27.11.2024
Generative AI models offer a wide range of possible applications and have the potential to significantly advance digitalization. However, in order to make a realistic assessment of the possibilities and limitations of this technology, it is essential to build up practical expertise. This can be done by implementing proof-of-concepts (PoCs) for smaller, non-critical use cases. It is crucial to observe regulatory requirements and ensure secure implementation.
With the AI Act, the European Union has passed the world's first comprehensive law on the regulation of artificial intelligence. This law follows a risk-based approach in which AI systems are subject to different requirements depending on their risk potential. High-risk AI systems, such as those used in safety-critical infrastructures or in the healthcare sector, must meet strict requirements. These include requirements for transparency, human oversight and risk management.
When introducing AI systems, companies should follow the principle of "secure by design". This means that security aspects are integrated into the development process right from the start. Important steps here are
The risk of security gaps and attacks can be minimized by taking security aspects into account at an early stage.
Companies should consider the following points when implementing PoCs for generative AI:
Developing practical expertise in dealing with generative AI models is essential in order to fully exploit their potential. By implementing proof-of-concepts, companies can gain valuable experience. However, it is essential to observe regulatory requirements and ensure secure implementation in order to minimize risks and promote trust in the technology.
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