Codex, a large language model (LLM) trained on a variety of codebases, exceeds the previous state of the art in its ability to synthesize and generate code. Although the Codex offers a multitude of benefits, models that can generate code on such a scale have significant limitations, alignment issues, the risk of being misused, and the potential to accelerate the pace of progress in technical areas that can themselves have destabilizing impacts or be misused. potential. However, these impacts on security are not yet known or remain to be explored. In this article, we describe a hazard analysis framework built by OpenAI to uncover the hazards or security risks that deploying models like Codex can impose technically, socially, politically, and economically. The analysis leverages a new evaluation framework that determines the capability of advanced code generation techniques against the complexity and expressiveness of specification prompts, as well as their ability to understand and execute them compared to human capabilities.
A risk analysis framework for large code synthesis language models
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