Posts Tagged: "AI"

Artificial Intelligence (AI) is global, and copyright laws are national. Thus, some countries will have strict laws on making copies of copyrighted content to “train” an AI system while others will be more relaxed. Laws are about economics, and countries with more relaxed laws are likely to be countries with smaller creative industries and which wish to use the relaxed legal regime to attract AI investment. AI companies will use these jurisdictional differences as leverage to lobby for the relaxation of legal standards in countries with stricter laws.

As reported on IPWatchdog, the UK Supreme court recently ruled that a trained neural network (an Artificial Intelligence known as DABUS) could not be listed as the inventor on two patent applications filed by Dr. Stephen Thaler at the UK Intellectual Property Office (UKIPO). As a result, the two applications were treated as withdrawn for failing to comply with the requirements of the UK Patents Act 1977. This not a surprising decision for reasons that will be set out below, and it is consistent both with the earlier UK court decisions, and with the decisions of other jurisdictions around the world where Dr. Thaler has argued his case. The decision has, however, sparked interest in the questions of artificial intelligence and its ability both to “autonomously” devise inventions and to subsequently own them.

In the dynamic landscape of the legal industry, the winds of change are blowing stronger than ever, and the eye of the storm is centered on intellectual property (IP) practices. The catalyst for this transformation is the rapid diffusion of Generative Artificial Intelligence (GenAI) across industries. If we liken this to historical breakthroughs, the emergence of the internet 30 years ago pales in comparison, as GenAI’s impact is a staggering 100 times faster. The legal industry, once considered somewhat sheltered from disruptive forces, now finds itself at the epicenter of a tornado of change. This is particularly true for IP practices, where the intricacies of patent prosecution have long relied on intensive human involvement. As a partner entrusted with steering the strategy of your firm over the next decade, understanding the seismic shifts brought about by GenAI is paramount.

On December 8, 2023, provisional agreement was reached between the European Union (EU) Parliament and the EU Council on the basic content of the new AI Regulation (the “AI Act”) to be implemented as legislation in the EU. The text is still not publicly available as it is subject to certain further refinement over the coming weeks. However, there is information available in the public domain (including press releases issued by the European Union) as to the likely format of the AI Act. Additional background on the legislative process towards the AI Act is available here.

Copyright exits everywhere—from books on a library shelf to music playing on the radio, to the software running the electronic device on which you are reading this article. Copyright’s broad scope and extensive reach foster a varied and fascinating landscape of copyright cases. From cases involving the use of a celebrity photograph, animated dancing video game characters, to artificial intelligence (AI) infringement inquiries, the number and type of matters copyright touches is seemingly infinite. This provides an evergreen bounty of copyright cases to digest. The following highlights some of the top copyright decisions of 2023.

Unsurprisingly, the UK Supreme Court today ruled that Stephen Thaler’s AI Machine, DABUS, cannot be granted patents for inventions it autonomously created. While the Court suggested that questions such as whether inventions like DABUS’ should be patentable and if the meaning of the term “inventor” should be expanded are important ones that should be considered at a policy level, the present case was concerned solely with the interpretation of the present law, which clearly does not contemplate non-human inventors.  

On December 11, the Review Board of the U.S. Copyright Office (USCO) released a letter affirming the USCO’s refusal to register a work created with the use of artificial intelligence (AI) software. The decision to affirm the refusal marks the fourth time a registrant has been documented as being denied the ability to obtain a copyright registration over the output of an AI system following requests for reconsideration.

The U.S. Supreme Court’s Alice decision alleges that “…merely requiring generic computer implementation fails to transform that abstract idea into a patent-eligible invention.” And the Patent Eligibility Restoration Act (PERA) of 2023 alleges that “adding a non-essential reference to a computer by merely stating, ‘do it on a computer’ shall not establish such eligibility.” Clearly, it is assumed that “merely” doing something on a computer or “merely” saying “do it on a computer” is not a desirable thing in the eyes of some; a computer supposedly invalidates the inventive effort and “merely” doing something on a computer is undeserving of even consideration of a patent.

