Up-to-date information on innovation trends? A fitting task for AI
We want to gain a clearer picture of innovation trends in the Netherlands and the use of advanced technology could play a part in this. TNO, Statistics Netherlands (CBS) and Dutch data science company Innovatiespotter are currently studying the use of new AI techniques to identify innovation trends.
How many Dutch organisations are working on innovations such as synthetic biology and AI? What sector are they focusing on? For what problems are they working to develop a possible solution? How much employment and added value does this represent?
Governments need this kind of information in order to properly develop their innovation policy and it is important for this information to be as up to date as possible. Besides the economic value of technological innovations, they can also play an important role in meeting societal challenges. For governments, it is therefore important to be able to respond quickly to innovation trends.
Why the innovation monitor needs AI
The difficulty is that although a lot of data are available on innovation trends in the Netherlands, it is often unclear what these data actually contain. Sometimes the data are not sufficiently up to date. It is actually impossible for humans to collect all these data continuously and combine them in a logical way.
An AI system can do this faster and can monitor more developments, but only if the system knows where to look and how to provide information so that the policymaker can act on it. This requires knowledge of the technology and the domain. TNO, CBS and Innovatiespotter are studying how an AI model can better capture new innovations and how collaboration between the technology expert, the AI model and the user can be shaped.
As transparent as possible
Data from sources such as an innovation monitor could support policy decisions such as strategic investments in technologies or innovation hubs, or network activities around a specific innovation theme.
It is important here for the policymaker to be able to interpret the information properly and to know what it does and does not contain, which is why we are studying how to make an AI system transparent and explainable, in order to make decisions responsibly. And we are focusing especially on the impact of this system on the government’s decision-making process. This will allow us to use artificial intelligence in a truly responsible way for a more effective innovation policy.
Demonstration version in the making
A trial is currently running in the Dutch province of Zuid-Holland. In this trial, a demonstration version of the innovation monitor is focusing on two specific topics: AI and synthetic biology. This demonstration version will go live in mid-2021.
Christopher BrewsterFunctie:Senior scientist
Christopher Brewster is a Senior Scientist in the Data Science group and Professor of the Application of Emerging Tecnologies in the Institute of Data Science, Maastricht University. His research has focussed on the application of Semantic Technologies, Open and Linked Data, interoperability architectures and Data Governance, mostly to the food and agriculture domains.
Daniël WormFunctie:Senior consultant
Judith DijkFunctie:senior research scientist
Judith is specialised in extracting information from camera images. She now applies the subject of her PhD thesis in Physics, which she obtained 18 years ago, to her work as a research scientist at TNO, including in a research programme on camera systems for the Dutch Ministry of Defence.
Looking for another expert?View all experts
You can read about how AI is educated in Chapter 1. How can we make clear to AI which goals we want to pursue as humans? Andhow can we ensure intelligent systems will always function in service of society?
Innovation with AI
What does that world look like in concrete terms? Using numerous examples, TNO has created a prognosis for the future in Chapter 2. Regarding construction, for example, in which AI will be used to check the quality, safety, and energy efficiency of buildings before they are actually built. Or healthcare, where robots will partly take over caregivers’ tasks and AI will be able to autonomously develop medicines.
Innovating with innovation AI
How AI will change research itself is explained in Chapter 3. For example, what role will AI be permitted to play in knowledge sharing? And what will happen when we make machines work with insurmountably large data sets?
David Deutsch on the development and application of AI
Peter Werkhoven, chief scientific officer at TNO, joins physicist, Oxford professor, and pioneer in the field of quantum computing, David Deutsch, for a virtual discussion. Deutsch set out his vision in 1997 in the book, The Fabric of Reality. Together, they talk about the significance of quantum computing for the development and application of AI. Will AI ever be able to generate ‘explained knowledge’ or learn about ethics from humans?
Rob de Wijk on the rise of AI in geopolitical context
Anne Fleur van Veenstra, director of science at TNO’s SA&P unit, interviews Rob de Wijk, emeritus professor of international relations in Leiden and founder of The Hague Centre for Strategic Studies. Rob is also a much sought-after expert who appears on radio and television programmes. What does the rise of AI mean geopolitically and in armed conflicts?