CPTEnglishIntermediate· Artificial Intelligence

AI, Copyright, and the Ownership of Training Data

Understanding the legal and ethical landscape of generative AI training data

Legal & Compliance 1h 30 lessons

What you'll learn

Analyze the ethical and economic tensions regarding ownership of training data.
Distinguish between generative AI outputs and traditional search engine indexing.
Identify the primary copyright concerns across the different stages of the AI life cycle.
Explain how foundation models learn through parameter adjustment rather than simple storage.
Apply fair use principles to the debate over mass web scraping for commercial AI training.
Evaluate the impact of high-quality data on the competitive landscape of AI development.

About this course

This course provides a detailed examination of the legal, ethical, and economic complexities surrounding generative AI training data. For SFC-licensed professionals operating in Hong Kong, understanding the intersection of intellectual property and machine learning is increasingly relevant as financial institutions integrate AI into investment research, algorithmic trading, and customer service. As the regulatory environment evolves to address the impact of new technologies on the financial services sector, this CPT program offers a foundation for evaluating how data sourcing practices intersect with broader compliance obligations and digital asset management strategies. The curriculum is designed to help professionals navigate the tension between the innovation potential of foundation models and the rights of creators whose work fuels AI development. By grounding the discussion in the mechanics of data collection, web scraping, and model learning, the course clarifies why standard copyright analogies—such as those used for traditional search engines—often fail to capture the unique risks posed by generative AI. It also examines the economic implications of data quality and the growing pressure for transparency in AI dataset governance, which are essential considerations for risk management frameworks. The course is structured into three thematic modules covering the technical reality of AI learning, the evolving copyright landscape, and the strategic policy challenges ahead. Through this structure, participants will gain an understanding of how fair use, transformative use, and market harm theories are currently applied to AI development, and how these concepts may influence the future regulatory landscape for financial institutions using third-party AI models. This material is prepared for practitioners aiming to stay informed on the shifting landscape of intellectual property, technology infrastructure, and regulatory expectations within the Hong Kong financial ecosystem.

Who should attend

Compliance Officers
Licensed Representatives in Asset Management
Technology Risk Managers
Legal Counsel for Financial Institutions
Investment Analysts
Data Governance Professionals

Key topics covered

The Technical and Economic Mechanics of AI

Understanding parameter adjustment in foundation models
The shift from narrow AI to large-scale data collection
Economic value of high-quality versus massive datasets
Differentiating generative AI from search engine indexing
The life cycle of training data from collection to deployment

Copyright Law and Ethical Obligations

Distinction between protected expression and uncopyrightable facts
Fair use doctrine and transformative use in machine learning
Analyzing copyright concerns in web scraping practices
Assessing market harm to authors, journalists, and artists
Addressing the controversy over unauthorized model training

Policy, Governance, and Future Markets

Transparency requirements for AI training datasets
The emergence of licensing markets for proprietary data
Balancing creator compensation with public interest research
Antitrust considerations in data ownership and concentration
Global copyright disparities and their impact on innovation

How this course satisfies CPT

This course covers Artificial Intelligence topics recognised by the SFC as eligible for CPT. Upon completion, you'll earn approximately 1 CPT hours and receive a certificate of completion for your training records. The course includes quizzes to verify your understanding, satisfying the SFC's requirement that online learning includes an independent assessment and maintains a reliable audit trail.

Learn more about CPT requirements

Curriculum · 30 lessons

1:03:34.1 of content

1.
Ownership and Ethics of Training Data in Generative AI
FREE
1:55.4
2.
The Economic Debate Over AI Training and Creator Compensation
FREE
1:50.2
3.
The Evolution of Large Scale Data Collection in AI
FREE
2:01.6
4.
Distinguishing Generative AI From Search Engine Indexing
1:59.4
5.
The Value of Human Creative Labor in AI Infrastructure
2:04.4
6.
Quiz: Ownership and Ethics of Training Data in Generative AI – The Value of Human Creative Labor in AI Infrastructure
QUIZ
5 questions · requires lessons
7.
Understanding Training Data, Prompts, and Model Life Cycles
2:00.8
8.
How Foundation Models Process Information and Learn Patterns
1:49.3
9.
Copyright Considerations Across the AI System Life Cycle
2:02.6
10.
The Legal and Ethical Conflicts of Large Scale Web Scraping
2:04.3
11.
The Critical Role of Data Quality in AI Development
2:15.5
12.
Quiz: Understanding Training Data, Prompts, and Model Life Cycles – The Critical Role of Data Quality in AI Development
QUIZ
5 questions · requires lessons
13.
Copyright Law Foundations and Protecting Original Creative Expression
2:11.2
14.
Analyzing the Legal Debate Over AI Model Training Reproductions
2:23.1
15.
Applying Fair Use Doctrines to Generative AI Training
2:06.3
16.
Evaluating Transformative Use in AI Model Development
1:57.3
17.
Assessing Market Harm in the AI Training Copyright Debate
2:01.8
18.
Quiz: Copyright Law Foundations and Protecting Original Creative Expression – Assessing Market Harm in the AI Training Copyright Debate
QUIZ
5 questions · requires lessons
19.
Navigating Licensing and Ownership Challenges for Authors and Publishers
2:02.3
20.
Journalism and the Economic Impact of AI Content Summarization
2:09.0
21.
The Impact of Generative AI on Visual Arts and Copyright
1:59.6
22.
Legal and Creative Challenges for Music and AI Voice Models
2:06.4
23.
Open Source Software, Licensing, and AI Coding Assistants
2:14.0
24.
Quiz: Navigating Licensing and Ownership Challenges for Authors and Publishers – Open Source Software, Licensing, and AI Coding Assistants
QUIZ
5 questions · requires lessons
25.
The Case for Transparency and Accountability in AI Datasets
2:13.2
26.
Transparency Requirements and Dataset Governance for AI Development
2:13.2
27.
Building Sustainable Licensing Markets for AI Training Data
2:11.1
28.
Developing Compensation Models for Creators in the AI Economy
2:44.5
29.
Balancing Creator Protections with Public Interest AI Research
2:12.9
30.
Quiz: The Case for Transparency and Accountability in AI Datasets – Balancing Creator Protections with Public Interest AI Research
QUIZ
5 questions · requires lessons
31.
Global Copyright Disparities and Their Impact on AI Innovation
2:15.0
32.
Antitrust Considerations and AI Data Ownership Concentration
2:09.0
33.
Evaluating Policy Trade-offs in AI Copyright Regulation
2:11.5
34.
Strategic Questions for Distributing Value in the AI Economy
2:08.8
35.
Building a Sustainable Future for Creativity and AI Innovation
2:00.5
36.
Quiz: Global Copyright Disparities and Their Impact on AI Innovation – Building a Sustainable Future for Creativity and AI Innovation
QUIZ
5 questions · requires lessons

Requirements

A basic understanding of how artificial intelligence systems generate content.
An interest in intellectual property law and digital policy.
Professional curiosity regarding the future of the creative economy and AI innovation.

Certificate of Completion

Complete this course to earn a verifiable Certificate of Completion for your CPT training record. Here's how:

1Watch all the lessons — work through every lesson in the curriculum. Each completed lesson brings your progress closer to 100%.
2Pass all the quizzes — score 70% or higher in each quiz within the course. Quizzes are part of the curriculum and must be passed to finish.
3Download your certificate — once you reach 100% progress, download a personalised Certificate of Completion showing your name, the CPT hours earned, and your quiz score.

Sample certificate: