David Kline is a journalist, author and intellectual property strategist. With every new trend comes a counter-trend. And so despite the current excitement over the wonders of artificial intelligence, one company is betting that human intelligence can still deliver solutions for businesses that AI cannot hope to match. Article One Partners (AOP) is a crowdsourced network of over 42,000 researchers in 170 countries -- 42% of whom have graduate degrees in a variety of science, technology, and engineering specialties. The firm got its start uncovering patent-busting prior art for defendants in high-stakes patent infringement suits, where it quickly earned a reputation for finding invalidating prior art in hidden corners of the globe that Google search could never reach -- an unpublished Korean-language PhD dissertation, a rural Norwegian library, even in a New York City pawn shop.

We argue that social simulation can help us understand social justice issues. In particular, modeling certain social dynamics within computational systems can be used to creatively explore and better understand the social and identity dynamics of oppression. Writing theories of oppression in code forces us to explicate everything, and question what we leave out or what we can’t account for. As an early step in this direction, we present an in-progress social simulation of group discussion in activist meetings, developed in the already-existing AI system, Ensemble. Through this minimal, highly constrained social arena, we can explore wide-reaching phenomena like privilege, intersectionality, and power dynamics in nonhierarchical groups, but in a way that’s grounded in concrete, person-to-person interactions. We propose that this kind of social simulation can aid in the process of unlearning hegemonic ways of being, and imagining liberatory alternatives.

We consider the problem of using observational data to learn treatment assignment policies that satisfy certain constraints specified by a practitioner, such as budget, fairness, or functional form constraints. This problem has previously been studied in economics, statistics, and computer science, and several regret-consistent methods have been proposed. However, several key analytical components are missing, including a characterization of optimal methods for policy learning, and sharp bounds for minimax regret. In this paper, we derive lower bounds for the minimax regret of policy learning under constraints, and propose a method that attains this bound asymptotically up to a constant factor. Whenever the class of policies under consideration has a bounded Vapnik-Chervonenkis dimension, we show that the problem of minimax-regret policy learning can be asymptotically reduced to first efficiently evaluating how much each candidate policy improves over a randomized baseline, and then maximizing this value estimate. Our analysis relies on uniform generalizations of classical semiparametric efficiency results for average treatment effect estimation, paired with sharp concentration bounds for weighted empirical risk minimization that may be of independent interest.

Documents uncovered as part of a separate court case reveal that multi-millionaire Silicon Valley elitist Anthony Levandowski started a religion based around the concept of worshipping artificial intelligence as a God. Levandowski, who is currently embroiled in a high profile lawsuit with Google over accusations he stole sensitive data about their self-driving car program and gave it to Uber, founded a religious organization called Way of the Future two years ago. The goal of the religion is to "develop and promote the realization of a Godhead based on Artificial Intelligence," in line with the species reaching the singularity, the point at which computers surpass humanity in intelligence.

This post was originally published on The Business Insider. Robots are coming for your job. That may sound vaguely dystopian, but it's on the horizon. A 2013 study from Oxford University found that a whopping 47% of US jobs could be automatized in 20 years. Jobcase CEO and founder Fred Goff has seen fears about this trend crop up among some of the 70 million users of his blue-collar-friendly job site.

It's not exactly news that Hugh Hefner, the perpetually robed Playboy founder who died Wednesday at the age of 91, is a polarizing figure. For decades Americans have disagreed about whether he should be remembered as a great liberator of Americans from their sexual puritanism or as a sexist exploiter of women. On Thursday, columnist Robin Abcarian came down strongly on the latter side, writing that although we shouldn't forget Hefner's support for smart journalism, reproductive rights and civil liberties, we should also not lose sight of the fact that his core business was the objectification of women -- mostly women under 30 -- and the exalting of exclusively male fantasies. Before Abcarian's column was published, the letters on Hefner's death reflected the typical mix of opinions we get after most notable celebrity passings: Several mentioned the existence of strong polarization over Hefner's work without taking a side, others reflected dispassionately on his work, and a few recounted their own experiences with Hefner. It was only in response to Abcarian's column that more readers started expressing stronger opinions on Hefner's work itself.

We've already written about using business case studies, whether your personality is too legal, the importance of eSignatures, and the nine ways the legal profession needs to change. We're now in our final article in our series based on learning from the Corporate Legal Operations Consortium (CLOC) annual meeting. Ginger Dolgow, senior manager at NetApp, Tami Baddeley, operations lead at Microsoft, and Mike Naughton, senior manager at Cisco, all agree: though it is a highly hyped topic of conversation, artificial intelligence is, indeed, the future of legal operations. "The good news is that AI is more than hype and can offer strong returns on investment," they explain. "The bad news is that getting a solid return on investment in AI often requires a further investment of time and money. These solutions do not deliver as promised right out of the box."

Customers, Financial Institutions (FIs) have seen the explosion of FinTech in the last several years. In fact, Financial Institutions are expected to invest more than $118.70 billion on technologies by 2020. RegTech is one of the most recent technologies disrupting the risk and compliance space. The Financial Conduct Authority (FCA) describes RegTech as the "adoption of new technologies to facilitate the delivery of regulatory requirements." Despite the fact that technology has been used to address regulatory requirements, RegTech innovations have enhanced the adoption and utilisation of technology for better and faster outcomes in the financial sector.

For those in the artificial intelligence community, AI has been around a long time. Originally dating back to the 1950s, AI research has been a fixed part of the landscape since the 1980s becoming a multibillion dollar industry long before the millennium. But for the wider public, AI has only received real attention in the last year or two. During that time, AI has made big news. Google images for AI show a range of anthropomorphized images typically illustrating scare stories of robots supplanting humans in a whole variety of jobs with a clear message echoed recently by Mark Carney: you will soon be redundant.

A dais stuffed with well-fed lawmakers sure doesn't look like a battlefield, but make no mistake: The long-awaited war between self-driving vehicles and the humans they would replace has begun. And the humans just won the first skirmish. Thursday morning, the Senate released the first version of autonomous vehicle legislation meant to clarify who exactly is in charge of robocar regulations. It comes a few weeks after senators circulated a draft of the rules, and contains a significant difference from the older version: The Senate deleted the original mention of commercial motor vehicles like trucks and buses. Now big vehicles are exempt from the bill--meaning that rules for self-driving trucks are still unclear.