Anirban Ghosal, senior writer for Computerworld, discusses how OpenAI are planning to use GPT-4 LLM for content moderation, and how this could help to eliminate bias. By automating the process of content moderation on digital platforms, especially social media, GPT-4 could interpret rules and nuances in long content policy documentation, as well as adapting instantly to policy updates. The company believe AI can help to moderate online traffic and relive the mental burden on a large number of human moderators. The company posit that custom content policies could be created in hours, and they could use data sets containing real-life examples of policy violations in order to label the data. Traditionally people label the data and this is time consuming and expensive.
People will then be used to read the policy and assign labels to the same dataset without seeing the answers. Using these discrepancies the experts can ask GPT-4 to explain the reasoning behind its labels, look into policy definitions, discuss the ambiguity and resolve any confusion. This iterative process will have many steps with data scientists and engineers before the LLM can generate good useful results.
So What: Using this approach should lead to a decrease in inconsistent labelling and a faster feedback loop. Results should be more consistent. Undesired biases can creep into content moderation during training, although results and output will need to be carefully looked at and further refined by maintaining humans in the loop, therefore, bias could be reduced. Industry experts suggest that this approach has potential and could lead to a massive multi-million dollar market for Open AI.
