Category: Decision Intelligence
-
Technology readiness levels for machine learning systems
The development and deployment of machine learning systems can be executed easily with modern tools, but the process is typically rushed and means-to-an-end. Lack of diligence can lead to technical debt, scope creep and misaligned objectives, model misuse and failures, and expensive consequences. Engineering systems, on the other hand, follow well-defined processes and testing standards…
-
Statistics: Are you Bayesian or Frequentist?
Cats bring success – they are ket part of the internet traffic and enjoyment. So let me show a great pic: The real purpose of the cats-pics (delivered by a dog person) is the great video and article from Cassie Kozyrkov What is the difference between Bayesian and Frequentist statistics? (demonstrated with one single coin…
-
Cynefin – Sensemaking
Het Cynefin® framework werd als “sensemaking” door Dave Snowden ontwikkeld vanuit een natuur-wetenschappelijke insteek, met als een doel projecten te laten evolueren vanuit de bestaande toestand, en de mogelijke evoluties in te schatten, in plaats van een vooraf gedefinieerd einddoel te fixeren. Cynefin® is in wezen een beslissingsondersteunend kader (framework), geen methode of model.Het is…
-
Beslissen: FEP, AI, Bayes
“We sample the world to ensure our predictions become a self-fulfilling prophecy.” Karl Friston De beslissingswetenschappen en neurowetenschappen werden recent verrijkt door het principe van vrije energie (Free Energy Principle / FEP) van Karl Friston. FEP is misschien wel het meest allesomvattende idee sinds de theorie van natuurlijke selectie van Charles Darwin. Samenvattend is het…
-
Rethinking Computational Approaches to the Mind
Rethinking Computational Approaches to the Mind Fundamental Challenges and Future Perspectives One-day Online Symposium21st October 2022 REGISTER HERE This one-day online event will bring together researchers with expertise in various areas such as complexity science, machine learning & artificial intelligence, information theory & data science, as well as computational/theoretical neuroscience & philosophy to explore different computational approaches…
-
Begin with the decision-maker
I enjoyed the article “The first step in AI might surprise you” on AI, ML, Data Science from Cassie so much, I decided to steal some quotes: Leaders, figure out who’s calling the shots. If it’s you, then let’s designate you “The Decision-Maker“ for this project. Otherwise, delegate the position to someone else and ask them to read the…
