The Supreme Court expressed sympathy Tuesday for the family of a Mexican teenager fatally shot from across the U.S.-Mexico line by a Border Patrol agent, but struggled to reach consensus on whether foreign nationals – like the teen's relatives – can sue in American courts. The divisions were on display during oral arguments for what has become a closely watched case, amid an escalating political debate in Washington over border security. The arguments were held the same day the Department of Homeland Security released new directives on immigration enforcement, and after a lower federal court blocked a separate executive action from President Trump on immigration and refugee restrictions. Apart from renewed interest in the court's consideration of immigration disputes, the case heard Tuesday also could have implications for other U.S. government actions taken overseas -- including military drone strikes against suspected terrorists, and electronic surveillance over the Internet. In the current dispute, 15-year-old Sergio Hernandez was just steps from the border on Mexican soil when he was killed in 2010 by Jesus Mesa Jr., an agent standing on the American side in El Paso, Texas. The federal agent was not prosecuted, and the U.S. refused to extradite him to Mexico.

The rapidity of recent Chinese advances in artificial intelligence indicates that the country is capable of keeping pace with, or perhaps even overtaking, the United States in this critical emerging technology. The successes of major Chinese technology companies, notably Baidu Inc., Alibaba Group and Tencent Holding Ltd.--and even a number of start-ups--have demonstrated the dynamism of these private-sector efforts in artificial intelligence. From speech recognition to self-driving cars, Chinese research is cutting edge. Although the military dimension of China's progress in artificial intelligence has remained relatively opaque, there is also relevant research occurring in the People's Liberation Army research institutes and the Chinese defense industry. Evidently, the PLA recognizes the disruptive potential of the varied military applications of artificial intelligence, from unmanned weapons systems to command and control. Looking forward, the PLA anticipates that the advent of artificial intelligence will fundamentally change the character of warfare, ultimately resulting in a transformation from today's "informationized" (信息化) ways of warfare to future "intelligentized" (智能化) warfare.

Not too long ago, online banking and live chat with a bank or credit card representative felt cutting-edge. Now, financial institutions are upping the ante by launching chatbots to interact with customers. Powered by artificial intelligence, these chatbots can quickly answer questions about balances, recent transactions or other queries. In addition to financial chatbots, bots used in other industries serve all kinds of purposes from helping you order a pizza to answering questions on the U.S. immigration website. Banks and credit card issuers hope that bots will help answer consumers' questions in the online environments where they already are -- without having to log in to a website or app each time they want to view recent transactions or check their balance.

Network embeddings have become very popular in learning effective feature representations of networks. Motivated by the recent successes of embeddings in natural language processing, researchers have tried to find network embeddings in order to exploit machine learning algorithms for mining tasks like node classification and edge prediction. However, most of the work focuses on finding distributed representations of nodes, which are inherently ill-suited to tasks such as community detection which are intuitively dependent on subgraphs. Here, we propose sub2vec, an unsupervised scalable algorithm to learn feature representations of arbitrary subgraphs. We provide means to characterize similarties between subgraphs and provide theoretical analysis of sub2vec and demonstrate that it preserves the so-called local proximity. We also highlight the usability of sub2vec by leveraging it for network mining tasks, like community detection. We show that sub2vec gets significant gains over state-of-the-art methods and node-embedding methods. In particular, sub2vec offers an approach to generate a richer vocabulary of features of subgraphs to support representation and reasoning.

Uber's sexual harassment case is the latest controversy in a long history of the ride-sharing company flouting regulations and, according to the company's critics, ignoring ethical and legal standards in the name of "disruption". The San Francisco-based technology corporation is facing a widespread backlash after a former engineer went public with her story of sexual harassment and discrimination by management and repeated rebuffs from the HR department, adding fuel to the #DeleteUber campaign that went viral last month. The company has hired former US attorney general Eric Holder to investigate the claims. Consumer activists and social justice organizers, who have pushed for stricter regulations of Uber, point to the scandal as another example of the company's disdain for business norms. From questionable labor practices to privacy concerns to flagrant rejections of transportation laws, Uber has built its service through a culture of defiance that opponents say stands out even in Silicon Valley, where rule-breaking under the guise of innovation is commonplace.

It is difficult not to view Donald Trump's administration, regardless of its politics, as combative towards at least some portion of the American public. Unlike previous presidents who ultimately relied on messages that conveyed some attempt -- real or theatrical -- at national unity, Trump's team has decided to draw very clear lines between his supporters and everyone else. Whether it is the press, "radical Islam," or the "politically correct," Trump's style of leadership appears to rely on scapegoats. This bitter political ideology will likely be ineffective in guiding the country through the next decade of developments in the economy. As artificial intelligence, robotics, and new forms of automation continue to flourish, the forms of work that millions of Americans rely on are at risk.

