Open Online Course: AI and Professions
Welcome to join our open online course, where we problematize and discuss the challenges of using AI in different professions, in particular medicine, education, journalism, and law. We start in September, but you can join whenever you want until May 2022. The course is open for everyone and has no specific entry requirements, although you probably need to know the basics of programming.
Software, machine learning and artificial intelligence have changed our lives in the last two decades. Everything from the fundamental infrastructure to advanced applications use computers and software. Artificial intelligence and machine learning take advantages of the prevalence of software and data, providing us with new possibilities.
In this course, we problematize and discuss the challenges of using AI in different professions. We present how AI influences medicine, education, journalism, and law. We start the course with presenting the technology around AI – neural networks, data mining and visualization and legal aspects of using AI. Then, we move to modules that present the use of AI in professions.
Course content and form
The course is given as an online course, where the participants can read each module in their own pace. During autumn 2021 and spring 2022, there will be coordinated Q&A sessions with the teachers, to ask questions.
The course offers the following modules:
- Fundamentals of AI
Convolutional Neural Networks
Natural Language Processing
Law of AI: legal aspects in AI systems
Data and visualization
AI and journalism
AI and Law: Legal professions and AI
AI and medical image analysis
AI and education technology
The course opens on the 1st of September 2021.
Link to course canvas website: AI and Professions
Application and Registration
To apply for the course, please sign up on this page.
The course is open for everyone and has no specific entry requirements, although you probably need to know the basics of programming.
Examination and Certificate of participation
The course will be examined through quizzes and tests based on the lectures and reading material.
Upon the completion of the course, you will be awarded a certificate of participation in the course. This certificate shows that you have followed the course and that you have fulfilled the requirements of the course.
This course is not part of the university’s ordinary education and therefore does not generate any study credits and can not be part of a degree.
About the teachers:
Elena Raviola is Torsten and Wanja Söderberg Professor in Design Management at the Academy of Art and Design, University of Gothenburg. She is the director of the Business and Design Lab, a research center between the Faculty of Arts and the School of Business, Economics and Law at the University of Gothenburg. Her research explores how digitalization and automation transform the organization of professional work, especially in the cultural and creative industries. She has conducted extensive ethnographic studies in media organizations, focusing on how digital technologies and more recently AI have changed professional practices, business models and ultimately media's democratic role. She has published in international journals, like Academy of Management Annals, Organization Studies, Social Science and Medicine, International Journal of Management Reviews, Information, Communication and Society. Her monograph Organizing Independence: Negotiations between Journalism and Management in News Organizations is forthcoming at Edward Elgar Publications.
Mats Granath is a senior lecturer at the Department of Physics. With a background in theoretical condensed matter physics he now works primarily on applications of machine learning in quantum computing and quantum algorithms as part of the Wallenberg Centre for Quantum Technology. He is director of the master's programme in Complex Adaptive Systems at University of Gothenburg (GU) and Chalmers and teaches courses ranging from basic physics to advanced machine learning. He is also the coordinator at GU for the Swedish National Infrastructure for Computing.
Simon Dobnik studied at University of Oxford where he got his PhD in computational linguistics. There he was working with mobile robots that learn language from human describers and are able to describe the same environment back to humans or follow instructions. Recently, at GU, he worked on grounding natural language in vision (or perception and action in general); what information is available to us, what can be learned and how representations are fused in deep-learning models; how we can use ML to learn language from interactions or conversations. He also teaches in the Master's programme in Language Technology (H2MLT) at GU.
Robert Lowe is docent in Cognitive Science, and Associate Professor, at the University of Gothenburg. His research interests are focused on computational modelling and gamification of cognitive science tasks focused on memory and decision making as affected by (social) interaction and emotion. He also works with robots to study how such models can be used as cognitive controllers in physically embodied artificial agents. He teaches courses in Artificial Intelligence focused on introduction to Deep Learning and Deep Reinforcement Learning in the context of gaming. He is Associate Editor on the journals Adaptive Behavior , Frontiers in Neurorobotics, and Frontiers in Psychology. He is also on the IEEE Cognitive and Developmental Systems Technical Committee .
Miroslaw Staron is professor in software engineering at University of Gothenburg. Prof. Staron specializes in software quality, measurements, safety-critical systems and software architecture software engineering and has published over 200 articles and three books. His current research interests include applications of artificial intelligence in intensive care.
For more information and/or questions, please contact: Miroslaw Staron.
 We reserve ourselves the right to remove a student from the course based on existing laws and policies of the University of Gothenburg.