Understanding Bias in AI
Artificial intelligence (AI) is increasingly used in healthcare. At the same time, research shows that AI systems are not neutral. Because they learn from historical data, they may reproduce existing discrimination, social inequalities, biased measurements, or the underrepresentation of certain groups. As a result, AI can influence how different patient groups are assessed and treated, potentially reinforcing unfair patterns. So what does this mean in practice, and what can organizations do about it?
In this webinar, we explore AI in healthcare from both technical and social science perspectives. We discuss how AI systems learn from historical data and how these data may contain patterns of discrimination and skewed representation.
We also present how technical methods are being developed to create more fairness-aware AI models. At the same time, we raise important questions about responsibility, power, and implementation: Who is accountable for ensuring that measures to address inequalities are actually carried out? And what practical barriers may arise?
No prior knowledge of AI is required. The webinar is open to anyone interested in learning more about the responsible use of AI.
Date: April 16
Time: 13:00–14:30
Location: Online (link sent after registration)
Language: Both Swedish and English
Who is this webinar for?
This webinar is designed for public sector organisations and companies interested in using AI responsibly and equitably.
Speakers
Mahmoud Rahat
Mahmoud Rahat is a Senior Lecturer in Machine Learning at Halmstad University. His research focuses on the application of AI across various domains, including predictive maintenance, cybersecurity, and healthcare.
Anna Isaksson
Anna Isaksson is an Associate Professor of Sociology at Halmstad University. Her research focuses on power relations, gender, and diversity across healthcare, working life, and higher education.
More Information
The webinar is organised within the framework of the EU project Health Data Sweden, a national ecosystem bringing together leading actors from across Sweden to support small and medium-sized enterprises and the public sector in digitalising health data. By offering tailored services, HDS facilitates innovation and development with a high level of digital maturity – both in Sweden and across Europe.
Its strength lies in a broad national network of regions, universities, innovation hubs and science parks, all of which play a key role in advancing Swedish and European life sciences.
European Digital Innovation Hub
Health Data Sweden is a European Digital Innovation Hub (EDIH), which can be described as the EU’s extended arm for driving digitalisation at the local and regional level in each country. The aim is to accelerate digital transformation in both industry and the public sector across Europe.
