Artificial Intelligence Law & Policy

1.             Overview.

In this course, each voice in the classroom has something of value to contribute. Please take care to respect the different experiences, beliefs and values expressed by students and staff involved in this course. My colleagues and I support UMass’s commitment to diversity, and welcome individuals regardless of age, background, citizenship, disability, sex, education, ethnicity, family status, gender, gender identity, geographical origin, language, military experience, political views, race, religion, sexual orientation, socioeconomic status, and work experience.

View this syllabus as a guide to the course. It provides important information regarding the course, its assignments, policies, grading, and available university resources. Students should refer to it regularly. Importantly, please note that document is a working document, and may be changed during the course. Throughout the semester, it is possible that a topic may take more time than expected, topics or assignments may change, or a class may be canceled due to a snow day or another emergency. If that is the case, the syllabus will be updated and a revised version will be posted on the Canvas course site.

2.             What, when, where, who.

• Course Title & Number: Artificial Intelligence Law and Policy – COMPSCI 590AD 
• Credits: 1
• Semester and year offered: Spring 2025
• Location: TBD
• Time and days of week: Mondays TBD
• Instructor: Marvin Cable, Esq.
• Email: mcable@umass.edu 
• Phone, Office, Office hours: To schedule time to meet with instructor outside of class please use: https://mcable.youcanbook.me/
  • To communicate with instructor in real time please use Zoom software.  Instructor’s Zoom contact link is: 
    • https://umass-amherst.zoom.us/my/mcable
  • Details of office hours, time, and place will be shared during class. 

3.             Communication policy.

Per the University Email Policy, students are expected to check their email regularly. Instructor will use student’s UMass email address as point of contact in all online tools (notably, Canvas) and as the primary means to contact students individually outside of class.

• Please check the syllabus and course web site before emailing the course staff.
• Course staff typically respond to emails within about one business day, but I (Marvin) do not typically respond to communications after about 5 P.M. or on weekends. There may be other times during the course where response time may be longer, due the nature of Instructor being a working attorney. Course staff tend to get a high volume of email when a deadline is approaching. If students contact us at least two full business day before a deadline, you should get a reply before the exam or deadline. Otherwise we’ll do our best, but no guarantees. 

For more info. on University Email Policy, see: https://www.umass.edu/it/policies/it-policy-email-communications

4.             Critical course information.

Enrollment Requirements: Open to COMP SCI majors -Juniors and Seniors only; and, COMP SCI graduate students.

Prerequisites:  

• UNIV LECT 01 COMPSCI undergrad majors only with C or better in COMPSCI 311, 383, or 360 (or 460)
• UNIV LECT 02 COMPSCI and ECE graduate students
• UNIV+ LECT 01 (UWW) COMPSCI graduate students; as well as any other student at the grad level with instructor permission (including non-matriculated/non-CS students).

Who is this course for? Graduates and Undergraduates with a strong technical background and an interest in the law as it applies to technology.

Course description: This course explores contemporary legal issues and emerging trends related to Artificial Intelligence (AI) technologies, catering specifically to computer science students. The curriculum covers a wide spectrum of legal subjects, aligned with core legal topics, such as criminal law, contracts, torts, constitutional law, property law, professional responsibility, and ethics. Among the specific topics are AI policing, autonomous vehicles, Blackhat AI, AI applications in the medical field, global trends in AI law, copyright implications, patents, trade secrets, products liability, the role of AI within the judicial system, and much more. Notably, this course maintains a dynamic approach, consistently incorporating updates to accommodate emerging issues and trends in this swiftly evolving domain.

The specific objectives for the course are as follows:

• To gain an understanding of and familiarity with Artificial Intelligence legal issues and general legal reasoning.
• To understand the implications that computer science advances have had on law historically.
• To reason about the implications of current and future computer science advances on hypothetical cases, based on past rulings.
• To gain a familiarity and understanding of current and future Artificial Intelligence technologies.
• To gain experience in formal writing, and experience in making well-reasoned arguments both on paper and in class discussion.

5.             Course textbook and other materials.

Required material: There is NO required text-book and all materials will be made available electronically on the course website. There is one optional textbook: Learning Legal Reasoning: Briefing, Analysis and Theory by John Delaney (ISBN-10: 0960851445). Chapter one is available online for free on the author’s web site. We will cover the content from chapter two in class, though students may prefer to purchase and read the author’s version.

This course will be making use of a “flipped classroom” model. Students will be expected to read papers before they attend class. Students who do not attend class will lose points towards their final grade.

6.             Time management and what to expect.

As a general guideline, the university suggests that students spend an additional two to three hours outside of class time per credit hour. This is a one (1) credit course, therefore students should plan to spend two (2) to three (3) hours a week on this class outside of class. In a typical week, students will attend one class and complete the assigned reading and questions before each lecture. The bulk of students time will be spent reading, as will be explained in the first lecture.

