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Simulations & Synchronous Work (Class Time)

Synchronous in-person class time is unique for one reason above all others. We have the benefit of each other’s company. Consequently, we will use this precious resource to do things we cannot do alone. We will simulate ten potentially precedent-making cases from trial through appeal. The fidelity of these simulations will vary from tabletop exercise to full oral arguments. Simulations will be graded pass-fail.

Though we will base simulations on real-world cases, at some point the two will diverge (e.g., when the fates step in to ensure simulated cases survive summary judgment and no one settles). At best, our simulations will predict the future, at worst, they become alternative histories. Because of how quickly things are moving, this list is subject to change up until the day we introduce a case.

Case Simulations

1. Tremblay v. OpenAI
2. New York Times v. Microsoft
3. Walters v. OpenAI
4. Andersen v. Stability AI
5. Getty Images (US) v. Stability AI
6. UMG Recordings v. Suno
7. IN RE: Realpage, Inc., Rental Software Antitrust Litigation
8. Mobley v. Workday
9. Banner v. Tesla
10. People v. Sol Ecom Inc.

• Each case will involve four stages. Each stage will occupy part of one class session. Fun fact: many of these cases are tracked by the AI Case Bot or can be found in the Database of AI Litigation.

Simulation Stages

1. Context & Assignment
2. Motions (including proposed jury instructions)
3. Trial
4. Appeal (oral argument)

A detailed explanation of these stages can be found below under Anatomy of Case Work.

Cases will be stacked such that we engage with different stages from different cases during a single class session.

In addition to our ten cases, students will also act as legislators with the ability to propose and amend various AI legislation. Working with a simplified version of Robert’s Rules of Order, we will debate as many such bills as time allows. A non-exhaustive list of potential legislation include:

• California’s Safe and Secure Innovation for Frontier Artificial Intelligence Models Act.
• portions of the EU’s AI Act
• The proposed USA NO FAKES Act
• Tennessee’s ELVIS Act

Below is a schedule showing which cases fall on which weeks, along with the stages we will cover. Legislative sessions are simply marked LS. The bill(s) and version(s) to be addressed in each legislative session will be announced a week prior. TC stands for “traditional class” and will involve a mix of lecture and discussion. Each row corresponds roughly to a quarter of our two-hour meeting time (~30min). The canary yellow columns are weeks we don’t have class, and Week 7 (10/15) is a Monday schedule on Tuesday.

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Asynchronous (Floating) AI Work

As a 3-credit hybrid course, students should expect an intensive asynchronous component.

As per ABA Standard 310(b), students should expect to spend roughly 10 hours and 20 minutes a week engaging with this course and its materials. This includes our two-hour synchronous time together.

In addition to preparing for simulations, asynchronous work will also involve a parallel track of AI Work in which students will be asked to work with, learn about, and create AI tools. There are ten weeks of such work. This work “floats” in that studens are to work through these assignments only on weeks when they aren’t activly simulating a case, shifting their due dates accordingly. More details below.

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Grading

As a capstone evaluation, students will write a legislative memo briefing a hypothetical legislator on AI issues. The memo will be anonymously graded using the rubric found below, and it is expected students will draw heavily from our legislative simulations.

Simulations and AI work will be graded pass-fail.

A student fails a simulation when the instructor finds that their performance would have been deemed negligent within the world of the simulation. This mirrors the standard used in most legal malpractice claims, but it does NOT require there to be actual harm to the hypothetical client, and the instructor will assume a reasonable student. That is, a student could win their case and still fail if the instructor believes they would have been found negligent in-game, but their actions will be measured against a reasonable student, not a reasonable practicing attorney.

AI work will be evaluated based on AI-mediated reflections. That is, every week you’ll be asked to “talk” with an AI about your work and transcripts of these conversations will be reviewed by your instructor. It’s just good old journaling but with an AI twist. To pass, a student’s reflections must accurately reflect their work, they must show completion of the assigned work and a good-faith attempt to engage with same. Note: absence of evidence will be taken as evidence of absence. “If you don’t mention it, it didn’t happen.”

The course grade is a weighted average of a student’s memo grade and their other work. It is calculated using the following weights. Note: a pass is counted as a 100%, with failures earning 0%.

