Are Algorithm Registers Transparent? Perspectives from Germany

2026-06-01

AI Summary

Germany currently lacks a unified national algorithmic registry, and existing platforms—such as MaKI and Lernende Systeme—exhibit significant fragmentation in their objectives, scope, and effectiveness, thereby falling short of enabling meaningful algorithmic transparency. This study operationalizes Alina Lorenz’s national AI transparency framework into a structured, multilingual audit checklist and, for the first time, evaluates both platforms through qualitative content analysis, framework mapping, and systematic external auditing. The research not only publicly releases a reusable audit instrument but also introduces a visualized transparency hierarchy and concrete recommendations for improvement, offering an empirical foundation and actionable design pathway toward establishing an effective and implementable national algorithmic registry in Germany.

Abstract

Algorithm registers are public-facing databases that display basic information about algorithms employed in public administration. While several such registers exist across Europe and globally, their capacity to deliver meaningful transparency remains contested. In Germany, the landscape is notably fragmented: no federal-level register exists, yet at least five state- and federal-level initiatives publish information about AI systems with varying scopes and objectives. A recent conceptual proposal by Alina Lorenz (2025), outlines technical and governance requirements for a national AI transparency register in Germany. We repurpose this proposal as an audit instrument, extracting structured checklists from the transparency goals and subgoals it formulates. The resulting checklists, translated from German into English, is made publicly available to support practitioners auditing existing registers or designing new ones. We apply this framework to conduct an external audit of the two main existing German transparency initiatives, MaKI and Lernende Systeme, evaluating the extent to which they fulfill the proposed goals. Our audit reveals that several adaptations are likely needed for these registers to serve as an useful transparency instrument. We further propose a visualization of register transparency levels and derive concrete action items for improving existing German platforms.

Problem

• algorithm registers
• transparency
• public administration
• AI governance
• Germany

Innovation

• algorithm register
• transparency audit
• AI governance
• structured checklist
• visualization of transparency