Syllabus Spring 2026 (version 2.3)

A.I. & Law (LAW 426D 001 Topics in Law & Technology)


ACKNOWLEDGEMENTS

UBC’s Point Grey Campus is located on the traditional, ancestral, and unceded territory of the xwməθkwəy̓əm (Musqueam) people. The land it is situated on has always been a place of learning for the Musqueam people, each generation having passed on their culture, history, and traditions on this site.


COURSE AND CONTACT INFORMATION

Course TitleCourse CodeTermCredit ValueTeaching Times & Rooms
  AI & Law  LAW 426D.001  Jan. – April 26  5Fall: Wed & Fri, 9:30 – 10:30 am Room 122 Spring: Wed & Fri, 9:30 – 11:00 am Room 122
Course InstructorEmail AddressOffice LocationOffice Hours
Jon Festinger, K.C.festinger@allard.ubc.caRoom 457Wednesdays, 2:00 – 5:00 pm

COURSE DESCRIPTION

This course explores the intersection of artificial intelligence (A.I.) and Canadian law, examining how emerging A.I.technologies challenge existing legal frameworks and create new regulatory needs. Students will analyze key issuesincluding, intellectual property rights, digital biases and algorithmic discrimination, privacy and data protection, labourimplications, misinformation, disinformation and manipulation through A.I. fueled media and social-media, liability forautonomous systems, and the role of A.I. in legal decision-making. Questions regarding the historical impact of technologyon the substantive law (and vice-versa) will be a recurring theme of the course which will also cover Canadian andinternational legal responses to A.I., including ethical considerations, policy debates, and legislative developments.Through case studies, legal analysis, discussions and presentations, students will gain a critical understanding of the legal,ethical, and societal implications of A.I. in Canada and beyond.


LEARNING OBJECTIVES

  • Understand and assess different theories, approaches, and goals of tort law.
  • Convey the basic principles and rules which govern liability in tort law.
  • Understand the historical development of tort law and the social, economic, and ideological context in which it has developed and continues to operate.
  • Identify legal issues in torts problems and work with substantive law and policy considerations to resolve them.


MATERIALS

Materials will be posted to the course website.


TEACHING METHODS & EXPECTATIONS

Expectations

Attendance and timeliness: Students are expected to attend all classes in-person and arrive on-time. I will aim to ensure class ends at the scheduled time. If you are unable to attend class, lecture captures of the classes will be available on through the course website.

Preparation: It is expected that you will have completed readings ahead of class. Classes will be prepared based on this assumption.

Communication: Students are encouraged to ask questions about the course content during class time. On occasion your question may requires a more substantive discussion than the allocated time allows, I may ask that you come discuss the question during my office hours. Students are also welcome to use the course website to raise issues and engage in discussions about legal issues in our area of study. I will also monitor the website and provide comments where relevant.

Health and wellbeing: The transition to Law School is incredibly difficult for many. If you or someone you know is struggling, there are a wealth of Student Wellbeing services at Allard, which you can learn about here – https://allard.ubc.ca/student-portal/student-wellbeing.

A.I. Policy:

  1. You are responsible to understand the many limitations of A.I. In particular, limitations relating to hallucinations (as they are commonly referred to), embedded biases, and A.I. over-confidence and avoidance when challenged.
  2. Your critical reasoning process must be wholly your own. Outsourcing your critical thinking to an A.I. wholly undermines the purpose of your legal education, which is to find your legal voice to help others. Accordingly, A.I. may never be used to think for you or as a substitute for your human judgments.
  3. A.I. may only be prompted to make suggestions, that you personally follow up in researching fully, regarding what may be missing in what you have written or what could be supplemented. A.I. can be useful as a devil’s advocate to challenge your arguments, reasoning, and conclusions – including illustrating other viewpoints.
  4. You are fully responsible for the originality, logic, citations, quotations, claims and mistakes in the work you have submitted. They should all be double-checked by you.
  5. You must briefly but precisely disclose in your paper and presentation all the ways you used A.I. to arrive at what is being submitted or presented.
  6. None of this is intended to chill experimentation – that is part of the course. However, misusing AI demonstrates a misunderstanding of AI, which is itself relevant, especially in this course. 


SCHEDULE OF TOPICS AND READINGS

While we will stick to the order outlined, the dates we will discuss each topic are an estimate only and may change depending upon the pace of our class. The syllabus and readings are subject to revision and change throughout the year at the discretion of the professor. Students will prepare their own individualized versions of the Syllabus emphasizing particular areas of interest and submit that to the professor as soon as is reasonable, and in no event (without permission) later that the end of reading week. This individualized syllabus can include materials outside the below, but must include at least one legally-oriented substantive reading per week which the student will come to class prepared to discuss.


