Rohan Light

This note adds a bit more nuance to the notion of AI depreciation/data appreciation, the interdependence between models and data contexts and the management requirements to realise the appreciating value of data. AI as a depreciating asset Base AI models look like they're depreciating rapidly: inference costs

AI is currently in a partial Solow phase: there is good micro‑level evidence of productivity gains and user benefits, but these are only beginning to show up in aggregate productivity statistics and will likely do so with a multi‑year lag. Why the paradox reappears with AI Generative AI

The transition of the global economy from an industrial paradigm rooted in physical capital to a digital era defined by intangible assets represents a structural shift of unprecedented magnitude. Within this transformation, data has emerged as more than a byproduct of activity: it is a primary factor of production, altering

I had my eyes opened to the possibility of leveraging organisational behaviour as an observational study by a behavioural scientist who used to train police hostage negotiators. We talked about why the evidence obtained from randomised controlled trials was a gold standard, which was interesting to me because my job

I think it's both useful and important to distinguish the information processes and outputs which have had artificial knowledge agent input. The usefulness of these probabilistic knowledge fetchers is based on how well they can help a human knowledge agent solve a problem, often brought to them by

I need a heuristic to be simple enough to do in my head, while doing other things like observing and engaging. Sounds trivial but isn't for a lot of people and it is great to see society being able to talk about thinks like autism and ADHD with