Reading Assignments
To allow for this course to be flexible in response to the pace and dynamics of our in-class discussions, reading assignments will be scheduled on a rolling basis. To allow you enough time to read the assigned material, I plan to post reading assignments at least one week in advance of class. Once I have posted a reading assignment for a particular day, I will not change the assignment by adding more reading for that day.
I highly encourage you to take notes as you read. Reading without taking notes is not reading at all. Jotting down notes only after finishing the assigned reading will almost always result in a subpar reading response. As you work through your reading assignments, don’t read passively and don’t take anything for granted. As you read, write down questions that come to mind. Ask yourself: What aspects of the author’s argument do you agree and disagree with? Why? Why not? What are the opportunities and limitations of these ideas? What assumptions are being taken for granted? What questions have been left unasked? What questions would you like to ask the author?
Jan. 14, 2026
Generative AI, the legal profession, and law school
Our first class will address some foundational questions:
- Why does this class exist and why are you taking it?
- How have you been thinking about generative AI up to this point? What impact do you think generative AI will have on your future?
- How should the legal profession respond to generative AI? How should law schools and law students respond to generative AI? What are the risks? What are the benefits? What would responsible engagement with generative AI even look like?
- To be able answer these prior questions, what do we need to know first? How would we go about acquiring that knowledge?
Assignment:
Part One: I’d like to devote time on the first day for students to introduce themselves. But there’s a catch: You are not allowed to introduce yourselves in your own words. Instead, you should use generative AI to create an introduction for you. The introduction can be text, an image, video, audio, or a combination of these formats. The introduction should address your background, why you are interested in this class, and your learning goals for the class.
If your introduction includes images, video, or audio, please email me a copy or a link to the material before 9am on Jan. 14 so that I can include the material within our class slides.
As an LMU student, you have access to Microsoft Copilot, available here, but you are free to use any generative AI tools that you would like to create your introduction. Feel free to experiment with different tools and approaches. Although the introduction should be composed of material generated by AI, you should feel free to cut up, edit, and recombine the material as you see fit.
Readings:
Edward J. McIntyre, Los Angeles County Bar Association, Ethical Pitfalls of Generative AI
Jonathan Lent and Kyu Young Paek, ABA Business Law Today, Common Issues That Arise in AI Sanction Jurisprudence and How the Federal Judiciary Has Responded to Prevent Them
Jeremy Sheff, Generative AI in the Law School Classroom
Colin Cornaby, In the Future All Food Will Be Cooked in a Microwave, and if You Can’t Deal With That Then You Need to Get Out of the Kitchen
Jan. 21, 2026
This week, we will continue our discussion of generative AI and the legal profession, starting close to home with law school by finishing our drafts and discussion of generative AI policies for law school classes.
The assignments for the groups assigned at the end of last class are:
Groups 1, 3: Draft a generative AI policy for this class
Groups 2, 4: Draft a default generative AI policy for seminar classes
Group 5: Draft a default generative AI policy for doctrinal classes
To prepare for class on Wednesday, students should take notes that address the following questions:
- What problems arise, if any, from a policy that allows unrestricted use of generative AI?
- What problems arise, if any, from a policy that bans all use of generative AI?
- How might these problems be mitigated through policy design?
- To design a better policy, what information, skills, or resources would be helpful?
At the start of class, each group will have 15 minutes to share notes with one another and create a draft policy. Each group will then present their draft policy to the class, along with their answers to the questions above.
Each of the first few weeks of class will also include some time dedicated to learning about how machine learning and generative AI tools are built and function under the hood.
The rest of the class will be devoted to a broader discussion of generative AI rules and policies for the legal profession. Included in the readings below are websites that have collected examples of lawyers filing court documents that included AI-generated hallucinations, as well as examples of courts issuing standing orders and local rules regarding the use of AI by lawyers. For class, you’re not expected to read through all of the examples on these websites. Instead, try to skim through a random selection of examples to get a sense of the types of issues that have arisen so far. Take notes on what stands out to you, what questions you have, what patterns you notice, and what additional information you would like to learn. Our discussion will start with students being randomly called on to share their notes and observations so that we can collectively get a better sense of the landscape of the issues and responses that have arisen so far.
Readings:
Damien Charlotin, Website, AI Hallucination Cases
Ropes & Gray, Standing Orders and Local Rules on the Use of AI
The State Bar of California Standing Committee on Professional Responsibility and Conduct, Practical Guidance for the Use of Generative Artificial Intelligence in the Practice of Law
Colin Doyle, Automation and Access to Justice, pgs. 61-75 (2025). I’m a little sheepish about assigning my own work as reading, but this passage is just a succinct, accessible introduction to how LLMs work and their limitations for legal reasoning. Anything I assign in class that I’ve written should be open to challenge and critique as much as anyone else’s work. I imagine (or at least hope) that I am my own worst critic.
