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research-control

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🗂️ AI & Agents · View mindmap

Research Control

Research Control is a feature introduced in the ChatGPT Deep Research update that provides users with granular authority over the information sources utilized during the research process. This functionality enables individuals to specify and manage the origin of data, allowing for more customized and targeted information gathering that aligns with specific requirements and preferences. Through this control mechanism, users can influence the selection and prioritization of sources that inform the final research output.

The feature allows users to define constraints on where the AI agent retrieves information, such as restricting searches to specific domains, academic journals, or verified websites. By setting these parameters, users can ensure that the generated reports adhere to particular credibility standards or focus on niche topics without interference from irrelevant or low-quality content. This level of oversight is particularly useful for professional and academic workflows where source reliability is critical.

Implementation of Research Control enhances the transparency and reproducibility of AI-assisted research. By explicitly managing the data pipeline, users can mitigate the risk of hallucination or bias stemming from unvetted sources. The system processes these instructions to filter and rank potential references, ensuring that the final synthesis is grounded in the user-defined ecosystem of information.

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