EVALUATION

Participation = 25%  includes any or all of:

  • attendance;
  • class contributions;
  • website contributions;
  • following & documenting “Self-Socratic” protocols.

Group presentation = 25%. This will be based on group preparation of a Discussion Outline that must be created and should be provided  to the class—preferably by posting on the course website – five days before your particular discussion takes place, and then leading the discussion for that week. All presentations are due by the final date of the teaching semester if they are not presented in class.

Term Paper/Major Project (18 to 20 pages or equivalent – 5000 words):  50%.

Note with respect to class participation:  Factors taken into consideration are attendance, level of engagement in course related discussions & activities including contributions to http://videogame.law.ubc.ca (or equivalent email contributions to the instructor), evidence of preparation for class, contributions to in class discussions, evidence of attention to the analysis of others and consideration of how such analysis might affect one’s own.

Note with respect to term paper/major project: Given the dynamic and emergent nature of the subject matter, the opportunities for scholarship are vast.  Cases and previous legal academic contributions have almost exclusively been non-Canadian and have generally not focused on how court decision in other jurisdictions might be resolved under Canadian law.  That said you are not limited to such topics or perspectives.  As well, large territories of legal interest have simply gone unexplored and even undiscovered. Grading will reward thoughtfulness, incisiveness, originality and depth of research, potential for publication/public availability as well as rigorousness of analysis and clarity of presentation.  Term paper is due in hard copy form (with digital copy by email) by 4 P.M. on the last day of the exam period.


AUDIO/VIDEO RECORDING POLICY

Students are permitted to record video or audio of classes, though with the availability of lecture capture there wouldn’t seem to be much gained.  Office hours, which are optional, cannot be recorded without the instructor’s prior consent.


UNIVERSITY POLICIES

Academic Integrity

All UBC law students are subject to the University’s rules on Academic Misconduct and are expected to act with academic integrity at all times.

Students should be especially aware of the University’s rules in relation to academic offence of plagiarism. Plagiarism includes: copying the work of another student; copying or paraphrasing from a textbook or reference book, journal article, case or electronic source without proper footnoting; copying your own work that has already been submitted for another course without the express permission of both instructor’s; and, passing off the ideas of another person as your own. If you plagiarize, you will be subject to penalties set out in the UBC calendar.

Academic honesty is an essential requirement in an institution of higher learning. Academic misconduct may have serious implications not only for your education, but also for your future career in law. Students are encouraged to consult the University’s Resources Guide on Academic Integrity.

To learn more about academic misconduct, visit the UBC Library’s website on Academic Integrity. Examples of academic misconduct can also be found in the UBC Annual Report on Student Discipline.

Attendance

Regular attendance in person is expected of students in all classes.

Student Support

UBC provides resources to support student learning and to maintain healthy lifestyles but recognizes that sometimes crises arise and so there are additional resources to access including those for survivors of sexual violence. UBC values respect for the person and ideas of all members of the academic community. Harassment and discrimination are not tolerated nor is suppression of academic freedom. UBC provides appropriate accommodation for students with disabilities and for religious observances. UBC values academic honesty and students are expected to acknowledge the ideas generated by others and to uphold the highest academic standards in all of their actions.

Details of the policies and how to access support are available on the UBC Senate website. Students can also be supported by UBC’s Early Alert service.


Schedule of Topics and Readings


Introduction

  1. Defining AI: Canadian and international perspectives
  2. Types of AI: supervised, unsupervised, reinforcement learning, deep learning, generative models
  3. Historical perspectives: Turing
  4. Technology basics: binary logic, computer architecture, networks, layers of abstraction

Readings:

 Optional:

  • Richard Susskind, How to Think About AI: A Guide for the Perplexed (Oxford, 2025)
  • Brian W. Kernighan, Understanding the Digital World (Princeton, 2021)
  • European Digital Rights, How the Internet Works (2012)
  • Mitchell: “Debates on the nature of artificial general intelligence”
  • Jon Bing, “The Riddle of the Robots” (2008)
  • IOG, Artificial Intelligence and Canadian Government Science (2023)
  • UNU, AI and the Law – Navigating the Future Together (2024)
  1. Intersecting Memes of Technology & Justice *technology’s impact on the substantive law
  1. Can AI be a creator?
  2. AI Slop: Is it really slop, or novel art? (e.g., AI country songs, Taylor Swift x Matty Healy covers)
    1. Does AI influence culture or the other way around?
  3. Deepfakes (e.g., Luigi Mangione modelling for Shein) – truth as justice, VR too much info
  4. Snapchat generation of faces
  5. Denmark IP people’s faces