7.             Technology in the classroom.

At the start of the semester, laptops, tablets, mobile-devices and the like will be permitted in the classroom. If it becomes clear that they are being used for purposes not directly related to the class, they will be banned . It is unfair to distract other students with Facebook feeds, animated ads, and the like. Regardless, we recommend taking notes by hand, using paper or a tablets. Research suggests that students who take written notes in class significantly outperform students who use electronic devices to take notes.

8.             Attendance.

Students are expected to attend all classes and exams.

If a student will be absent (either from class, or from an exam) due to religious reasons, student must provide instructor with a written list of such dates within one week of enrollment in the course. If student will be absent for a University-related event, such as an athletic event, field trip, or performance, student must notify instructor as soon as possible. If student is absent for health reasons, notify instructor as soon as possible and provide written documentation. If student is absent for other extenuating non-academic reasons, such as a military obligation, family illness, jury duty, automobile collision, etc., notify instructor as soon as possible and provide written documentation. If student must miss an exam for an excusable reason, instructor will work with student to find an acceptable time to take a makeup. If student misses an exam without prior notice, instructor will require an explanation and clear written documentation in order to judge whether the absence is excusable. Exams must be made up within a week unless there are documented exceptional circumstances (such as a hospitalization or extended jury duty). Similarly, if a student misses a class without prior notice, instructor will require an explanation and written documentation in order to judge whether the absence is excusable.

9.             Schedule.

Please see the Canvas site for a class-by-class schedule.

10.          Grading.

This course will be making use of a “flipped classroom” model. Students will be expected to read papers before they attend class. Students who do not attend class will lose points towards their final grade.

Students’ overall grade for the course will be derived from three components. There will be four components to the final grade, each worth one-fourth:

• 25% Class participation
• 25% Panel participant (required to pass)
• 25% Respondent to panel
• 25% Project

Each week of class, we’ll discuss 2–3 papers. For all but two weeks of the class, students’ job is to attend class having already read the assigned papers and to participate in discussion. The quality of this participation is the first quarter. During one week, students’ job will be to lead discussion of the paper as part of a panel with 1–2 other students. During some other week, students’ job will be to be one of main participants that respond to the panel as a class participant. In other words, the most work during the course will be when students serve on a panel. The most work when students aren’t on a panel will be when students are a lead respondent. The other 10 weeks, students will be asked to participate, but not so little that students never speak all semester and not so much that there isn’t space for the panel leads and respondents.

During the first week, the instructor will go over class logistics and provide an introductory lecture. During the second week, instructor will do a sample panel and demonstrate how it should be done. By the second week students will be assigned to a panel; instructor will do best to satisfy students’ preferences.

This is a one credit course and the stakes are not high. But as noted above, if students never serve on a panel (perhaps you oversleep that day), students cannot pass the course. The intention is to give everyone an ”A” grade based on a good effort on a panel and as a respondent and for participating occasionally otherwise. People that clearly don’t prepare for their panel, or clearly don’t prepare for their day as a respondent, or who can’t find a way to comment ever otherwise in class will not get an A.

There are no opportunities for extra credit in this course. Late work will not be accepted.

Incompletes: Incompletes will be granted only in exceptional cases, and only if students have completed at least half the course with a passing grade. Prior to that, withdrawal is the recommended course of action.

• Course Grade Scale
  • A 93-100
  • A- 90-92
  • B+ 87-89
  • B 83-86
  • B- 80-82
  • C+ 77-79
  • C 73-76
  • C-* 70-72
  • D+* 67-69
  • D* 63-66
  • F 0-62
• Please note that a grade of D- is not valid.

Every so often, surveys will be assigned. They are a way for Instructor to see how the class is doing.

11.          Exams.

There will be no exams.

12.          Class participation.

Students will assigned this portion of grade on the basis of presence and participation in class. As stated in this syllabus, students are expected to attend all classes. Further, students are expected to participate in class discussion — posing and answering questions as appropriate. Students will be assigned grades of only full, half, or no credit for class participation. Students may ask at any time what the current estimate of their class participation grade may be. 