Course Grade =
Simulation Stage B * 0.1 +
Simulation Stage C * 0.1 +
Simulation Stage D * 0.1 +
Weekly Reflections * 0.1 +
Legislative Memo * 0.6

This score is translated into a traditional letter grade, with grades capped at an A.

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Details

Let’s take some time to dig into the details.

Anatomy of Simulations (Case Work)

A number of our simulations resemble tabletop role playing games like Dungeons & Dragons with the instructor acting as the game master (GM). This format allows us to inhabit various roles within the justice system without the need to make every simulation a high-fidelity dress rehearsal. There is no expectation that students have any prior experience with tabletop role playing games. Hopefully, the game mechanics will be easily understood after exposure to a few examples. See below (and in-class).

A. Context & Assignment

The case and its context will be introduced during class time. This will include a very brief orientation involving the relevant legal standards. Each case will be assigned two attorneys, one for each side of the case. Students may approach the instructor beforehand about assignments and are encouraged to do so if they foresee scheduling conflicts (e.g., they won’t be able to argue on a specific date because of a pre-scheduled event like a wedding). They are also encouraged to volunteer for cases they are interested in or that they would like to avoid (e.g., because of past personal trauma). Assignments will be made randomly after taking into consideration any student preferences (i.e., excluding those for whom it wouldn’t work or favoring those with an expressed preference).

Following class, all students are asked to engage with the case materials. The two student attorneys, however, are tasked with preparing their case. All other students need to be prepared to rule on questions of law relating to the case. That is, they should be ready to play the part of a fractional judge in Stage B. Unlike the attorneys, they won’t need to talk, just decide.

B. Motions (including proposed jury instructions)

In the time between stage A and stage B, each of the two student attorneys must complete their own case sheet. Functionally, the sheet acts as a proposed set of jury instructions (the rows in the elements column) and a witness list (subsequent columns), along with expected testimony in lined up with its source and the element it aims to bolster or undermine. Student attorneys must have their case sheet turned into the instructor, with a copy to opposing counsel, before 9am on the day of class.

In class, the instructor will use the two case sheets to run a low-fidelity tabletop simulation of motion practice, acting both as judge and game master. The end goal will be to produce a single case sheet which will serve to drive the trial simulation.

The simulation might go something like this:

JUDGE/GM: I see we have agreement on all but one of the elements. Counselor, please explain to me why I should take your instruction on element three over the other side’s.

ATTORNEY 1: [Makes an argument. NOTE: Since this is a low-fidelity simulation the argument doesn’t have to be polished, just cogent.]

JUDGE/GM: Attorney Two?

ATTORNEY 2: [counter argument]

JUDGE/GM: [speaking to the rest of the class] How many of you think Attorney Two had the better argument?

CLASS: [Using an online polling tool the class registers their opinions. The number of affirmative votes plus 2 is the argument’s difficulty class. 2 means no one thinks Attorney Two had the better argument, 20 means 18 people did. NOTE: the “2” might change based on how many folks are present we’re just trying to make the math easy for a 20-sided dice roll.]

JUDGE/GM: [Decides on a modifier between 0 and 10 based on their assessment of the relative strength of Attorney 1’s argument, where 0 means they didn’t give it much weight and 10 means they gave it a lot of weight] Attorney one, your modifier is X. Roll.

ATTORNEY 1: [Rolls a 20-sided dice. If their roll plus their modifier is larger than or equal to the argument’s difficulty class, the Judge/GM will implement some version of their suggestion]…

This basic structure will repeat for substantive questions faced by the court. These might include oral motions for summary judgment or to exclude evidence. FWIW, our simulated jurisdiction has procedural rules loosely based on the federal rules, and the GM can always clarify rules upon request. If you’re making a motion based on a particular phrasing be prepared to argue that this language is the rule. The GM will make the final call. Likewise, you can argue for the inclusion of certain truth’s in-game. For example, if one of the real-world parties in your case does something in real life not noted in the case materials, you can argue that it happened in-game too. The GM might shut you down quickly or give you room to argue and put it to the class. One important note: a defendant can never fully succeed on summary judgment or a motion to dismiss. We need the case to survive to trial after all. However, parts of a case may be thrown out esp. if the fates deem them as unnecessary to the course’s learning objectives.

