Over the past several decades, artificial intelligence has advanced tremendously, and today it promises new opportunities for more accurate healthcare, enhanced national security and more effective education, researchers say. How do increased computing power and machine learning help create safer, more sustainable and resilient infrastructure? U.S. National Science Foundation-funded researchers at the Computational Modeling and Simulation Center, or SimCenter, have developed a suite of tools called BRAILS -- short for Building Recognition using AI at Large-Scale -- that can automatically identify characteristics of buildings in a city and detect the risks a city's structures would face in the event of an earthquake, hurricane or tsunami. SimCenter is part of the NSF-funded Natural Hazards Engineering Research Infrastructure program and serves as a computational modeling and simulation center for natural hazards engineering researchers at the University of California, Berkeley. Charles Wang, the lead developer of BRAILS, says the project grew out of a need to "quickly and reliably characterize the structures in a city. We want to simulate the impact of hazards on all the buildings in a region, but we don't have a description of the building attributes."

Recent controversies related to topics such as fake news, privacy, and algorithmic bias have prompted increased public scrutiny of digital technologies and soul-searching among many of the people associated with their development. In response, the tech industry, academia, civil society, and governments have rapidly increased their attention to "ethics" in the design and use of digital technologies ("tech ethics"). Yet almost as quickly as ethics discourse has proliferated across the world of digital technologies, the limitations of these approaches have also become apparent: tech ethics is vague and toothless, is subsumed into corporate logics and incentives, and has a myopic focus on individual engineers and technology design rather than on the structures and cultures of technology production. As a result of these limitations, many have grown skeptical of tech ethics and its proponents, charging them with "ethics-washing": promoting ethics research and discourse to defuse criticism and government regulation without committing to ethical behavior. By looking at how ethics has been taken up in both science and business in superficial and depoliticizing ways, I recast tech ethics as a terrain of contestation where the central fault line is not whether it is desirable to be ethical, but what "ethics" entails and who gets to define it. This framing highlights the significant limits of current approaches to tech ethics and the importance of studying the formulation and real-world effects of tech ethics. In order to identify and develop more rigorous strategies for reforming digital technologies and the social relations that they mediate, I describe a sociotechnical approach to tech ethics, one that reflexively applies many of tech ethics' own lessons regarding digital technologies to tech ethics itself.

Improved computing power and an exponential increase in data have helped fuel the rapid rise of artificial intelligence. But as AI systems become more sophisticated, they'll need even more computational power to address their needs, which traditional computing hardware most likely won't be able to keep up with. To solve the problem, MIT spinout Lightelligence is developing the next generation of computing hardware. The Lightelligence solution makes use of the silicon fabrication platform used for traditional semiconductor chips, but in a novel way. Rather than building chips that use electricity to carry out computations, Lightelligence develops components powered by light that are low energy and fast, and they might just be the hardware we need to power the AI revolution.

I say a dream, and not a goal or a mission, not because of its loftiness but because most don't see it. And, if it ever becomes reality, it will be nothing less than a dream come true. A future in which the nonprofit sector is the driving force of our society, where our incentives to succeed aren't guided mainly by greed and self-sustenance but rather by our ability to do good. It's a future where we are measured and rewarded by our mastery of several key balances: profit and ethics; self and other; shareholders and customers; privacy and prominence; Heaven and earth. Doing good does not have to be unprofitable, and therefore, a nonincentivized endeavor.

Satellite images showing the expansion of large detention camps in Xinjiang, China, between 2016 and 2018 provided some of the strongest evidence of a government crackdown on more than a million Muslims, triggering international condemnation and sanctions. Other aerial images--of nuclear installations in Iran and missile sites in North Korea, for example--have had a similar impact on world events. Now, image-manipulation tools made possible by artificial intelligence may make it harder to accept such images at face value. In a paper published online last month, University of Washington professor Bo Zhao employed AI techniques similar to those used to create so-called deepfakes to alter satellite images of several cities. Zhao and colleagues swapped features between images of Seattle and Beijing to show buildings where there are none in Seattle and to remove structures and replace them with greenery in Beijing.

