Events

The third edition of the KI & Wir * Convention will focus on the topic of AI literacy. The term refers to the need for basic AI competence in the broader population. “(How) can we learn AI?” Is the central question in view of a rapidly developing technology that arouses fear and uncertainty in many people rather than enthusiasm and acceptance.

Answers to this question should be found together with those interested in AI and experts. While the first day of the convention explores the topic discursively, in interactive workshops, webinars and live lectures with an exchange of ideas, the focus on day two is on learning by doing: DIY AI – what can you “do yourself” with AI? Which offers, tools, instruments invite the audience to participate? In addition, selected creative applications of AI will be presented on the digital stage.

Applications based on artificial intelligence help to keep jobs in Germany and Europe in the long term. As part of robots, quality and measuring devices and IT applications, AI makes factories, warehouses and entire supply chains faster, more punctual and climate-neutral. The lecture shows what the factory of the future can look like, what AI is already doing, what it still has to learn and which ethical questions we have to ask ourselves when using AI in production and logistics.

As a practice expert, Dr. Alexander Skorna from the Funk Group on how AI can help prevent fires and explosions in factories and even insure the interruption of an entire supply chain.

If you enter the keyword “Artificial Intelligence” in the Google image search today, you will see a homogeneous blue wall of graphics that depict AI as humanoid robots. Most of the time these robots are white and inexplicably sexualized. Often bundles of cables come out of their heads or they sit in front of computers that they operate on keyboards. Of course, this has nothing to do with the AI systems that science and industry create. The imagery for artificial intelligence is in a crisis!

When are metaphors appropriate in visual language and when do they reinforce existing myths and misinformation? Designers discuss this Amelie Goldfuß , Alexa Steinbrück from the XLab at Burg Giebichenstein Kunsthochschule Halle and Michael Pfister , Head of the picture editing department at ZEIT Online.

Artificial intelligence algorithms are increasingly permeating the world of work and daily life, often without our being aware of it. Machine learning methods, especially neural networks, can sort people and objects into categories and unfortunately reinforce prejudices and role models. Is it possible to make AI algorithms fair and non-discriminatory? What solution does the so-called explainable AI provide, which tries to make the decision-making process hidden in the algorithm transparent and comprehensible?

Interview partner: Francesca Schmidt , Gunda Werner Institute for Feminism and Gender Democracy

Interlocutor: Johannes Abraham Coertze , Co-Founder Link Health Technologies, Research Assistant Anhalt University

How does the data get into AI? A search for clues based on examples from the medical field.
The speakers will explain which forms of artificial intelligence are used in the medical field and which role data play in this. In addition, they outline the current state of research and present possible areas of application. Ethical and legal issues also come into focus.

In the context of an emerging debate on the purpose and use of AI applications in education, this keynote speech focuses on the interplay of language processing and language teaching as well as language and didactic action. The interactions between roles, functions and (media) design of teaching-learning settings come into focus on a multidimensional basis.

Interview partner: Prof. Dr. Katharina Scheiter , Leibniz Institute for Knowledge Media