Time and room:

15:00 – 15:30 | Audimax B

Presented by

Elyesa Seidel, Andre Machon
Heinrich-Heine-University Düsseldorf, FlowConAI 

Summary

Privacy by Design is well established in the ILIAS community, but scaling it sustainably remains a challenge. Privacy documentation, in particular PRIVACY.md files for individual components, plays a key role in making data processing transparent and understandable in practice. At the same time, the underlying processes are often time-consuming and procedurally demanding.

This talk focuses on how AI can meaningfully support and streamline privacy documentation workflows in ILIAS. It demonstrates how AI can assist in generating structured drafts of PRIVACY.md files and in updating existing documentation by analyzing code changes and comparing them with the current documentation. In this way, AI can help identify gaps, suggest concrete revisions, and ensure that privacy documentation accurately reflects the data processing logic implemented in the system.

The aim is to explore how AI-assisted processes can reduce manual effort while preserving human oversight and responsibility, thereby contributing to scalable and sustainable Privacy by Design practices in ILIAS.

Type

Presentation

Target group

Developer | Designer | Concepter | Systemadministrators | Project Managers | User / Teacher / Tutors

Length of slot

30'

Language

English | German 

Recording

Contribution will be recorded and published.