REASONING ON DATA & ALGORITHMIC BIAS
Explaining the network effect in opinion dynamics and the training data bias in machine learning.
Abstract: Data science is creating novel means to study the complexity of our societies and to measure, understand and predict social phenomena. My seminar gives an overview of recent research at the Knowledge Discovery (KDD) Lab in Pisa within the SoBigData.eu research infrastructure, targeted at explaining the effects of data and algorithmic bias in different domains, using both data-driven and model-driven arguments.
First, I introduce a model showing how algorithmic bias instilled in an opinion diffusion process artificially yields increased polarisation, fragmentation and instability in a population. Second, I focus on the urgent open challenge of how to construct meaningful explanations of opaque AI/ML black-box decision systems, introducing the local-to-global framework for the explanation of ML classifiers.
The two cases show how the combination of data-driven and model-driven interdisciplinary research has a huge potential to shed new light on complex phenomena like discrimination and polarisation, as well as to explain how decision making black-boxes, both human and artificial, actually work.
I conclude with an account of the open data science paradigm pursued in SoBigData.eu Research Infrastructure and its importance for interdisciplinary data driven science that impacts societal challenges.
Fosca Giannotti is Director of Research at the Information Science and Technology Institute “A. Faedo” of the National Research Council, Pisa, Italy. Fosca Giannotti is a scientist in Data mining and Machine Learning and Big Data Analytics. Fosca leads the Pisa KDD Lab - Knowledge Discovery and Data Mining Laboratory http://kdd.isti.cnr.it, a joint research initiative of the University of Pisa and ISTI-CNR, founded in 1994 as one of the earliest research lab centered on data mining. Fosca's research focus is on social mining from big data: human dynamics, social networks, diffusion of innovation, privacy enhancing technology and explainable AI. She has coordinated tens of research projects and industrial collaborations. Fosca is now the coordinator of SoBigData, the European research infrastructure on Big Data Analytics and Social Mining, an ecosystem of ten cutting edge European research centres providing an open platform for interdisciplinary data science and data-driven innovation http://www.sobigdata.eu . In 2012-2015 Fosca has been general chair of Steering board of ECML-PKDD (European conference on Machine Learning) and is currently member of the steering committee EuADS (European Association on Data Science) and on the Italian Lab. of Artificial Intelligence and Autonomous Systems.
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