Readings:

Optional:

  1. What AI Isn’t & Is *AI surrogates and anthropomorphism
  1. Agentic vs. Conscious AI
  2. Agents/AI therapists/AI significant others (e.g., “Her” movie)

Readings:

  • Nataliya Kos’myna et al., “Your Brain on ChatGPT: Accumulation of Cognitive Debt when Using an AI Assistant for Essay Writing Task”, arXiv preprint, June 2025
  • Vincent C. Müller, Philosophy of AI: A Structured Overview
  • Mustafa Suleyman, Seemingly Conscious AI is Coming (2024)
  • Pinar Saygin et al., Turing Test: 50 Years Later (2000)
  1. A.I., post-structuralist ideas of AI
  1. Post-structuralism, recursion, and synthetic data
  2. Freedom of thought, manipulation, and AI-enabled totalitarianism
  3. Thought ownership, predictive analytics, and surveillance

Readings:

  • Jean Baudrillard, Simulacra and Simulation (1994)
  • Susie Alegre, Protecting Freedom of Thought in the Digital Age (2021)
  • Jack Balkin, “Free Speech in the Algorithmic Society” (2018)
  • Peer Zumbansen, “AI’s Democratic Challenge: Reflections on the Law and Political Economy of Artificial Intelligence” (2023)
  • Foucault, “Ceci n’est pas une pipe” (This Is Not a Pipe)
  • Ray Bradbury, The Veldt (1950)
  • Barbora Bukovska, Spotlight on AI and Freedom of Expression (OSCE, 2020)
  • Carchidi, Vincent. “Rescuing Mind from the Machines.” Philosophy Now: a magazine of ideas, 2025. https://philosophynow.org/issues/168/Rescuing_Mind_from_the_Machines.

Optional:

  • Lewis Carroll, Through the Looking Glass (1871)
  • Film: Ex Machina
  1. A.I. & IP 1 (copyright ingestion + trademark + patents)
  1. AI as author/inventor (copyright & patent debates)
  2. Deepfakes and IP over likenesses

            Readings:

  1. A.I. & IP 2 (the derivative rights problem)
  1. Generative AI and derivative works
  2. Balancing innovation vs. strict protection
  3. Philosophical reflections: Frankenstein and authorship

Readings (for both V and VI):

  • Anke Moerland, “Intellectual Property Law and AI” (2024)
  • Simon Chesterman, “Good Models Borrow, Great Models Steal” (2025)
  • Gil Appel et al., “Generative AI Has an IP Problem” (HBR, 2023)
  • Jozefien Vanherpe, AI and IP Law (2025)
  • Ryan Abbott, “I Think, Therefore I Invent” (2016)
  • Forbes, Copyright or Copywrong? (2025)
  • Helen Nissenbaum, “Accountability in a Computerized Society” (1996)
  • Kang’Ethe, “Should Kenya’s Patent Law Recognize AI?” (2023)
  • Policy & Society, Balance of Protecting IP (2025)
  • Mary Shelley, Frankenstein (1818)
  • Daniel Gervais, “The Machine as Author” (2019)
  1. A.I., Privacy, Surveillance & Personal Safety
  1. Algorithmic surveillance and commodification of data
  2. Privacy risks in Canada and beyond
  3. Freedom of thought, predictive AI, and the Panopticon

Readings:

  • Simon McCarthy-Jones, The Autonomous Mind (2022)
  • Privacy experts on AI decision-making (National Magazine, 2025)
  • David Lyon, “Surveillance, Power, and Everyday Life” (2009)
  • Shoshana Zuboff, The Age of Surveillance Capitalism (2019)
  • Oscar Gandy, The Panoptic Sort (2021)
  • Roxana Vatanparast, “The Code of Data Capital” (2021)
  • Jeremy Bentham, The Panopticon Writings (1995)
  • National Magazine, Privacy Experts Grappling with AI (2025)
  • Hill Notes, Privacy and AI in Canada (2025)
  1. A.I. Liability
  1. Tort liability and the “problem of many hands”
  2. Vicarious liability for autonomous systems
  3. Emotional harm and tort law in AI-human interaction
  4. Criminal liability and AI in armed conflict

Readings:

