Date: 13 June 2022
Time: 16:00 (CEST)
Abstract: Making a software product more intelligent, powering it with ML-fuelled features to personalise experiences and automate tasks is the holy grail for many software companies. At the same time, as appealing as full task automation may sound to businesses, that’s not always the case for the final users. There is often a tension between the user desire of being more efficient in their work (where automation would certainly help) and their need to keep feeling in control as well as relevant (will this software take over my job??). In this talk, I am going to explore this tension between desire for efficiency, trust, and control and provide a couple of examples of how automation can be replaced by user-ML collaboration to still deliver the desired efficiency while keeping the user in the driver’s seat.
Speaker Biography: As Director of Data at Miro, Judith leads the Data Science and Data Engineering groups in delivering data products that enable data-informed decision making and intelligent collaboration for both Mironeers and Miro’s customers. A past in academia (with a PhD in Machine Learning and an assistant Professorship at TU Delft), Judith has worked for many years at the intersection of ML and HCI, with a focus on modelling the Quality of multimedia Experiences. She has then made the leap to the business world, discovering the thrill of using Machine Learning to build intelligent features in Saas products to make the tasks of countless users easier. Having built the Data Science and Engineering Department at Exact and led data Science Departments at a few startups, Judith has now landed at Miro, where she has had the opportunity to bring back the combination of ML and HCI to make Miro (the most amazing collaborative platform!) an intelligent collaborator itself.
Currently Director of Data Science at Geophy, leading a department of 15 data scientists and analysts delivering data science products for the commercial real estate domain.