DataLit research consortium is headed by Professor Petri Ylikoski of the University of Helsinki.
”The development of machine learning and other AI methods have created new opportunities to utilise data, both in private and public sectors. This makes data governance a challenge for both individuals and organisations”, says Ylikoski.
Good data governance requires both understanding what data is and a grasp of the complex socio-legal-technical issues related to it. Ylikoski defines data literacy as an understanding of how data is generated, processed, analysed, and presented.
“It provides a basis for understanding both the limitations and opportunities of data. Improved data literacy means better decision-making, more realistic expectations about the possibilities of data analytics, and sharper critical discourse on future dangers,” says Ylikoski.
Assistant Professor Pekka Marttinen is part of the new DataLit research consortium headed by Professor Ylikoski.
“My task is to develop machine learning methods and models for health and social services data. With the help of these methods and models it is possible to examine societal questions related to health care”, Marttinen says.
DataLit also produces tools for the responsible and reliable use of register data, for example forecast models to support decision-making, and methods for anonymising data.
“It is especially important to take good care of data. This means data security, consideration of ethical questions, the implementation of data analysis in a protected environment – in general, the secure use of data. The use must be transparent and acceptable”, Marttinen says.
The project will produce novel tools and solutions for data analysis and governance, anonymisation, and interactive visualisation.
The work package led by Associate Professor Antti Honkela will develop concrete methods for creating anonymised synthetic data to enable easier use of personal data in various tasks. Such data will have similar statistical properties to the target data and can be used similarly for statistical analyses, but it cannot be linked to any individual data subject from the target data set.
Social science research will produce novel insights into development processes, data governance practices, and interpretation of laws relating to data use.
DataLit is closely related to FCAI agenda of advancing ethical and trustworthy AI. It brings together research programs Privacy-preserving and secure AI (R4) and AI in society (R7), as well as highlight programs Applications of AI in healthcare (HB) and Intelligent service assistant for people in Finland (HC).
The first phase of the DataLit project will take three years and its total budget is € 3.9 million. In addition to the University of Helsinki and Aalto University, the University of Eastern Finland and several other cooperative partners are involved in the project: The Finnish Institute for Health and Welfare (THL), The Social Insurance Institution (Kela), the Joint municipal authority for North Karelia social and health services (Siun sote), the Cancer Society of Finland, the Ministry of Finance, Statistics Finland, the Digital and Population Data services Agency, and the Helsinki Institute for Social Sciences and Humanities (HSSH).
Read more about DataLit.