If a major disaster like Fukushima or Chornobyl ever happens again, the world would know almost straight away, thanks to an array of government and DIY radiation-monitoring programs running globally.

More than 20 years later, the system is getting a makeover. After 9/11, Washington, D.C.'s airspace got a significant security boost. Now, over two decades later, this system is getting a cutting-edge makeover. The National Capital Region (NCR) is rolling out an advanced artificial intelligence-based visual recognition system that's taking air defense to a whole new level. GET SECURITY ALERTS, EXPERT TIPS -- SIGN UP FOR KURT'S NEWSLETTER -- THE CYBERGUY REPORT HERE The Enhanced Regional Situational Awareness (ERSA) system represents a dramatic upgrade from previous security technologies.

It has also collaborated with large organizations, including Microsoft. The system uses machine-learning algorithms on satellite imagery to categorize damage in the disaster area at a much faster rate than is possible using other existing methods. This method is incredibly important given the number of separate earthquakes and aftershocks that have occurred since the first earthquake incident in the early hours of February 6. Yesterday, February 20, for example, another 6.4 magnitude tremor struck near the city of Antakya, close to the border with Syria, trapping more people under the rubble. An MIT Technology Review report points out that xView2 has recently also been deployed in response to wildfires in California as well as during recovery efforts after flooding in Nepal, where it helped to identify damage from landslides caused by the floods.

But one effort from the US Department of Defense does seem to be effective: xView2. Though it's still in its early phases of deployment, this visual computing project has already helped with disaster logistics and on the ground rescue missions in Turkey. An open-source project that was sponsored and developed by the Pentagon's Defense Innovation Unit and Carnegie Mellon University's Software Engineering Institute in 2019, xView2 has collaborated with many research partners, including Microsoft and the University of California, Berkeley. It uses machine-learning algorithms in conjunction with satellite imagery from other providers to identify building and infrastructure damage in the disaster area and categorize its severity much faster than is possible with current methods. Ritwik Gupta, the principal AI scientist at the Defense Innovation Unit and a researcher at Berkeley, tells me this means the program can directly help first responders and recovery experts on the ground quickly get an assessment that can aid in finding survivors and help coordinate reconstruction efforts over time.

U.S. Cyber Command wants to expand the use of artificial intelligence and machine learning, and to do so, it's kicked off a broader survey of machine learning requirements across the Defense Department. It's working with the Defense Innovation Unit, the new Chief Digital and Artificial Intelligence Office and the Defense Advanced Research Project Agency to do that. The idea is to determine priorities for greater investment in the near future. U.S. Cyber Command wants to expand the use of artificial intelligence and machine learning, and to do so, it's kicked off a broader survey of machine learning requirements across the Defense Department. It's working with the Defense Innovation Unit, the new Chief Digital and Artificial Intelligence Office and the Defense Advanced Research Project Agency to do that.

In 2018, thousands of Google employees protested a Pentagon contract dubbed Project Maven that used the company's artificial intelligence technology to analyze drone surveillance footage. Google said it wouldn't renew the contract and announced guiding principles for future AI projects that forbid work on weapons and surveillance projects "violating internationally accepted norms." At the same time, Google made clear it would still seek defense contracts. "While we are not developing AI for use in weapons," CEO Sundar Pichai wrote, "we will continue our work with governments and the military in many other areas." In the three years since, Google has stayed true to his word.

In 2018, when Google employees found out about their company's involvement in Project Maven, a controversial US military effort to develop AI to analyze surveillance video, they weren't happy. "We believe that Google should not be in the business of war," they wrote in a letter to the company's leadership. Around a dozen employees resigned. Google did not renew the contract in 2019. Project Maven still exists, and other tech companies, including Amazon and Microsoft, have since taken Google's place.

In a bid to promote transparency, the Defense Innovation Unit, which awards DoD contracts to companies, has released what it calls "responsible artificial intelligence" guidelines that it will require third-party developers to use when building AI for the military, whether that AI is for an HR system or target recognition. The guidelines provide a step-by-step process for companies to follow during planning, development, and deployment. They include procedures for identifying who might use the technology, who might be harmed by it, what those harms might be, and how they might be avoided--both before the system is built and once it is up and running. "There are no other guidelines that exist, either within the DoD or, frankly, the United States government, that go into this level of detail," says Bryce Goodman at the Defense Innovation Unit, who coauthored the guidelines. The work could change how AI is developed by the US government, if the DoD's guidelines are adopted or adapted by other departments.

REDWOOD CITY, Calif., Sept. 2, 2020 – C3.ai, an enterprise artificial intelligence (AI) software provider for accelerating digital transformation, announced an agreement with the United States Air Force (USAF) Rapid Sustainment Office (RSO) to deliver and deploy the C3 AI Suite and C3.ai Readiness to support predictive analytics and maintenance across the Air Force enterprise. Predicting an aircraft weapon system's readiness and increasing fleet availability is essential to the U.S. military's operational success. RSO's Condition-Based Maintenance Plus (CBM) Program Office will use the C3 AI Suite and extend C3.ai Readiness to deploy an AI-based predictive maintenance application for the USAF to improve the efficiency and effectiveness of maintenance processes. The RSO will deploy this application to the HH-60 Pave Hawk aircraft weapon system and then assess further fielding to additional aircraft weapon systems. This initiative will also lay a foundation and framework for the enhancement of RSO's overall AI and machine learning capabilities. "C3.ai's proven technology has demonstrated success across multiple industries with its AI-based readiness application for predictive maintenance and logistics planning, making C3.ai an ideal partner to implement RSO's vision to increase mission readiness," said Nathan Parker‚ RSO Deputy Program Executive Officer.

In 2017, a poker bot called Libratus made headlines when it roundly defeated four top human players at no-limit Texas Hold'Em. Now, Libratus' technology is being adapted to take on opponents of a different kind--in service of the US military. Libratus--Latin for balanced--was created by researchers from Carnegie Mellon University to test ideas for automated decisionmaking based on game theory. Early last year, the professor who led the project, Tuomas Sandholm, founded a startup called Strategy Robot to adapt his lab's game-playing technology for government use, such as in war games and simulations used to explore military strategy and planning. Late in August, public records show, the company received a two-year contract of up to $10 million with the US Army.