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If there's been a recent update to a package you're using, ChatGPT won't know about it, since its training data ends in 2021.

This is obviously less than ideal if you need a reproducible workflow. For instance, when I asked multiple times for a ggplot2 bar chart with blue bars, the code generated a graph with blue bars sometimes but not others, even though I submitted the exact same request.

ChatGPT can generate different responses to the same query-and some answers might be accurate while others aren't.

Kyle Walker, an associate professor at Texas Christian University and author of the popular tidycensus R package, recently tweeted that ChatGPT can "supercharge your work if you understand a topic well," or it can leave you "exposed for not knowing what you are doing." The difference is in knowing when the AI output isn't right. Even incorrect responses can be a time-saving starting point, but don't assume the code will do exactly what you expect.

ChatGPT may confidently return answers that are wrong.

Don't use ChatGPT tools to process sensitive information.

Everything you ask with these tools gets sent to OpenAI's servers.

But before you begin using ChatGPT and tools associated with it for projects in R, there are a few important things to keep in mind: (A large language model, or LLM, is the technology underpinning AI chatbots like OpenAI's ChatGPT.)Īn ecosystem is forming around ChatGPT and R, making it easy to incorporate the AI technology into your R language workflow. That means ChatGPT's power is available to any R programmer, even one who knows little about large language models. Without fine-tuning or being trained on a specific topic, ChatGPT can answer questions about a wide range of technology subjects-including how to write R code.