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…

A computer science professor at Cornell University has a new twist on Marc Andreessen’s 2011 pronouncement that software is “eating the world.”  According to Vitaly Shmatikov, it is “machine learning [that] is eating the world” today.  His personification is clear: machine learning and other applications of artificial intelligence are disrupting society at a rate that shows little sign of leveling off.  With increasing numbers of companies and individual developers producing customer-facing AI systems, it…

By signing into law the John S. McCain National Defense Authorization Act for Fiscal Year 2019 (H.R.5515; Public Law No: 115-232; Aug. 13, 2018), the Trump Administration has established a strategy for major new national defense and national security-related initiatives involving artificial intelligence (AI) technologies.  Some of the law’s $717 billion spending authorization for fiscal year 2019 includes proposed funding to assess the current state of AI and deploy AI across the Department…