataset lies a human decision about what to measure
By Iain Brown
Social•Feb 13, 2026
Algorithms Reflect Our Worldview—Shape Them Responsibly
Every algorithm we build carries a piece of our worldview. Responsibility means shaping that view with care
By Iain Brown
Social•Feb 11, 2026
Human Creativity Thrives Beyond AI's Logical Limits
AI will never replace human creativity because creativity begins where logic ends
By Iain Brown
Social•Feb 6, 2026
Never Stop Questioning Models, Or They'll Mislead You
The moment we stop questioning our models is the moment they start misleading us
By Iain Brown
Social•Feb 5, 2026
Dashboards Aren’t Enough: Visibility Doesn’t Ensure AI Oversight
Why More AI Dashboards Don’t Mean Better Oversight -------------------------------------------------- A few years ago, when AI systems were still something of a novelty in most organisations, oversight felt tangible. Models were fewer, pipelines were simpler, and the distance between a data...
By Iain Brown
Social•Feb 4, 2026
Iteration Fuels Data Science: Insight Grows Through Error
Data science thrives on iteration because insight is rarely born perfect. It evolves through error and refinement
By Iain Brown
Social•Jan 30, 2026
Wisdom Needed to Recognize Model Limits
A model can approximate truth, but only wisdom can interpret its limits
By Iain Brown
Social•Jan 23, 2026
AI Demands Ethical Curiosity: Not Every Question Deserves an Answer
AI challenges us to balance curiosity with conscience, because not every question worth asking deserves an answer
By Iain Brown
Social•Jan 22, 2026
Satisficing Choices Compound Into Enterprise‑scale AI Risk
How satisficing models, degraded baselines, and compromises compound at scale There is a moment in almost every AI project when someone says the words “This is probably good enough.” It is rarely said carelessly. More often it arrives after months...
By Iain Brown
Social•Jan 16, 2026
Machine Learning Shows Knowledge Is Built, Not Discovered
Machine learning is a reminder that knowledge is built, not found. Each model is a version of understanding, never the final word
By Iain Brown
Social•Jan 14, 2026
AI Progress Measured by Impact, Not Just Accuracy
Progress in AI is not only measured by accuracy, but by awareness of its consequences
By Iain Brown
Social•Jan 13, 2026
UK Leaders Overconfident, Underinvested in AI Trust
AI confidence is high in the UK. AI impact… much less so. I’ve just published an article with The AI Journal exploring what we’re seeing across UK organisations: a growing trust gap between how much leaders say they trust AI...
By Iain Brown
Social•Jan 8, 2026
Synthetic Data Outperforms Reality, Raising Trust Challenges
When machines begin learning from machines, the risk is not rebellion, but distortion. The opportunity is designing AI systems that remain grounded, trustworthy and human-led. I still remember the first time I saw a synthetic data set outperform the real...
By Iain Brown