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Digital Literacy and Machine Learning

Understanding digital technology to support active, democratic citizenship

This project aims to develop specific, hands-on courses in digital technology targeting artificial intelligence and machine learning for Danish citizens aged 40-70 with a view to supporting active citizenship, creativity and empowerment in a digitalised contemporary reality.

Predictive technologies play a vital role in the development of the Danish welfare state ranging from screening for breast cancer and predictions of neglect in families to everyday technologies, helping consumers to make the right choices based on our individual preferences.

An understanding of technology is being integrated increasingly into the education system, all the way from primary and lower-secondary schools to colleges and university colleges; but a range of citizens do not have the necessary digital competences to understand and take an active part in the process of digitalisation which will dominate society in the years ahead. In collaboration with relevant partners, SHAPE will focus on increasing the amount of information provided for citizens about digital technology and (specifically) artificial intelligence and machine learning. This will be done in libraries and under the auspices of trade unions, with workshops focusing on constructive, critical and creative processes in which citizens gain hands-on understanding of the potential and consequences of technology.

SHAPE will develop a digital tool-kit called ml-machine.org, designed in particular for citizens with no previous experience of digital technology. In a co-design process with Dokk1 and trade unions, we will develop and test a citizens’ information process in which citizens are given the chance to construct their own artificial intelligence systems with a view to understanding the technologies that are currently being integrated throughout society. This process integrates four areas of competence: the technological ability to act, computational thinking, digital design and digital empowerment. But it focuses on digital empowerment.

Platform for machine learning for everyone
ml-machine.org is an online learning platform which uses machine learning to train a computer model to recognise various movements. Connecting a micro:bit to a computer enables ml-machine.org to use the built-in accelerometer to collect and train the model to recognise movement data. ml-machine.org can also be set up to react to recognition with various outputs, making it possible to create an interactive system. ml-machine.org is designed to enable users to quickly create a functional system and then explore more advanced details in the machine learning process, depending on what they are most interested in. The system uses a standard web browser, so it is easy to access and you only need a micro:bit to get started. The user’s data is also secure because it never leaves the user’s computer.


Peter Dalsgaard

Professor School of Communication and Culture - Department of Digital Design and Information Studies

Christian Dindler

Associate Professor School of Communication and Culture - Department of Digital Design and Information Studies

Ole Sejer Iversen

Professor School of Communication and Culture - Department of Digital Design and Information Studies


Magnus Høholt Kaspersen

Postdoc Department of Computer Science


Karl-Emil Kjær Bilstrup

Postdoc Department of Computer Science

Line Have Musaeus

Postdoc Department of Computer Science

Marianne Graves Petersen

Professor Department of Computer Science