Students and researchers at Aalborg University Business School (AAUBS) explore approaches, methods, and techniques from data science and machine learning to generate data-driven insights to help the missions of UNESCO, OECD and other organisations.
Data science and machine learning skills are part of many business processes, from recommender systems embedded in smartphones and apps that most people use daily to machine learning algorithms automating processes in public sector administrations. According to Roman Jurowetzki, Associate Professor at Aalborg University Business School, these examples from business and industry can be and are used by students.
“We see the best learning outcomes when students get the chance to work with real data, even though that is much more challenging than working with pre-defined cases and curated datasets”, says Roman Jurowetzki, Associate Professor at AAUBS.
With his colleague Daniel Hain, Roman Jurowetzki has been running the Social Data Science specialisation semester at AAUBS since 2018. The semester has gained popularity among students ever since. Starting in September 2022, AAUBS launched a full master’s degree (MSc.) in Business Data Science to allow students to obtain an even more streamlined profile within the field.
“Our students have always been collaborating with companies and public sector actors, but since 2021 we have a stronger focus on building collaborations with organisations that work with societal and environmental and other global challenges”, says Roman Jurowetzki. He adds that the students are motivated by the feeling that the cases they work with are making a difference.
Contributing to UNESCO policies
Roman Jurowetzki and Daniel Hain are in charge of the AI:Growth Lab at AAUBS, which is a space dedicated to projects focusing on business value creation from data-driven applications such as data-driven decision-making, machine learning, and artificial intelligence (AI) systems. The lab bridges business understanding and AI technology expertise to support value creation through sustainable and ethical usage of machine learning and AI technologies.
The AI:Growth lab has been working with the Social Science and Humanities division of UNESCO on technology mapping within the field of Neurotechnology. Insights are used to inform high-level policy-making and regulation. This partnership also led to the development of project ideas with UNESCO’s Sports and Anti-Doping Section.
Students will deploy machine learning and natural language processing techniques to generate insights on the state of sports education worldwide, its impact on educational equality, and policy measures facilitating positive developments. This is closely linked to UNESCO’s Sport for Life programme and will involve several selected student groups and thesis students working on this project under the supervision of AI:Growth and UNESCO experts starting in fall 2022.
Commenting on the collaboration between UNESCO and AAUBS, Mariagrazia Squicciarini, Chief, Executive Office in the Social and Human Sciences Sector at UNESCO, states:
“Roman Jurowetzki and Daniel Hain have done an amazing job in relation to the UNESCO neurotechnology project. The AI techniques they devised and implemented in the project were very useful and relevant”.
Participation in OECD Policy Hackathon
In May 2022, AAUBS was represented with a student team at the OECD Policy Hackathon along with teams from elite institutions around the world, including the University of Tokyo, Korea Advanced Institute of Science and Technology, Georgia Tech (USA) and Fraunhofer Institute (Germany).
The AAUBS team was tasked with identifying policy goals and approaches that reflect a novel co-creation approach for research and innovation, as opposed to the traditional knowledge-transfer approach. “We are very proud seeing our students competing in hackathons and online competitions”, Roman Jurowetzki explains.
The students’ work directly informed the OECD Science Technology and Innovation division and participating EU policymakers to use modern data science techniques to monitor policy trends and assess the impact of policy initiatives. It also set the stage and spurred interest for future collaborative work on these topics.
Sirinant Khunakornbodintr from the AAUBS student team states:
“It was my first time working on text mining and tackling policy problems. The project was quite challenging but also exciting. We have learned a variety of possible data mining techniques from each other and other teams, as well as how to extract meaningful policy recommendations from the data. For those whose would like to have an experience working closely with the OECD policymakers, the OECD Hackathon is the place”.
Ensuring safe childbirth for women and newborns
Another developing collaboration is with the Maternity Foundation maternity.dk, which works to ensure safe childbirth for women and newborns around the globe. The foundation contacted AAUBS in spring 2022 and Roman Jurowetzki and his colleagues at AAUBS are currently looking into data extracts from the foundation’s Safe Delivery App, used by midwives and nurses in many countries in the Global South.
The Safe Delivery App can improve the skills, knowledge, and confidence of these health professionals, whether as part of pre-service education or on-the-job training. With over 230,000 downloads, it has a broad user base. The hope is that AAUBS Data Science students can help integrate machine learning and AI techniques to make the app even more efficient in delivering the right content to users.
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