FILE - In this June 7, 2010 file photo, Mexican forensic experts examine the body of 14-year-old Sergio Adrian Hernandez Guereca under the Paso Del Norte border bridge in the city of Ciudad Juarez, Mexico. The Supreme Court appears to be evenly divided about the right of Mexican parents to use American courts to sue a U.S. Border Patrol agent who fired across the U.S.-Mexican border and killed their teenage son. FILE - In this June 7, 2010 file photo, Mexican forensic experts examine the body of 14-year-old Sergio Adrian Hernandez Guereca under the Paso Del Norte border bridge in the city of Ciudad Juarez, Mexico. The Supreme Court appears to be evenly divided about the right of Mexican parents to use American courts to sue a U.S. Border Patrol agent who fired across the U.S.-Mexican border and killed their teenage son. FILE - In this June 7, 2010 file photo, Mexican federal police and forensic experts stand next to the body of 14 year-old Sergio Adrian Hernandez Guereca, under the Paso Del Norte border bridge, as US officials watch from the US side at right, in Ciudad Juarez, northern Mexico.

Businessman and Dallas Mavericks owner Mark Cuban turned to Twitter to warn about robots' threat to unemployment. "Automation is going to cause unemployment and we need to prepare for it," Cuban said Sunday. The tweet also included a link to warnings about artificial intelligence from tech leaders, including Tesla CEO Elon Musk, Bill Gates and Stephen Hawking. Cuban didn't elaborate on the subject, but in a recent interview with CNBC he said President Donald Trump and his administration don't understand technology advancements in machine learning and artificial intelligence. Cuban is a strong critic of Trump and had endorsed his opponent, former Secretary of State Hillary Clinton, during the presidential campaign.

Jonathan Lazar (jlazar@towson.edu) is a professor of computer and information sciences and director of the Undergraduate Program in Information Systems at Towson University, Towson, MD, and recipient of the SIGCHI 2016 Social Impact Award. Elizabeth Churchill (churchill@acm.org) is a director of user experience at Google, San Francisco, CA, and Secretary/Treasurer of ACM. Tovi Grossman (tovi.grossman@autodesk.com) is a distinguished research scientist in the User Interface Research Group at Autodesk Research, Toronto, Canada. Gerrit C. van der Veer (gerrit@acm.org) is an emeritus professor of multimedia and culture at the Vrije Universiteit Amsterdam, the Netherlands, guest professor of human-media interaction at Twente University, Twente, the Netherlands, of human-computer and society at the Dutch Open University, Heerlen, Netherlands, of interaction design at the Dalian Maritime University, Dalian, China, and of animation and multimedia at the Lushun Academy of Fine Arts, Shenyang, China. Philippe Palanque (palanque@irit.fr) is a professor of computer science at Université Paul Sabatier Paul Sabatier – Toulouse III, France, and head of the Interactive Critical Systems research group of the IRIT laboratory, Toulouse, France. John "Scooter" Morris (scooter@cgl.ucsf.edu) is an adjunct professor in the Department of Pharmaceutical Chemistry at the University of California San Francisco and executive director of the Resource for Biocomputing, Visualization and Informatics, a U.S. National Institutes of Health Biomedical Technology Research Resource at the University of California San Francisco. Jennifer Mankoff (mankoff@cs.cmu.edu) is a professor in the Human Computer Interaction Institute at Carnegie Mellon University, Pittsburgh, PA.

The viewpoints by Alan Bundy "Smart Machines Are Not a Threat to Humanity" and Devdatt Dubhashi and Shalom Lappin "AI Dangers: Imagined and Real" (both Feb. 2017) argued against the possibility of a near-term singularity wherein super-intelligent AIs exceed human capabilities and control. Both relied heavily on the lack of direct relevance of Moore's Law, noting raw computing power does not by itself lead to human-like intelligence. Bundy also emphasized the difference between a computer's efficiency in working an algorithm to solve a narrow, well-defined problem and human-like generalized problem-solving ability. Dubhashi and Lappin noted incremental progress in machine learning or better knowledge of a biological brain's wiring do not automatically lead to the "unanticipated spurts" of progress that characterize scientific breakthroughs. These points are valid, but a more accurate characterization of the situation is that computer science may well be just one conceptual breakthrough away from being able to build an artificial general intelligence.