Note: students can always ask the GM to fill in details where you feel there is unnecessary ambiguity and need some context. They will not, however, do your work for you (e.g., tell you what elements to argue for in the jury instructions). Additionally, those students with non-speaking rolls (like fractional judge) may be on the class chat during simulations to ask each other questions and share insights in real time.

C. Trial

We will run a low-fidelity trial simulation in class based on the case sheet that came out of Stage B. The instructor will serve as the JUDGE/GM and the students not arguing the case will serve as the finders of fact.

There will be no opening statements. Rather, the JUDGE/GM will move through each of the sheet’s columns. The simulation might go something like this:

JUDGE/GM: We have here a witness for the plaintiff, and it says they would testify to facts A, B, and C on direct. I think that’s a hard bargain. You need to roll 12 or above for that all to come in. Roll.

ATTORNEY 1: [rolls 20-sided dice]

JUDGE/GM: [provides a brief narration of the outcome based on the roll (e.g., if they rolled 12 or above they describe how all of that evidence came in, under 12 how it didn’t all come in)] Attorney 2, what did you hope to accomplish on cross?

ATTORNEY 2: I want to impeach them and get them to break down on the stand while screaming, “You can’t handle the truth!”

JUDGE/GM: Woah, alright, you have to roll a 20 for that…

After working through all the rows, we’ll break for jury deliberation at which time everyone but the student attorneys will discuss whether or not they think the plaintiff/prosecution met their burden. To make things manageable we may break into small groups and then report back with an online poll. For our purposes, a simple majority will win the day.

In class or shortly afterward, I will inform folks of the exact shape of the appeal. It is this appeal the attorneys will argue in Stage D.

D. Appeal (oral arguments)

This simulation will be of greater fidelity than Stages B and C. It will be in front of a panel of three randomly chosen student judges, drawn from students without an active case. Each attorney will be given ten minutes to speak, during which the judges may pepper them with questions and hypotheticals. The instructor will serve as DM, helping to make things run smoothly and fielding questions about the world as they come up. Attorneys are only allowed paper notes.

Immediately following arguments we will break into a whole class discussion of who won. This discussion will be led by the student judges. They will use the class as a resource to help them decide on their vote. The attorneys may not participate in this discussion.

Note: The role of student judge is not graded. It is simply assumed that as justices on our highest court you will live up to expectations. This mirrors the arrangement of US supreme court justices who lack a binding code of ethics.

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Anatomy of AI Work

Nearly every week students will be assigned to create an AI workflow using the LIT Prompts extension. Most of these exercises will draw from 50 Days of LIT Prompts. This will require students to sign up for OpenAI API access and spend a nominal amount on API costs (estimated to be <$20). If this presents a financial hardship, please reach out to the instructor as limited subsidies are available. It may also be possible for students to use a free open-weight model. These assignments will include associated media consumption including readings and asynchronous lectures. There are ten weeks of such work. This work “floats” in that studens are to work through these assignments only on weeks when they aren’t activly simulating a case, shifting their due dates accordingly.

Students will make clear what work they have done as part of weekly reflections. These will be AI-mediated chats (i.e., students will engage a custom GPT in a guided conversation about their week’s work.

In addition to learning about AI and using it to build tools, students will make use of AI to interact with case materials. In addition to independent legal research, expected of student attorneys, all students will engage with cases by reading provided matterials and engaging in one of the following AI interactions:

• Distill & Question a Docket. Have an AI summarize filings and ask questions of them.
• Go Socrates on a Docket. Have an AI engage the student in a Socratic dialogue based on filings.
• Moot a Case based on a Docket. Play the part of an attorney arguing one side of the case before an AI-simulated judge.

Student attorneys are expected to choose two of the above for their case.

Students will provide their instructor with links to their AI interactions, including their weekly reflections and case-related discussions by 9am on the day of class.

