AI safety is crucial
AI systems behave fundamentally differently from traditional software: they are non-deterministic, data-driven, and highly context-dependent. Risks are often invisible and become apparent in critical situations.
Challenge
1. Unpredictable model behavior
AI models work statistically; they can produce unexpected or incorrect outputs in certain situations.
2. Risks have different causes
Risks can arise from different sources and must be analyzed specifically for each AI system.
3. Difficult assessment and quantification
A reliable assessment of performance, limitations, and risks is complex. Traditional software metrics are insufficient to evaluate behavior in challenging situations.
4. Susceptibility to manipulation
Generative or interactive AI, in particular, is sensitive to unwanted input and can be influenced by targeted manipulation.
Integrated AI safety
1. Well-informed architectural and product decisions
Teams know what is critical and which technical risks should be prioritized.
2. Stable, scalable AI products
Safe models reduce misconduct, operational risks, and unexpected costs.
3. Trust
Safe AI systems create trust among users, partners, and within the company itself.
4. More efficient development
Less rework in later phases.
5. Regulatory Compliance
Particularly in high-risk areas, clear technical safety requirements are defined, which must be addressed and verifiably documented.
My services
Technical classification and knowledge transfer
Precise, stakeholder-oriented communication of the fundamentals of AI safety, risk sources and technical requirements.
Sparring and technical support
Support in architecture, product and safety decisions, as well as the integration of AI safety into existing processes.
AI risk assessment and product safety
Systematic analysis of AI risks and development of appropriate safety measures
What sets me apart
Technical depth with safety engineering expertise
Extensive experience with safety-critical AI systems as an engineer and tech lead.
Clear Communication
I make technical complexities understandable, prioritize risks, and enable informed decision-making for the next steps.
hands-on
We always work on real systems, specific questions, and existing processes. The result is measures that can be applied directly.