AI in Learning at Workplaces Ethical Consideration - Explainability?
14:00About presentation
Algorithmic systems are provided for various learning activities in companies, but do the providers, managers and workers know what the system is based on, what data it uses, and how. One solution suggested is explainability of the algorithmic systems. In the talk examples of challenges are presented between providers and users in workplaces. Explainability is discussed as the solution, is it? Or not?
About speaker
Merja Bauters is a research professor in digital transformation and lifelong learning at School of Digital Technologies, Tallinn University and a docent of semiotics in the University of Helsinki. Bauters has been involved and executed research, planned and guided co-design, participatory and design thinking processes in multiple EU- and national projects, on learning and technology-enhanced learning.
The main projects are the following: Learning Layers (FP7 IST), Erasmus+ project, DesignIT, IlluminatED and Spotlighters; Creating Knowledge Through Design & Conceptual Innovation LLP – ERASMUS, KP-Lab (FP6 IST/TEL), COOP PBL in VET (LLP/LdV), NetPro (LLP/LdV).
Bauters has been lecturing in over 30 different courses on design, design methods, semiotics and project communication. She was a president, UMWEB International association of semiotics and publishing house 2003–2010. She received her PhD from the Department of Philosophy, History, Culture and Art Studies, University of Helsinki 2007, discussing Charles Peirce thoughts on interpretation.