Interpretability and explainability in machine learning.
Isel Grau will cover the interpretability and explainability terminology, state-of-the-art methods, measures, and open problems in the field.
Practical information:
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- Register until: 03 Mar 2022
- Prerequisites: master's degree
- Price: free
a Sense & Sensibility of AI seminar
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Georganiseerd door:
In recent years, AI and particularly machine learning have experienced a clear increase in interest from outside academia. The unprecedented performance of machine learning algorithms in solving complex tasks from a high volume of structured and unstructured data caught the attention of industry, governments, and society. The use of sub-symbolic ensembles or deep learning techniques led to this massive performance capacity in very specific tasks. However, the responsible use of machine learning has added another variable to this equation: the interpretability component. Multiple application domains exist in which predicting with high accuracy is not enough. For high-stakes decisions affecting humans, explaining why or how an intelligent algorithm made a decision or took action is also required.
“ I want to contribute to AI solutions that are accurate and useful, but also transparent and fair. ”
Teacher / speaker
Isel Grau Garcia
Isel Grau is an Assistant Professor in the Information Systems group at Eindhoven University of Technology (TU/e). Her research interests lie in the area of Artificial Intelligence, particularly recurrent neural networks, cognitive networks, (semi-)supervised classification, time-series analysis, data-driven decision making, and explainable AI. Her main research activity focuses on making machine learning black boxes more interpretable, formalizing prior knowledge from experts and using their feedback to improve AI models, identifying and correcting bias, and exploring these challenges in healthcare or business settings. She aims to develop more trustable and meaningful decision support systems that put human experts in the loop.
Academic background.
Isel Grau received her Ph.D. in Computer Science from the Vrije Universiteit Brussel (VUB), Belgium, and her MSc degree in Computer Science from the Central University of Las Villas, Cuba. Her Ph.D. research focused on machine learning interpretability and semi-supervised classification. During her postdoctoral research at the Artificial Intelligence Laboratory of the VUB, she closely collaborated with institutions such as the Interuniversity Institute of Bioinformatics Brussels, the Universitair Ziekenhuis Brussel, and industry partners (e.g., Collibra NV) on interdisciplinary projects funded by VUB and INNOVIRIS. She has active collaboration with researchers from Queen’s University Belfast, Hasselt University, Universidad de Talca, Warsaw University of Technology, and Tilburg University.
Sense & Sensibility of AI
AI has an increasing influence on our daily lives, examples include automated decision-making for high-stake decisions such as mortgages and loans, automated risk assessments for bail or recommenders on the internet. These AI systems carry the risk of creating filter bubbles and polarization. While AI is being rolled out into society, the discussion on how AI-based systems may align with and even affect our values, is pushed to the forefront. We gave the computer senses, but how can we give it sensibility? It requires a multi-disciplinary view, where both technical and non-technical perspectives have a prominent place.
In our lecture series ‘Sense & Sensibility of AI,’ we aim for Ph.D. Students to learn about the different aspects of Ethics in AI, not only to become aware of them but also to learn about the impact of AI on society and about methodologies to identify, assess, and possibly address ethical issues. The monthly seminars tackle subjects such as bias and fairness, privacy, trustworthiness, balancing technical, social, and regulatory perspectives.
The series is targeted towards doctoral students working in the broad field of AI and data science. To understand the lectures in full, it may be required to have a background in the technical aspects of AI/machine learning.
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Sense & Sensibility of AI is a seminar series developed by Flemish AI Academy in collaboration and with the support of all our partners, all universities in Flanders, and Knowledge Center Data & Society.
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