Anxiety and disdain for participating in class is real, and very scary to some students. Please talk to the instructor if there are any problems with anxiety or the like. We are not in the business of scaring people. Students thrive in comfortable and supportive environments

13.          University and course policies.

Accommodation statement: The University of Massachusetts Amherst is committed to providing an equal educational opportunity for all students.  If you have a documented physical, psychological, or learning disability on file with Disability Services (DS), you may be eligible for reasonable academic accommodations to help you succeed in this course.  If you have a documented disability that requires an accommodation, please notify me within the first two weeks of the semester so that we may make appropriate arrangements.  For further information, please visit Disability Services (https://www.umass.edu/disability/)

General academic honesty statement: Since the integrity of the academic enterprise of any institution of higher education requires honesty in scholarship and research, academic honesty is required of all students at the University of Massachusetts Amherst.  Academic dishonesty is prohibited in all programs of the University.  Academic dishonesty includes but is not limited to: cheating, fabrication, plagiarism, and facilitating dishonesty.  Appropriate sanctions may be imposed on any student who has committed an act of academic dishonesty.  Instructors should take reasonable steps to address academic misconduct.  Any person who has reason to believe that a student has committed academic dishonesty should bring such information to the attention of the appropriate course instructor as soon as possible.  Instances of academic dishonesty not related to a specific course should be brought to the attention of the appropriate department Head or Chair.  Since students are expected to be familiar with this policy and the commonly accepted standards of academic integrity, ignorance of such standards is not normally sufficient evidence of lack of intent. (http://www.umass.edu/dean_students/codeofconduct/acadhonesty/)

Course-specific academic honesty information: Cheating is usually the result of other problems in school. If a student is unable to keep up with the work for any reason, please contact see the course staff to attempt to work something out. Staff wants to see students succeed and will do everything they can to help each student.

Students may discuss material with others, but work must be student’s own. When in doubt, contact the instructor about whether a potential action would be considered plagiarism. When discussing problems or assignments with others, students may not show any of their work to others. When students ask other peers for help, students must not take notes other than to jot down publicly available references. Use only verbal communication.

If students discuss material with anyone besides the instructor, students should acknowledge collaborators in each write-up. If a student obtains a key insight with help, e.g., through library, work, or a friend, student must acknowledge their source, they must briefly state the insight, and write up the work on their own. In a fair fraction of write-ups, students should provide citations, though students need not cite the course texts.

Students should never misrepresent someone else’s work as their own. It must be absolutely clear what material is student’s original work. Students MUST cite all their sources properly. Students must remove any possibility of someone else’s work from being misconstrued as theirs. Also note that the facilitation of plagiarism, e.g., giving work to someone else, is academic dishonesty as well.

Student must not provide their solutions to others, either directly or via some sort of public posting. Doing so is a violation of the University Honesty Policy’s prohibition against facilitating academic dishonesty.

Plagiarism and other anti-intellectual behavior will be dealt with severely. If a student engages in academic dishonesty, student will almost certainly receive an ‘F’ for the course. Further, if there are formal disciplinary proceedings, instructor will lobby for the maximum possible penalty. Investigating plagiarism is a miserable experience for both instructor and student — students should help by avoiding any questionable behavior.

Other academic regulations: The Office of the Registrar publishes Academic Regulations yearly. Students should be familiar with them. Particularly relevant are the policies on attendance, absences due to religious observance, and examinations.

• https://www.umass.edu/registrar/sites/default/files/academicregs.pdf
• http://www.umass.edu/registrar

Offensive topics and material: This class will often include discussion of real-life court cases and criminal scenarios. Students may find some topics of discussion distasteful, offensive, disturbing, and shocking, which is atypical for Computer Science. For example, we will openly discuss true and hypothetical scenarios and cases of child sexual exploitation, adult pornography, homicide, and other violent crimes. Students are welcome to sit out for any discussion if they feel uncomfortable, no questions asked, no need to ask ahead of time. Instructor will try to keep all discussions at a high level and avoid lurid details — and, students should do the same. It is inevitable, however, that there will be some frankness in discussion as well as in candid court decisions students will read. 

A word about copyrights: Some of the material (lecture notes, lectures, assignments, and so on) in this course is original work created by the instructor (and prior instructors); exceptions are clearly noted. While students are welcome to use the material for their own personal and educational use, students may not redistribute them to others outside the class. In particular, selling or otherwise redistributing notes, and making or selling audio, video, or still recordings of course material, is not allowed without express written permission from instructor. 

14.          Legal statements.

While the instructor of this course is an attorney, no statements made by the instructor as a result of being engaged to teach this course should be construed as legal advice nor relied upon for any legal matter. Furthermore, no statement made by instructor as a result of teaching this course should be construed as having created of an attorney-client relationship. In order to comply with Massachusetts’s wiretapping statute, all students should be aware and understand that all communications for this class may be recorded. By participating in this course, a student consents to any recordings made as a result of student’s activity in the course. 

15.          Wellness and Success.

You are not alone at UMass – many people care about your well-being and many resources are available to help you thrive and succeed. Coursework is challenging and classes are not the only demand in your life.

You have resilience and are already using effective strategies to help you achieve your educational goals. Take stock of these and consider what new steps or resources could be helpful. Getting enough sleep, exercising, eating well, and connecting with others are all antidotes to stress. If you are struggling academically, reach out to your instructors and advisors prior to deadlines and before the demands of exams, papers, and projects reach their peak.

