FAIR-AI

In addition to positive effects, the application of AI also has numerous implications for Europe's citizens and its economy. This FFG flagship project addresses the research gap that still exists in Austria with regard to the application of the European AI Act. The aim is to make it easier for small and medium-sized enterprises to implement the AI Act and to minimize risks.

FAIR-AI is a major flagship project in the field of artificial intelligence. It aims to simplify the research and development of AI systems in Austria in order to support the Austrian research landscape and economic application development. This is to be achieved through various measures:

• Development of solutions in the areas of sustainability, circular economy and climate neutrality
• Minimizing risks in AI development through new tools developed as part of the project and specially tailored educational opportunities
• Supporting the Austrian innovation system in the field of AI
• Optimizing R&D processes
• Networking stakeholders with the aim of increasing the competitiveness of the Austrian AI landscape and pooling research activities and results

There are many challenges, for example in the implementation of machine learning: the need for highly qualified employees, high initial costs and risks at the project management level are just some of the issues. In the area of data protection and discrimination, there is a lack of risk awareness when using AI. The human approach to AI-supported decisions can also have problematic consequences, for example if automation bias occurs.

FAIR-AI takes the identification, monitoring and anticipation of risks at all levels of system development and application as a key factor. Different types of risk are analyzed. Instead of looking for a general solution, the project partners examine specific development and application contexts in order to create a collection of exemplary, self-contained use cases. In this way, tools and assistance developed in parallel can be tested in different subject areas. The co-creation process also supports the development work.

The aim is to find ways to predict risks and integrate them into a recommendation system that offers active support and guidance. In addition, the project should lead to better networking between the stakeholders and also make a positive contribution to the acquisition of skills at universities and in continuing vocational training.