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Office Hours/Game Time

Unless otherwise stated, office hours will take place in suite 685 on Mondays between 11am and 1pm. This time is meant as a drop in community time and will likely take place in the LIT Lab space unless a conversation warrants privacy. Use this time to talk with your instructor and fellow students about your class work, or play with LEGO and talk about your plans for the future. Most weeks, we’ll have a chess board, and the instructor can be convinced to bring in a battle deck of Pokémon cards (his kids love the game so he has recently learned). Students are encouraged to bring in their own board games and coordinate with other students to reach critical mass when needed. As your memo will be graded anonymously, and other work is pass-fail, there’s not a lot of advantage to be gained (grade wise) by getting your instructor to like you. So, it is hoped folks will take advantage of this time for what it is meant to be, an opportunity to learn and build community.

Of course, substantive questions about class will take precedence over “having fun,” but there’s no rule against asking/answering questions while playing with LEGO. Additionally, if you would like to meet at some time outside of office hours, you can book a time using the link found on our Canvas home page.

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Legislative Memo Grading Rubric

Students must write a memo briefing hypothetical legislators or rule makers on issues of AI relevant to either: one of the “AI bills” discussed in class; or a proposed AI legislation/regulation of their choosing. If the latter, they must first get permission from their instructor on the legislation/regulation. This choose-your-own option may focus on real or imagined legislation, including that of the student’s own making. Memos will be graded against four equally-weighted categories. The average score across these categories will be used as the “Memo Grade” when calculating ones final grade. The following rubric lays out the scoring criteria:

All memos are due on December 12th at 12pm. However, given our legislative simulations at the close of the semester, there is no reason they cannot be turned in earlier. That is, if one is keeping up with class work, one will have done most, if not all, of the work needed to write their memo by the close of classes.

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Accommodations

For what it’s worth, I made use of accommodations when I was a law student, and it was a life saver. That being said, if you anticipate issues related to the format or requirements of this course due to a disability, you should contact the Law School’s Dean of Student Office for further information and assistance, including information on disability-related accommodations. We can then plan how best to coordinate any accommodations. Additionally, regardless of your accommodations status, if you’re having an issue with the nature of the course materials or expectations, or anticipate having one, please let me know, and we can work to find a solution.

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Detailed Schedule with Links

This is a brand new class. So expect that some of the details below may change during the semester. This page will have the most up-to-date schedule and links.

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Wk1: 2024-08-26 (skips next Monday)

Here is this week’s slide deck.

Tremblay v. OpenAI. GPT Summary of the case:

Paul Tremblay and Mona Awad have filed a class action lawsuit against OpenAI, Inc. and related entities. They allege that OpenAI infringed their copyrights by using their books, without consent, as part of the training data for ChatGPT’s language models (GPT-3.5 and GPT-4). The plaintiffs claim that this training enabled ChatGPT to generate summaries and outputs that are based on their copyrighted works, constituting direct and vicarious copyright infringement. They also accuse OpenAI of violating the Digital Millennium Copyright Act (DMCA) by removing copyright management information from their works and engaging in unfair competition. The plaintiffs seek damages and injunctive relief.

Our simulation will start with facts based on the case as it stood at the filing of these documents:

• Complaint
• Motion to Dismiss

FWIW, you can find the real-world docket here.

Download each of the above files, and use one (or more) of the GPTs below to engage with them. If you choose Socrates or Moot, you’ll want to read through them first, and if you use Distill & Question, you’ll need to read them afterward. Every student has to turn in a transcript for at least one interaction. If you’ve been assigned as an attorney to this case, you must turn in a transcript of your MOOT interaction(s).

• GPT: Distill & Question a Docket
• GPT: Go Socrates on a Docket
• GPT: Moot a Case based on a Docket

“Floating” AI Work: Remember, if you are activly working a case, you don’t have to do this work until after you finish your case, hence the “floating” modifier.

• Work through Week 1 of 50 Days of LIT Prompts.
• Read On the Dangers of Stochastic Parrots 🦜
• Read ChatGPT Is a Blurry JPEG of the Web (Internet archive copy)
• Read Will A.I. Become the New McKinsey? (Internet archive copy)

Weekly Reflection: This is how we know what you worked on. Remember, absence of evidence will be taken as evidence of absence. “If you don’t mention it, it didn’t happen.”

