NASA has awarded a $187 million contract to Northrop Grumman to build a crew module that astronauts will stay in before landing on the Moon. Known as the habitation and logistics outpost (HALO), it will be the size of a small flat and form part of the Lunar Gateway, a small space station that will orbit the Moon. The Gateway is part of the Artemis mission - that will see the first woman and next man return to the Moon by 2024 and regular return trips over the next decade. HALO and the Gateway's Power and Propulsion Element (PPE), will launch in 2023, a year ahead of the first mission to land humans on the Moon since 1972. NASA says the Gateway will help them build a sustainable presence at the Moon as it expands its efforts to land astronauts on the surface and even build a base.

The US Air Force has long been exploring the way artificial intelligence (AI) can assist in its operations -- back in 2016 we saw combat AI beat some of the Air Force's top tactical experts, for example. Now, researchers are working on an autonomous drone designed to take down a piloted plane in air-to-air combat, with a showdown slated for July 2021. As reported by Air Force Magazine, the Air Force Research Laboratory (AFRL) has been developing an autonomous fighter jet since 2018, with plans to use machine-learning technology in less advanced planes initially -- such as the F-16 -- before graduating to newer models, such as the F-22 or F-35. Of course, details are a little hazy -- it's a military project after all and therefore subject to hefty classification. In a video, however, head of the Pentagon's Joint Artificial Intelligence Center Lt. Gen. Jack Shanahan said the AFRL is "pushing the boundaries" of AI in a military application, adding that the team is quietly confident that the "machine [will] beat the human."

Deep neural networks can now perform many tasks that were once thought to be only feasible for humans. Unfortunately, while reaching impressive performance under standard settings, such networks are known to be susceptible to adversarial attacks -- slight but carefully constructed perturbations of the inputs which drastically decrease the network performance and reduce their trustworthiness. Here we propose to improve network robustness to input perturbations via an adversarial training procedure which we call Adversarial Feature Desensitization (AFD). We augment the normal supervised training with an adversarial game between the embedding network and an additional adversarial decoder which is trained to discriminate between the clean and perturbed inputs from their high-level embeddings. Our theoretical and empirical evidence acknowledges the effectiveness of this approach in learning robust features on MNIST, CIFAR10, and CIFAR100 datasets -- substantially improving the state-of-the-art in robust classification against previously observed adversarial attacks. More importantly, we demonstrate that AFD has better generalization ability than previous methods, as the learned features maintain their robustness against a large range of perturbations, including perturbations not seen during training. These results indicate that reducing feature sensitivity using adversarial training is a promising approach for ameliorating the problem of adversarial attacks in deep neural networks.

This paper targets the automated extraction of components of argumentative information and their relations from natural language text. Moreover, we address a current lack of systems to provide complete argumentative structure from arbitrary natural language text for general usage. We present an argument mining pipeline as a universally applicable approach for transforming German and English language texts to graph-based argument representations. We also introduce new methods for evaluating the results based on existing benchmark argument structures. Our results show that the generated argument graphs can be beneficial to detect new connections between different statements of an argumentative text. Our pipeline implementation is publicly available on GitHub.

Companies have considered adoption of various high-level artificial intelligence (AI) principles for responsible AI, but there is less clarity on how to implement these principles as organizational practices. This paper reviews the principles-to-practices gap. We outline five explanations for this gap ranging from a disciplinary divide to an overabundance of tools. In turn, we argue that an impact assessment framework which is broad, operationalizable, flexible, iterative, guided, and participatory is a promising approach to close the principles-to-practices gap. Finally, to help practitioners with applying these recommendations, we review a case study of AI's use in forest ecosystem restoration, demonstrating how an impact assessment framework can translate into effective and responsible AI practices.

The World Post Pandemic: How surveillance and weapon systems, used unwisely, can harm humanity! Mark Twain once wrote "against the assault of laughter nothing can stand." Ethics In Technology is planning to put Mark Twain's statement to the test about the military-industrial complex and the surveillance state. Join us for a night of thought-provoking presentations followed by some wonderful comedy. The show is hosted by nonprofit organization Ethics in Technology, a nonprofit watchdog group advocating for a world where big tech firms and technology work to serve humanity and the planet, rather than the other way around.

Sen. Rob Portman recently introduced a bill with bipartisan backing to develop a national cloud computer for AI research, which would allow those with barriers to entry or facing hurdles to more efficiently progress their work.The bill, if passed, would establish a task force to develop a roadmap for development of AI technology, which figures to have wide ranging impacts on fields such as health care, transport and communications, among others, over the next few decades.Artificial intelligence is the simulation of human intelligence processes, learning, in machines. According to a release from Portman's office, the legislation would convene a group of technical experts across academia, government, and industry to develop a detailed roadmap for how the United States can build, deploy, govern, and sustain a national research cloud.A companion bill has been introduced in the U.S. House of Representatives."We With China focused on toppling the United States' leadership in AI, we need to redouble our efforts with a sustained commitment to the best and brightest by developing a national research cloud to ensure our technical researchers get the tools they need to succeed," said Portman."This …

An MQ-9 Reaper assigned to the 214th Attack Group, Arizona Air National Guard, flies over Michigan. The U.S. Air Force wants a new hunter-killer drone to replace its current fleet of 306 propeller-driven MQ-9 Reapers. And it could end up including a version of the service's Skyborg artificial intelligence. Where the Reaper is pretty dumb, the new drone could be very clever. The Air Force on June 3 released a request for information to the aerospace industry for a next-generation unmanned intelligence-strike platform.

A bipartisan cadre of tech-focused legislators in the House and Senate have introduced legislation that would direct the federal government to develop a national cloud computing infrastructure for artificial intelligence research. Introduced by Sens. Rob Portman, R-Ohio, and Martin Heinrich, D-N.M., Thursday, the National Cloud Computing Task Force Act would convene a mix of technical experts across academic, industry and government. The group would develop a nuanced roadmap for how the nation should build, deploy, govern and sustain a national research cloud for AI. "With China focused on toppling the United States' leadership in AI, we need to redouble our efforts with a sustained commitment to the best and brightest by developing a national research cloud to ensure our technical researchers get the tools they need to succeed," Portman said in a statement. "By democratizing access to computing power we ensure that any American with computer science talent can pursue their good ideas."

Army Lt. Gen. John N.T. ''Jack'' Shanahan spoke remotely from the Pentagon yesterday with Dave Deptula, dean of the Mitchell Institute for Aerospace Studies. ''It is my conviction and deep passion that AI will transform the character of warfare in the Department of Defense in the course of the next 20 years,'' Shanahan said. ''There is no part of the department that will not be impacted by this, from the back office to the battlefield, from under sea to cyberspace and outer space, and all points in between.'' Artificial intelligence, often called AI, has been happening in commercial industry, but that effort only started in earnest in the department about 10 years ago, he noted, but ''we've been stuck in first gear in terms of fielding.'' DOD has long struggled with how to take the world's best research and development and field it at speed and at scale, he added.