A short series about data preparation, human-AI interaction and team empowerment

Generative AI stands as a transformative force set to disrupt industries, offering businesses unparalleled opportunities to automate content generation, personalize customer experiences, and streamline product development processes, ultimately driving innovation and competitiveness in the marketplace.

During this webinar series, with five episodes, the EDIHs ATTRACT and Südwestfalen will pool their expertise as part of their collaboration and highlight five interesting facets in the field of generative AI that enable companies to leverage the technology to their business advantage.

All episodes start at 10:00 CET.


In the rapidly evolving landscape of AI, the “Generative AI from a Human-Centered Perspective” webinar aims to delve deep into the symbiotic relationship between human intuition and AI capabilities.  This session is designed to explore the critical role of the human factor in guiding and refining the outputs of generative AI technologies. One part of the discussion will be the concept of  “Human in the Loop” – a framework that emphasizes theimportance of human oversight in AI systems.

 We will examine how integrating human judgment can not only enhance the reliability of AI-generated content but also ensure that these outputs align with ethical standards andsocietal values. Second, this webinar willprovide insights into how participants can critically assess the quality and   accuracy of AI outputs.

by Louisa Sauter and Robert Fischbach, from EDIH Südwestfalen

The importance of paying attention to the quality of data

Generative AI models rely heavily on well-prepared data to function effectively. However, thepresence of  noise, errors, and biases in the input data can significantly impact the training process and produce subpar outputs. This webinar aims to explore the methods of data preparation and cleaning specifically   tailored for Generative AI. By focusing on practicaltechniques and best practices, attendees will gain valuable insights into optimizing data quality to enhance the performance and reliability of their generative models.

by Sphesihle Ndlela, from EDIH Südwestfalen

A collaborative initiative by