Speaker
Description
Modern large language models (LLMs) have reshaped workflows of people across countless fields - and biostatistics is no exception. These models offer novel support in drafting study plans, generating software code, or writing reports. However, reliance on LLMs carries the risk of inaccuracies due to potential hallucinations that may produce fabricated "facts", leading to erroneous statistical statements and conclusions. Such errors could compromise the high precision and transparency fundamental to our field.
In this talk we assess the utilization of ChatGPT for various contemporary biostatistical tasks. We explore both the risks and opportunities presented by this new era of artificial intelligence. We emphasize that advanced applications should only be used in combination with sufficient background knowledge. Regular verifications of LLM outputs may lead to an appropriately calibrated trust in these tools among users.
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