Jan. 28, 2026
In class this week, we will start by continuing our discussion from last week regarding generative AI policies for the law schools and the legal profession. Then, we will take a moment to understand the fundamentals of what machine learing is and how machine learning models are trained. Finally, we will turn to the topic of experimental design and how to design experiments to test hypotheses about AI and law. It’s an information-dense week, but it will provide a foundation that will enrich our discussions in the weeks to come.
Readings:
DOWNLOAD ALL READINGS FOR JAN. 28 HERE
Machine Learning: A Primer: an introduction for both technical and non-technical readers
Lizzie Turner, Medium: Artificial Intelligence (May 26, 2018)
Read all.
An Introduction to Statistical Learning with Applications in R
Gareth James, Daniela Witten, Trevor Hastie, & Robert Tibshirani (2021)
Read Introduction pages 1-9 (stop at “Who Should Read This Book?), 15-42.
Teaching Empirical Legal Research Study Design: Topics & Resources (2015)
Sarah E. Ryan
Read all.
Feb. 4, 2026
This week, we will continue our discussion of experimental design and how to design experiments to test hypotheses about AI and law. The readings for this week are light because your main assignment is to design a small, informal experiment to test a hypothesis about generative AI and the law.
Readings:
To inspire you to do great work: Richard Hamming, You and Your Research (1986)
To give you a sense of structure for experimental design and reporting (along with citations to related literature that you might find useful): Matthew Dahl, Bye-bye, Bluebook? Automating Legal Procedure with Large Language Models (2025)
Assignment:
Informal Experiment Design
Due on Tuesday, February 3 by midnight, the night before class via email. Please attach your experiment design notes as a Word document or PDF.
Your assignment is to design a small, informal experiment about language models and law. Think of it as a prototype for a publishable study idea: you’re kicking the tires on a research question and testing out ideas for experimental design. In class on Wednesday, we will workshop some of your experiment designs together and conduct at least one of the experiments live as a class.
Your design document should include the following:
Title (give your experiment a name)
Research question
Hypothesis
Experimental design
Limitations and Future Directions
I have created a sample design document to illustrate what is expected. You can find it here.
Some notes:
Research Question: Select a research question that genuinely interests you. What is a question about generative AI and the law that you want answered? What do you wonder about? Do not use generative AI to come up with your research question as it should be something that you care about.
Hypothesis: Your hypothesis should be a clear, testable statement that predicts an outcome.
Experiment Design: Describe how you will test your hypothesis, including the language models you will use and the interactions you will have with them.
You may use generative AI to help you think through experimental design. This is a new kind of task for most people. Language models can be useful for pointing out blind spots, suggesting controls, or helping you see alternative designs you hadn’t considered. But engage critically with any suggestions the model makes. You are responsible for the final design of your experiment. You should not include any experimental design or analysis choice that you cannot fully explain and defend.
Limitations and Future Directions This is really important! Your experiment won’t be able to fully answer your research question. What are the limitations of your design? What might complicate your findings? How might your results not provide a full explanation of the question you’re trying to ask? How could future work build on your experiment to provide a more complete answer to your research question?
Feb. 11, 2026
This week, we’ll turn to AI tools that have been built specifically for doing legal work and consider how to engage with these tools in a critical way to expose their vulnerabilities. The purpose of this lesson is to introduce you to red teaming as a philosophy for critically understanding and engaging with legal tech.
As you do this week’s readings, keep in mind that your role for this week’s class is to be a member of a red team that maliciously and benevolently stress-tests legal AI software, trying to discover weaknesses.
Readings:
Blake Bullwinkel, et al., Lessons From Red Teaming 100 Generative AI Products, arXiv preprint, (2025).
Varun Magesh, et al., Hallucination-Free? Assessing the Reliability of Leading AI Legal Research Tools, J. Emp. L. Studies (2025).
Assignment:
After finishing this week’s reading, your job is to get onto WestLaw and LexisNexis and start red-teaming on your own, trying to get their generative AI tools to fail by drawing erroneous conclusions, hallucinating information, or otherwise making errors or misbehaving. Take notes on any methods that produce an interesting or unexpected result. In class, students will be selected at random to share their methods, and the class will collectively try to replicate their results and test out alternatives.
Feb. 18, 2026
This week, we will focus on the technology of language models and how the legal profession is engaging with AI.
Readings:
Cole Stryker, What are large language models?, IBM.
LexisNexis, Aspen Publishing, & Themis Bar Review, Bridging the AI Readiness Gap: A 360-Degree Assessment of the Needs of Law Schools, Students, and Employers(2025).
Thomas Reuters Institute, 2025 Generative AI in Professional Services Report (2025).