• GPT: Weekly Reflection

turn in your assignments | contents

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Wk2: 2024-09-09

New York Times v. Microsoft. GPT Summary of the case:

The New York Times Company has filed a lawsuit against Microsoft Corporation and OpenAI, alleging that they unlawfully used The Times’ copyrighted content to develop and deploy Large Language Models (LLMs) like ChatGPT. The Times claims this constitutes copyright infringement, violations of the Digital Millennium Copyright Act (DMCA), and unfair competition through misappropriation. Microsoft has responded with a motion to dismiss several of these claims, arguing that The Times has not provided specific instances of infringement, that the use of the content for training LLMs is protected as fair use, and that the misappropriation claim is preempted by copyright law.

Our simulation will start with facts based on the case as it stood at the filing of these documents:

• Complaint
• Motion to Dismiss

FWIW, you can find the real-world docket here.

Download each of the above files, and use one (or more) of the GPTs below to engage with them. If you choose Socrates or Moot, you’ll want to read through them first, and if you use Distill & Question, you’ll need to read them afterward. Every student has to turn in a transcript for at least one interaction. If you’ve been assigned as an attorney to this case, you must turn in a transcript of your MOOT interaction(s).

• GPT: Distill & Question a Docket
• GPT: Go Socrates on a Docket
• GPT: Moot a Case based on a Docket

“Floating” AI Work: Remember, if you are activly working a case, you don’t have to do this work until after you finish your case, hence the “floating” modifier.

• Work through Week 2 of 50 Days of LIT Prompts.
• TBD

Weekly Reflection: This is how we know what you worked on. Remember, absence of evidence will be taken as evidence of absence. “If you don’t mention it, it didn’t happen.”

• GPT: Weekly Reflection

turn in your assignments | contents

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Wk3: 2024-09-16

Walters v. OpenAI. GPT Summary of the case:

This case involves Mark Walters suing OpenAI for defamation after a journalist, Fred Riehl, used OpenAI’s ChatGPT to summarize a legal complaint. ChatGPT erroneously generated a summary falsely stating that Walters had embezzled funds from the Second Amendment Foundation. Walters claims that these statements were entirely false and damaging to his reputation. He is seeking damages for libel. OpenAI has moved to dismiss the case, arguing that the court lacks jurisdiction and that Walters has not sufficiently established the elements of a defamation claim, including publication and actual malice​​.

Our simulation will start with facts based on the case as it stood at the filing of these documents:

• Complaint
• Motion to Dismiss

FWIW, you can find the real-world docket here.

Download each of the above files, and use one (or more) of the GPTs below to engage with them. If you choose Socrates or Moot, you’ll want to read through them first, and if you use Distill & Question, you’ll need to read them afterward. Every student has to turn in a transcript for at least one interaction. If you’ve been assigned as an attorney to this case, you must turn in a transcript of your MOOT interaction(s).

• GPT: Distill & Question a Docket
• GPT: Go Socrates on a Docket
• GPT: Moot a Case based on a Docket

“Floating” AI Work: Remember, if you are activly working a case, you don’t have to do this work until after you finish your case, hence the “floating” modifier.

• Work through Week 3 of 50 Days of LIT Prompts.
• TBD

Weekly Reflection: This is how we know what you worked on. Remember, absence of evidence will be taken as evidence of absence. “If you don’t mention it, it didn’t happen.”

• GPT: Weekly Reflection

turn in your assignments | contents

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Wk4: 2024-09-23

Andersen v. Stability AI. GPT Summary of the case:

The plaintiffs are artists who allege that their copyrighted works were used without permission to train AI models, specifically Stability AI’s “Stable Diffusion,” Midjourney’s product, and DeviantArt’s “DreamUp.” These AI models generate images based on user prompts, utilizing billions of images (including the plaintiffs’) as training data. The plaintiffs claim that the defendants have violated copyright laws, including the Digital Millennium Copyright Act (DMCA), and have also infringed on their rights of publicity, engaged in unfair competition, and more. They seek damages, injunctive relief, and a halt to these practices, which they argue threaten the livelihood of artists by flooding the market with AI-generated images that derive from their original works.

Our simulation will start with facts based on the case as it stood at the filing of these documents:

• Complaint
• Motion to Dismiss

FWIW, you can find the real-world docket here.

