New York City has released a 116-page strategic vision for how it plans to benefit from artificial intelligence as a community, with an emphasis on doing so in ethical and responsible ways. The plan, dubbed The New York City Artificial Intelligence Strategy, was released yesterday by the NYC Mayor's Office of the Chief Technology Officer. This plan is perhaps unprecedented in many ways, marking the most extensive and proactive action taken toward one of the world's fast-evolving technologies by a U.S. city government. "AI will touch virtually every area of life in the years ahead," said John Paul Farmer, NYC's chief technology officer, during a conversation with Government Technology. While most prominently the report features the city's planned approach toward supporting AI, it also serves in part as a primer on the basics of how AI works.

The Pentagon has offered unspecified condolence payments to the family of 10 civilians who were killed in a botched US drone attack in Afghanistan in August during the final days before American troops withdrew from the country. The US Department of Defense said it made a commitment that included offering "ex-gratia condolence payments", in addition to working with the US Department of State in support of the family members who were interested in relocation to the United States. Colin Kahl, the US under-secretary of defense for policy, held a virtual meeting on Thursday with Steven Kwon, the founder and president of Nutrition & Education International, the aid organisation that employed Zemari Ahmadi, who was killed in the August 29 drone attack, Pentagon press secretary John Kirby said late on Friday. Ahmadi and others who were killed in the drone raid were innocent victims who bore no blame and were not affiliated with Islamic State in Khorasan Province, ISKP (ISIS-K) or threats to US forces, Kirby said. The drone raid in Kabul killed as many as 10 civilians, including seven children.

The set of local modes and the ridge lines estimated from a dataset are important summary characteristics of the data-generating distribution. In this work, we consider estimating the local modes and ridges from point cloud data in a product space with two or more Euclidean/directional metric spaces. Specifically, we generalize the well-known (subspace constrained) mean shift algorithm to the product space setting and illuminate some pitfalls in such generalization. We derive the algorithmic convergence of the proposed method, provide practical guidelines on the implementation, and demonstrate its effectiveness on both simulated and real datasets.

Traffic state prediction is necessary for many Intelligent Transportation Systems applications. Recent developments of the topic have focused on network-wide, multi-step prediction, where state of the art performance is achieved via deep learning models, in particular, graph neural network-based models. While the prediction accuracy of deep learning models is high, these models' robustness has raised many safety concerns, given that imperceptible perturbations added to input can substantially degrade the model performance. In this work, we propose an adversarial attack framework by treating the prediction model as a black-box, i.e., assuming no knowledge of the model architecture, training data, and (hyper)parameters. However, we assume that the adversary can oracle the prediction model with any input and obtain corresponding output. Next, the adversary can train a substitute model using input-output pairs and generate adversarial signals based on the substitute model. To test the attack effectiveness, two state of the art, graph neural network-based models (GCGRNN and DCRNN) are examined. As a result, the adversary can degrade the target model's prediction accuracy up to $54\%$. In comparison, two conventional statistical models (linear regression and historical average) are also examined. While these two models do not produce high prediction accuracy, they are either influenced negligibly (less than $3\%$) or are immune to the adversary's attack.

A top Pentagon software official recently quit his job, claiming that the US is dragging its heels. The Pentagon's first-ever chief software officer abruptly quit earlier this month, and now we know exactly why: Nicolas Chaillan, former CSO of the United States Air Force and Space Force, told the Financial Times that the United States has "no competing fighting chance against China in 15 to 20 years" when it comes to cyberwarfare and artificial intelligence. Chaillan, a 37-year-old tech entrepreneur, added that cyber defenses at many government agencies are at "kindergarten level," and that companies like Google were doing the US a disservice by not working with the military more on AI, since Chinese companies were making a "massive investment" in AI without getting all hung up on the ethics of it all. And while quitting your job because America has already lost the AI race is a bit dramatic, Chaillan isn't the only one who's concerned about China's dominance in this arena.

A new startup that replaces pilots with robots has received $100 million in funding. Reliable Robotics argues that, with many planes now being controlled automatically, that pilots are the most expensive aspects of cargo operations. Trucking is monotonous and uninteresting work, meaning it is also the source of the most mistakes. Its technology is aimed at handling the taxi, takeoff, landing, and parking parts of cargo flights – monitored by licensed pilots remotely in the control centre. It is claimed that autonomous planes could save airlines approximately $60 billion per year.

The U.S. cyber team's head coach, retired U.S. Army Special Forces Lt. Col. TJ O'Connor, noted the unique platform presented by cybersecurity competitions. Unlike other forms of computer science education, O'Connor said, staying up to date on the latest developments in cybersecurity is difficult, with hackers constantly iterating on and developing new tactics to break through cyberdefenses. it would still be hard to simulate being in the thick of such an operation, .

Artificial intelligence has significantly changed the way we interact with technology. Although some may not realize it, artificial intelligence has become part of everyone's daily lives. An overview of how artificial intelligence can help in making decisions can be found here. Amazon Echo and Google Homeowners know how convenient these AI-powered devices are, especially given their ability and accuracy. During voice searches, AI can deliver results and enhance customer experience by seamlessly processing voice commands. These statistics show the extent to which artificial intelligence has grown.

A U.S. Army soldier monitors a 14' Shadow surveillance drone from a control room after it's launched. There is now interest in taking AI beyond the courtroom and into the realms of conflict resolution. There is growing concern that current mediation and peacemaking approaches are proving less and less effective in resolving localized and international conflicts. In response, interest is rising in the potential for artificial intelligence to play a role in advising on or resolving complex conflicts. A combination of situational complexity, intractable positions of opposing sides and escalating costs is driving the search for AI-based approaches that could replace humans in resolving legal cases, international disputes and military conflicts.

International diplomacy has traditionally relied on bargaining power, covert channels of communication and personal chemistry between leaders. But a new era is upon us in which the dispassionate insights of AI algorithms and mathematical techniques such as game theory will play a growing role in deals struck between nations, according to the co-founder of the world's first centre for science in diplomacy. Michael Ambühl, a professor of negotiation and conflict management and former chief Swiss-EU negotiator, said recent advances in AI and machine learning mean that these technologies now have a meaningful part to play in international diplomacy, including at the Cop26 summit starting later this month and in post-Brexit deals on trade and immigration. "These technologies are partially already used and it will be the intention to use them more," said Ambühl. "Everything around data science, artificial intelligence, machine learning … we want to see how can it be made beneficial for multilateral or bilateral diplomacy."