Ensuring data quality in AI: Practical and ethical challenges | 12 February 2025
Overview
Join us for an insightful FREE webinar on Ensuring data quality in AI: Practical and ethical challenges.
The next in our series of AI-focused webinars will be taking place on 12 February 2025, starting at 09:30
The webinar will feature experts in data quality and related ethical challenges and focus on addressing common challenges associated with the use of AI in clinical research including data bias, missing data, and ethical concerns.
This is free to attend and delegates must REGISTER HERE in advance via Zoom
What will you learn?
- To gain knowledge of data quality and related ethical challenges presented by healthcare AI by understanding the meaning and importance of data quality in healthcare AI, recognising challenges including data bias, missing data, and ethical concerns that affect both AI system development and implementation in clinical settings
- To understand the impact of data quality on AI effectiveness and fairness in healthcare practice by learning how poor quality data can impact the accuracy, fairness, and generalisability of AI systems used in healthcare, to help identify potential limitations and ethical risks of AI tools.
Talks include:
- Dealing with missingness when analysing electronic health records: Patient-level observational analyses, Professor Evan Kontopantelis
- The ethics of data quality in healthcare AI: What is it, and why does it matter?, Dr Alex McKeown
- Data Bias in Healthcare AI: Strategies for detection and mitigation, Mr Cato Pauling
- AI in health care: What kind of consent is appropriate and what should patients know about data and decision quality?, Professor Soren Holm
Course convenor:
Professor Evan Kontopantelis
Professor of Data Science & Health Services Research, University of Manchester
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Dr Alex McKeown
Head of Data Ethics. Information Governance Services Limited
Alex is head of Data Ethics at IGS. A bioethicist and philosopher by training, Alex has specialisms including data and AI ethics. After completing his PhD at the University of Bristol, Alex spent a decade in academia, the final six at the University of Oxford, where he remains a Visiting Fellow. At Oxford Alex worked on data and AI projects for funders including the UK Medical Research Council, Novartis Pharmaceuticals and the EU Innovative Medicines Initiative. Alex co-chaired the Oxford Mental Health Data Ethics Leadership Group and was an invited tutor at the Yale University Summer Institute in Bioethics. He has published journal articles on a range of issues in data and AI ethics and is committed to providing high quality, rigorous advice to clients on all aspects of ethics in data and AI governance.
Mr Cato Pauling
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Professor of Bioethics, University of Manchester
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Dr Claudia Lindner
Senior Research Fellow, Sir Henry Dale Fellow, University of Manchester
Dr Claudia Lindner is a Senior Research Fellow and Sir Henry Dale Fellow in Translational Medical Imaging at The University of Manchester. Her career includes over 20 years of international experience in the development and application of computational methods, working within multi-disciplinary teams in both industrial and academic settings. She uses methods from computer vision, machine learning and data science to develop automatic systems for analysing structures in medical images, with a particular focus on musculoskeletal applications. Dr Lindner has published over 50 peer-reviewed papers, and is dedicated to impactful research, actively advancing her work towards real-world solutions. In her role as the Translation Lead for the Christabel Pankhurst Institute for Health Technology Research and Innovation, she directs her efforts towards enhancing the academic research culture to facilitate the translation of research findings into benefits for society. She has won several national and international awards including the Wellcome-Beit Prize for outstanding biomedical researchers in 2021.