SoBigData researchers awarded ERC Advanced Grant

SoBigData researchers awarded ERC Advanced Grant

It is a pleasure to announce that 4 researchers of SoBigData, Marlon Dumas, Dirk Helbing, Aris Gionis and Fosca Giannotti have been awarded ERC Advanced Investigator Grant, an extremely competitive and particularly well funded Advanced Investigator Grants by the European Research Council.

Prof. Dirk Helbing, from ETH Zurich, has been granted for his work on how to use the wisdom of crowds to make cities smarter and, more specifically, how could networks of innovative cities contribute to the solution of humanity’s existential problems.

Given the on-going digital revolution and our present-day sustainability challenges, we have to reinvent the way cities are operated. We propose that the requirement of organizing societies in a more resilient way implies the need for more decentralized solutions, based on digitally assisted self-organization and that this concept is also compatible with sustainability requirements and stronger democratic participation.

Prof. Marlon Dumas, at the University of Tartu -Estonia-, intends to develop methods to discover opportunities for process improvement. Making business processes more efficient and agile is, in fact, of vital importance for modern organizations.

My project will develop methods to analyze data extracted from enterprise systems in order to automatically discover opportunities for improving the quality and efficiency of business processes. The methods to be developed in this project will combine machine learning and optimization techniques to ensure that all possible improvement opportunities are considered and that the optimal combination of improvement opportunities is selected.

Prof. Aristides Gionis, from the Computer Science Department of Aalto University, Finland, received the grant for studying how social media users shut themselves into closed off communities and explore the effectiveness of techniques designed to encourage users to be willing to engage with viewpoints which conflict with their own.
In fact, while online media is often promoted as a place which breaks information barriers and promotes diversity and democracy – in practice the opposite is often observed. Social media users tend to favour content that agrees with their existing world-view and gets less exposure to conflicting viewpoints.

Without any kind of intervention current social media platforms are gravitating towards a state in which net-citizens constantly reinforce their pre-existing opinions only.

Fosca Giannotti Research Director at National Research Council, Pisa, Italy and Project Coordinator of SoBigData, has been granted for her work on explaining and making human-understandable the decisions suggested by AI algorithms learned by data.

To understand why it is so important to make human-understandable the decisions suggested by AI, let's imagine that situation: a friend of mine asks for a vacation credit card to his bank, to discover that the credit he is offered is surprisingly low. The bank teller cannot explain why. My stubborn friend continues his quest for explanation up to the bank executives, to discover that it was an algorithm that automatically lowered his credit score. Why? After a long, ad-hoc investigation, it turns out that this was due to ... bad credit by the former owner of the house where my friend lives.

In the project XAI, Science and Technology for the eXplanation of AI decision making, Prof. Giannotti focuses on the urgent open challenge of how to construct meaningful explanations of opaque AI/ML systems, introducing a framework for theory and practice for black box explanation. Black box AI systems for automated decision making, often based on machine learning over (big) data, map a user's features into a class or a score without exposing the reasons why. This is problematic not only for lack of transparency but also for possible biases inherited by the algorithms from human prejudices and collection artefacts hidden in the training data, which may lead to unfair or wrong decisions.


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The ERC's mission is to encourage the highest quality research in Europe through competitive funding and to support investigator-driven frontier research across all fields, on the basis of scientific excellence.
ERC grants are awarded through open competition to projects headed by starting and established researchers, irrespective of their origins, who are working or moving to work in Europe. The sole criterion for selection is scientific excellence. The aim is to recognise the best ideas and confer status and visibility on the best brains in Europe, while also attracting talent from abroad.
The ERC approach allows researchers to identify new opportunities and directions in any field of research, rather than being led by priorities set by politicians. This ensures that funds are channelled into new and promising areas of research with a greater degree of flexibility.

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