Google Maps users have been urged to act now to avoid permanently losing their important data. Starting next year, the popular navigation app will begin deleting users' personal Timeline from its servers. Originally known as Location History, this feature tracks Google Maps users' every movement, keeping a record of places visited and routes taken. However, according to emails received by Google Maps users, this feature is set to vanish from June 9, 2025, along with almost a decade of user data. Google says it will be moving users' movement history from the cloud to a more secure on-device option.

The increasing reliance of drivers on navigation applications has made transportation networks more susceptible to data-manipulation attacks by malicious actors. Adversaries may exploit vulnerabilities in the data collection or processing of navigation services to inject false information, and to thus interfere with the drivers' route selection. Such attacks can significantly increase traffic congestions, resulting in substantial waste of time and resources, and may even disrupt essential services that rely on road networks. To assess the threat posed by such attacks, we introduce a computational framework to find worst-case data-injection attacks against transportation networks. First, we devise an adversarial model with a threat actor who can manipulate drivers by increasing the travel times that they perceive on certain roads. Then, we employ hierarchical multi-agent reinforcement learning to find an approximate optimal adversarial strategy for data manipulation. We demonstrate the applicability of our approach through simulating attacks on the Sioux Falls, ND network topology.

The rise of large-scale socio-technical systems in which humans interact with artificial intelligence (AI) systems (including assistants and recommenders, in short AIs) multiplies the opportunity for the emergence of collective phenomena and tipping points, with unexpected, possibly unintended, consequences. For example, navigation systems' suggestions may create chaos if too many drivers are directed on the same route, and personalised recommendations on social media may amplify polarisation, filter bubbles, and radicalisation. On the other hand, we may learn how to foster the "wisdom of crowds" and collective action effects to face social and environmental challenges. In order to understand the impact of AI on socio-technical systems and design next-generation AIs that team with humans to help overcome societal problems rather than exacerbate them, we propose to build the foundations of Social AI at the intersection of Complex Systems, Network Science and AI. In this perspective paper, we discuss the main open questions in Social AI, outlining possible technical and scientific challenges and suggesting research avenues.

Saildrone Explorer unmanned surface vessels (USV) operate with USS Delbert D. Black (DDG-119) on Oct. 7, 2022. The Navy is thinking about artificial intelligence in two ways: the infrastructure to make unmanned systems work and technology meant to enhance how sailor and their commanders make decisions, a panel of technical and policy experts said Tuesday. The output provided by AI is there help the human or supplement manned operations with unmanned assets, said Brett Vaughan, Navy Chief AI Officer, speaking at the U.S. Naval Institute on Tuesday. A human will always be in the loop and play a central role. "By and large, the AI is there to augment and provide a human decision maker a range of options and recommendations," Vaughan said.

With cutting edge technologies such as computer vision, blockchain and machine learning, Atlas Navi is set to become the leading navigation choice for drivers around the world. Atlas Navi is a navigation app that uses A.I. and the smartphone camera to avoid traffic by detecting road conditions, accidents, traffic in each lane, police vehicles and many more. It analyses the road 25 times per second which generates 100 times better data than other navigation apps; other drivers are routed to avoid areas with problems. Purchase Brand Ambassador NFTs for lifetime royalties when users buy NFT cars from that brand. Brand Ambassador positions are VERY RARE and will likely increase in value.

Navigation apps use routing algorithms to suggest the best path to reach a user's desired destination. Although undoubtedly useful, navigation apps' impact on the urban environment (e.g., carbon dioxide emissions and population exposure to pollution) is still largely unclear. In this work, we design a simulation framework to assess the impact of routing algorithms on carbon dioxide emissions within an urban environment. Using APIs from TomTom and OpenStreetMap, we find that settings in which either all vehicles or none of them follow a navigation app's suggestion lead to the worst impact in terms of CO2 emissions. In contrast, when just a portion (around half) of vehicles follow these suggestions, and some degree of randomness is added to the remaining vehicles' paths, we observe a reduction in the overall CO2 emissions over the road network. Our work is a first step towards designing next-generation routing principles that may increase urban well-being while satisfying individual needs.

With the rise of artificial intelligence, our definitions of certain technological processes are increasingly important. Much like in the way virtual reality, augmented reality and mixed reality are often confused, so what most people call artificial intelligence can become muddled with virtual intelligence. The difference between these two is vital. If we hope to know which technology to use in our everyday and business lives, we must know what differentiates them. But there is a sea of badly written and, quite frankly, misinformed articles out there on the topic.

People are terrified of the prospect of robots replacing humans in the workforce. But apparently they're not so scared that they fear a robot may be coming for their own job. That's according to a recent Gallup survey, which found that roughly 75% of U.S. adults think AI will'eliminate more jobs than it creates.' However, only 23% of American workers fear they will lose their own job to technology. There is no research that can definitively predict just how many or what kinds of jobs will be lost as a result of continued automation and advanced technologies like artificial intelligence.

People are terrified of the prospect of robots replacing humans in the workforce. But apparently they're not so scared that they fear a robot may be coming for their own job. That's according to a recent Gallup survey, which found that roughly 75% of U.S. adults think AI will'eliminate more jobs than it creates.' However, only 23% of American workers fear they will lose their own job to technology. A new Gallup survey finds that people believe robots are going to replace more and more human jobs, just not their own.

Nearly nine in 10 Americans (85%) say they currently use at least one of six devices, programs or services that feature elements of artificial intelligence (AI). These data come from a Northeastern University/Gallup survey of Americans' attitudes toward artificial intelligence (AI) and its effect on their lives and work. The mail survey of 3,297 U.S. adults was conducted Sept. 15-Oct. The study found 79% of Americans saying AI has had a very or mostly positive impact on their lives so far. The percentage of Americans using different consumer AI products may be at least partly related to the length of time these products have been on the market.