Grant: Project Grant

Policy decisions in healthcare often require quick access to accurate and up-to-date information. However, traditional research methods can take months to deliver the necessary evidence. By using Artificial Intelligence (AI) like ChatGPT, the time needed to gather, analyze, and summarize research could be reduced to weeks or even days. This speed could make it easier for healthcare leaders to make timely and informed decisions. While AI have the potential to revolutionize how we gather knowledge, it's important to understand if these tools introduce biases or errors, and how these could affect vulnerable populations. Our project aims to compare the effectiveness, speed, and potential risks of using AI versus human-led teams for creating policy briefings-concise reports that provide crucial information for decision-makers. To do this, we will work with policymakers and healthcare managers to develop a list of important research questions. These questions will then be answered using both AI-assisted methods and traditional human-led research approaches. We will assess how well each method works, looking at the quality, relevance, and practical use of the findings. In addition, we will consult with people from at-risk groups to understand how any biases in AI-driven results might affect them and explore ways to reduce these risks. By comparing AI with traditional research, we hope to learn whether these tools can safely and effectively speed up the decision-making process in healthcare. The results could help improve how evidence is used in policy decisions, leading to faster, more efficient responses to healthcare challenges.