From RAI 2 XAI

The project's goal is to transition the BEP learning environment from Responsible AI to Explainable AI. This means that the transparency and lessons the designers have integrated into the learning environment are also understood and applied by users. 

We will transform our learning environment using the Value-Sensitive Design method. This involves engaging potential users in discussions about the potential impact of a proposed solution and the values underlying it. The design of the learning environment positions humans as experts, rejects analyses without human input, and frames the outcomes as socio-technical—in other words, as a co-creation between a human and an algorithm. 

• Building a new XAI version of the BEP (birds eye perspective) learning environment and tool. 
• Knowledge creation on online escalation and XAI. As well as providing empirical data on the adaptation of XAI environments. 

We work in five stages, namely; 1) literary review, 2) sketch design, 3) VSD, 4) co-creation session with stakeholders, and 5) empirically testing the didactic qualities of the new learning environment.  

Educational activities: developing workshops, internships and assignments for the Communications Institute and HU consultancy Scompany.  

Professional Practice: Workshops for lecturers/researchers, networking events, pilot projects in the field (project teams, public organizations). Authoring publications in (scientific and professional) journals and trade journals (researchers and partners). Presenting results at (scientific and professional) conferences (researchers and professional partners).