Collaborating Authors


Challenges of DoD's Ethical Principles for AI


In February of this year, the Department of Defense (DoD) issued five Ethical Principles for Artificial Intelligence (AI): Responsible, Equitable, Traceable, Reliable and Governable. The DoD principles build off recommendations from 2019 by the Defense Innovation Board and the interim report of the National Security Commission on AI (NSCAI). The defense industry and others in the private sector have also been considering ethical issues regarding AI, including the issue of whether businesses should have an AI code of ethics. When cyber first became an issue about 22-years ago, the trend was to raise awareness and think through the consequences. Similarly, now we are developing awareness of the issues and beginning to think through the consequences of AI.

Drones – the New Critical Infrastructure


Be prepared in the near future when you gaze into the blue skies to perceive a whole series of strange-looking things – no, they will not be birds, nor planes, or even superman. They may be temporarily, and in some cases startlingly mistaken as UFOs, given their bizarre and ominous appearance. But, in due course, they will become recognized as valuable objects of a new era of human-made flying machines, intended to serve a broad range of missions and objectives. Many such applications are already incorporated and well entrenched in serving essential functions for extending capabilities in our vital infrastructures such as transportation, utilities, the electric grid, agriculture, emergency services, and many others. Rapidly advancing technologies have made possible the dramatic capabilities of unmanned aerial vehicles (UAV/drones) to uniquely perform various functions that were inconceivable a mere few years ago.

How 'Microsoft Flight Simulator' became a 'living game' with Azure AI


Microsoft Flight Simulator is a triumph, one that fully captures the meditative experience of soaring through the clouds. But to bring the game to life, Microsoft and developer Asobo Studio needed more than an upgraded graphics engine to make its planes look more realistic. They needed a way to let you believably fly anywhere on the planet, with true-to-life topography and 3D models for almost everything you see, something that's especially difficult in dense cities. A task like that would be practically impossible to accomplish by hand. But it's the sort of large-scale data processing that Microsoft's Azure AI was built for.

US military is testing wearable devices that detects illnesses TWO days before symptoms arise

Daily Mail - Science & tech

The US military is testing a smart watch and ring system capable of detecting illnesses two days before the wearer develops symptoms. Called Rapid Analysis of Threat Exposure (RATE), the project is using Garmin and Oura devices that have been program with artificial intelligence trained on nearly 250,000 coronavirus cases and other sicknesses. The system notifies the user of an oncoming illness using a scale from one to 100 on how likely it will happen over the next 48 hours. Military officials note that'Within two weeks of us going live we had our first successful COVID-19 detect.' The US military is testing a smart watch and ring system capable of detecting illness two days before the wearer develops symptoms.

Top 5 Creepy Robots


We were used to hearing that we'll be out of a job in twenty years, because of robots. Then the virus came, and now many are out of a job a bit faster, and not because of anything more intelligent or capable than themselves. Here are five currently existing robots that score pretty high on the creepiness scale, even without threatening to take away one's job. Sophia has somehow become the flagship of humanoid robotics. Constructed in Hong Kong, it has taken part in major TV talk shows and has been granted Saudi Arabian citizenship, although it is, essentially, not more than a "chatbot with a face" [1]. What the citizenship thing really means is unclear: Can Sophia vote?

Thwarting adversarial AI with context awareness -- GCN


Researchers at the University of California at Riverside are working to teach computer vision systems what objects typically exist in close proximity to one another so that if one is altered, the system can flag it, potentially thwarting malicious interference with artificial intelligence systems. The yearlong project, supported by a nearly $1 million grant from the Defense Advanced Research Projects Agency, aims to understand how hackers target machine-vision systems with adversarial AI attacks. Led by Amit Roy-Chowdhury, an electrical and computer engineering professor at the school's Marlan and Rosemary Bourns College of Engineering, the project is part of the Machine Vision Disruption program within DARPA's AI Explorations program. Adversarial AI attacks – which attempt to fool machine learning models by supplying deceptive input -- are gaining attention. "Adversarial attacks can destabilize AI technologies, rendering them less safe, predictable, or reliable," Carnegie Mellon University Professor David Danks wrote in IEEE's Spectrum in February.

Driving Business Results with Artificial Intelligence Services


Companies that incorporate Artificial Intelligence solutions in their core values reap the benefits of the technical progress and the informational revolution as we are all standing at the dawn of a new era of virtual transformation and automation. AI is indispensable in dynamic environments, requiring you to work with data on a large scale. It makes data processing faster and more efficient, as it's specifically designed to work in a data-intense environment and learn through operating large volumes of data and analyzing information. Combining Artificial Intelligence services with Cloud Computing would be something to consider in this regard as it gives instant advantages in terms of data manipulation. The cloud environment allows you to store massive volumes of data and makes it easily accessible.

From bomb-affixed drones to narco tanks and ventilated tunnels: How well-equipped are the Mexican cartels?

FOX News

Mexico's increasingly militarized crackdown of powerful drug cartels has left nearly 39,000 unidentified bodies languishing in the country's morgues – a grotesque symbol of the ever-burgeoning war on drugs and rampant violence. Investigative NGO Quinto Elemento Labs, in a recent report, found that an alarming number of people have been simply buried in common graves without proper postmortems, while others were left in funeral homes. The so-called war of drugs has claimed the lives of nearly 300,000 people over the last 14 years, while another 73,000 have gone missing. All the while, these cartels have yet to be designated formal terrorist organizations despite boasting well-documented arsenals of sophisticated weaponry to rival most fear-inducing militias on battlefields abroad. Just last month, reports surfaced that Mexico's Jalisco New Generation Cartel (CJNG) now possess bomb-toting drones – which The Drive's Warzone depicts as "small quadcopter-type drones carrying small explosive devices to attack its enemies."

China Is Not Ahead Of US On AI: JAIC Chief & Gen. Hyten


WASHINGTON: China may lead the world in some aspects of artificial intelligence, such as surveillance and censorship. But in the ways that matter most for future warfare, "the US is still ahead compared to China [in terms of] sophistication and breadth," says the acting director of the Pentagon's Joint AI Center. "The question becomes, how can we quickly adopt this and bring this into the DoD?" Nand Mulchandani asked. It's not the US Department of Defense that's leading the world on AI – although there are definitely some clever coders in the DoD – but American companies, which have invested massively in cutting-edge techniques driven by such mundane missions as targeting online advertising. "[We're] absorbing and wielding it, as opposed to building it from scratch," he said, and that's a big advantage.

POC – Artificial Intelligence for Maneuver


Future near-peer adversaries will attempt to contest all domains and utilize complex and congested terrain to mitigate current joint force capabilities and reduce effectiveness of U.S. Department of Defense (DoD) tactical maneuver elements. To help deter or defeat peer threats in contested multi-domain environments, the DoD should leverage advances in artificial intelligence and machine learning algorithms in support of robotic autonomous systems, miniaturized sensors, computing power and storage, and secure autonomous communication networks to create human-machine teams bringing greater precision, certainty, speed and mass to the battlefield.