Please join Duane Morris partner Agatha Liu and representatives from the USPTO and U.S. Copyright Office for a discussion on the development of AI policies on October 26, 2023, from 12:00 p.m. to 1:00 p.m. Pacific.
This webinar, hosted by the California Lawyers Association, will address the US Copyright Office’s and USPTO’s recent requests for public comments, which touch on several novel and hotly contested issues regarding determining how to incorporate copyrighted works in datasets used to train AI models, tracking and disclosing AI models and the input and output data of AI models, and assigning liability for outputs produced by AI models.
For more information and to register, please visit the CLA website.
Now that artificial intelligence (AI) is employed widely with unprecedented consequences, there is quite a scramble to implement mitigating measures. For example, the United Trademark and Patent Office (USPTO) is soliciting public comments on what steps the USPTO should take to mitigate harms and risks from AI-enabled invention. Many of the proposed guardrails are applicable to the deployment of AI technology, to conform original output of the AI technology to desired principles, policies, guidelines, etc. However, it is no less valuable to improve the design of the AI technology, especially when various computational techniques can be readily applied.
One fundamental issue with the AI technology is producing inaccurate output, with random, sporadic errors or, more damagingly, systemic deviations leading to bias. This article presents a systematic review of how computational techniques can be utilized to help mitigate such bias. […]
Read the full article by Agatha Liu, Ph.D.
The rapidly evolving landscape of advanced technology renders data one of the most valuable commodities today. This is especially true for artificial intelligence (AI), which can advance significantly in capability and complexity by learning from massive data sets used as training data. …
[This article identifies] considerations companies should account for when undertaking efforts to protect their online data based on an analysis of legal protections applicable to companies’ online data against unauthorized use.
Read the full article by Agatha H. Liu and Ariel Seidner.
The Copyright Registration Guidance (Guidance) published by the United States Copyright Office in March mainly addressed whether a human providing simple prompts or other input to an artificial intelligence (AI) algorithm could obtain a copyright registration for the output that the AI algorithm generated based on the human input. Working with AI algorithms all the time, I previously discussed whether the creator of the AI algorithm, and not the user, could obtain a copyright registration for that output. Now a few months later, a court has handed out a decision on whether to grant a copyright registration to the AI algorithm in Thaler v. Perlmutter, 1:22-cv-01564 (D.D.C).
That’s right. The court was confronted with the issue of whether to grant a copyright registration to the AI algorithm or the machine running the AI algorithm, rather than the creator of the AI algorithm. The plaintiff in this case has been a proponent of giving credit to machines running the plaintiff’s AI algorithms instead of the plaintiff directly, regardless of whether the AI algorithms output more algorithms or artworks. See Thaler v. Vidal, No. 21-2347 (Fed. Cir. 2022).
To support the position that the plaintiff’s machine should be granted a copyright registration, the plaintiff consistently represented in the copyright application that the AI algorithm generated the work “autonomously” and that the plaintiff played “no role” in the generation. This representation undermines any creative effort that the plaintiff may have made in producing the work. In general, while an AI algorithm once developed may be executed autonomously without human intervention, the AI algorithm was not developed in a vacuum and a human could have incorporated various creative elements into the AI algorithm, as discussed in my previous blog post.
Continue reading “Can a Human Behind AI Be Creative?”
Digital data is becoming a hot commodity these days because it enables AI tools to do powerful things. Companies that offer content should keep up with the evolving technology and laws that can help them protect their online data.
As data becomes available online, it can be accessed in different ways leading to various legal issues. In general, one basis for protecting online data lies in the creativity of the data under the Copyright Act of 1976. Another basis lies in the technological barrier of the computer system hosting the data under the Computer Fraud and Abuse Act (CFAA) and Digital Millennium Copyright Act. It is also possible to protect online data based on contractual obligations or tort principles under state common law. In terms of the data, a company would need to consider its proprietary data and user-generated data separately, but any creative content is invariably entitled to copyright protection. Without owning the data, the company can still enforce the copyright via an exclusive license from its users. In terms of the computer system, a company could evaluate different security measures for restricting access to the data without severely sacrificing visibility and usability of the company, the data and/or the computer system.
In a typical scenario, a company may make its data accessible to the public as is, publicly available in an obscured or tracked form, and/or accessible only to a select group. Let’s consider these scenarios separately.
Continue reading “Protecting Your Company’s Online Data”
On March 16, 2023, the United States Copyright Office (USCO) published Copyright Registration Guidance (Guidance) on generative AI. In the Guidance, the USCO reminded us that it “will not register works produced by a machine or mere mechanical process that operates randomly or automatically without any creative input or intervention from a human author.” This statement curiously conjures the notion of a machine creating copyrightable works autonomously.
While the operation of a machine, or specifically the execution of the underlying AI technology, may be largely mechanical with little human involvement, the design of the AI technology can take significant human effort. If we look at protecting human works that power machines as intellectual property in the broad context where AI has been applied, just like authorship has been an issue when an AI technology is used in creating copyrightable subject matter, inventorship has been an issue when an AI technology is used in generating an idea that may be eligible for patent protection. Unlike the evaluation of authorship, though, the assessment of inventorship puts human contribution to the AI technology front and center. Without getting into the reasons for this difference in treatment, let’s consider the question of whether an AI technology used in creating copyrightable subject matter, or specifically the human contribution to such an AI technology, generally does or does not provide any “creative input.”
Continue reading “Can A Machine Be Creative?”