Welcome to Invisibilia Season 4! The NPR program and podcast explores the invisible forces that shape human behavior, and we here at Shots are joining in to probe the science of why we act the way we do. On paper, Shon Hopwood's life doesn't make a lot of sense, not even to him. "I don't have a great excuse as to why I did these things. And everybody always wants that," he tells me. "It closes the circle for people. But that's not really how it happened."

Maintaining regulatory compliance is a daunting task. Up to 200 regulatory changes occur every day, varying from large scale regulation like Dodd Frank, to minute changes to the font and size of footnotes in regulation text. The cost of not being compliant is astronomical – since 2008, more than $50 billion in fines have been paid. Banks and financial institutions are looking for any advantage they can get to streamline operations and reduce compliance costs. IBM Think, the three-and-a-half day event that emphasizes'mankind machine', highlights using IBM's vast background in cognitive computing to, in this instance, help compliance professionals to play by the rules and maintain compliance, avoid sizeable penalties and leverage machine learning and artificial intelligence to make their jobs easier.

But the state Court of Appeals ruled Thursday that the satirical representations of "a modern, beach-going" young woman are not identifiable as Lohan. The court affirmed a ruling from a lower state appeals court dismissing her lawsuit.

Dark data is the material a company collects, stores and processes during its daily operations, but typically does not use for purposes that could be beneficial. There are numerous ways dark data is impacting the ways entities analyze and use data. Data collected as part of publicly funded research occurring in the United States and some other nations must be kept in public databases. However, one research study investigated how materials collected in the 1970s and 1980s about zooplankton existed during a time when the technology was not available to publicize that data. Scientists know this kind of dark data could give valuable information about how the ocean has changed since those past generations due to climate change.

On December 15, 2017, the United Nations Special Rapporteur on extreme poverty and human rights, Philip Alston, issued a damning report on his visit to the United States. He cited data from the Stanford Center on Inequality and Poverty, which reports that "in terms of labor markets, poverty, safety net, wealth inequality, and economic mobility, the US comes in last of the top 10 most well-off countries, and 18th amongst the top 21." Alston wrote that "the American Dream is rapidly becoming the American Illusion, as the US now has the lowest rate of social mobility of any of the rich countries." Just a few days before, on December 11, The Boston Globe's Spotlight team ran a story showing that the median net worth of nonimmigrant African American households in the Boston area is $8, in contrast to the $247,500 net worth for white households in the Boston area. Clearly income disparity is ripping the nation apart, and none of the efforts or programs seeking to address it seems to be working. I myself have been, for the past couple of years, engaged in a broad discussion about the future of work with some thoughtful tech leaders and representatives of the Catholic Church who have similar concerns, and the notion of a universal basic income (UBI) keeps coming up.

Predictive algorithms promoted and used by Hackney council to identify those most in need of scarce preventive services is an important issue for us to think more deeply about. In that article, Steve Liddicott reasoned that in the context of reduced spending on prevention services, identifying those most in need earlier could prevent children ending up in more intensive services like child protection. The article presents the reduction of spending as a given and promotes algorithms as a method of distributing what little is left. In this response, we argue this is not a benign activity and is ethically fraught. Firstly, the reduction of services leaves significant holes that an algorithm can't fix.

MENTION ARTIFICIAL INTELLIGENCE, and most people will think of robots. But a more fitting image may be that of Janus, the Roman god of beginnings, transitions and endings, who has two faces looking in opposite directions. On one side are the positive changes that AI will bring, enabling people to achieve more, far more quickly, by using technology to enhance their existing skills. Recruiters will be able to pinpoint the best candidates more easily, and customer-service staff will be able to handle queries faster. Jobs that never existed before could be created.

The technology entrepreneur Elon Musk recently urged the nation's governors to regulate artificial intelligence "before it's too late." Mr. Musk insists that artificial intelligence represents an "existential threat to humanity," an alarmist view that confuses A.I. science with science fiction. Nevertheless, even A.I. researchers like me recognize that there are valid concerns about its impact on weapons, jobs and privacy. It's natural to ask whether we should develop A.I. at all. I believe the answer is yes. But shouldn't we take steps to at least slow down progress on A.I., in the interest of caution?

The family of the woman killed by an Uber self-driving vehicle in Arizona has reached a settlement with the ride services company, ending a potential legal battle over the first fatality caused by an autonomous vehicle. Cristina Perez Hesano, attorney with the firm of Bellah Perez in Glendale, Arizona, said "the matter has been resolved" between Uber and daughter and husband of Elaine Herzberg, 49, who died after being hit by an Uber self-driving SUV in Tempe earlier this month. Terms of the settlement were not given. The law firm representing them said Herzberg's daughter and husband, whose names were not disclosed, will have no further comment on the matter as they consider it resolved. Fall-out from the accident could stall the development and testing of self-driving vehicles, which are designed to eventually perform far better than human drivers and sharply reduce the number of motor vehicle fatalities.

Tempe Police are still investigating the fatal crash where an Uber autonomous SUV struck and killed a pedestrian and there are many questions about the safety of its procedures and technology. However, one aspect of the case has been resolved, as Reuters reports that the family of Elaine Herzberg has reached a settlement with the company, avoiding a civil trial in this, the first known incident where someone has died after being struck by a self-driving car. Cristina Perez Hesano, an attorney with Bellah Perez, said "the matter has been resolved," while Uber declined to comment. The terms of the agreement are confidential. Questions over liability in the case of a crash with a self-driving car have been asked ever since the technology became a realistic option. In this situation, it's Uber's technology, vehicle and test driver behind the wheel, but how this would go for a vehicle owned by a private citizen -- or what may happen if the police find Uber's car is at fault -- is still unknown.