It's long been thought that robots equipped with artificial intelligence would be the cold, purely objective counterpart to humans' emotional subjectivity. Unfortunately, it would seem that many of our imperfections have found their way into the machines. It turns out that these A.I. and machine-learning tools can have blind spots when it comes to women and minorities. This is especially concerning, considering that many companies, governmental organizations, and even hospitals are using machine learning and other A.I. tools to help with everything from preventing and treating injuries and diseases to predicting creditworthiness for loan applicants. These racial and gender biases have manifested in a variety of ways.

A petition calls on Amazon and Apple to reprogram Alexa and Siri so the voice assistants can push back against sexual harasments comments from users toward the voice assistant. The call comes as the #MeToo movement gives a voice to those who have been sexually harassed. Actress Alyssa Milano started the online campaign in October after Miramax co-founder Harvey Weinstein was accused of sexual harassment and rape by multiple women. The recent Siri and Alexa petition was launched on Care2 and has more than 6,000 supporters out its 10,000 signature goal. "In this #MeToo moment, where sexual harassment may finally be being taken seriously society, we have a unique opportunity to develop AI in a way that creates a kinder world," the petition said.

Understanding the causes of crime is a longstanding issue in researcher's agenda. While it is a hard task to extract causality from data, several linear models have been proposed to predict crime through the existing correlations between crime and urban metrics. However, because of non-Gaussian distributions and multicollinearity in urban indicators, it is common to find controversial conclusions about the influence of some urban indicators on crime. Machine learning ensemble-based algorithms can handle well such problems. Here, we use a random forest regressor to predict crime and quantify the influence of urban indicators on homicides. Our approach can have up to $97\%$ of accuracy on crime prediction and the importance of urban indicators is ranked and clustered in groups of equal influence, which are robust under slightly changes in the data sample analyzed. Our results determine the rank of importance of urban indicators to predict crime, unveiling that unemployment and illiteracy are the most important variables for describing homicides in Brazilian cities. We further believe that our approach helps in producing more robust conclusions regarding the effects of urban indicators on crime, having potential applications for guiding public policies for crime control.

Leading artificial-intelligence researchers gathered this week for the prestigious Neural Information Processing Systems conference have a new topic on their agenda. The issue was crystallized in a keynote from Microsoft researcher Kate Crawford Tuesday. The conference, which drew nearly 8,000 researchers to Long Beach, California, is deeply technical, swirling in dense clouds of math and algorithms. Crawford's good-humored talk featured nary an equation and took the form of an ethical wake-up call. She urged attendees to start considering, and finding ways to mitigate, accidental or intentional harms caused by their creations. "Amongst the very real excitement about what we can do there are also some really concerning problems arising," Crawford said.

Companies that are testing delivery robots hit a stumbling block in San Francisco this week. The city's Board of Supervisors voted to require permits for any autonomous delivery devices, restricting them to specific (and less-crowded) areas of the city. Additionally, these robots aren't allowed to make actual deliveries -- they are only allowed to be used for testing purposes. This restriction doesn't apply to delivery drones; the San Francisco Board of Supervisors only has jurisdiction over the sidewalks. Complaints were first brought by a group called Walk San Francisco, which campaigns for the safety of pedestrians.

During a pair of explosive pre-trial hearings last week, the lawsuit between self-driving Alphabet spinoff Waymo and Uber over trade secrets got an unlikely, new star player. It wasn't an engineer, like Anthony Levadowski, the former Google engineer who allegedly brought reams of Waymo trade secrets to his next big gig as head of autonomous driving at Uber. It wasn't a security analyst, like Ric Jacobs, a former Uber employee whose allegations of malfeasance within the company delayed the Uber-Waymo trial by two months as the judge reopened the document discovery process. It was a messaging app. Anybody can download Wickr to send encrypted messages that destroy themselves, but its professional, workplace product takes the extra step of giving the employers the power to determine how long the messages stick around before it deletes them.

The digital revolution has brought with it a new way of thinking about manufacturing and operations. Emerging challenges associated with logistics and energy costs are influencing global production and associated distribution decisions. Significant advances in technology, including big data analytics, AI, Internet of Things, robotics and additive manufacturing, are shifting the capabilities and value proposition of global manufacturing. In response, manufacturing and operations require a digital renovation: the value chain must be redesigned and retooled and the workforce retrained. Total delivered cost must be analyzed to determine the best places to locate sources of supply, manufacturing and assembly operations around the world.

You don't even need to make a purchase or visit a website for data science companies to collect information about you. There are all kinds of public data, from property tax records to company and university information, aggregated through startups such as Enigma while Thasos and Reveal Mobile sell pedestrian geolocation data. "I can show that someone saw that ad [online] and actually went into the store," Reveal Mobile CEO Brian Handly told the audience how his startup makes user profiles to map diverse data about individuals at the Artificial Intelligence & Data Science conference in New York City. "Then using that to enhance the advertising targeting." Reveal Mobile passively collects data from more than 50 million phones per month through local news apps, weather apps, travel apps such as Roadtripper and many more.

Advent is upon us, and the season of overconsumption begins! My wife and I attended our first Christmas party of the year yesterday and the tree and decorations are going up this evening, in a solid attempt to be better organised this year! Whilst many of us might be starting to ease off for Christmas now, the LawTech sector has had another busy week. Legal Futures' Dan Bindman has written a great in depth piece on the Ailira chatbot that we mentioned in last weeks LawTech Review. Artificial Intelligence may help you win your next court case!

New York, NY - October 18 - Trial lawyer John H. Snyder, counsel for the former Trustees of the Healthcare Industry Trust of New York, which collapsed in 2007 as a result of corporate venality and governmental incompetence (see here), has asked Albany Supreme Court Justice Richard M. Platkin to order the Workers Compensation Board and certain "Ringleaders" of the infamous CRM insurance scam to submit their emails for analysis by Artificial Intelligence. Previously, lawyers for the disgraced CRM Ringleaders Daniel Hickey Jr., Daniel Hickey Sr., Martin Rakoff, and Louis Viglotti argued that discovery would cost $4 million. Snyder has responded with a plan to accomplish discovery at a cost to CRM of $140K, a 96% savings. Snyder's plan involves the use of Artificial Intelligence in lieu of manual review of millions of emails, which is expensive and ineffective. At Snyder's request, Yippy, Inc. has agreed to host the discovery data and provide its world-leading email search functionality for the benefit of the Court, the parties, and the taxpayers, free of charge.