Sign up for the full-day workshop on Artificial Intelligence and Machine Learning for humanities researchers
DIGHUMLAB and Human Futures at Aarhus University invite humanities researchers to join us for a full-day workshop on artificial intelligence (AI) and machine learning (ML) on November 28, 2019 from 9AM to 4PM in Richard Mortensen Stuen (building 1422).
The workshop is a basic introduction to AI and ML that touches upon e.g. natural language processing and computer vision. The format of the workshop provides rich opportunities to ask questions, discuss, network and situate the learnings within your own research projects.
After the workshop, there will be an informal networking event in Studiecaféen, Studenterhus AARHUS (the room just opposite Richard Mortensen Stuen) to discuss further.
The workshop is free of charge and open to all interested researchers (PhD level and above) at Danish institutions.
Use #hum_ai on Twitter
We encourage all participants to use the hashtag #hum_ai on Twitter for the workshop. You’re also welcome to use the Twitter handles @HumanFuturesAU and @DIGHUMLAB.
Detailed programme for AI intro by Thomas Bolander, Professor, DTU | 9.30-12.30
"What is artificial intelligence – and where is it heading?" by Thomas Bolander, Professor, DTU
What is artificial intelligence (AI)? And how does it differ from human intelligence? Will AI change our ways of thinking and interacting? The technological development is moving at high speed, and the boundaries of what is possible are constantly being pushed. Humanoid robots engaging in complex reasoning and communicating in natural language are no longer just something we see in science fiction movies. One thing is for sure, our everyday lives and the society as a whole are bound to change due to AI. The lecture will give a thorough introduction to AI, including its major paradigms and their respective strengths and weaknesses. AI will be related to human intelligence in order to gain a deeper understanding of the difference between how machines “see the world” as opposed to how we humans see it. The lecture will also address the future perspectives, both technologically and in terms of societal consequences.
"Sociolinguistics from data, on the back of an envelope" by Leon Derczynski, Assistant Professor, ITU
The way people write tells us about both the world around the author and about the author themself. In this hour, we’ll look at some sociolinguistic signals present in contemporary texts across a variety of genres and registers, and we’ll run tools – live – to see how these signals can be used to reconstruct demographic and other information about authors, using natural language processing and machine learning technology, which will be explained intuitively during the time.
"Deep learning is for everyone" by Henrik Pedersen, Head of Visual Computing Lab, Alexandra Institute
Deep learning has enabled today’s AI systems to drive cars autonomously, beat humans in computer games, and paint whatever you tell them to. The deep learning revolution is upon us, and it is transforming many businesses and changing how we write software. But deep learning is not only for engineers. Deep learning is for everyone. In his talk, Henrik will present selected cases, where the Alexandra Institute – a Danish non-profit company – has helped companies and organizations apply deep learning technology. The focus will be on deep learning for visual recognition (or computer vision).
Professor, Department of Applied Mathematics and Computer Science, DTU
Research in logic and artificial intelligence (AI), with particular focus on social aspects of AI. Serves on a number of commissions, expert panels and boards, primarily concerning technical and societal aspects of AI. Teacher of the year award at DTU, 2006; H. C. Ørsted Silver Medal for excellence in science communication, 2019.
Assistant Professor, Department of Computer Science, ITU
Leon researches in natural language processing. His research covers noisy and high-variation text, NLP for Nordic languages, social media processing, and information extraction. He was program co-chair for COLING 2018, co-investigator of an EC Horizon 2020 RIA, Comrades, and has co-organised SemEval shared tasks in 2013/15/16/17/19. He also has both published and spoken.
Head of Visual Computing Lab, PhD, Alexandra Institute
Over his career, Henrik has been in various academic positions, covering research and teaching in computer vision and deep learning. He still teaches the “Deep Learning for Visual Recognition” course at Department of Computer Science at Aarhus University. In his current position, Henrik heads several national research and innovation projects all with the mission of leveraging recent advances in deep learning to make computer vision technology available and accessible to Danish companies and organizations.