Knowledge
Practical pieces on responsible AI use, written for business owners and organisations without a technical background. Further down you will also find my research and the reading list that goes with my manifesto.
Google BERT has understood language since 2019; ChatGPT and Claude write text of their own. On what they share, and when a small model is the better choice.
Machine learning predicts, generative AI creates. Knowing the difference tells you which questions to ask of an AI tool.
When an AI project disappoints, the model gets the blame. Usually the problem is everything around it: the data, the fit with your systems, and who’s watching.
Between AI principles and practice lies a gap. The maturity model from Erasmus University shows you where you stand, across six dimensions.
Every technology carries its makers’ intentions in it. On humane technology, human-seeming AI, and the manifesto I hold my work to.
The AI Act sounds like something for the lawyers at big tech companies. It touches you too, though in practice it turns out to be manageable once you know what to look for.
Most data leaks through AI come not from hackers but from well-meaning prompts. Three rules of thumb you can apply today.
My master’s thesis at the University of Amsterdam: research into bias in algorithms that detect hate speech on Twitter.
The technical heart of my thesis, from labelling by hand to a trained classification model, step by step in the notebook.
The reading list that goes with my AI manifesto: books on technology, ethics and people that I recommend to anyone.