ChatGPT & Generative AI - An Advanced Guide to The Legal & Regulatory Aspects - Learn Live

Introduction

Ideal for those who want to take their knowledge of ChatGPT and generative AI to the next level, this new virtual classroom seminar will take a more in-depth look at the significant legal issues and regulatory aspects when using this technology and the techniques organisations can use to mitigate the risks involved.

This session is led by Jacob Turner of Fountain Court Chambers who is an expert in the legal regulation of AI and has acted in some of the world’s most significant AI-related cases, including as counsel for Dr Thaler in the UK Supreme court in Thaler v Comptroller-General of Patents (the ‘AI Inventor’ case), representing the claimants in Drivers v Uber and OLA Cabs (the ‘robo-firing’ case), and defending (successfully) the first company investigated by the UK data protection regulator for alleged AI bias.

For those who would like to develop a working knowledge of the topic, including the basics of how the technology works, please see Jacob’s session ChatGPT & Generative AI - The Legal & Ethical Issues - Learn Live

What You Will Learn

This live and interactive session will cover the following:

• The general risks of generative AI (bias, hallucinations, confidentiality)
• IP issues in generative AI input, including:
• Breach of contract )
• Database rights)
• Copyright breaches (comparing the UK, EU, US, Singapore, and Japanese approaches)
• Criminal law issues in data scraping)
• IP issues in generative AI output, including:
• Copyright protection for the output (comparing UK and US approaches)
• Patents (focussing on the Dabus case in jurisdictions around the world)
• Personal data issues in generative AI, including:
• The training data
• Storage
• The accuracy of output
• Key issues arising from emerging legislation, including:
• The EU AI Act
• The US Executive Order of October 2023
• Chinese regulations on recommendation and generative AI
• Practical steps which organisation can take to mitigate against risks including:
• Algorithmic audits
• Due diligence
• Internal policies and procedures
• Training for relevant personnel
• Preparing ‘AI explainability statements’
• Choice of providers (open v closed-end)
• Legal issues such as indemnities offered