A data scientist’s look on the Norwegian Strategy for AI

January 26, 2022

This article refers to an event that took place before the Covid measures were enforced. Corona necessarily meant a general shift of focus to face the emergency.  Now more than ever there is the need of to make the effort to integrate a strategy for AI into exiting this challenging time. This article refers to where we were before the Corona escalation.

On March 4 I attended a presentation at the Norwegian academy of technical science (Norges Tekniske Vitenskapsakademi) on the national strategy for AI, organised in collaboration with Digital Norway. I am always a bit afraid when I join this kind of events, since the political and bureaucratical content of this events can easily be too high for someone like me that is more interested to the technical aspects of it.

I was pleasantly surprised to find food for my thoughts, and therefore I decided to write a small summary of my impressions. Before starting, I have to disclaim that I will focus on more data-sciency aspects of the matter, avoiding financial and political details, on which I am far less competent.

A concrete strategy


When talking about such a vast subject as a national strategy it is easy to make it all propaganda and nothing concrete. From what I grasped from the presentation this is not the attitude that this macro-project intends to promote. Concrete projects were presented by Sintef and Skanska, openly in opposition with the rather widespread attitude of wanting to use AI just because is AI. The right attitude is first to pinpoint a problem to solve and then apply machine learning and optimisation to solve it. Therefore, I was happy to hear examples of down to earth and useful projects like optimising the idle time of heavy machinery in construction sites or making the air traffic more efficient. Both projects that are ongoing now, are producing results, that will improve with time. No mention of magical solutions, no promises of a future as glorious as foggy. Instead plans on the short and middle term, as a base for a sustainable strategy.

Strategies like this are an optimisation problem per se: they need to balance profit, immediate usefulness and “grater good”. It is going to be a challenge to coordinate a project like this, but the starting point seems to be a good one. One last remark, that I was actually incredibly pleased was mentioned, is that part of the strategy’s intent is to increase competencies. It seems that for the moment the focus is not on using out-of-the-box tools, but on supporting and forming competent people. As I often say, even when using out of the box tools it is important to know what you are using and why that is going to bring value to you. Assessment capabilities of a tool don’t come out of a box, they come with knowledge.

I really hope that the political and financial aspects will follow the guidelines of this declaration of intents.


PhD in Theoretical Physics and AIMS Data Scientist. Home beer brewer and excellent Italian cook.

Alessandra Cagnazzo

PhD in Theoretical Physics and AIMS Data Scientist. Home beer brewer and excellent Italian cook.

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