Non-discrimination is a recognized objective in algorithmic decision making. In this paper, we introduce a novel probabilistic formulation of data pre-processing for reducing discrimination. We propose a convex optimization for learning a data transformation with three goals: controlling discrimination, limiting distortion in individual data samples, and preserving utility. We characterize the impact of limited sample size in accomplishing this objective, and apply two instances of the proposed optimization to datasets, including one on real-world criminal recidivism. The results demonstrate that all three criteria can be simultaneously achieved and also reveal interesting patterns of bias in American society.

There are approximately 1.3 million lawyers in America. A law firm is also made up of support staff such as paralegals, legal assistants and legal secretaries. In total, are approximately 271,000 paralegals and 202,000 legal secretaries in the United States. So with almost 500,000 law firm support staff jobs in America, the most common question I'm asked is: "Will automation and machine learning cause me to lose my job?" Duties carried out by most law firm support staff are administrative in nature. The most common are word processing, research, proofreading, data entry, filing and in some cases, document drafting.

The SEC began to do exactly that in reaction to the 2008 09 financial crisis and the 2010 flash crash systemic breakdowns that regulators didn t see coming. Hedge fund industry veteran Gregg Berman joined the SEC s division of trading and markets and spearheaded development of the Market Information Data Analytics System (MIDAS), which seeks to improve transparency to analyze trends and prevent crashes. The more ambitious Consolidated Audit Trail (CAT), an idea first floated in 2010 to give the SEC a complete database of market activity, is finally getting off the ground following the awarding of a contract in January to Thesys Technologies, the same trading technology company that worked with Berman on MIDAS.

For the past few years, analysts, politicians, and other thinkers have fretted about the potential impact of a "robot revolution" which could see AI drive humans out of the workforce. The LA Times recently reported that robots could take over 38 percent of current human jobs within 15 years, and we have seen AI steadily move into new fields such as law or journalism which few had predicted before. Despite the hype around AI, we will probably not see a world where humans are no longer needed. But as AI develops, businesses need to think about how to adapt to this changing paradigm. An examination of certain sectors should show both the benefits and limits of AI, and reveal that the future will be one where humans and AI cooperate instead of one supplanting the other.

A new website that predicts congressional bills' success foresaw the Affordable Care Act replacement bill would be shelved instead of passed – awarding it only a 15 percent chance of being enacted. Users can look up any pending bill on PredictGov or find predictions through its partner, legislation tracker GovTrack, which now includes a "prognosis" line in its overview of each bill. Vanderbilt University law Professor J.B. Ruhl is a co-founder in bill forecasting site PredictGov. PredictGov, which uses big data and artificial intelligence to reach its conclusions, is the invention of Vanderbilt University law Professor J.B. Ruhl; computer scientist and doctoral candidate John Nay, and their team. It pulls from decades of congressional data plus hundreds of variables, including the bill's sponsor, amendments, economic trends and political shifts.

Uber and Google are locked in a legal battle that could have huge implications for the future of the self-driving car industry. If Uber loses its lawsuit, it could cost the company millions and set back Uber's self-driving car effort by months -- months Uber probably can't afford to lose. The lawsuit started when Waymo, Google's self-driving car unit, alleged that Uber is using sensors based on stolen Waymo designs and asked the courts to block Uber from using the designs. Uber fired back in a legal brief on Friday, denying that its sensors were based on Waymo's technology and accusing Waymo of trying to tie up a legitimate competitor with frivolous litigation. It's not uncommon for the invention of an important new technology to be followed by legal battles over rights to that technology. Apple, for example, fought a years-long legal battle with Samsung, Motorola, HTC, and other makers of Android-based phones in the early years of the smartphone industry.

There are a lot of things that can go and have gone wrong throughout history -- earthquakes and wars and plagues and whatnot. The present state of our planet does not have to be highlighted by me in this post but a major change is coming, over unknown timescales but across every segment of society, and the people playing a part in that transition have a huge responsibility and opportunity to shape it for the best. What is triggering this change? Although most of us are unaware of it, AI systems are everywhere, from bank apps that let us deposit checks with a picture, to everyone's favorite Snapchat filter, to our handheld mobile assistants. While many countries' laws are deficient in terms of artificial intelligence ("AI") – which is defined as the simulation of human intelligence processes by computer systems and other machines,should we ignore the risks of any technology and not take precautions?

General artificial intelligence attempts to solve this problem using a traditional vision of artificial intelligence. This solution is akin to the vision often depicted in fictional books and movies. Hard artificial intelligence solves the problem by creating a computer that thinks like a human. This solution is to create artificial intelligence that thinks and acts like a reasonable person under the circumstance by creating a machine with a general intelligence that is broadly applicable to whatever problem might be presented. Conceptually speaking, this is identical to how human intelligence works.

Uber Technologies Inc said its self-driving technology was "fundamentally different" from Waymo's in a court filing, Friday. This comes after Waymo sued Uber in February, seeking a preliminary injunction to stop it from using trade secrets and other intellectual property. Uber, which has gone into damage control mode, presented a list of reasons to averse the possible injunction. According to a report filed in the Fortune, Uber made several arguments in its Friday's filing, which included: "To hinder Uber's continued progress in its independent development of an in-house LiDAR that is fundamentally different than Waymo's, when Uber has not used any of Waymo's trade secrets, would impede Uber's efforts to remain a viable business, stifle the talent and ingenuity that are the primary drivers of this emerging industry, and risk delaying the implementation of technology that could prevent car accidents. Ultimately, that would be harmful to the public," Uber said in its filing as Fortune reported.

Google's lawsuit alleging that Uber straight-up stole its autonomous vehicle technology won't go before a jury until October, but Uber already finds itself on dangerous ground. This week, the judge presiding over the civil case said he might just grant Google's request for a preliminary injunction, which could force Uber to rein in or even stop testing its robocar technology testing until the case is resolved. Eager to avoid the worst, Uber issued a response designed to limit the damage. All of this started in February when Waymo, Google's autonomous vehicle division, filed a lawsuit claiming former employee Anthony Levandowski downloaded 14,000 technical files from a company server and used the info to launch his autonomous truck startup Otto. Uber acquired Otto a few months later and put Levandowski in charge of its autonomous vehicle program.