ARTIFICIAL INTELLIGENCE LAW

In this welcome lesson, you’ll meet your instructor, go over some basic housekeeping, and get a clear overview of what’s ahead.

• Instructor introduction
• General housekeeping
• Course & assignments overview

This class will introduce you to the basics of AI Law, starting with defining AI and exploring its various applications. Learn about ethical frameworks for AI and gain an overview of different regulatory approaches, both direct and indirect.

• Introduction to AI Law
• Defining AI and its applications
• Ethical frameworks for AI
• Overview of ‘direct’ & ‘indirect’ regulation 

Dive into the structure, scope, and objectives of the EU AI Act, including its crucial risk-based regulation framework that identifies high-risk and prohibited AI systems. You will also explore the act's extraterritorial reach, its implications for the UK, provisions for general-purpose AI, and details on enforcement mechanisms and penalties.

• Structure, scope, & objectives
• Risk-based regulation
• Extraterritorial impact & UK implications
• General-purpose AI, enforcement, & penalties 

Assignment 1: Short Report on the EU AI Act 
Analyse the potential impact of the EU AI Act on a specific UK business. You will also compare the UK's approach to AI regulation with the EU's stance.

This class explores the critical role of data protection and privacy in the world of AI. You'll get an introduction to major data protection laws and examine different legal and regulatory approaches to safeguarding personal data.

• Data protection & privacy law in AI
• Key data protection & privacy laws
• Data protection and privacy approaches

Delve into the specifics of automated decision making and profiling. You’ll explore key data subject rights, see how regulators enforce these protections, and examine real-world court cases that bring these issues to life.

• Automated decision making & profiling
• Other data subject rights
• Regulatory enforcement actions
• Court case examples
• Case study: Uber worker rights claims relating to automated decision making

Assignment 2: UK Data Protection Law & AI Report
Discuss GDPR-related issues associated with a chosen AI system. Consider the compliance obligations and risks applicable to the system's user, as well as the rights available to individuals whose data is processed by the system.

This class explores the evolving relationship between AI and Intellectual Property law, with a spotlight on copyright challenges surrounding AI-generated works. You'll dive into the legal questions that arise when machines become creators.

• Intersection of AI & IP Law
• AI-Generated works: Copyright issues 
• Case Study: The Author’s Guild class-action suit against OpenAI

Deep dive into the patentability of AI-generated inventions and the evolving concept of inventorship. You'll also learn how trade secret law applies to AI algorithms, with real-world context provided by landmark cases.

• Patentability of AI inventions
• Trade secret protection 
• Case Study: Thaler v Comptroller-General of Patents, Designs and Trademarks

Assignment 3: IP Legal Strategy
Working in groups, prepare a presentation outlining a legal strategy. It will involve either challenging or defending AI-generated content from IP infringement claims.

Learn about the impact of AI on consumer rights and protections. Delve into automated decision-making in services like lending and insurance, AI applications in advertising and marketing, and the implications for consumer autonomy.

• Consumer rights & protections: Ai impact
• Automated decision-making in services
• AI in advertising and marketing
• Implications for consumer autonomy 
• Workshop: Break into groups and discuss a fictional AI-enabled consumer product from the perspective of (i) a consumer rights group; and (ii) the company manufacturing the product.

This class breaks down why sector-specific AI regulations matter, spotlighting the UK’s “pro-innovation” guidelines. You’ll also explore specific use cases and guidance in sectors such as Financial Services, Healthcare, and the Public Sector.

• Sector-specific regulation of AI
• Regulatory strategy for AI in the UK
• Defining “pro-innovation” guidelines
• Use cases & guidance in sectors

Assignment 4: Sector-specific AI Regulation in the UK Presentation
Select a specific sector in the UK and analyse how AI is regulated within that sector. Refer to relevant UK regulatory bodies and their specific guidelines concerning AI use.

