News and Analysis of Artificial Intelligence Technology Legal Issues
US Capitol Building

Artificial Intelligence, GANs, and the law of Synthetic Data: Lawmakers React to False Media Content

It didn’t take long for someone to turn generative adversarial networks (GAN)–a machine learning technique that at first blush seemed benign and of somewhat limited utility at its unveiling–into a tool with the ability to cause real harm.  Now, Congress has stepped up and passed legislation to focus the federal government’s attention on the technology.  If signed by the president, the legislation will require two federal agencies to study the role GANs play in producing false media content and report their findings back to respective House and Senate committees, which is seen as a prelude to possible notice-and-comment regulations and…

A collage of individual images in an image data set

The Role of Explainable Artificial Intelligence in Patent Law

Although the notion of “explainable artificial intelligence” (AI) has been suggested as a necessary component of governing AI technology, at least for the reason that transparency leads to trust and better management of AI systems in the wild, one area of US law already places a burden on AI developers and producers to explain how their AI technology works: patent law.  Patent law’s focus on how AI systems work was not borne from a Congressional mandate. Rather, the Supreme Court gets all the credit–or blame, as some might contend–for this legal development, which began with the Court’s 2014 decision in Alice…

A colorful image generated by a GAN without real-world context

Generative Adversarial Networks and the Rise of Fake Faces: an Intellectual Property Perspective

The tremendous growth in the artificial intelligence (AI) sector over the last several years may be attributed in large part to the proliferation of so-called big data.  But even today, data sets of sufficient size and quality are not always available for certain applications.  That’s where a technology called generative adversarial networks (GANs) comes in.  GANs, which are neural networks comprising two separate networks (a generator and a discriminator network that face off against each another), are useful for creating new (“synthetic” or “fake”) data samples.  As a result, one of the hottest areas for AI research today involves GANs,…