Webinar: Artificial Intelligence Applications and Systems: Design principles for Explainable, Unbiased, and Reproducible AI by Elsevier

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Artificial Intelligence Applications and Systems: Design principles for Explainable, Unbiased, and Reproducible AI

About

Since 2016, we are experiencing a rapid technological evolution in applications and systems that utilize Machine Learning, as well as algorithms and tools from several other areas of Artificial Intelligence such as Natural Language Processing and Computer Vision. Key facets have played an important role in this growth of applications: 1) The re-birth of (deep) neural networks, 2) advances and accessibility in cloud computing services and environments, and 3) capabilities evolution of several well adopted programing languages. However, these aspects have also introduced some key challenges:

How can we explain and interpret the responses of complex AI systems?
How can we relieve AI systems and applications from all sorts of bias they can learn from the data, the engineering process, and the human-in-the-loop providing feedback in production?
How can we disseminate the documentation, data, and design details of an AI system in such a way that the solution is reproducible?

In this webinar, we will provide some design principles for addressing these challenges that are equally applicable in industrial and research systems, and give examples of standards and policies that are considered best practices in this space by the AI community.

Presenter

George Tsatsaronis

VP Data Science RCO, Elsevier

Dr. George Tsatsaronis is Vice President of Data Science at the Operations division of Elsevier, in Amsterdam, The Netherlands. Prior to joining Elsevier in 2016 he worked in academia for more than 10 years, doing research and teaching in the fields of machine learning, natural language processing and bioinformatics in universities in Greece, Norway and Germany. He has published more than 60 scientific articles in high impact peer review journals and conference proceedings in various areas of Artificial Intelligence, primarily natural language processing and text mining. In Elsevier, Dr. George Tsatsaronis is responsible for the design, implementation, deployment and quality assurance for several of Elsevier’s machine learning solutions and capabilities.

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