Posts Tagged: "artificial intelligence"

Voice cloning, a technology that enables the replication of human voices from large language models using artificial intelligence (AI), presents both exciting possibilities and legal challenges. Recent machine-learning advances have made it possible for people’s voices to be imitated with only a few short seconds of a voice sample as training data. It’s a development that brings exciting possibilities for personalized and immersive experiences, such as creating realistic voiceovers for content, lifelike personal assistants and even preserving the voices of loved ones for future generations. But it’s also ripe with potential for abuse, as it could easily be used to commit fraud, spread misinformation and generate fake audio evidence.

On July 12, the U.S. Senate Judiciary Committee’s Subcommittee on Intellectual Property held its second hearing in two months on the intersection of artificial intelligence (AI) developments and intellectual property rights. This most recent hearing focused on potential violations of copyright law by generative AI platforms, the impact of those platforms on human creators, and ways in which AI companies can implement technological solutions to protect copyright owners and consumers alike.

Last week, comedian Sarah Silverman and authors Christopher Golden and Richard Kadrey sued OpenAI in a U.S. district court, alleging the company’s generative AI product, ChatGPT, infringes on their copyrighted content. In addition to copyright infringement, the trio also claimed that the AI company violated the Digital Millennium Copyright Act (DMCA), unfair competition laws and unjustly enriched the company. The lawsuit accuses OpenAI of “copying massive amounts of text” used to train ChatGPT to produce new text from prompts. Language models like OpenAI rely on datasets of text or other media to train its generative capabilities.

The generative artificial intelligence (AI) revolution the world is currently experiencing is powered by data. But what exactly are “data” and how can we make the term fit for use in the complex landscape of generative AI? In simple terms, data in this context can be any digitally formatted information. However, there is an inconsistency in the usage and understanding of the term when it comes to what is encompassed in a dataset used for training a generative AI model. Often, there is metadata or even identifiable information which, although possibly unintended, ends up being part of the training data. There can also be legal implications linked to the data, including systems trained on copyrighted or licensed works, or, for example, systems trained with any visual or textual information containing personal health information.

In the first installment of this two-part series, we posed a question: What is at the intersection of name, image, likeness rights (NILs), non-fungible tokens (NFTs), artificial intelligence (AI) creations, big data, blockchain, and the metaverse? The answer is – intellectual property. Our hypothetical described a high school basketball star, Sky-Freeze, who sought to leverage their name, image, and likeness (NIL) on a metaverse platform, illustrating how a digital avatar, corresponding NFTs in the metaverse, AI, and big data intersect. This second installment explores how AI impacts the intersection, giving rise to legal issues concerning intellectual property rights.

There is no question that artificial intelligence (AI) has led to a monumental shift in intellectual property law and strategy. Most companies and attorneys are familiar with the current unsettled legal landscape as it relates to inventorship laws for intellectual property—namely, that inventions and works that are created through AI may or may not be eligible for patent or copyright protection, depending on the circumstances. But quietly in the background, AI has already been changing—and continues to change—how IP portfolios are created and managed. Below are five key ways that AI is changing how companies handle their IP portfolios. 

The use of Artificial Intelligence (AI) has taken center stage in popular culture thanks to the significant advances of tools like ChatGPT. Of course, the use of these new, high-powered AI tools presents real issues for businesses of all types and all sizes. Notably, Samsung employees shared confidential information with ChatGPT while using the chatbot at work. Subsequently, Samsung decided to restrict the use of generative AI tools on company-owned devices and on any device with access to internal networks. Concerned about the loss of confidential information, Apple has likewise restricted employees from using ChatGPT and other external AI tools. The actual or potential loss of confidential information is a matter of critical importance to technology companies, but it also must be of the utmost concern for all attorneys who have an ethical obligation to keep client information confidential.

Artificial Intelligence (AI) has become a crucial tool for organizations in various sectors, particularly in the generation of content and code by generative AI systems such as ChatGPT, GitHub Copilot, AlphaCode, Bard and DALL-E, among other tools. As the promise of incorporating these generative tools in the corporate setting is all but assured in the near term, there are a number of risks that need to be minimized as companies more forward. In particular, as AI applications grow increasingly sophisticated, they raise concerns with several forms of intellectual property (IP), such as patents, copyrights, and trade secrets. This article aims to discuss these issues and provide a sample company policy for using AI-generated content such as software code.

In response to last week’s hearing of the House of Representatives’ Subcommittee on Courts, Intellectual Property and the Internet about the impact of artificial intelligence (AI) on copyright law, former Copyright Office General Counsel, Jon Baumgarten, submitted a letter this week to the Subcommittee expressing his concerns with the testimony of one of the witnesses, Sy Damle of Latham & Watkins, who also formerly served as U.S. Copyright Office General Counsel. The letter was published in full on the Copyright Alliance website.

The House of Representatives’ Subcommittee on Courts, Intellectual Property and the Internet today held the first of several planned hearings about the impact of artificial intelligence (AI) on intellectual property, focusing in this initial hearing on copyright law. The witnesses included three artists, a professor, and an attorney with varying perspectives on the matter, although the artists all expressed similar concerns about the potentially dire effects of generative AI (GAI) applications on their respective industries and careers.

The patent examination process is subject to the well-known issue of hindsight bias. Issues with hindsight bias come up when a patent examiner, without realizing it, uses their knowledge of the invention itself to reject a claim as being obvious. If left unchecked, these issues can lead to incorrect determinations of obviousness, which prolong prosecution, cause unnecessary ex parte appeals to be filed, and force unfair narrowing of independent claims. However, even when an examiner learns about an invention that seems straightforward, human emotions and subjectivity can make it difficult for that examiner to appreciate that the invention was not obvious based on prior art that existed before the invention.

The issue of AI inventorship in the United States remains at large following the Supreme Court’s denial of cert in Thaler v. Vidal, meaning that the U.S. Patent and Trademark Office (USPTO) finding that AI cannot be considered a named inventor to a patent application remains the law of the land. Now that the agency is seeking public comments on the issue of AI inventorship, I reached out to Dr. Thaler to get his comments on the current AI inventorship debate within the patent space.

Generative Artificial Intelligence (GAI) promises to improve information gathering and reduce costs in a myriad of economic processes. Since patent law is essentially about recording and accessing information, tools like ChatGPT are great candidates to ease the tasks of patent professionals. As of today, it is not possible to trust GAI tools with confidential information, since any prompt provided to these tools does not guarantee confidentiality and data protection, unless an entity creates its own sandbox with customized implementations that protect the data.

On April 27, a pair of legal measures were advanced within the European Union that promise to greatly impact the state of technological commercialization within Europe for both standardized and artificial intelligence (AI) technologies. While political leaders in the EU maintain that either proposal addresses consumer safety and competition concerns, multiple commentators have pointed out issues that could slow the rate of technological commercialization to the detriment of Europeans across the continent.

The U.S. Patent and Trademark Office (USPTO) held its East Coast Listening Session on AI Inventorship today, featuring both USPTO staff and patent stakeholder speakers contemplating possible approaches to patenting in a world in which generative artificial intelligence (AI) almost seems to have snuck up on everyone. While many speakers cautioned against moving too quickly to change the rules for AI-generated inventions, others warned that doing nothing could result in chaos for the USPTO and grave economic and innovation losses for the country.