On challenges and approaches to test AI systems
This article featured in the renowned Datenschutz und Datensicherheit magazine (Issue 04/2025) and is written in English.
The rapid evolution of AI, from rule-based systems to foundation models, has introduced significant complexities and challenges in testing AI systems.
This article discusses inherent trade-offs such as standardization versus customization and measurement accuracy versus resource constraints.
QuantPi’s Chief Scientist and Co-Founder, Dr. Antoine Gautier, Head of Policy and Grants, Lukas Bieringer and Senior Researcher, Dr. Stefan Klößner introduce an abstract approach to design test scenarios and tests for standardized yet customizable assessment.
Read the full article to explore:
- The complexities and challenges in testing AI systems.
- Two fundamental trade-offs in real-world testing of AI systems.
- An abstract approach to test biases and robustness aspects of AI models.
- A standardized, yet customizable manner for consistent and comparable test results.
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