Looking to use DeepSeek R1 in the EU? This new study shows it’s missing key criteria to comply with the EU AI Act
The popular AI model DeepSeek R1 may contain inherent flaws that make it incompatible with the EU AI Act, according to new research.
DeepSeek R1 took the tech industry by storm in early January, offering an open source option for performance comparable to OpenAI’s o1 at a fraction of the cost.
But the model’s outputs may contain vulnerabilities that jeopardize its rollout in the EU. Using a new framework known as COMPL-AI, researchers analyzed both DeepSeek R1 models: one distilled from Meta’s Llama 3.1 and the other from Alibaba’s Qwen 2.5.
The framework was created by researchers at ETH Zurich, the Institute for Computer Science, Artificial Intelligence and Technology (INSAIT), and LatticeFlow AI. It aims to evaluate models on a range of factors such as transparency, risk, bias, and cybersecurity readiness, measured against the requirements of the EU AI Act.
In a test of whether the model could be hijacked with jailbreaks and prompt injection attacks, both DeepSeek models scored the lowest of all models benchmarked by COMPL-AI. DeepSeek R1 Distill Llama 8B scored just 0.15 for the hijacking and prompt leakage out of a possible 1.0, compared to 0.43 for Llama 2 70B and 0.84 for Claude 3 Opus.
This could put it in jeopardy with Article 15, paragraph 5 of the EU AI Act, which states: “High-risk AI systems shall be resilient against attempts by unauthorized third parties to alter their use, outputs or performance by exploiting system vulnerabilities”.
The analysis comes after similar research into DeepSeek jailbreaking techniques conducted by Cisco, which found the model was susceptible to prompts intended to produce malicious outputs 100% of the time.
In other areas, the models outperformed some of the most popular open and proprietary LLMs. The model was found to consistently deny it was human, a feat not achieved by GPT-4 or the baseline version of Qwen.
Tested with HumanEval, a widely-used benchmark for assessing an LLM’s code generation capabilities, DeepSeek also outperformed other open source models. DeepSeek R1 Qwen 14B scored 0.71 versus Llama 2 70b’s 0.31, exceeded in COMPL-AI’s leaderboard only by GPT-3.5 (0.76), GPT-4 (0.84) and Claude 3 Opus (0.85).
“As corporate AI governance requirements tighten, enterprises need to bridge internal AI governance and external compliance with technical evaluations to assess risks and ensure their AI systems can be safely deployed for commercial use,” said Dr. Petar Tsankov, co-founder and CEO at LatticeFlow AI.
“Our evaluation of DeepSeek models underscores a growing challenge: while progress has been made in improving capabilities and reducing inference costs, one cannot ignore critical gaps in key areas that directly impact business risks – cybersecurity, bias, and censorship. With COMPL-AI, we commit to serving society and businesses with a comprehensive, technical, transparent approach to assessing and mitigating AI risks.”
COMPL-AI is not formally associated with the EU Commission, nor able to provide an official third-party analysis of the EU AI Act. Companies looking to adopt DeepSeek or other models into their tech stack will still need to follow best practices for implementing generative AI.
Leaders may also look into hiring for roles such as chief AI officers and data ethicists, alongside the establishment of sovereign cloud clusters to ensure data used for AI within the EU is compliant with regional laws.
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