Invited Speakers
We are excited to announce an outstanding lineup of invited speakers for the KI2024 conference. Our speakers are leading experts in their respective fields, offering valuable insights and pioneering research. Stay tuned as we reveal more details about their talks and contributions.
Elisabeth André
University of Augsburg, Head of Chair for Human-Centered Artificial Intelligence
Topic: Amplifying Human-Human and Human-Agent Interaction with AI
Abstract: Advances in analytic and generative AI present promising opportunities for enhancing communication by augmenting individuals' perceptual and expressive capabilities. This talk will explore recent advancements and practical applications of conversation-enhancing technologies, with a focus on their potential benefits for individuals facing communication challenges. Collaborative efforts have resulted in innovative applications tailored to diverse user needs. Examples include signing avatars designed to assist the hearing impaired, as well as more expressive voices for users of AAC (Augmentative and Alternative Communication) devices. Additionally, virtual reality environments have been developed to facilitate social skill training for both children and adults, leveraging role play interactions with virtual agents. We will discuss how analytic and generative AI can serve as powerful tools to overcome communication barriers, foster authentic expression, and promote social inclusion. By analyzing the potential of these technologies to support users with varying communication abilities, we aim to address the challenges inherent in designing empathetic solutions that cater to the specific needs of diverse audiences, while mitigating the risk of reinforcing stereotypes.
Christian Baukhage
University of Bonn, Institute for Computer Science
Topic: Quantum AI / ML – Hype or Hope?
Abstract: Over the past decade, we have seen encouraging progress in technical realizations of quantum computers and there are now rising hopes for practical applications of quantum computing. A noteworthy trend in this regard is that the quantum computing community has jumped on the machine learning bandwagon and is promising quantum advantages for artificial intelligence. Our goals with this presentation are therefore threefold: First, we provide an ever so brief introduction to quantum computing and its expected benefits. Second, we point out the sobering fact that most promises as to quantum supremacy for ML and AI are and likely will remain severely exaggerated. Third, we emphasize that there still is hope for quantum AI as long as we are looking for appropriate use cases. As an example of such a use case, we discuss how quantum algorithms can accelerate Bayesian network inference.