Students experiencing challenges including stress, anxiety, difficulty concentrating, loneliness, and trauma, or who feel down or alienated, can find it helpful to connect with one or more of the many supportive resources on campus that stand ready to assist you. You matter at UMass.

16.          Title IX.

In accordance with Title IX of the Education Amendments of 1972 that prohibits gender-based discrimination in educational settings that receive federal funds, the University of Massachusetts Amherst is committed to providing a safe learning environment for all students, free from all forms of discrimination, including sexual assault, sexual harassment, domestic violence, dating violence, stalking, and retaliation. This includes interactions in person or online through digital platforms and social media. Title IX also protects against discrimination on the basis of pregnancy, childbirth, false pregnancy, miscarriage, abortion, or related conditions, including recovery. There are resources here on campus to support you. A summary of the available Title IX resources (confidential and non-confidential) can be found at the following link: https://www.umass.edu/titleix/resources. You do not need to make a formal report to access them. If you need immediate support, you are not alone. Free and confidential support is available 24 hours a day / 7 days a week / 365 days a year at the SASA Hotline 413-545-0800.

17.          Name and Pronouns.

Everyone has the right to be addressed by the name and pronouns that they use for themselves. Students can indicate their preferred/chosen first name and pronouns on SPIRE, which appear on class rosters. Please let instructor know what name and pronouns instructor should use, especially if they are not on the roster. A student’s chosen name and pronouns are to be respected at all times in the classroom.

18.          Schedule.

Below is an overview of the topics that will be covered throughout the semester.  Assignments will follow these modules and topics. Assignments will be posted at least one week prior to being due. Assignments will consist of readings and responses. Readings will be a mix of case opinions, law review articles, and general articles. There will be a case opinion, however, given with each assignment.  Each class will be have an Assignment that should be read before class.

Module 1: Introduction to AI and Legal Landscape

• Overview of Artificial Intelligence
  • Definition and types of AI
  • Historical development and current state
• Legal Foundations
  • Basic principles of law

Module 2: Intellectual Property and AI

• Copyright and AI
  • Ownership of AI-generated content
  • Fair use and AI-generated works, and related Copyright issues
• Patents and AI
  • Can AI be an inventor?
  • Patentability of AI-generated inventions

Module 3: Privacy and Data Protection

• Data Privacy Laws
  • Privacy considerations in AI applications
  • GDPR, CCPA, and other global regulations
• Data Ownership and Consent
  • Who owns AI-generated data?
  • Informed consent in AI contexts
• Surveillance
  • AI in surveillance and privacy
  • Governmental use of AI versus privacy

Module 4: Liability and Accountability

• Legal Responsibility
  • Attribution of liability in AI accidents
  • Legal personhood for AI entities
• Tort Law and AI
  • Negligence and AI
  • Strict liability in AI cases

Module 5: Regulation and Compliance

• National and International Regulation
  • Overview of AI regulations worldwide
  • Challenges in harmonizing global AI regulations
• AI in Specific Sectors
  • Healthcare, finance, transportation, etc.
  • Sector-specific regulatory challenges

Module 6: Governance and Policy-making

• Ethical Frameworks for AI
  • Development and implementation of ethical guidelines
  • Challenges in enforcing ethical standards
• Governmental Policies
  • National AI strategies
  • Regulatory sandboxes and innovation hubs
  • AI and democracy
• AI and the criminal justice system

Module 7: Social Implications

• Employment and Workforce
  • Impact of AI on employment
  • Reskilling and upskilling initiatives
• Equity and Access
  • Bridging the digital divide
  • Ensuring equitable access to AI technologies
• Education
  • Impact of AI on education
  • Legal implications of AI in education
• AI versus Humans
  • AI systems legal personhood
  • AI liability versus Human Liability

Module 8: Future Trends and Emerging Issues

• Explainability and Transparency
  • Challenges in understanding AI decision-making
  • Importance of transparency in AI systems
• Human Rights and AI
  • Impact on freedom of expression, privacy, etc.
  • Ensuring AI respects fundamental human rights

Module 9: Case Studies and Practical Applications

• Real-world Examples
  • High-profile legal cases related to AI
  • Successful and problematic implementations
• Interactive Discussions and Debates
  • Engaging students in analyzing and discussing AI legal issues
  • Mock trials and legal simulations

Module 10: Future Directions and Student Projects

• Emerging Technologies
  • Quantum computing, neurotechnology, etc.
  • Legal and policy implications of future AI advancements
• Capstone Projects
  • Students develop and present projects on a specific AI law and policy topic
  • Integration of multidisciplinary approaches