Activities of Amsterdam AI
Amsterdam AI, technology for people will champion the development of responsible AI in 3 key areas: business, health and citizen support. Some of the projects include financial fraud detection, providing better care and outcomes for patients, and combating inequality.
General AI activities
- Who is involved: Elsevier, University of Amsterdam and Vrije Universiteit Amsterdam
- Goal: Driving scientific discovery using machine intelligence. The researchers study and develop technology, infrastructure and methods to support the current transformation of science. They focus on data-driven activity, where scientists increasingly rely on intelligent tooling for searching and reading scientific literature, to formulate hypotheses, and to interpret data.
- Who is involved: University of Amsterdam, VU Amsterdam, CWI, Utrecht University, Radboud University, Eindhoven University of Technology, university medical centres in Amsterdam, Utrecht and Nijmegen and the National Research Institute for Mathematics and Computer Sciences, supported by fund manager LUMO Labs
- Goal: TTT.AI will apply knowledge from pioneering AI research and fund startups to accelerate bringing innovations to market and society. In the future, the consortium will be a one-stop shop for AI startups rooted in knowledge institutions.
- Who is involved: A consortium of the Faculties of Science and Humanities at the University of Amsterdam
- Goal: The Language Technology for People (LT4P) consortium combines fundamental and applied research to develop human-centric, responsible language technologies (methods and applications), that foster a more inclusive and safer society.
AI for business innovation
- Who is involved: Amsterdam University of Applied Sciences (AUAS): Finance Lab, Legal Tech Lab, Responsible AI lab, Smart Asset Management Lab and Centre for Market Insights
- Goal: The Centre of Expertise Applied AI drives the development of applications of AI technology in a responsible and inclusive manner. AI technology and its implications can only be understood in context and through experimentation. Each faculty of the AUAS has created a lab that brings research, education and practices together to solve challenges in the application of AI.
- Who is involved: TomTom and University of Amsterdam
- Goal: Atlas Lab will focus on using AI for developing advanced, highly accurate and safe high definition (HD) maps for self-driving vehicles. PhD students will work in the Atlas Lab on projects contributing to automated recognition of items like traffic signs, 3D-localization of vehicles and combining LIDAR (light detection and ranging) laser and camera images. For retrieving data, mobile mapping vans equipped with sensors, like LIDAR-systems and cameras, are being used.
- Who is involved: Ahold Delhaize and University of Amsterdam
- Goal: AIRLab conducts research into socially responsible algorithms that can be used to make recommendations to consumers and into transparent AI technology for managing goods flows. The research takes place at Albert Heijn and bol.com, both brands of Ahold Delhaize. In addition, AIRLab Amsterdam focuses on talent development tracks.
AI for health
- Who is involved: Amsterdam Economic Board, Amsterdam UMC, Antoni van Leeuwenhoek/Netherlands Cancer Institute (NKI), City of Amsterdam, OLVG, Philips, Vrije Universiteit Amsterdam, University of Amsterdam
- Goal: Even though we collect medical data daily and we have enough computing power, we currently don't process and analyse that data because the majority of it is still not readily accessible. To change this, we need an integrated health data infrastructure at a national level. This infrastructure will allow for faster and better medical research, and it willl help us use AI solutions to improve patient care, public health and disease prevention.
- Who is involved: University of Amsterdam and Antoni van Leeuwenhoek/Netherlands Cancer Institute (NKI)
- Goal: Developing new AI algorithms to treat cancer more effectively. Prior to and during treatment, a lot of complex patient information becomes available through medical imaging, pathology, DNA, et cetera. It is a challenge for medical specialists to choose and carry out the best treatment based on the wide range of information. The use of self-learning algorithms can offer a solution.
- Who is involved: Amsterdam University of Applied Sciences (AUAS) - Smart Health/Care Lab
- Goal: The Centre of Expertise Applied AI drives the development of applications of AI technology in a responsible and inclusive manner. AI technology and its implications for companies, organisations, governments and people can only be understood in context and through experimentation. The Smart Health/Care Lab is part of the Faculties of Health & Sports and Nutrition and brings research, education and practices together to solve challenges in the application of AI.
AI for citizens
- Who is involved: University of Amsterdam, Amsterdam University of Applied Sciences (AUAS) and CWI (national research institute for mathematics and computer science)
- Goal: The AI Media & Democracy Lab focuses on how AI and digital technology are transforming media and democracy, such as ways to develop more human-centred and diverse systems and the possible role of chatbots in news provision. They will think about what tomorrow's media should look like and combine this with cutting-edge research at the interface between social sciences, law, humanities and computer science.
- Who is involved: City of Amsterdam, Vrije Universiteit Amsterdam, University of Amsterdam, Ministry of the Interior and Kingdom Relations
- Goal: In the Civic AI Lab, PhD students will conduct research on AI issues in the areas of education, welfare, the environment, mobility and health. They will examine examples of friction so AI can be used to promote equality and provide fair opportunities. The lab will develop AI technology that highlights the inequality of opportunity in society, and actively increasing its prospects. The lab should make residents aware of both the opportunities and risks of AI.
- Who is involved: CWI, University of Amsterdam, KNAW Humanities Cluster, KB (national library), Nederlands Instituut voor Beeld en Geluid, Rijksmuseum, TNO and Vrije Universiteit Amsterdam
- Goal: Cultural AI builds a bridge between cultural heritage institutions, the humanities and computer science. Data and information from heritage institutions and technical knowledge from research institutions form the basis for developing AI tools that do justice to the complexity of human culture and that can be applied within the cultural heritage sector in the Netherlands. The aim is to make AI technology more aware of cultural contexts, and to connect cultural institutions to AI research in the Netherlands.