  • Pinchas Huberman, “Vicarious Liability for AI Harm” (2021)
  • Mary Shelley, Frankenstein (1818)
  • Katerina Yordanova, AI and Armed Conflicts (2025)
  • Emily Laidlaw, “Technology Mindfulness & Tort of Privacy” (2023)
  • Dennis Thompson, “The Problem of Many Hands” (1980)
  1. A.I., the End of the World problem & International Law
  1. AI, war, and international armed conflict
  2. Superintelligence, AGI, and existential risk

Readings:

  • Nick Bostrom, Superintelligence (2014)
  • Blaise Agüera y Arcas & Peter Norvig, “AGI Is Already Here” (2023)
  • Meredith Ringel Morris et al., “Levels of AGI” (2023)
  • Will Henshall, “When Might AI Outsmart Us?” (2024)
  • Katerina Yordanova, AI and Armed Conflicts (2025)
  • Film: War Games (1983)
  1. A.I. Personhood
  1. Legal personhood debates
  2. Sliding scales of recognition (agents, corporate analogies)
  3. The AI agent as “a real boy” – rights, obligations, protection
  4. Philosophical debates on consciousness and qualia

Readings:

  • Nadia Banteka, “AI Personhood on a Sliding Scale” (2024)
  • James Boyle, The Line: AI and the Future of Personhood (2024)
  • Ex Machina (Film, 2014)
  • Frank Jackson, “Epiphenomenal Qualia” (1982)
  • Lauwaert & Oimann, “Moral Responsibility and Autonomous Technologies”
  1. A.I. Governance & Regulation
  1. Comparative regulatory frameworks: EU, US, Canada (AIDA), OECD principles
  2. AI colonialism: incorporeal (privacy) and corporeal (environmental)
  3. Hard law vs. soft law approaches
  4. Standards-setting and global governance challenges

Readings:

  • OECD, Principles on AI (2019)
  • European Commission, Ethics Guidelines for Trustworthy AI (2019)
  • Tom Wheeler, Three Challenges of AI Regulation (2023)
  • Future of Life Institute, EU AI Act Draft Overview (2024)
  • Judge, Nitzberg & Russell, When Code Isn’t Law (2025)
  • White House, Blueprint for an AI Bill of Rights (2022)
  • Gary Merchant, Soft Law for AI (2021)
  • Montreal AI Ethics, Death of AIDA in Canada (2025)
  • Critical perspectives on “AI Colonialism”
  1. Conclusions: A.I. & The Rule of Law
  1. Synthesis of themes: justice, accountability, governance
  2. Open questions: Should AI emulate humanity or define its own rationality?

Readings:

  • Christina Pazzanese, “Great Promise but Potential for Peril” (Harvard Gazette, 2020)
  • David Leslie, Understanding AI Ethics and Safety (2019)

Extra topic: AI and Misinformation

  1. Deepfakes and misinformation in democracy
  2. Manufactured evidence and the integrity of courts
  3. Case studies: fabricated evidence, judicial misinformation

Required Readings:

  • Sanchez-Acedo et al., “AI & Misinformation” (2024)
  • UK Case: Ayinde v London Borough of Haringey (2025)
  • Thomson Reuters, Deepfakes on Trial (2025)
  • National Magazine, “AI in the Courtroom” (2024)

Extra topic: AI and Decision-Making

  1. Automated decision-making in administration & governance
  2. Judicial use of AI: opportunities, risks, and accountability
  3. Bias, transparency, explainability, and due process
  4. AI-generated evidence and admissibility in courts

Readings:

  • Jennifer Raso, “AI and Administrative Law” (2021)
  • Angwin et al., “Machine Bias” (2016)
  • Laurens Naudts & Anton Vedder, Fairness and AI
  • Susan Leigh Anderson, “Asimov’s Three Laws & Metaethics” (2007)
  • Safiya Noble, Algorithms of Oppression (2018)
  • Michael Binns, “Fairness in Machine Learning” (2018)
  • Relying on AI in Judicial Decision-Making (2025, PublicPolicy.ie)
  • From Case Law to Code (Montreal AI Ethics, 2025)

Extra topic: AI and Private Law Dimensions

  1. AI and Contract Law
  2. AI and Competition/Antitrust Law
  3. AI and Corporate Governance

Readings:

  • Martin Ebers, Cristina Poncibò & Mimi Zou, Contracting and Contract Law in the Age of AI (2022)
  • T.T. Arvind, “AI-Infused Contracting” (2024)
  • Hua & Belfield, “AI & Antitrust” (2021)
  • Martin Petrin, “Corporate Management in the Age of AI” (2019)
  • Deirdre Ahern, “Are We Ready for Robots in the Boardroom?” (2024)

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