Quartz: “Large language models (LLMs)—like ChatGPT—can help economists do better research, if they know how to use them correctly. This is part of the premise of a recent paper published in the National Bureau of Economic Research by Anton Korinek, an economics professor at the University of Virginia. To illustrate what LLMs could do in economics research, Korinek used the most powerful system available, which is currently GPT-3. This is “slightly more powerful” than ChatGPT but has a similar output, Korinek added. Like OpenAI’s ChatGPT, the GPT-3 system was trained on public data up until 2021 and cannot access the internet. Korinek sees research potential in LLMs because they can generate content and consume large amounts of text faster than humans. LLMs can produce text that sounds authoritative but may be inaccurate. Therefore, he says, humans—who are better at examining and evaluating the accuracy of content—should use them carefully. All of Korinek’s suggestions are related to “micro tasks”: small jobs that researchers do every day, but that are too minor to assign to other human assistants. “I have found that many of my students are already quite well-versed with ChatGPT and have used it for lots of different tasks,” Korinek said. “In fact, some of the examples in my paper were inspired by my students. And I also learned from my students that they use language models not only as assistants but also as tutors.” Korinek’s fellow faculty are more split on ChatGPT. Some use it as he does. Others dismiss it because of its faults, and others haven’t tried it.  “My goal in writing the article has been twofold: to expose the regular users of language models to a variety of different use cases and to try to win over some of the skeptics,” Korinek said. “I believe that we as a society have so much to gain if we use these tools responsibly to enhance our productivity and accelerate scientific progress.” Here are 22 of Korinek’s ideas for how economists can use the technology..”