AI tools allow users to generate images, audio, and textual works in response to textual prompts. These tools "learn" how to generate this content by ingesting massive sets of preexisting, human-authored works. How and to what extent the use of AI impacts the ability to secure intellectual property (IP) rights are evolving questions in IP law. Recently, in Thaler v. Vidal2, the U.S. Federal Circuit Court analyzed AI inventorship in view of the U.S. Patent Act – ultimately concluding that the Patent Act unambiguously "requires that inventors must be natural persons; that is, human beings." In Thaler, the AI technology known as "DABUS" used general background knowledge of a technical field to conceive and recognize the utility of inventions without specific guidance from a human being.

Laguna Hills, Calif. – DATE, 2022 – BrainChip Holdings Ltd (ASX: BRN, OTCQX: BRCHF, ADR: BCHPY), the world's first commercial producer of ultra-low power neuromorphic AI IP, has extended the breadth and depth of its neuromorphic IP with two new patents granted by the US Patents and Trademarks Office (USPTO), and the acquisition of previously licensed technology from Toulouse Tech Transfer (TTT). These latest additions of technical assets reinforce BrainChip's event-based processor differentiation for high performance, ultra-low power AI inference and on-chip learning. BrainChip also acquired full ownership of the IP rights related to JAST learning rule and algorithms from French technology transfer-based company TTT, including issued patent EP3324344 and pending patents US2019/0286944 and EP3324343. The invention related to the acquired IP rights include pattern detection algorithms that provide BrainChip with significant competitive advantages. The company held an exclusive license for the IP prior to their acquisition.

With the drafting of the "Artificial Intelligence Act" (April 2021), the European Commission has made its first attempt at comprehensively regulating the expansive world of AI. Whilst the draft legislation extensively addresses the regulation and classification of AI technology, it does not mention another area of concern regarding Artificial Intelligence, namely intellectual property rights. Identifying IP rights as a major issue, the EU Parliament adopted a resolution on IP rights for the development of AI technologies in October 2020. In it, the Parliament called upon the Commission to ensure a high level protection of intellectual property rights when regulating AI. Despite the report being forwarded to the Commission well before it finalized its proposal for the "Artificial Intelligence Act", the protection of intellectual property rights is not mentioned in the draft legislation. Merely an Annex published alongside it briefly mentions the challenges of protecting intellectual property rights in connection with AI-assisted outputs.

Intellectual Property rewards people for creativity and innovation. It is crucial to the proper functioning of an innovative economy. The UK is voted one of the best IP environments in the world. To keep it that way we are keen to look ahead to the challenges that new technologies bring. We need to make sure the UK's IP environment is adapted to accommodate them.

Despite the dreaded, looming uncertainty felt throughout 2020, the prevalence of Artificial Intelligence (AI) has been undeniable. Over the last four years, AI specialists reportedly represent the fastest-growing role in the United States. According to recent data from job site Indeed, jobs in AI have seen a recent explosion with a steady hike over the last five years. The report notes that AI job postings have gone up consistently over the past two years, with a 46% hike between 2018-2019, and a 51% spike between 2019-2020. The dramatic increase in job openings within AI hasn't gone unnoticed by savvy job seekers in the market.

Manufacturers and suppliers commonly offer maintenance contracts to companies who purchase operation-critical equipment. A preventative maintenance application based on a machine learning (ML) model can be used to help avoid failures that could impact business. To build the model, the manufacturer or supplier must spend time, money, and effort. However, to eliminate the costs of a maintenance contract, the customer could duplicate the model and manage the maintenance without the supplier's assistance. To build a machine learning (ML) model for maintenance, an appropriate training set must be collected and labeled; the architecture and training parameters must be chosen for optimal accuracy–speed trade-offs for the algorithm; and computing time is required to train it.

AI systems are already creating works that, if created by a human, would warrant IP protection. Reports of AI-created art, music, literary works, data, technology, formulas, flavors, and other innovations are becoming increasingly common. In 2016, for example, a new "Rembrandt" portrait was unveiled in the Netherlands, generated by an AI system that analyzed more than 300 real paintings of the Dutch master and then used AI, facial recognition, and 3D printing technologies to create an entirely new work in the same style. In 2018, a portrait created using AI sold for $432,500 at auction. A novel publicized as being the first book written by AI was published last year.

From self-driving vehicles and autonomous drones, to virtual doctors and automated personal assistants, AI is expected to fundamentally disrupt the way that people live, work and interact with each other. AI is increasingly the key to significant innovations across almost all segments of society, manifesting itself in vastly different applications. There are vast opportunities for businesses operating in industries where AI has become more prevalent. However, with these opportunities come significant challenges. Ashurst's series of articles on AI will consider these issues from an IP perspective.

In one of our latest blog posts, we went through the first part of our hints and tips on outsourcing agreements and artificial intelligence, covering #1 Technological evolution and benchmarking clauses, #2 Liability and limitations, and #3 Know-how transfer, insourcing and supplier replacement. Below is the second part on: #4 Intellectual Property, #5 Data protection and #6 Cyber risk and Insurance. Where AI systems are employed in the outsourcing of processes there could be a tight interdependency between customer's data and supplier's AI technology processing such data. It follows that customer and supplier must accurately regulate the ownership of the IP rights in the relevant data and technologies within the scope of their relationship. What should be particularly considered by the contracting parties is the ownership of data, databases and of any other protectable item of both parties existing before entering into the contractual relationship (background IP). The parties should also regulate the ownership of IP rights on the customisations of the AI system and on the protectable results thereof generated during the performance of the agreement, if any.

In 2016 The Washington Post unleashed a new reporter on the world, an artificial intelligence (AI) system called Heliograf. In its first year, it churned out 300 short reports on the Rio Olympics, followed by 500 brief articles about the presidential election, which clocked up pretty good engagement online. Meanwhile, pharmaceutical companies are increasingly turning to AI to drastically speed up the process of discovering new drugs, analysing huge quantities of data to come up with new molecules that could potentially have a therapeutic effect. However, according to most legal and technology experts, this scenario is a long way off. "From my perspective, at present AI is little more than a tool that can be wielded by the creator of a creative work or inventor of a new technical innovation in the same way a paintbrush is wielded by an artist or a CAD [computer-aided design] tool by an inventor," says Jeremy Smith, chartered patent attorney and partner at IP law firm Mathys & Squire.