Download each of the above files, and use one (or more) of the GPTs below to engage with them. If you choose Socrates or Moot, you’ll want to read through them first, and if you use Distill & Question, you’ll need to read them afterward. Every student has to turn in a transcript for at least one interaction. If you’ve been assigned as an attorney to this case, you must turn in a transcript of your MOOT interaction(s).

• GPT: Distill & Question a Docket
• GPT: Go Socrates on a Docket
• GPT: Moot a Case based on a Docket

“Floating” AI Work: Remember, if you are activly working a case, you don’t have to do this work until after you finish your case, hence the “floating” modifier.

• Work through Week 4 of 50 Days of LIT Prompts.
• TBD

Weekly Reflection: This is how we know what you worked on. Remember, absence of evidence will be taken as evidence of absence. “If you don’t mention it, it didn’t happen.”

• GPT: Weekly Reflection

turn in your assignments | contents

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Wk5: 2024-09-30

Getty Images (US) v. Stability AI. GPT Summary of the case:

Getty Images has filed a lawsuit against Stability AI, Inc., accusing the company of unlawfully using over 12 million of its copyrighted images, along with associated captions and metadata, to train its AI model, Stable Diffusion. Getty Images claims that Stability AI copied these images without permission, removed or altered Getty’s copyright management information, and misused Getty’s trademarks, including watermarks. The complaint asserts multiple legal claims, including copyright infringement, trademark infringement, and unfair competition. Getty Images is seeking damages, a permanent injunction against Stability AI, and the destruction of all versions of the AI model trained on its content.

Our simulation will start with facts based on the case as it stood at the filing of these documents:

• Complaint
• Motion to Dismiss

FWIW, you can find the real-world docket here.

Download each of the above files, and use one (or more) of the GPTs below to engage with them. If you choose Socrates or Moot, you’ll want to read through them first, and if you use Distill & Question, you’ll need to read them afterward. Every student has to turn in a transcript for at least one interaction. If you’ve been assigned as an attorney to this case, you must turn in a transcript of your MOOT interaction(s).

• GPT: Distill & Question a Docket
• GPT: Go Socrates on a Docket
• GPT: Moot a Case based on a Docket

“Floating” AI Work: Remember, if you are activly working a case, you don’t have to do this work until after you finish your case, hence the “floating” modifier.

• Work through Week 5 of 50 Days of LIT Prompts.
• TBD

Weekly Reflection: This is how we know what you worked on. Remember, absence of evidence will be taken as evidence of absence. “If you don’t mention it, it didn’t happen.”

• GPT: Weekly Reflection

turn in your assignments | contents

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Wk6: 2024-10-07

UMG Recordings v. Suno. GPT Summary of the case:

The plaintiffs are suing Suno, Inc. for copyright infringement. They allege that Suno, which operates a generative AI service that creates digital music files, has unlawfully copied and used their copyrighted sound recordings to train its AI model. The plaintiffs argue that Suno’s AI-generated music files closely mimic these recordings, which violates their exclusive rights under copyright law. They seek injunctive relief and damages, asserting that Suno’s actions could harm the music industry by saturating the market with AI-generated music that competes directly with human-created works. The plaintiffs also challenge Suno’s defense of fair use, arguing that Suno’s copying is not transformative and poses significant harm to the market for original sound recordings.

Our simulation will start with facts based on the case as it stood at the filing of these documents:

• Complaint
• Motion to Dismiss

FWIW, you can find the real-world docket here.

Download each of the above files, and use one (or more) of the GPTs below to engage with them. If you choose Socrates or Moot, you’ll want to read through them first, and if you use Distill & Question, you’ll need to read them afterward. Every student has to turn in a transcript for at least one interaction. If you’ve been assigned as an attorney to this case, you must turn in a transcript of your MOOT interaction(s).

• GPT: Distill & Question a Docket
• GPT: Go Socrates on a Docket
• GPT: Moot a Case based on a Docket

“Floating” AI Work: Remember, if you are activly working a case, you don’t have to do this work until after you finish your case, hence the “floating” modifier.

