This analysis summarizes and reflects on the following research: Suchman, L. (2020). Project Maven was introduced to the media and U.S. general public in the summer of 2018 when several Google employees voiced concerns over the company's contract to automate the labeling of images from U.S. military drones to determine "objects of interest" (including vehicles, buildings, and persons) with sparse details on its intended purpose. In solidarity, academic researchers supported Google employees' concerns and added that "further automation…of the US drone program can only serve to worsen an operation that is already highly problematic, even arguably illegal and immoral under the laws and norms of armed conflict." While Google decided not to renew the contract following its employees' protests, the project's contract was picked up and continued by a different company. This story, and Project Maven more generally, typifies an intersection of critical security studies and technology studies that Lucy Suchman examines in research on automation and artificial intelligence technologies in U.S. counterterrorism strategies.

Last August, several dozen military drones and tank-like robots took to the skies and roads 40 miles south of Seattle. Their mission: Find terrorists suspected of hiding among several buildings. So many robots were involved in the operation that no human operator could keep a close eye on all of them. So they were given instructions to find--and eliminate--enemy combatants when necessary. The mission was just an exercise, organized by the Defense Advanced Research Projects Agency, a blue-sky research division of the Pentagon; the robots were armed with nothing more lethal than radio transmitters designed to simulate interactions with both friendly and enemy robots.

It's not just online and big-box retailers that are exploring deliveries by drone. Following in the footsteps of the Swiss Post, the UK's Royal Mail is the latest postal service to trial drone flights. The company has announced a landmark project to deliver packages -- including personal protective equipment, COVID testing kits and assorted mail -- to a UK island using an autonomous Uncrewed Aerial Vehicle (UAV). As part of the government-backed project, a large drone will take off from the mainland and fly to the Scilly Isles (a remote archipelago off the Cornish coast in southwest England). The twin-engine UAV can carry up to 100kg of mail of all shapes and sizes, which the Royal Mail said is equivalent to a typical delivery round.

Fox News Flash top headlines are here. Check out what's clicking on Foxnews.com. Israel shared three cell phone numbers used by Qasem Soleimani with U.S. intelligence in the hours before American drones unleashed Hellfire missiles on the Iranian general last year, Yahoo News reported Saturday. The revelation sheds new light on the role that Israel played in the killing of Soleimani, who the State Department says was responsible for hundreds of U.S. troop deaths as the head of the Revolutionary Guard's elite Quds Force. The drone strike occurred shortly after midnight on Jan. 2, 2020, as Soleimani and his entourage were leaving Baghdad's international airport.

A photograph of the sky by Trevor Paglen can look like a massive abstraction, except for a tiny speck, a surveillance drone, spotted like a malignant dot on a chest x-ray. His images of secluded military sites in Nevada can also ooze with colour from the churning heat and dust. In the new documentary film Unseen Skies, directed by Yaara Bou Melhem, Paglen calls the effect "impressionistic haze". Photographing those places, often from miles away (or farther), is about "seeing and not seeing at the same time," Paglen says. "For me those images were about capturing that paradox."

We've been hearing how "data is the new oil" for more than a decade now, and in certain sectors, it's a maxim that has more than panned out. From marketing and logistics to finance and product, decision-making is now dominated by data at all levels of most big private orgs (and if it isn't, I'd be getting a resume put together, stat). So it might be a something of a surprise to learn that data, which could transform how we respond to the increasingly deadly disasters that regularly plague us, has been all but absent from much of emergency response this past decade. Far from being a geyser of digital oil, disaster response agencies and private organizations alike have for years tried to swell the scope and scale of the data being inputted into disaster response, with relatively meager results. That's starting to change though, mostly thanks to the internet of things (IoT), and frontline crisis managers today increasingly have the data they need to make better decisions across the resilience, response and recovery cycle.

