Evaluating Privacy Compliance in Commercial Large Language Models - ChatGPT, Claude, and Gemini DOI Creative Commons

Oliver Cartwright,

H. Flanders Dunbar,

Theo Radcliffe

et al.

Research Square (Research Square), Journal Year: 2024, Volume and Issue: unknown

Published: July 26, 2024

Abstract The integration of artificial intelligence systems into various domains has raised significant privacy concerns, necessitating stringent regulatory measures to protect user data. Evaluating the compliance commercial large language models (LLMs) such as ChatGPT-4o, Claude Sonet, and Gemini Flash under EU AI Act presents a novel approach, providing critical insights their adherence standards. study utilized hypothetical case studies assess practices these LLMs, focusing on data collection, storage, sharing mechanisms. Findings revealed that ChatGPT-4o exhibited issues with minimization access control, while Sonet demonstrated robust effective security measures. However, showed inconsistencies in collection higher incidence anonymization failures. comparative analysis underscored importance tailored strategies continuous monitoring ensure compliance. These results provide valuable for developers policymakers, emphasizing necessity multifaceted approach deployment LLMs.

Language: Английский

Evaluating Privacy Compliance in Commercial Large Language Models - ChatGPT, Claude, and Gemini DOI Creative Commons

Oliver Cartwright,

H. Flanders Dunbar,

Theo Radcliffe

et al.

Research Square (Research Square), Journal Year: 2024, Volume and Issue: unknown

Published: July 26, 2024

Abstract The integration of artificial intelligence systems into various domains has raised significant privacy concerns, necessitating stringent regulatory measures to protect user data. Evaluating the compliance commercial large language models (LLMs) such as ChatGPT-4o, Claude Sonet, and Gemini Flash under EU AI Act presents a novel approach, providing critical insights their adherence standards. study utilized hypothetical case studies assess practices these LLMs, focusing on data collection, storage, sharing mechanisms. Findings revealed that ChatGPT-4o exhibited issues with minimization access control, while Sonet demonstrated robust effective security measures. However, showed inconsistencies in collection higher incidence anonymization failures. comparative analysis underscored importance tailored strategies continuous monitoring ensure compliance. These results provide valuable for developers policymakers, emphasizing necessity multifaceted approach deployment LLMs.

Language: Английский

Citations

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