When? Friday November 3rd 14-16
Where? Onsite: D1140 at Linnaeus University in Växjö and online
Registration: Please sign up for the PhD-seminar via this link https://forms.gle/txd4g2Un1qfYSvr2A by November 1st (especially important if you plan on attending onsite so we have fika for everyone)
14.00-14.10 Welcome and practical information from Welf Löwe
14.10-14.55 Presentation and discussion: Unlock the Power of Mobile Robotics with AI based Vision – Daniel Nilsson, PhD student at Kuka Nordic
14.55 – 15.05 Coffee break
15.05 – 15.50 Presentation and discussion – AI and data literacy: What knowledge and skills are needed in a data-driven society? – Johanna Velander, PhD student UPGRADE and WASP-HS
15.50 -16.00 Sum up and the Big Data Conference and plan for our next seminar on January 12th
Unlock the Power of Mobile Robotics with AI based Vision – Daniel Nilsson, PhD student at Kuka Nordic
This research project proposes a transformation of KUKA’s AMRs into multifunctional agents using the vehicles existing sensors and AI. In the current solutions Autonomous Mobile Robots (AMRs) primarily serve as single-function devices, enabling driverless transportation between various points within a facility. At the same time automation of processes such inventory tracking tend to involve additional investments in additional systems and costly hardware installations, adding to the financial dilemma when striving to transform the operation toward industry 4.0. By allowing AMRs to manage transportation, inventory tracking, and safety compliance simultaneously, such advancement would significantly add to the AMR’s value in production environments.
AI and data literacy: What knowledge and skills are needed in a data-driven society? Johanna Velander, PhD student UPGRADE and WASP-HS
Uncovering patterns and trends in vast, ever-increasing quantities of data has been enabled by different machine learning methods and techniques used in many of the applications that we use in our daily lives. Permeating many aspects of our lives and influencing our choices, development in this field continues to advance and increasingly impacts us as individuals and our society. The risks and unintended effects such as bias from input data or algorithm design have recently stirred discourse about how to inform and teach about AI in K-12 education. As AI is a new topic not only for pupils in K-12 but also for teachers, new skill sets are required that enable critical engagement with AI.
In this presentation, I will talk about my PhD project, which sits at the intersection of computer science and teacher education. In a recent study deploying a Learning Analytics plugin at some LNU courses students’ thoughts, attitudes and emotions were investigated when engaging with their own data (collected by the LMS Moodle). Results revealed a low awareness of data collection and potential data-driven practices and also worries about how this data could be used and who could have access to it. Following these insights and according to my Ph.D. affiliation with UPGRADE and WASP-HS I have continued to investigate how awareness and knowledge of AI concepts, applications and potential ethical concerns often referred to as AI literacy can be taught at a K-12 level in order to inspire future data scientists and to enable equal participation in a digital data-driven society according to a critical literacy perspective that empowers learners to act on and find alternatives to issues present in current AI practice.