OpenAI’s GPT-4 Sets Out to Revolutionize Content Moderation
OpenAI claims that GPT-4 has the potential to accelerate content moderation.
The company said that GPT-4 can help companies speed up their process of content moderation, reducing it from months to hours.
OpenAI, the creator of the widely recognized AI-powered chatbot ChatGPT, announced that GPT-4 has the potential to accelerate content moderation. The company shared the research on its blog on August 15.
Content moderation plays a pivotal role for social media platforms like Facebook and Instagram. Presently, these platforms collaborate with numerous global moderators to prevent users from encountering harmful content. However, individuals may grapple with the platforms’ evolving policies and the volume of published content.
To mitigate such growing challenges, Open AI claims that GPT-4 can help companies speed up their process of content moderation, reducing it from months to hours.
In addition, OpenAI’s said that its large language model’s (LLM) ’s ability to interpret complex rules and nuances in extensive content policy documentation enables immediate adaptation to policy updates, leading to uniform labeling across platforms. The company believes that AI can help moderate online traffic according to platform-specific policies.
Different from constitutional AI, which mainly relies on the model’s own internalized judgment of what is safe,OpenAI’s approach aims to aid platform-specific content policy, making iteration faster and less tedious.
OpenAI introduced GPT-4 in March of this year. As of today, it outperforms all existing LLMs, having reached a score of 85.5% in the English language.
OpenAI also announced that it will be enhancing GPT-4’s predictive quality by exploring chain-of-thought reasoning and self-critique. The company aims to detect unknown risks inspired by constitutional AI and update content policies accordingly.
However, the technology also has its limitations. For instance, LLMs are vulnerable to undesired biases that might have occurred during the model training. So, as with any AI application, results and output will need to be carefully monitored, validated, and refined by humans.
“By reducing human involvement in some parts of the moderation process that can be handled by language models, human resources can be more focused on addressing the complex edge cases most needed for policy refinement,” said OpenAI, in the announcement.
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