AI Law - I Am Not A Lawyer But My Co-Presenter Is

A joint presentation between Jon Festinger, King’s Counsel, and Mattias Andersson, at the Peter A. Allard School of Law at the University of British Columbia and hosted by the Emerging Media Community of Practice.

Learn more about Jon, here.

Transcript

1. A Surprisingly Interesting Look at Intellectual Property Law in an AI World Mattias Andersson & Jon Festinger, K.C.
2. Intro
3. Rough Agenda: • Intro & Foundation • AI/ML Data Flow • What Goes In (2) • What Comes Out (1) • IP Law & Society • Practical Takeaways
4. MATTIAS ANDERSSON ‣ SFU Computing Science grad, 2001 ‣ Dev on Microsoft Office Shared Services ‣ Many hats in software development: architecture, security, leadership, etc. ‣ Taught hundreds of thousands to architect, build, & run cloud systems ‣ AWS Community Builder, Serverless
5. I AM NOT A LAWYER!
6. I AM NOT A LAWYER! BUT JON IS!
7. Rumsfeld Matrix
8. I AM NOT A LAWYER!
9. Foundation
10. AI Data Flow AI: Artificial Intelligence ML: Machine Learning DL: Deep Learning LLM: Large Language Model FM: Foundation Model GenAI: Generative AI
11. Training Data (e.g. Books) Input Data (e.g. Prompt) Trained Model (e.g. FM, LLM) Model Output Output Usage AI Data Flow
12. Ownership
24. Title • Notes for this slide
28. I AM NOT A LAWYER!
29. Types of Intellectual Property (IP) 1. Copyright 2. Patents 3. Trademarks 4. Trade Dress 5. Industrial Design Rights 6. Plant Varieties 7. Trade Secrets
30. I AM NOT A LAWYER!
31. Training Data (e.g. Books) Input Data (e.g. Prompt) Trained Model (e.g. FM, LLM) Model Output Output Usage
34. I AM NOT A LAWYER!
37. I AM NOT A LAWYER!
38. Training Inputs
39. Training Data (e.g. Books) Input Data (e.g. Prompt) Trained Model (e.g. FM, LLM) Model Output Output Usage
41. Training Data (e.g. Books) Input Data (e.g. Prompt) Trained Model (e.g. FM, LLM) Model Output Output Usage
42. I AM NOT A LAWYER!
45. Training Data (e.g. Books) Input Data (e.g. Prompt) Trained Model (e.g. FM, LLM) Model Output Output Usage
46. I AM NOT A LAWYER!
48. I AM NOT A LAWYER!
50. I AM NOT A LAWYER!
51. Practical Takeaways
52. Training Data (e.g. Books) Input Data (e.g. Prompt) Trained Model (e.g. FM, LLM) Model Output Output Usage • Copyright Infringement • Bias • Defamation • Privacy • Fraud • Malpractice • Broken Trust • Copyright Infringement • Bias • Privacy • Injection Attacks • Regulatory Consider the Data Flow • Copyright Infr. • Trademark Infr. • Trade Dress Infr. • Confidential Info Leaking • Right to be Forgotten (GDPR) • Costs
53. I AM NOT A LAWYER!
54. Tool with Indemnification Known Requirements Azure OpenAI Service May need to follow Required Mitigations Microsoft 365 Copilot Year-long commitment at Business level, on top of Microsoft 365 suite GitHub Copilot Business/Enterprise (NOT Individual!) Must turn on duplication detection filter GCP Vertex AI Gemini for Google Workspace OpenAI API OpenAI Teams (2+ users) or Enterprise (call sales) (NOT Plus!) Adobe Firefly Enterprise Shutterstock Enterprise Content must pass Content Review process
55. I AM NOT A LAWYER!
56. Other possibilities • Secrecy • Make derivative works to re-protect: Embrace and extend. • Force manual-ness • The long game: Litigate and escalate
57. I AM NOT A LAWYER!
58. Wrap-Up & Resources
59. Rumsfeld Matrix
62. IP is for us (i.e. society)
64. Extra Info During Q’s
67. https://www.linkedin.com/in/mattias-andersson Reach out! MATTIAS ANDERSSON
68. I AM NOT A LAWYER!