Data Literacy &
Data Science Skills
Parallel Session 3.3
From Big Data to AI and Beyond
- Welcome & Introduction - Edward Curry (LERO)
- Panel Discussion - Interacting Q & A with Panel and Audience
Q1: Are we seeing the death of the data scientists?
Q2: How well is society prepared for the AI Innovation?
- Recap & Closing Statements - Viktoria Pammer-Schindler (Know-Center)
The rise of Big Data has caused a huge demand of data analysts, data scientists, data engineers and data-savvy business executives. As the AI wave becomes transformational across end-markets from enterprise to consumer platforms, from cybersecurity to robotics, the demand for data scientists is growing exponentially. Universities across the world are rising to meet this demand with new degrees and courses. However, the unprecedented demand for data science talent is creating a considerable gap between the demand and supply of data scientists. A recent article in the New York Times estimated that only 10,000 people worldwide have the skills necessary to tackle serious AI research.
What does this mean for our society?
What do individuals need to know about data analytics and AI?
This Interactive Debate Session will explore these questions by bringing together a rich set of panellists from multi-disciplines to offer a different perspective from the academic and university community, Industry, and Public Organisations. n order to foster the participation of the audience in the session, we propose an “Interactive Debate” session. After a brief introduction (5 min.) from the moderator, the following two discussion questions will be debated for 40 minutes each:
1. In the context of AI, are we seeing the death of the data scientists?
2. User, SME, Entrepreneur: Is European society prepared for AI-driven Innovation?
At the start of the question, we will use an “Interactive Poll” to gauge the level of support for the positions. Two selected panellists will present their different perspectives on these questions followed by a Q&A discussion with audience questions. At the end of the question, we will again poll the audience to gauge the reaction to the discussion. This format provides an active method, engaging the audience, and because the process is somewhat anonymous, even the most reluctant attendants will be motivated to participate.
At the end of the session, the moderator will provide some concluding remarks to engage the community in the skills activity of the BDV PPP.
The objective of this session is to discuss the evolving nature of Data Science skills needed to deal with Big Data and AI technology. The session will enable a diverse group of cross-disciplinary big data and AI stakeholders to a network to discuss challenges and opportunities for Europe in Data Science Skills. The outcome of the session will support the BDV PPP and the larger audience by gaining further information from stakeholders about the challenges for data science and AI skills. As a result of the three interactive debate questions, we will have an overview of the evolution, future role and skills required by data scientists, organisations and the wider society. We will have insight on the lessons learnt from the broader introduction of computer science skills into society. We will explore the skills challenges associated with AI-driven innovation. Answers to these questions are vital to understanding research and policy needs, good practice recommendations and possible future actions with the Digital Skills and Jobs Coalition. Finally, the session will conclude by inviting participants to join the BDV PPP in its actions to move the Data and AI skills agenda forward and support the Digital Skills and Jobs Coalition.
Edward Curry is currently a research leader at the Insight Centre for Data Analytics and at LERO The Irish Software Research Centre. His research interests are predominantly in open distributed systems, particularly in the areas of incremental data management, approximation, and unstructured event processing, with a special interest in applications for smart environments and data ecosystems. His research work is currently focused on engineering adaptive systems that are a foundation of smart and ubiquitous computing environments. He is a Vice President of the Big Data Value Association—a non-profit industry-led organization with the objective of increasing the competitiveness of European Companies with data-driven innovation. He is a Lecturer in Informatics at the National University of Ireland Galway.
Research Area Manager at the Know-Center
Viktoria Pammer-Schindler is assistant professor at the Graz University of Technology, research area manager at the Know-Center, and member of the managing committee of the European Association for Technology-Enhanced Learning. Viktoria researches designing for lifelong and workplace learning, and other knowledge creating activities. The latter includes, as one instance, the identification and elaboration of data- and artificial intelligence-enabled business models. Viktoria holds a PhD in computer science and a diploma degree in computer science and electrical engineering from the Graz University of Technology, both with distinction.
Gert Breitfuss is a senior researcher at Know-Center (Research Center for data-driven business and big data analytics). His research field is (open) innovation management with special focus on (data-driven) business model innovation. Gert has a technical background and received a master degree in business administration from Karl-Franzens University Graz.
Prof. Sylvia Ilieva is a Full Professor of software engineering at the Faculty of Mathematics and Informatics, Sofia University and part time at Bulgarian Academy of Sciences. She was head of department Software Engineering for almost 10 years. She is head of MSc program ‘Software Engineering’ and founder of BSc program “Software Engineering” in compliance with ACM/IEEE recommendations. Her research Interests are in the areas of software as a service, software platforms, software development processes, and software engineering for complex systems. She is member of Scientific Expert Council of "Sofia Tech Park" JSC, Bulgarian national representative in IFIP TC2. Prof. Ilieva has good record of successful participation in number of EC RTD projects and national projects.
Gerhard Schagerl received his MSc in 2003 in computer science at the Johannes Kepler University Linz, Austria. Gerhard is employed at AVL List GmbH since 2000. In the majority of this time he was in a team leading role for AVL’s motorsport business. Beside other duties in this position he was responsible for the development of a vehicle lap time simulation tool and its implementation into cloud computing environment. From 2018 Gerhard joined AVL’s Big Data efforts in the role as Product Manager for Big Data services. In this position he defines Big Data strategy and product portfolios, but also develops new data-driven business models.
Gerhard’s experience in computer science and deep knowledge of the automotive industry as well as big data applications will provide valuable input the MADEin4 program.