Building Reliable AI Workflows for Academic Research

For whom: Researchers, PhD students, and teachers from all disciplines

How can we harness the power of AI in research without sacrificing scientific rigor? Since AI can generate fabricated sources and draw on poor-quality material, academia is facing new methodological challenges that demand new solutions.

A central challenge is source management: How can we build systems that handle both established, trusted sources and new, unknown ones that require careful scrutiny? By developing a “source trustworthiness platform,” we can streamline work with well-known sources while focusing our critical efforts where they are needed most: on new, untested material.

WARA Media & Language invites you to a hands-on seminar exploring how AI can become a reliable partner in the research process. Alexandra Kafka Larsson from Parsd will share experiences from developing methodological support for differentiated source management in AI-assisted research together with Swedish universities.

During the seminar:
-    Concrete examples of AI challenges and solutions in research
-    Build differentiated source verification strategies
-    Practice categorizing and reviewing sources by trustworthiness
-    Balance efficiency with scientific rigor in AI workflows    
-    Shape implementation of academic methodology in AI tools

Relevant because you:
-    Handle large, cross-disciplinary source materials
-    Need efficient yet critical source management
-    Teach or develop academic methods
-    Want to influence AI standards in research

Register here (limited seats)