Frontier AI Regulation

• Anticipating Technological Advancements
• Preparing for emerging AI technologies and their implications.
• Adaptive Regulatory Frameworks
• Developing flexible regulations that evolve with AI progress. 

AI Safety

• Safety, Security, and Robustness
• Ensuring AI systems operate reliably and securely.
• Limiting High Risk Systems
• Limiting the scale and impact of high risk systems.
• Human Oversight
• Balancing automation with human control and intervention.
• Societal Impact
• Assessing AI’s effects on employment and social structures.

The International Landscape

• How the UK’s AI regulation aligns with or differs from global standards.
• Impact and warnings from the EU 
• Competitive opportunities for the UK to exploit
• Where should the UK AI Bill appear on the global regulatory landscape
• How should the UK work with other global bodies to regulate
• Implications of a Trump administration on US regulation
• Setting Benchmarks
• Who should lead? OECD, UN?

Transparency and Misinformation

• Identifying when AI tools have been used to create false information
• Identifying Deepfakes, dealing with the consequences
• Fairness and Non-Discrimination
• Preventing biases and ensuring equitable AI outcomes.
• Transparency and Explainability
• Making AI decisions understandable to users and stakeholders.
• Ensuring Compliance with Existing Laws (e.g. FSA)

Data Protection and Privacy

• Compliance with UK GDPR
• Ensuring AI systems adhere to data protection regulations.
• Data Sovereignty
• Managing data storage and processing within UK jurisdictions.
• Anonymisation and De-identification
• Techniques to protect individual identities in AI datasets.

Intellectual Property and Copyright

• Text and Data Mining Exceptions
• What needs to be protected, what should be made available?
• AI – Generated Content
• Determining ownership rights for AI-created works.
• Use of Protected Material in AI Training
• Legal considerations for using copyrighted data in AI models.
• Digital Watermarking
• Frequency Domain, Quantum Image Processing (QIMP), 
• Impact on Publishers’ revenues
• Freedom of the press

Compliance and Enforcement

• Role of Regulatory Bodies
• Functions of organizations like the Information Commissioner’s Office (ICO) in AI oversight.
• Sector-specific or sector-agnostic
• Monitoring and Auditing AI Systems
• Processes for evaluating AI compliance with regulations.
• Penalties for Non-Compliance
• Consequences of violating AI regulatory standards.
• Are fines too easy for Big Tech to write off
• Accountability and Governance
• Defining responsibility for AI actions and decisions.
• Contestability and Redress
• Providing mechanisms to challenge and rectify AI decisions.
• Limiting Monopolies
• Moving from Big Tech to Big AI. Antitrust, CMA and EU taking on Google.

Encouraging Innovation and Growth

• Supporting AI Startups
• Initiatives to foster AI entrepreneurship in the UK.
• Balancing Regulation with Innovation
• Ensuring regulations do not stifle technological advancement.
• Self-regulation
• Effective and up-to-date or a smoke-screen?
• Businesses role to educate the public
• Increase accessibility and usage, building trust

Protecting the Environment

• Energy Consumption Standards
• Transparency in reporting
• Incentives for Green AI
• Certification for Green Data Centres
• Mandate Renewable and Efficient Energy
• Limitations on high energy intense AI models
• Encourage distributed AI systems
• Reduce reliance on data centres
• Support Hardware Recycling