In September 2023, one man grabbed the authors’ attention with his astonishing story about defending his trademark registration from an opposition by professional trademark attorneys using ChatGPT. His months-long battle began in December 2022, less than a month after the public launch of the now infamous AI chatbot. Nine months later, Jamiel Sheikh — an entrepreneur, tech-guru, and adjunct professor — survived the pressure from formal proceedings and obtained a settlement from his opposer without spending a dime. As young trademark attorneys, we were horrified yet extremely curious about what he had done. This article is the result of speaking with Sheikh about his experience and the evolving needs and expectations of sophisticated legal service consumers.

Recently, Wen Xie argued on IPWatchdog that the U.S. Copyright Office (USCO) and the U.S. Patent and Trademark Office (USPTO) have reached different conclusions regarding “the creative and conceiving capabilities of machines,” which leads to intellectual property (IP) law being self-contradictory. According to Xie, the USCO presumes that artificial intelligence (AI) is creative, while the USPTO does not reach a similar conclusion regarding AI inventorship. I disagree.

In today’s high-tech landscape, the ancient fable of the goose that laid the golden eggs imparts profound wisdom. The farmer in that tale weighed the decision to continue accumulating wealth slowly by selling the golden eggs that his magical goose laid (one per day) or taking a risk by killing the goose to harvest all of the gold within it at once. (Ultimately, the farmer chose the murderous path only to discover the goose did not contain any riches.) Just as the farmer faced thorny decisions in the tale, modern tech executives grapple with complex choices between immediate returns and long-term potential while also maintaining a competitive edge. In the real world, an artificial intelligence (AI) system that can generate patentable outputs (such as designs for new drugs) stands as the metaphorical “goose” while the inventions it produces are analogous to the “golden eggs.” Steadfastly guiding this delicate dance is the patent attorney with expertise in AI technology.

Last week, the U.S. Copyright Office issued a notice of proposed rulemaking (NRPM) in the Federal Register as part of the triennial rulemaking process for exceptions to 17 U.S.C. § 1201’s prohibition against circumventing technological protection measures (TPMs) controlling digital access to copyrighted works. This proceeding is the ninth triennial Section 1201 rulemaking since passage of the Digital Millennium Copyright Act (DMCA) in 1998, and it starts with the Copyright Office intending to recommend renewal of all but one existing exemption. The Office also announced that it has received petitions for seven classes of newly proposed exemptions for which the agency will initiate three rounds of public comments.

Last week, the Writers Guild of America (WGA) reached a tentative three-year deal to resolve a writer’s strike following a labor dispute with the Alliance of Motion Picture and Television Producers (AMPTP). The deal was reached on September 27, 2023, after a 148-day strike, which was the second-longest in the union’s history. According to USA Today, the WGA’s leadership board has lifted the restraining order barring writers from returning to work, and its members will vote to officially ratify the agreement between October 2 and October 9. In a storyline that at one time would have been considered science fiction, a major point of contention between writers and producers was the use of artificial intelligence in the screenwriting process.

PERA is no doubt an ambitious bill. In terms of its design, the proposed legislation attempts to deal with each of the Supreme Court’s decisions in Alice, Mayo and Myriad, plus all of their progeny applications thereafter engendered by the Federal Circuit, the Patent Trial and Appeal Board (PTAB), all the way down to the U.S. Patent and Trademark Office (USPTO) examining corp. In a nutshell, the bill, if passed, would return us to a time when Bilski was the law of the land, which will no doubt be welcomed by many innovators.

Artificial intelligence (AI) is a field of computer science that creates software or models that mimic human reasoning or inference. Machine learning is a subset of AI which uses algorithms trained on massive amounts of data to allow the computer to learn with gradually improving accuracy without explicitly being programmed. The biopharmaceutical and healthcare fields produce massive amounts of data, including properties and characteristics of drug compounds, biological, genomic, and clinical data, efficacy of treatments, adverse events and risks, and electronic health records. The data may come from many sources, both public and proprietary. AI systems trained on such data can streamline and optimize the drug development process, including drug discovery, diagnosing diseases, identifying treatments and risks, designing clinical trials, and predicting safety and efficacy profiles, leading to increasing efficiency and reducing costs.