Feb. 25, 2026
Going forward for the semester, we will have fewer reading assignments as students are expected to begin doing their own independent research and reading for their projects and papers. As you explore potential research questions and topics, I encourage you to reach out to me for help finding relevant literature and resources. I will also be available to help you think through your research questions and design your projects. We will continue to dedicate time at the start of each class for students to share their research questions, ideas, and progress with one another. This will be an opportunity for you to get feedback from your peers and to learn about what others are working on.
This week, you will be programming your first computer applications. How exciting! The term ”vibe coding” is a bit of a pejorative term, and ”vibe coders” are often rightly criticized for mindlessly using LLMs to create programs that they think work but that are laden with errors and vulnerabilities. But just because coding with AI assistance can be done in a mindless way doesn’t mean that it can’t be done in a thoughtful way. This is the same issue we’ve confronted with lawyers use of generative AI more generally. When used thoughtfully and critically, generative AI can be a helpful tool for making basic programming more accessible.
My goal in this lesson is to set you up with the skills – and an example portfolio project – that will set you apart as you apply for jobs and enter the legal profession. As we learned in our readings last week, employers are eager to hire candidates with AI skills and eager to integrate AI tools into their work, but they are disappointed by the lack of AI skills among law school graduates. This week, we will start to address that gap by learning how to use generative AI tools to create simple applications that can be used in legal work. We will also discuss how to critically evaluate and test the applications you create to ensure that they are reliable and secure.
Class this week will be broken up into two parts. The first part will be a demonstration in which I will use generative AI to create a simple, useful application. The second part will be a workshop in which you will use generative AI to create your own simple application, either independently or with a partner. I will be available to help you troubleshoot and think through your projects as you work on them.
Readings:
Ethan Mollick, A Guide to Which AI to Use in the Agentic Era, One Useful Thing (Feb. 17, 2026)
Anthropic, How Claude Code Works
Anthropic, Best Practices
Assignment:
You need to install some software on your computer before class. I will send out instructions for how to do this in a separate email. Please make sure to complete the installation before class so that you can participate in the workshop portion of the lesson.
You should also decide on an application that you want to create for the workshop. The application should be useful. The goal is to create something that can solve a real problem. But limit the scope to doing one thing. Even if you have plans to build out a larger application over time, you want to focuse on creating one feature or function and then building from there. Some examples of applications that came up from our class discussion include:
Tracking weather data and event from calendar and make outfit suggestions
Intake process - alternative to web form or initial interview
To-do list organizer based on your actual performance vs. expectations
Save sources and then retrieve relevant information
Quick social media scroll for information about a person
App that optimizes search queries based on website / overcome navigation issues
Deposition summaries - with pincites to transcript that are also hyperlinks to the exact text moment or quote, closing down reference to any sources, has to be able to parse through nonsense
Deposition reducer
Automatically organize folders or emails
Interactive audio flashcards
Gather resources related to a concept to understand
Mar. 4, 2026
No class (Spring Break).
Mar. 11, 2026
As previously discussed, we will have fewer reading assignments for the rest of the semester as students are expected to be doing more independent research and reading for their projects and papers. This week, we will have a discussion about how to find relevant literature and resources for your research projects. We will continue to discuss the role of legal technology in the legal profession.
Readings:
This is a Twitter post that went viral recently. Many of you may have seen it already. Before class, I would like you to read through it and take a pause to reflect (and take notes!) on the following thoughts and questions:
For a moment, forget about any ideas of what the future will be or how AI will evolve. Instead, let’s assume that the technological developments that we’ve seen so far this semester are all that there will be. With that in mind, what skills will you need to learn that previous generations of lawyers didn’t need to learn? What will law firms and legal departments need to do? What are the risks and benefits of these changes?
It is very important for this exercise that you don’t imagine AI capabalities that don’t exist yet. The point of this exercise is to think critically about the changes that are already here and how to adapt to them, not to speculate about what might be possible in the future.
Mar. 18, 2026
Assignment:
This week, you should focus on doing research related to your final paper and presentation. By midnight on Tuesday, March 17, please email me a research update that includes the following:
A description of the current draft of your research question. At this stage, you are not expected to have a final thesis or argument, but you should have a clear sense of the question you are trying to answer and why it is important.
A research plan. Please do not treat this as busy work. Write this up primarily as a document for yourself, not for me. The purpose of this assignment is to help you think through how you will go about doing research for your paper. By reading your plan, I should be able to help direct you to relevant literature and resources, and I should be able to give you feedback on how to improve your research plan.
If you are working with a partner or in a group for your final paper and presentation, please submit one research update per group rather than one per person.
Mar. 25, 2026
Because last week’s class was cancelled, there is no new reading assignment for this week. Students can revise and resend their research update from last week if they have continued to make progress.
Apr. 1, 2026
You should continue to work on your research and writing for your final paper and presentation.
Apr. 8, 2026
Student Presentations (No reading assignment)
Apr. 15, 2026
Student Presentations (No reading assignment)