In this class, you will discuss the transformative effects of AI in the workplace. This includes the resulting shifting roles and responsibilities for workers, the increasing use of automation, and the practice of algorithmic management.

• AI in the workplace
• Shifting roles & responsibilities 
• Automation & algorithmic management 

Delve into the use of AI for hiring and firing employees and its associated legal implications. You will cover human and worker rights, data privacy, and the concept of the right to explanation concerning AI-driven employment decisions.

• AI for hiring and firing employees
• Legal implications 
• The right to explanation 
• Case Study: Amazon’s Biased AI Recruitment Tool

Assignment 5: Case Study Analysis & Report on AI in UK Employment Practices 
Examine the legal implications of a scenario involving AI-driven hiring and firing decisions within the UK, with a focus will be on potential discrimination issues under the Equality Act 2010.

Explore liability and product safety challenges posed by AI, focusing on the EU AI Act’s role. You’ll learn about product liability for faulty AI systems and how negligence applies in AI development and deployment.

• AI act: Product safety
• Legal implications 
• Product liability for defective AI systems
• Negligence in AI development or deployment

In this class, you will tackle the challenges involved in establishing causality in AI-related hardware failures or actions. You will also delve into principles of AI safety engineering, risk mitigation strategies, and important ethical considerations in ensuring AI safety.

• Establishing causality in AI-related hardware
• AI safety engineering & risk mitigation
• Ethical considerations in AI safety 

This class introduces the fundamentals of contract law in the AI context, covering contract formation, execution, and the legal standing of AI-generated agreements. You’ll also explore dispute resolution methods and real-world case studies involving smart contracts.

• Contracting for AI
• Contract formation & execution 
• AI-generated agreements: Legal validity
• Dispute resolution
• Case Study: Smart contracts and self-executing code 

Expanding on the basics, you will cover liability, potential losses, and limitations in AI contracts. You’ll also learn about service level agreements, IP ownership, data protection concerns, and how to craft AI-specific contract clauses and addenda.

• Liability, losses, & limitations 
• Service levels & support
• IP ownership 
• Data protection & implications 
• AI addenda & different approaches 

Assignment 6: AI & Contract Negotiation
Take on the role of either a customer or a supplier of an AI system. Identify which clauses within an example contract you would want to negotiate or change, providing justification for your choices.

This class examines how AI is involved in criminal activities and the complex legal challenges that follow. You’ll explore questions of criminal responsibility, agency and intent with AI, causation and foreseeability, and the unique liability issues posed by the “black box problem.”

• AI uses in criminal activities 
• Criminal responsibility & legal challenges
• The black box problem 

Continuing the criminal law discussion, dive into AI’s role in law enforcement—from its various applications to its use as evidence—and cover into the complex jurisdictional challenges in AI-related criminal cases.

• AI & implications: Law enforcement
• Workshop: Break into groups and deal with AI-related crime scenarios, focusing on analysing AI’s role as both a law enforcement tool and a criminal perpetrator. Develop practical strategies and present your findings for class discussion. 

Learn about the necessity of auditing AI systems and ensuring regulatory compliance. Delve into documentation and transparency, conducting conformity assessments, different audit types, and the data mapping and skill requirements needed for effective compliance.

• AI auditing & regulatory compliance 
• AI systems: Documentation & transparency 
• Conformity assessments & audit types
• Data mapping & skill requirements

In this final class, you’ll explore the future of AI law—from the rise of General AI (AGI) and superintelligence to efforts toward global regulatory harmonisation. The session also delves into evolving concepts like AI legal personhood and agency, as well as the existential risks and broader societal impacts of advanced AI.

• General AI (AGI) & superintelligence
• International harmonisation & governance
• Legal personhood & agency
• Existential risks & long-term societal impacts

Final Project:
Conduct a case study analysis of the legal issues associated with a real-world AI-related use case. This will demonstrate your ability to apply AI law principles to the practical challenges presented by emerging technologies.