• Work through Week 6 of 50 Days of LIT Prompts.
• TBD

Weekly Reflection: This is how we know what you worked on. Remember, absence of evidence will be taken as evidence of absence. “If you don’t mention it, it didn’t happen.”

• GPT: Weekly Reflection

turn in your assignments | contents

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Wk7: 2024-10-15 (Monday schedule on a Tuesday)

IN RE: Realpage, Inc., Rental Software Antitrust Litigation. GPT Summary of the case:

The plaintiffs in a lawsuit accuse RealPage, Inc., and several student housing lessors of conspiring to fix rental prices using RealPage’s revenue management software, which they claim facilitated coordinated pricing strategies in violation of antitrust laws. The defendants have filed a motion to dismiss, arguing that the plaintiffs lack concrete evidence of a conspiracy and that using the software for price optimization is not inherently collusive. The defendants assert that the plaintiffs’ allegations are speculative and fail to demonstrate a violation of the Sherman Act or state antitrust laws.

Our simulation will start with facts based on the case as it stood at the filing of these documents:

• Complaint
• Motion to Dismiss

FWIW, you can find the real-world docket here.

Download each of the above files, and use one (or more) of the GPTs below to engage with them. If you choose Socrates or Moot, you’ll want to read through them first, and if you use Distill & Question, you’ll need to read them afterward. Every student has to turn in a transcript for at least one interaction. If you’ve been assigned as an attorney to this case, you must turn in a transcript of your MOOT interaction(s).

• GPT: Distill & Question a Docket
• GPT: Go Socrates on a Docket
• GPT: Moot a Case based on a Docket

“Floating” AI Work: Remember, if you are activly working a case, you don’t have to do this work until after you finish your case, hence the “floating” modifier.

• Work through Week 7 of 50 Days of LIT Prompts.
• TBD

Weekly Reflection: This is how we know what you worked on. Remember, absence of evidence will be taken as evidence of absence. “If you don’t mention it, it didn’t happen.”

• GPT: Weekly Reflection

turn in your assignments | contents

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Wk8: 2024-10-21

Mobley v. Workday. GPT Summary of the case:

Derek L. Mobley filed a class-action lawsuit against Workday, Inc., alleging that its AI-based job screening tools discriminate against African-Americans, individuals over 40, and those with disabilities, violating federal laws including Title VII, the ADEA, and the ADAAA. Mobley claims these tools disproportionately disqualify people in these groups from employment. In response, Workday filed a motion to dismiss, arguing that Mobley failed to adequately allege that Workday is an “employment agency” under the law and that the discrimination claims are insufficiently supported by facts.

Our simulation will start with facts based on the case as it stood at the filing of these documents:

• Complaint
• Motion to Dismiss

FWIW, you can find the real-world docket here.

Download each of the above files, and use one (or more) of the GPTs below to engage with them. If you choose Socrates or Moot, you’ll want to read through them first, and if you use Distill & Question, you’ll need to read them afterward. Every student has to turn in a transcript for at least one interaction. If you’ve been assigned as an attorney to this case, you must turn in a transcript of your MOOT interaction(s).

• GPT: Distill & Question a Docket
• GPT: Go Socrates on a Docket
• GPT: Moot a Case based on a Docket

“Floating” AI Work: Remember, if you are activly working a case, you don’t have to do this work until after you finish your case, hence the “floating” modifier.

• Work through Week 8 of 50 Days of LIT Prompts.
• TBD

Weekly Reflection: This is how we know what you worked on. Remember, absence of evidence will be taken as evidence of absence. “If you don’t mention it, it didn’t happen.”

• GPT: Weekly Reflection

turn in your assignments | contents

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Wk9: 2024-10-28

Banner v. Tesla. GPT Summary of the case:

This case involves a wrongful death lawsuit filed by Kim Banner, representing the estate of her late husband, Jeremy Banner, who died in a collision involving a Tesla Model 3 and a semi-tractor trailer. The complaint alleges that Tesla’s autopilot system failed to prevent the crash due to defective design, and also holds the truck driver, Richard Keith Wood, and his employer, FirstFleet, Inc., responsible for the accident. Tesla denies liability, claiming the vehicle was properly designed and that the accident was caused by Banner’s or others’ negligence. The lawsuit seeks damages under Florida’s Wrongful Death Act.

