Large language models (LLMs) are being deployed in many domains of our lives ranging
from browsing, to voice assistants, to coding assistance tools, and have potential for vast societal
impacts.[1, 2, 3, 4, 5, 6, 7] This system card analyzes GPT-4, the latest LLM in the GPT family
of models.[8, 9, 10] First, we highlight safety challenges presented by the model’s limitations
(e.g., producing convincing text that is subtly false) and capabilities (e.g., increased adeptness
at providing illicit advice, performance in dual-use capabilities, and risky emergent behaviors).
Second, we give a high-level overview of the safety processes OpenAI adopted to prepare GPT-4
for deployment. This spans our work across measurements, model-level changes, product- and
system-level interventions (such as monitoring and policies), and external expert engagement.
Finally, we demonstrate that while our mitigations and processes alter GPT-4’s behavior and
prevent certain kinds of misuses, they are limited and remain brittle in some cases. This points
to the need for anticipatory planning and governance.[11]
Content Warning: This document contains content that some may find disturbing or offensive,
including content that is sexual, hateful, or violent in nature.