January 21 (Tuesday), 2020
Tiedekulma - Think Corner (Yliopistonkatu 4)
How can data science methods be used in planning better social and health services? What kind of data do social media provide nowadays and how can we make use of it? What kind of new services could we create with the help of data science? How can data science support evidence-based decision-making for the government, organizations and private companies? What kind of ethical challenges machine learning and artificial intelligence developers are facing and how are they being handled?
You will find the materials under the links of each talk.
9:00 Programme starts
Opening words and Introduction of HiDATA
Director Sasu Tarkoma
Director Krista Lagus
Työelämätieto: how data science and open knowledge support decision-making
Riku Louhimo, TTL, Finnish Institute of Occupational Health
Data science in Kela: cases and challenges
Aaro Viertiö, Kela, the Social Insurance Institution of Finland
Data, Decision making and Public Services. Introducing the panelists
moderator Deputy Mayor of Helsinki City Pia Pakarinen
Hearing the voice of people using data science, Krista Lagus Professor of Digital Social Science and Director of CSDS, University of Helsinki
Testing AI and ethical issues, Jukka K. Nurminen Professor, HiDATA, Software Systems for Data-Intensive Computing, University of Helsinki
Engaging Everyone with Open Data Science, Kimmo Vehkalahti Senior Lecturer of Applied Statistics, CSDS, University of Helsinki
The challenge of understandability, Petri Ylikoski, Professor, Science and Technology Studies, University of Helsinki. Coordinating professor, Finnish Center for Artificial Intelligence, FCAI
Panel discussion: Better data, better society?
11:00 End of programme, time to mingle
Pia Pakarinen is graduated as a Master of Laws and a Master of Political Sciences at University of Helsinki and as a Master of Science (Economics) at Helsinki School of Economics and Business Administration. Pia Pakarinen joined the Court of Justice of the European Union in the early years of the membership of Finland in the EU as a lawyer-linguist and lawyer-revisor. She is a former marketing and sales professional, entrepreneur, CEO of Helsinki Entrepreneurs and director of Helsinki Region Chamber of Commerce. Pia Pakarinen has been Deputy Mayor for Education Division in City of Helsinki since June, 2017
Sasu Tarkoma is Professor of Computer Science at the University of Helsinki and Head of the Department of Computer Science. He is also Director of the Helsinki Center for Data Science and affiliated with the Helsinki Institute for Information Technology HIIT and the Finnish Center for AI (FCAI). He is chairman of the Finnish Scientific Advisory Board for Defence (MATINE). He has authored 4 textbooks and has published over 200 scientific articles. He has seven granted US Patents. His research has received a number of Best Paper awards and mentions, for example at IEEE PerCom, ACM CCR, and ACM OSR. As an example flagship research project, he is leading the MegaSense project, which aims at deploying a wide array of low-cost urban air-monitoring stations and employing the data in prediction models.
Krista Lagus is Professor of Digital Social Science at the University of Helsinki and co-founder and Director of the Centre for Social Data Science (CSDS), located at the Faculty of Social Sciences. She has published over 70 scientific articles related to data science, in particular data exploration and visualization, text mining, modeling language and cognition, and the study of social and societal phenomena, emotions and wellbeing from large data. Previously she led the VirtualCoach research consortium, and was centrally involved in the Citizen Mindscapes research collaborative concerning the study of a discussion forum with 80 million comments in Finnish. Together with others she has co-developed several data exploration tools, namely Websom, Morfessor and Medicine Radar (Lääketutka). Her current research interests include how can societies better hear and thus empower the individuals that comprise the society. Her passion is how can we together facilitate the development of a good society for all.
Riku Louhimo is Product Manager at the Finnish Institute of Occupational Health (FIOH). He is managing the Work-life Knowledge open data service, which aims at disseminating reliable, open information on the intersection of work and well-being. He has an MSc in Bioinformatics and a PhD in Oncology (Bioinformatics) from the University of Helsinki. Currently his interested in developing data science and analytics at FIOH and improving work-life via data-driven solutions.
Aaro Viertiö is Product Owner of Data Science at Kela, the Social Insurance Institution of Finland. He is responsible for the Data Science service in Kela's Information Services, leading an agile team of data scientists serving the whole institution. With a background in economics, he has worked in data science in both private and public sectors. His current interests include proactive social security, shfiting data science from trials and talk to actual applications in large organizations, and finding ways to support daily decision making of professionals from customer service agents to directors.
Jukka K. Nurminen started as professor of computer science at the University of Helsinki in spring 2019. He has worked extensively on software research in industry at Nokia Research Center, in academia at Aalto University, and in applied research at VTT. His key research contributions are on energy-efficient software as well as mobile peer-to-peer and cloud solutions but his experience ranges widely from applied optimization to AI, from network planning tools to mobile apps, and from software project management to tens of patented inventions. He received his MSc degree in 1986 and PhD degree in 2003 from Helsinki University of Technology (now Aalto University). Currently his main interests are tools and techniques for developing data-intensive software systems including testing of AI solutions, computational moral, and software development for quantum computers.
Kimmo Vehkalahti is fellow of the Teachers’ Academy at the University of Helsinki. He has been a part of the faculty of Social Sciences for over 25 years, currently as senior lecturer of applied statistics in the Centre for Social Data Science (CSDS). He is author of a popular Finnish textbook on measurement and survey methods, cited in over 2000 publications. He has recently authored an international textbook on Multivariate Analysis for the Behavioral Sciences. His research and teaching activities are related to open data science, multivariate analysis, and introductory statistics.
Petri Ylikoski is Professor of Science and Technology Studies at the University of Helsinki and the Vice-Dean (Research) of the Faculty of Social Sciences. He is also coordinating professor for the Finnish Center for AI (FCAI) research programme AI in Society. Petri started his career as a philosopher, but now considers himself as a social scientist. His research interests include theories of explanation and evidence, science studies, and social theory. His current research focuses on the foundations of mechanism-based social science, institutional epistemology, and the social consequences of artificial intelligence.
Helsinki Centre for Data Science (HiDATA) is a world-class hub of Data Science in Helsinki. Data Science is an interdisciplinary field focusing on methodologies for extracting knowledge and insights from data thus contributing to different areas of science. The centre builds on the pioneering scientific results of the community and paves way for new breakthrough results across disciplines. The overarching goal of HiDATA is to leverage the synergies of the network in solving significant societal and industrial challenges related to data analysis. HiDATA is a joint hub of the two participating universities University of Helsinki and Aalto University.
The aim of Centre for Social Data Science (CSDS) is to advance methodologically oriented, applied and theoretical research and teaching in the social sciences. CSDS promotes open data and open science as well as the development of infrastructures for data. In addition, CSDS aims at increasing the collaboration between researchers and methodology experts, with the goal of improving both applied research as well as methods research. Operational responsibility of the CSDS is at the Faculty of Social Sciences.