Our simulation will start with facts based on the case as it stood at the filing of these documents:

• Complaint
• Motion to Dismiss

FWIW, you can find the real-world docket here (search for Case Number: 50-2019-CA-009962-XXXX-MB after completing a CAPTCHA).

Download each of the above files, and use one (or more) of the GPTs below to engage with them. If you choose Socrates or Moot, you’ll want to read through them first, and if you use Distill & Question, you’ll need to read them afterward. Every student has to turn in a transcript for at least one interaction. If you’ve been assigned as an attorney to this case, you must turn in a transcript of your MOOT interaction(s).

• GPT: Distill & Question a Docket
• GPT: Go Socrates on a Docket
• GPT: Moot a Case based on a Docket

“Floating” AI Work: Remember, if you are activly working a case, you don’t have to do this work until after you finish your case, hence the “floating” modifier.

• Work through Week 9 of 50 Days of LIT Prompts.
• TBD

Weekly Reflection: This is how we know what you worked on. Remember, absence of evidence will be taken as evidence of absence. “If you don’t mention it, it didn’t happen.”

• GPT: Weekly Reflection

turn in your assignments | contents

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Wk10: 2024-11-04 (skips next Monday)

People v. Sol Ecom Inc. GPT Summary of the case:

The complaint filed by the People of the State of California, represented by the San Francisco City Attorney, targets several defendants, including Sol Ecom, Inc., Briver LLC, Itai Tech Ltd., and others. The lawsuit alleges that these defendants operate websites that use AI to create nonconsensual intimate images (NCII) of women and girls, commonly referred to as “deepfake pornography” or “deepnudes.” These websites allow users to upload images of clothed individuals and generate fake nude images, often without the subject’s consent. The complaint seeks injunctive relief and civil penalties under California’s Business and Professions Code section 17200 for unlawful, unfair, and fraudulent business practices. The defendants are accused of violating state and federal laws, including those prohibiting the creation and distribution of nonconsensual sexually explicit images.

Our simulation will start with facts based on the case as it stood at the filing of these documents:

• Complaint

Download each of the above files, and use one (or more) of the GPTs below to engage with them. If you choose Socrates or Moot, you’ll want to read through them first, and if you use Distill & Question, you’ll need to read them afterward. Every student has to turn in a transcript for at least one interaction. If you’ve been assigned as an attorney to this case, you must turn in a transcript of your MOOT interaction(s).

• GPT: Distill & Question a Docket
• GPT: Go Socrates on a Docket
• GPT: Moot a Case based on a Docket

Legislation. Next week our legislative session may consider the following:

• TBD

“Floating” AI Work: Remember, if you are activly working a case, you don’t have to do this work until after you finish your case, hence the “floating” modifier.

• Work through Week 10 of 50 Days of LIT Prompts.
• TBD

Weekly Reflection: This is how we know what you worked on. Remember, absence of evidence will be taken as evidence of absence. “If you don’t mention it, it didn’t happen.”

• GPT: Weekly Reflection

turn in your assignments | contents

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Wk11: 2024-11-18

Legislation. Next week our legislative session may consider the following:

• TBD

“Floating” AI Work: Work on any work that is still “floating.”

Weekly Reflection: This is how we know what you worked on. Remember, absence of evidence will be taken as evidence of absence. “If you don’t mention it, it didn’t happen.”

• GPT: Weekly Reflection

turn in your assignments | contents

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Wk12: 2024-11-25

Legislation. Next week our legislative session may consider the following:

• TBD

“Floating” AI Work: Work on any work that is still “floating.”

Weekly Reflection: This is how we know what you worked on. Remember, absence of evidence will be taken as evidence of absence. “If you don’t mention it, it didn’t happen.”

• GPT: Weekly Reflection

turn in your assignments | contents

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Wk13: 2024-12-02

Work on your memo.

“Floating” AI Work: Work on any work that is still “floating.”

Weekly Reflection: This is how we know what you worked on. Remember, absence of evidence will be taken as evidence of absence. “If you don’t mention it, it didn’t happen.”

• GPT: Weekly Reflection

turn in your assignments | contents

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