AIOLIA: From AI ethics to practical application

When AI ethics meets the real world

AI systems are playing an increasingly important role in society, influencing how we make decisions, work and interact with technology. At the same time, it can be difficult to determine whether an AI system truly meets principles of transparency, fairness and human oversight. How can these principles be translated into concrete requirements, and how can we assess whether those requirements are being met?

AIOLIA addresses these questions by developing methods to identify, assess and manage ethical risks throughout the AI system lifecycle. The project brings together research on AI ethics, technical development and regulatory frameworks such as the EU AI Act. Its aim is to provide researchers, developers and organisations with practical support for developing and using AI responsibly.

RISE develops methods for assessing ethical readiness

A key challenge for organisations is understanding how far they have progressed in their efforts to develop responsible AI, and what still needs to be done.

Within AIOLIA, RISE has led the development of a framework that combines Ethics Readiness Levels (ERL) with Algorithmic Impact Assessment. The framework helps organisations systematically identify ethical risks, evaluate existing safeguards and prioritise improvements. It also enables them to track progress over time, from early design decisions through to fully developed AI systems.

The approach has already been adopted in other European research projects and within Sweden AI Factory. It has also attracted international interest, with discussions about potential applications in Japan, South Korea, China and Canada.

From research to industrial applications

AIOLIA brings together international research and industry partners to explore how AI ethics can be integrated into real-world development processes. Through 16 industrial use cases, the project examines the ethical challenges that arise in different applications and how they can be addressed through technical solutions and organisational practices.

The findings are used to develop technical guidelines and educational materials that help more organisations take a systematic approach to responsible AI.