Researchers on the OcéanIA project are developing new artificial intelligence and mathematical modelling tools to contribute to the understanding of the oceans and their role in regulating and sustaining the biosphere, and tackling climate change. You may have seen our recent interview with the director of the project, and of Inria Chile, Nayat Sánchez-Pi. She explained the challenges of research in the field, what they are working on as part of the project, and the role that AI methods play. A key part of the project is data, and much of this is being collected by the Tara Microbiome-CEODOS expedition. The objective of this expedition is to study the marine microorganisms which play a fundamental role in ocean ecosystems.

There are dozens of routes that Alaska Airlines Flight 1405 can take from Oklahoma City to Seattle, and dispatcher Brad Ward zeroed in on what he thought was the best one, taking into account weather, wind speeds, and other air traffic. But his new colleague at the Alaska Airlines operations center had other thoughts. A storm cell near Oklahoma City was likely to turn into a thunderstorm around the time Flight 1405 took off, and the airspace north of Amarillo would be closed for military exercises. Better to reroute, the young colleague said, suggesting an alternative that Ward admitted was safer and more efficient. The entire conversation lasted just seconds and passed without a word being spoken: a red box lit up on Ward's computer screen when the colleague, an artificial intelligence program he has affectionately nicknamed Algo, had an idea.

Drones aren't just flying through the air -- they're also sailing the Pacific Ocean as the newest scientific weapon to combat climate change. The hope is that by mapping the ocean floor, collecting weather and ocean data, and counting fish and wildlife populations, the autonomous Saildrones will measure the changes happening right now on our planet. Climate change is reshaping planet Earth, causing sea levels to rise, melting Arctic ice and raising global temperatures. According to NASA, the global average sea level has risen seven inches over the past 100 years. Arctic summer sea ice has shrunk to its lowest levels on record, and the average global temperature has gone up 2.1 degrees Fahrenheit since 2000, posing a threat to life as we know it.

Chinese fishing is increasing security risks near South Korea's tense nautical border, said a top Cabinet member in Seoul, pledging to deploy advanced technology to crack down on illegal trawling. Minister of Oceans and Fisheries Moon Seong-hyeok said in an interview that illegal fishing must be "completely eradicated," joining in calls from across Asia to end what many see as Beijing's assertive push into regional waters. South Korea has long complained about Chinese trawlers operating in the Yellow Sea -- what Koreans call the West Sea -- near its islands off the coast of North Korea. "When it comes to illegal fishing, whether it be foreign or domestic vessels, we will crack down," Moon told Bloomberg News on Friday, saying South Korea will from next year increase its maritime surveillance systems using drones at sea and artificial intelligence. South Korea, which lists the U.S. as its main military ally and China as its biggest trading partner, turned up the pressure on Beijing over the weekend when it won from Washington a termination of bilateral missile guidelines that have long restricted Seoul's development of missiles to under the range of 800 kilometers (500 miles).

The detection of critical infrastructures is of high importance in several fields such as security, anomaly detection, land use planning and land use change detection. However, critical infrastructures detection in aerial and satellite images is still a challenge as each one has completely different size and requires different spacial resolution to be identified correctly. Heretofore, there are no special datasets for training critical infrastructures detectors. This paper presents a smart dataset as well as a resolution-independent critical infrastructure detection system. In particular, guided by the performance of the detection model, we built a dataset organized into two scales, small and large scale, and designed a two-stage deep learning detection of different scale critical infrastructures (DetDSCI) methodology in ortho-images. DetDSCI methodology first determines the input image zoom level using a classification model, then analyses the input image with the appropriate scale detection model. Our experiments show that DetDSCI methodology achieves up to 37,53% F1 improvement with respect to the baseline detector.