Brian Higgins

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In Part I, new proposed federal and state laws governing the collection, storage, and use of face (biometric) data in connection with facial recognition technology were described.  If enacted, those new laws would join Illinois’ Biometric Information Privacy Act (BIPA), California’s Consumer Data Privacy Act (CCPA), and Texas’ “biometric identifier” regulations in the governance of face-related data.  It is reasonable for businesses to assume that other state laws and regulations will follow, and with them…
Companies developing artificial intelligence-based products and services have been on the lookout for laws and regulations aimed at their technology.  In the case of facial recognition, new federal and state laws seem closer than ever.  Examples include Washington State’s recent data privacy and facial recognition bill (SB 5376; recent action on March 6, 2019) and the federal Commercial Facial Recognition Privacy Act of 2019 (S. 847, introduced March 14, 2019).  If…
On February 11, 2019, the White House published a plan for developing and protecting artificial intelligence technologies in the United States, citing economic and national security concerns among other reasons for the action.  Coming two years after Beijing’s 2017 announcement that China intends to be the global leader in AI by 2030, President Trump’s Executive Order on Maintaining American Leadership in Artificial Intelligence lays out five principles for AI, including “development of appropriate technical standards…
The harmful effects of biased algorithms have been widely reported.  Indeed, some of the world’s leading tech companies have been accused of producing applications, powered by artificial intelligence (AI) technologies, that were later discovered to exhibit certain racial, cultural, gender, and other biases.  Some of the anecdotes are quite alarming, to say the least.  And while not all AI applications have these problems, it only takes a few concrete examples before lawmakers begin to take…
Due in part to the learned nature of artificial intelligence technologies, the spectrum of things that exhibit “intelligence” has, in debates over such things, expanded to include certain advanced AI systems.  If a computer vision system can “learn” to recognize real objects and make decisions, the argument goes, its ability to do so can be compared to that of humans and thus should not be excluded from the intelligence debate.  By extension, AI systems that…
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…
One of the concerns expressed by those studying algorithmic decision-making is the apparent lack of transparency. Those impacted by adverse algorithmic decisions often seek transparency to better understand the basis for the decisions. In the case of software used in legal proceedings, parties who seek explanations about software face a number of obstacles, including those imposed by evidentiary rules, criminal or civil procedural rules, and by software companies that resist discovery requests. The closely-followed issue…
Digital conversational agents, like Amazon’s Alexa and Apple’s Siri, and communications agents, like those found on customer service website pages, seem to be everywhere.  The remarkable increase in the use of these and other artificial intelligence-powered “bots” in everyday customer-facing devices like smartphones, websites, desktop speakers, and toys, has been exceeded only by bots in the background that account for over half of the traffic visiting some websites.  Recently reported harms caused by certain…
As contentious political issues continue to distract Congress before the November midterm elections, federal legislative proposals aimed at governing artificial intelligence (AI) have largely stalled in the Senate and House.  Since December 2017, nine AI-focused bills, such as the AI Reporting Act of 2018 (AIR Act) and the AI in Government Act of 2018, have been waiting for congressional committee attention.  Even so, there has been a noticeable uptick in the number of individual federal lawmakers looking…
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…