In a groundbreaking move, OpenAI has recently unveiled its use of GPT-4, a large language model, for the development of content policy and moderation decisions. This innovative approach has resulted in a more streamlined process, with consistent labeling and a faster feedback loop for policy refinement.
GPT-4’s application in this context has significantly reduced the need for human moderators, transforming the time taken for policy changes from a matter of months to mere hours. This is a testament to the model’s ability to interpret rules and nuances in extensive content policy documentation, and adapt instantly to policy updates.
“Content moderation plays a crucial role in sustaining the health of digital platforms. A content moderation system using GPT-4 results in much faster iteration on policy changes, reducing the cycle from months to hours. GPT-4 is also able to interpret rules and nuances in long content policy documentation and adapt instantly to policy updates, resulting in more consistent labeling. We believe this offers a more positive vision of the future of digital platforms, where AI can help moderate online traffic according to platform-specific policy and relieve the mental burden of a large number of human moderators. Anyone with OpenAI API access can implement this approach to create their own AI-assisted moderation system.”
GPT-4 content policy development and moderation
OpenAI’s API access extends this capability to the wider community, allowing anyone to implement this approach and create their own AI-assisted moderation system. This is a significant step forward, as large language models like GPT-4 have the ability to understand and generate natural language, making them highly applicable to content moderation.
These models can make moderation judgments based on policy guidelines provided to them, significantly reducing the process of developing and customizing content policies. Furthermore, GPT-4’s predictions can be used to fine-tune a much smaller model, enabling it to handle large amounts of data at scale.
This approach is a departure from Constitutional AI, which relies on the model’s own internalized judgment of what is safe versus what is not. Instead, OpenAI is exploring further enhancements of GPT-4 prediction quality, including chain-of-thought reasoning or self-critique, and ways to detect unknown risks.
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The insights gained from these explorations will inform updates to existing content policies or the development of policies on new risk areas. However, it’s important to note that language models are vulnerable to undesired biases introduced during training. As such, results and output need to be carefully monitored, validated, and refined by maintaining humans in the loop.
By reducing human involvement in some parts of the moderation process, human resources can focus more on addressing complex edge cases most needed for policy refinement. OpenAI is committed to transparency and will continue to share learnings and progress with the community, ensuring that the evolution of AI-assisted moderation remains an open and collaborative process.
Source: Openai
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