After reporting last week that the "raw" Jeffrey Epstein prison video posted by the FBI was likely modified in at least some ways (though there is no evidence that the footage was deceptively manipulated), WIRED reported on Tuesday that metadata analysis of the video shows approximately 2 minutes and 53 seconds were removed from one of two stitched-together clips. The United States Department of Homeland Security is facing controversy over DNA samples taken from approximately 133,000 migrant children and teens that the department added to a criminal database. Meanwhile, researcher Jeremiah Fowler published findings this week that more than 2 GB of extremely sensitive adoption-related data--including information about biological parents, children, and adoptive parents--was exposed and publicly accessible on the open internet. Roblox's new Trusted Connections feature includes age verification that uses AI to scan teens' video selfies and determine whether they can be granted access to unfiltered chatting with people they know. And as video deepfake capabilities mature--including AI tools that can even manipulate live video footage--AI "nudify" platforms are drawing millions of users and generating millions of dollars in revenue using tech from US companies.

The Indian government has asked tech companies to seek its explicit nod before publicly launching "unreliable" or "under-tested" generative AI models or tools. It has also warned companies that their AI products should not generate responses that "threaten the integrity of the electoral process" as the country gears up for a national vote. The Indian government's efforts to regulate artificial intelligence represent a walk-back from its earlier stance of a hands-off approach when it informed Parliament in April 2023 that it was not eyeing any legislation to regulate AI. The advisory was issued last week by India's Ministry of Electronics and Information Technology (MeitY) briefly after Google's Gemini faced a right-wing backlash for its response over a query: 'Is Modi a fascist?' It responded that Indian Prime Minister Narendra Modi was "accused of implementing policies some experts have characterised as fascist", citing his government's "crackdown on dissent and its use of violence against religious minorities".

It is critical for vehicles to prevent any collisions with pedestrians. Current methods for pedestrian collision prevention focus on integrating visual pedestrian detectors with Automatic Emergency Braking (AEB) systems which can trigger warnings and apply brakes as a pedestrian enters a vehicle's path. Unfortunately, pedestrian-detection-based systems can be hindered in certain situations such as night-time or when pedestrians are occluded. Our system addresses such issues using an online, map-based pedestrian detection aggregation system where common pedestrian locations are learned after repeated passes of locations. Using a carefully collected and annotated dataset in La Jolla, CA, we demonstrate the system's ability to learn pedestrian zones and generate advisory notices when a vehicle is approaching a pedestrian despite challenges like dark lighting or pedestrian occlusion. Using the number of correct advisories, false advisories, and missed advisories to define precision and recall performance metrics, we evaluate our system and discuss future positive effects with further data collection. We have made our code available at https://github.com/s7desai/ped-mapping, and a video demonstration of the CHAMP system at https://youtu.be/dxeCrS_Gpkw.

Eugenia Kuyda defended AI companion bots during the interview with Fox News Digital and argued that dating app Replika is just one of many possible solutions to loneliness. Credit it to the rise of technology, political polarization or even the pandemic, but loneliness is on the rise. It's an epidemic with consequences so severe that Surgeon General Dr. Vivek Murthy warns they could be deadly. "We now know that loneliness is a common feeling that many people experience. It's a feeling the body sends us when something we need for survival is missing," Murthy said, per The Associated Press.

Security experts are on the alert for the next evolution of social engineering in business settings: deepfake employment interviews. The latest trend offers a glimpse into the future arsenal of criminals who use convincing, faked personae against business users to steal data and commit fraud. The concern comes following a new advisory this week from the FBI Internet Crime Complaint Center (IC3), which warned of increased activity from fraudsters trying to game the online interview process for remote-work positions. The advisory said that criminals are using a combination of deepfake videos and stolen personal data to misrepresent themselves and gain employment in a range of work-from-home positions that include information technology, computer programming, database maintenance, and software-related job functions. Federal law-enforcement officials said in the advisory that they've received a rash of complaints from businesses.

Neural networks serve as effective controllers in a variety of complex settings due to their ability to represent expressive policies. The complex nature of neural networks, however, makes their output difficult to verify and predict, which limits their use in safety-critical applications. While simulations provide insight into the performance of neural network controllers, they are not enough to guarantee that the controller will perform safely in all scenarios. To address this problem, recent work has focused on formal methods to verify properties of neural network outputs. For neural network controllers, we can use a dynamics model to determine the output properties that must hold for the controller to operate safely. In this work, we develop a method to use the results from neural network verification tools to provide probabilistic safety guarantees on a neural network controller. We develop an adaptive verification approach to efficiently generate an overapproximation of the neural network policy. Next, we modify the traditional formulation of Markov decision process (MDP) model checking to provide guarantees on the overapproximated policy given a stochastic dynamics model. Finally, we incorporate techniques in state abstraction to reduce overapproximation error during the model checking process. We show that our method is able to generate meaningful probabilistic safety guarantees for aircraft collision avoidance neural networks that are loosely inspired by Airborne Collision Avoidance System X (ACAS X), a family of collision avoidance systems that formulates the problem as a partially observable Markov decision process (POMDP).

Amazon's property-surveillance company Ring has "recalled" hundreds of thousands of its namesake doorbell video cameras after some caught fire and people were burned. The company said there's only a risk if the wrong screws were used for installation. "Ring has received 85 incident reports of incorrect doorbell screws installed, with 23 of those doorbells igniting, resulting in minor property damage," the federal Consumer Product Safety Commission said in an advisory. "The firm has received eight reports of minor burns." Ring said in its own advisory that if the doorbell is installed correctly, "there is no risk to consumers or potential hazard." Though classified by Ring and the commission as a "recall," the problem with the 2nd Generation devices, model number 5UM5E5, should be addressed via re-installation, the company and commission said.

We present an approach for designing correct-by-construction neural networks (and other machine learning models) that are guaranteed to be consistent with a collection of input-output specifications before, during, and after algorithm training. Our method involves designing a constrained predictor for each set of compatible constraints, and combining them safely via a convex combination of their predictions. We demonstrate our approach on synthetic datasets and an aircraft collision avoidance problem.

Posted on June 15, 2019 by Capt. The introduction of machines to replace humans is growing steadily ever since the industrial revolution. The use of data-driven approach has led to the development of artificial intelligence and machine learning. Popping out from computer science and data science as the third matryoshka doll is artificial intelligence. Artificial intelligence, or AI, encompasses the ability of machines to perform intelligent and cognitive tasks.

The resulting collision avoidance strategy can be represented as a numeric table. This methodology has been used in the development of the Airborne Collision Avoidance System X (ACAS X) family of collision avoidance systems for manned and unmanned aircraft, but the high dimensionality of the state space leads to very large tables. To improve storage efficiency, a deep neural network is used to approximate the table. With the use of an asymmetric loss function and a gradient descent algorithm, the parameters for this network can be trained to provide accurate estimates of table values while preserving the relative preferences of the possible advisories for each state. By training multiple networks to represent subtables, the network also decreases the required runtime for computing the collision avoidance advisory. Simulation studies show that the network improves the safety and efficiency of the collision avoidance system. Because only the network parameters need to be stored, the required storage space is reduced by a factor of 1000, enabling the collision avoidance system to operate using current avionics systems.