On the 4th of May, IEAI researchers Auxane Boch, Ellen Hohma, and Maria Pokholkova hosted the workshop “System of AI Accountability in Financial Services” as part of their current project “Towards an Accountability Framework for AI Systems” in collaboration with Fujitsu Global at the TUM Think Tank.
The event aimed to exchange with specialists on quantifying AI ethics through defining scalable characteristics to evaluate the ethicality of AI applications. Participants of the event included experts from the financial industry, including insurance, fintech and financial services, with a variety of backgrounds such as from data science, AI ethics, AI governance and strategy.
The workshop took place over four hours in which participants collectively formulated and reached a consensus on five key scalable characteristics that define the ethicality of an example use case in the field of AI Credit Scoring. The characteristics were identified with a view to reflecting the degree to which AI products adhere to the ethical principles of AI, in particular the investigated example principle of ‘explainability & transparency’. To allow for a quantitative comparison of the ethicality of the use case application, a numeric scale was developed to score the defined characteristics. The event was concluded with lunch and an opportunity to network between the speakers and participants.
Feel free to check the workshop’s handout, write-up and slides