Artificial intelligence (AI) has witnessed a substantial breakthrough in a variety of Internet of Things (IoT) applications and services, spanning from recommendation systems to robotics control and military surveillance. This is driven by the easier access to sensory data and the enormous scale of pervasive/ubiquitous devices that generate zettabytes (ZB) of real-time data streams. Designing accurate models using such data streams, to predict future insights and revolutionize the decision-taking process, inaugurates pervasive systems as a worthy paradigm for a better quality-of-life. The confluence of pervasive computing and artificial intelligence, Pervasive AI, expanded the role of ubiquitous IoT systems from mainly data collection to executing distributed computations with a promising alternative to centralized learning, presenting various challenges. In this context, a wise cooperation and resource scheduling should be envisaged among IoT devices (e.g., smartphones, smart vehicles) and infrastructure (e.g. edge nodes, and base stations) to avoid communication and computation overheads and ensure maximum performance. In this paper, we conduct a comprehensive survey of the recent techniques developed to overcome these resource challenges in pervasive AI systems. Specifically, we first present an overview of the pervasive computing, its architecture, and its intersection with artificial intelligence. We then review the background, applications and performance metrics of AI, particularly Deep Learning (DL) and online learning, running in a ubiquitous system. Next, we provide a deep literature review of communication-efficient techniques, from both algorithmic and system perspectives, of distributed inference, training and online learning tasks across the combination of IoT devices, edge devices and cloud servers. Finally, we discuss our future vision and research challenges.

We've been hearing how "data is the new oil" for more than a decade now, and in certain sectors, it's a maxim that has more than panned out. From marketing and logistics to finance and product, decision-making is now dominated by data at all levels of most big private orgs (and if it isn't, I'd be getting a résumé put together, stat). So it might be a something of a surprise to learn that data, which could transform how we respond to the increasingly deadly disasters that regularly plague us, has been all but absent from much of emergency response this past decade. Far from being a geyser of digital oil, disaster response agencies and private organizations alike have for years tried to swell the scope and scale of the data being inputted into disaster response, with relatively meager results. That's starting to change though, mostly thanks to the internet of things (IoT), and frontline crisis managers today increasingly have the data they need to make better decisions across the resilience, response, and recovery cycle.

In 2019, the border town of Chula Vista, about 15 minutes from Tijuana, became California's first " Welcoming City," highlighting the city's financial and educational opportunities for immigrants. It's also one of the nation's most surveilled cities, where the police department uses license plate readers, drones, and body cameras to track residents and has explored facial-recognition technology. Now, those distinctions are clashing, as residents and activists accuse city leaders of "betraying" immigrant residents by permitting federal immigration authorities to access data from license plate readers. That's sparked a citywide movement questioning the city's police department, its surveillance apparatus, and its relationship with residents and immigration enforcement. Since 2015, the Chula Vista Police Department has quietly amassed surveillance tools as part of a smart city approach to policing.

A total of nine Artificial Intelligence (AI) research and development (R&D) projects by the DOST-Advanced Science and Technology Institute (DOST-ASTI), University of the Philippines Mindanao (UPMin), De La Salle University (DLSU), University of the Philippines Los Baños (UPLB), and Caraga State University (CarSU) were launched by the Philippines' Department of Science and Technology (DOST Philippines) in April 2021. The AI R&D projects ranging from applications in agriculture to the education sector were launched on April 8 by the Department of Science and Technology – Philippine Council for Industry, Energy and Emerging Technology Research and Development (DOST-PCIEERD) to spur growth in the AI industry in the Philippines. "AI is one of our priority areas as it truly can boost the country and usher us to the fourth industrial revolution. As a powerful agent for good, AI can disrupt traditional processes and provide solutions and opportunities that Filipinos can maximize," said DOST-PCIEERD Executive Director Dr. Enrico C. Paringit during the virtual launch. The Autonomous Societally Inspired Mission Oriented Vehicles (ASIMOV) Program, composed of two-component projects, will be implemented by DOST-ASTI and UPMin.