Tag: ChatGPT and Law

Article: Using ChatGPT in legal writing

Post by Stephen Horowitz, Professor of Legal English

Prof. Joe Regalia

Joe Regalia, Associate Professor of Law at the William S. Boyd School of Law at University of Nevada Las Vegas, recently shared on the Legal Writing Institute listserv that he’s been working on a chapter of a book that he will be publishing with Aspen Publishing later this year—tentatively called Leveling Up Your Legal Writing: Techniques and Technology to Create Amazing Documents.

The chapter–still in draft form–aims to be a practical guide for using ChatGPT in legal writing and can be viewed at this link for free in PDF format:

https://ssrn.com/abstract=4371460

Joe noted that even though he hasn’t even added sources yet to the draft chapter, he wanted to share in case any of the ideas are helpful to folks exploring using GPT in their classes.

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Analyzing ChatGPT’s ability as a grammar fixer


Post by Stephen Horowitz, Professor of Legal English

I recently tried a simple yet potentially helpful ChatGPT activity with my LLM students to (a) build individual grammar awareness, (b) build a better understanding of the benefits and limitations of using ChatGPT to fix one’s grammar, and (c) gain a better understanding of what happens grammatically when ChatGPT is asked to fix grammar.

The Process:

  1. As part of the Legal English II course (which teaches US case reading and analysis via a series of Supreme Court decisions about Miranda rights to students in Georgetown Law’s 2-Year LLM program), my students were required to write an essentially IRAC-style answer in response to a fact pattern under timed conditions.
  2. Afterwards, as an assignment, I asked my students to input their essay into ChatGPT with the instruction to “Please fix any language issues in this essay:“
  3. Students then had to compare the two versions of their essay and write a short analysis or commentary on what they noticed, what ChatGPT did/didn’t do well, how they felt about it, etc. I told students to either put the two versions in a table so they could compare the language side by side, or they could do a use the redline/track changes function to show the differences.
  4. I next reviewed the students’ submissions myself. And I then invited two Georgetown Legal English colleagues with PhDs in applied linguistics–Prof. Julie Lake and Prof. Heather Weger–to review the student submissions and then have a group discussion about what we noticed.
  5. Upon additional consideration (and inspired by a suggestion from Jack Kenigsberg, a former Hunter MA TESOL classmate), I took one paragraph from one student’s essay and fed it into ChatGPT with the instruction: “Fix any grammar errors in the quoted text. For each change you make, explain why you made the change.” And after it provided its answer, I clicked “Regenerate response” to create a second response to see what (if anything) came out different a second time.

The Takeaways:

The main takeaways by my students, my colleagues and myself were:

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