Responsible Artificial Intelligence: A Need for Healthcare Applications Passed
Wednesday May 24, 2023 15:45 - 17:15 G1
Lecturers: Carlos Luis Parra Calderón, Denis Newman-Griffis, Riccardo Bellazzi, Stephane Meystre
Track: MIE: Natural Language Processing
Remarkable progress in artificial intelligence (AI) algorithms performance, and the fast growth in “real world” data available in electronic form generate high hopes for healthcare quality, efficiency, and accessibility improvements. But this game changing progress also causes growing concerns about the effects of growing AI use and its unintended, unanticipated, or even intentionally unethical consequences. Numerous issues and limitations of the algorithms and data used in healthcare and beyond have become more visible, and several organizations and researchers have proposed advice and guidelines to help address these concerns, issues, and limitations. Principles of Responsible AI are now promoted by several important organizations and stakeholders in the AI industry, but there is a need to move these principles towards practical realization and application in real-world scenarios. This panel will address several key aspects of responsible AI in health: explainability and interpretability; bias and fairness; reliability, reusability, and efficiency; privacy and confidentiality protection.
Language
English
Seminar type
On site only
Objective of lecture
Inspiration
Level of knowledge
Advanced
Target audience
Management/decision makers
Politicians
Organizational development
Technicians/IT/Developers
Researchers
Students
Keyword
Actual examples (good/bad)
Benefits/effects
Innovation/research
Test/validation
Information security
Ethics
Conference
MIE
Authors
Stéphane Meystre, Carlos Luis Parra-Calderón, Denis Newman-Griffis, Riccardo Bellazzi
Lecturers
Carlos Luis Parra Calderón Lecturer
Andalusian Health Service
Denis Newman-Griffis Lecturer
Lecturer in Data Science
University of Sheffield
Denis Newman-Griffis (they/them) is a Lecturer in Data Science in the University of Sheffield Information School and a member of the UK Young Academy. Their work investigates the principles, processes, and practices that inform the development of data science and artificial intelligence (AI) technologies, and how transdisciplinary design thinking can help reduce and manage bias in AI systems.
They bring their work into practice at the intersection of disability and data science, and have developed AI systems for analysing information on disability experience as well as critical tools to understand how AI materialises disability. They aim to bring together diverse voices to drive disability-led design of AI and data systems and develop more inclusive, person-centred ways of working with disability data. Denis was recognized with the American Medical Informatics Association’s Doctoral Dissertation Award and is an active advocate for LGBTQIA+ support and inclusion in STEM.
Riccardo Bellazzi Lecturer
Full Professor
University of Pavia
Full Professor of Biomedical Engineering, Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Italy
Director of Biomedical Informatics Labs, IRCCS ISC Maugeri, Pavia
Stephane Meystre Lecturer
Scientific Director for Data Science and AI
OnePlanet & imec
Dr. Stephane Meystre is scientific director at the OnePlanet Research Center, guiding data science, AI, and data platform efforts in precision health, nutrition and behavior as well as precision agriculture, food and environment. He has a medical and biomedical informatics background, with extensive academic research and technology transfer experience in AI applications in healthcare to enable reuse of clinical data, from natural language processing applications for clinical information extraction and text de-identification, to clinical trial eligibility surveillance and predictive analytics applied to COVID-19 as examples. He has been elected fellow of the American College of Medical Informatics (FACMI), fellow of the International Academy of Health Sciences Informatics (IAHSI) and fellow of the American Medical Informatics Association (FAMIA).