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Germany Issues Guidance on the Opportunities and Risks of Generative AI Models

Client Updates / Apr 30, 2024

Written by: Haim Ravia and Dotan Hammer

The German Federal Office for Information Security (BSI) recently published a guide titled “Generative AI Models – Opportunities and Risks for Industry and Authorities”. The guide provides an in-depth overview of the opportunities and risks associated with large language models (LLMs), a specialized subset of generative artificial intelligence (AI). LLMs extend beyond simple text processing to fields such as computer science, history, law, medicine, and mathematics, generating relevant texts and solutions for various challenges. The guide stresses the importance of implementing safety measures for generative AI before integration into systems. The risks associated with LLMs are categorized into three primary areas:

  • Risks associated with proper use. Even with correct usage, LLMs can present risks due to their stochastic nature and the composition of their training data.
  • Risks due to misuse. The wide and sometimes unrestricted availability of high-quality LLM outputs can lead to their exploitation, resulting in harmful or illegal text outputs.
  • Risks from attacks on LLMs. LLMs are susceptible to various attacks, including privacy, evasion, and poisoning attacks, which aim to extract information, manipulate responses, or induce malfunctions.

To address these risks, the German BSI’s guide recommends the following measures:

  • Organize and monitor training data rigorously to quickly address anomalies and ensure robust data management practices.
  • Collect data at varied times from credible sources to prevent manipulation and maintain integrity.
  • Apply differential privacy and anonymization techniques to protect sensitive training data from potential threats.
  • Implement security measures like cryptographic techniques to prevent and detect model theft.
  • Perform extensive testing, including red teaming, to identify vulnerabilities and ensure model robustness.
  • Develop criteria for selecting reliable models and operators that adhere to security and functionality standards.
  • Strictly limit access and user rights to essential personnel only and consider temporary restrictions for suspicious activities.
  • Clearly communicate the capabilities, limitations, and risks associated with LLMs to all users.
  • Regularly audit outputs for manipulation or sensitive information and apply necessary post-processing measures.
  • Implement stringent data protection measures during model training and operation to safeguard sensitive information.

Click here to read the German BSI’s Guide to the Opportunities and Risks of Generative AI