“There is a pool of really good female experts but in many cases recruiting is through networks. We are not doing enough to reach out to these women.” Leid Zejnilovic, Professor Nova SBE, Nova School of Business and Economics, Portugal, and Chair of Data Science for Social Good Foundation
- While data science is yet to influence education to the same depth as it has other sectors, such as banking, significant amounts of venture capital are going into education technology in China and South East Asia. As Professor Euro Beinat, Global Head of Data Science and AI; Professor of Data Science at Prosus Group/Naspers and University of Salzburg, Austria, points out, data personalisation and interventions in education are predicated on data science and AI, and this linkage is going to grow in importance.
- According to Professor Jim Ridgway, director of the SMART Centre, at Durham University, much of what is taught in data science is irrelevant to the global challenges we face, such as inequality, refuges and pollution. As well as asking the sophisticated questions about what is measured and why, students need the skills to evaluate the data which underpins evidence-based claims.
Every summer, a group of leading specialists and aspiring young data scientists from around the world gather together and offer their time and expertise to work on data sets which show promise in solving the world’s social problems. From tackling fraud for the World Bank to predicting localized pollution levels on London’s streets, and from tracking illegal fishing activity to increasing the efficiency of heart function assessment.
These summer fellowships, which serve both to train the next generation of data experts and to solve genuine societal problems, are part of the Data Science for Social Good organization, itself just one of several not-for-profit organizations including Data Kind, GovLab, AI for Good and Data-dot-org, which apply data science in the search for solutions to humanity’s burgeoning challenges.
While prestigious HE institutions have been very much involved in such movements (Data Science for Social Good, for example, has involved collaboration between Carnegie Mellon, Imperial College, King’s College, Warwick University, The Alan Turing Institute and Nova University, to name just a few), such projects, however impactful, merely scratch the surface of the potential of data science to forge stronger, greener and fairer societies.
Our session invites three leading data experts from around the world to address the vital roles of Higher Education Institutions in forging the direction of tomorrow’s data science landscape, as well as the limitations which current HE political and organizational models place on fulfilling the promise of data science as a driver for better societies.
Among the key questions the session hopes to address are:
• Is Higher Education playing catch up in the data science revolution?
• What role will higher education online teaching platforms play?
• How sustainable is the data science landscape? Is there a looming talent crisis and if so, who will fill the gap?
• How do traditional HE organizational models and mindsets affect our ability to think across boundaries and to act swiftly to solve global issues?
• How can social issues drive what we teach and how?
• Are we convincing society with data? What are the implications for behavioural change.
The Session brings together 3 leading global players who work at the intersection between data science, higher education and society:
- Prof. Euro Beinat, Global Head of Data Science and AI; Professor of Data Science, Prosus Group/Naspers and University of Salzburg, Austria
He will address how HE institutions are meeting the challenge of developing the data scientists of the future. To what extent are they adapting their curricula and teaching to meet real-world demands and equip the scientists of the future with the right tools? Is this role of HE under threat from non-traditional players? Current state of AI in meeting business and social challenges, and the extent to which HE is equipped to meet those challenges, in a presentation entitled: Is the data revolution sustainable? The roles and responsibilities of Higher Education Institutions.
Professor Euro Beinat Professor Beinat is Global Head of Data Science and AI at Prosus Group and Naspers, the largest consumer internet company in Europe, he is also Professor of Data Science and Geoinformatics at the University of Salzburg and Co-founder of the Data Science for Social Good Foundation. He has spent his career working with global organizations, corporations and start-ups to develop businesses based on data science.
- Prof. Jim Ridgway, Emeritus Professor, School of Education, Director of the SMART Centre, Durham University, UK
His current research focuses on reasoning with evidence, data visualization, thinking and problem-solving, equity issues and educational change. His particular current interest is in public understanding of arguments involving data.
Professor Jim Ridgway will focus on his work rethinking the teaching of quantitative skills in HE, in a presentation entitled: Reimagining the quantitative sciences as tools for citizen empowerment. He will illustrate the use of global challenges as motivational tools in forging engagement with data science across the entire undergraduate curriculum, using data relevant to global warming, epidemics, and global corruption,while highlighting some data science big ideas that all citizens should become familiar with.
- Prof. Leid Zejnilovic, Chair, Data Science for Social Good Europe; Professor Nova SBE, Nova School of Business and Economics, Portugal
Co-founded the Data Science Knowledge Center and teaches on master, MBA, and executive programs. He also serves as Chair of Data Science for Social Good Foundation Europe, and a Consultant at Patient Innovation, a non-profit platform and social network. Each of our Speakers will address a core question relating to the role of Higher Education in forging better societies through data:
Professor Leid Zejnilovic will present his vision of the challenges and opportunities for HE in leveraging scientific excellence for the benefit of society, in a presentation entitled Project-based learning with a social impact: collaboration between data movements and academia. He will combine real-life examples of how social improvement can be achieved through data science with his insights into how HE institutions, government and society can better work together to maximize the social impact of the data they collect, with a particular focus on the need to rethink traditional academic structures and mindsets.
The session will conclude with a round table discussion and audience Q&A.