Dr Rachel Free

This Practice Note considers the interaction between artificial intelligence (AI) and copyright law. Lawmakers across the world are grappling with how to ensure that right holders maintain the high levels of copyright protection afforded to their works under national laws while at the same time not stifling innovation and remaining attractive jurisdictions for AI model developers. Uncertainty remains around questions such as: what permission is required from right holders to train AI models? when does training amount to copyright infringement? to what extent do existing exceptions apply? how does the territory in which training occurs impact the enforceability of a claim? This Practice Note outlines the various approaches taken to address these challenges in the UK and EU through consultations, guidance, legislation and case law, as well as industry initiatives. US policies and decisions are also briefly discussed. It also deals with the rights in the instructions and prompts, as well as the training algorithms themselves, and examines whether and how AI outputs can be protected under copyright laws, labelling requirements for content

This Practice Note examines the interaction between artificial intelligence (AI), research and development (R&D) and patent law. It considers the issues arising from the use of AI tools in R&D, including patent ownership where AI tools are used in the development of an invention. It also looks at patent protection for AI systems and their training data and algorithms, the use of AI to draft patent applications, and the use of AI by Intellectual Property Offices (IPOs). Why use AI to assist with the inventive process?AI can be used throughout the inventive process to analyse large volumes of technical information, identify patterns, automate repetitive tasks and generate data-driven solutions. It therefore has the potential to accelerate innovation, reduce development costs and improve the quality of inventions.AI is already being used to improve the efficiency of drug development and reduce associated costs and timescales. For example, it can facilitate the faster identification of therapeutic targets, while AI-based screening platforms can analyse large and diverse datasets to predict and profile the properties of potential

This Practice Note discusses the interplay between artificial intelligence (AI) (or machine learning) and intellectual property (IP). First, it explains what AI is and its use in different sectors before considering the implications of AI for the development of IP law, including the protection of: training data, training algorithms, AI systems themselves, and the output of AI. It then looks at the issues to consider when contracting with a third-party AI solution provider and whether changes to the current IP system are necessary to deal with AI.

This Practice Note considers intellectual property issues specifically in relation to fintech. It covers: fintech and intangible assets, fintech IP strategy, copyright, open source software, brand protection, trade secrets, impact of artificial intelligence and practical steps.