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Friday
May092014

Can Robots Make Moral Decisions? 

Are machines capable of making moral decisions?

Researchers from Tufts University, Brown University and Rensselaer Polytechnic Institute are working with the U.S. Navy to attempt to answer this question. 

They are exploring whether robots can learn right, wrong, and the consequences of both, which would be beneficial in the battlefield. 

In one scenario, a robot medic is responsible for helping wounded soldiers. It is ordered to transport urgently needed medication to a nearby field hospital. En route, it encounters a Marine with a fractured leg. Should the robot abort the mission to assist the injured? Will it?

If the machine stops, a new set of questions arises. The robot assesses the soldier's physical state and determines that unless it applies traction, internal bleeding in the soldier's thigh could prove fatal. However, applying traction will cause intense pain. Is the robot morally permitted to cause the soldier pain, even if it's for the soldier's well-being?

According to a Tufts University press release, the plan to develop moral robots includes isolating essential elements of human moral competence through theoretical and empirical research. Based on the results, the team will develop formal frameworks for modeling human-level moral reasoning that can be verified. Next, it will implement corresponding mechanisms for moral competence in a computational architecture.

The goal is to create a completely autonomous moral robot. According to Selmer Bringsjord, head of the Cognitive Science Department at RPI, all robot decisions would automatically go through at least a preliminary, lightning-quick ethical check using simple logics inspired by today's most advanced artificially intelligent and question-answering computers. If that check reveals a need for deep, deliberate moral reasoning, such reasoning would be fired inside the robot, using newly invented logics tailor-made for the task.

Monday
May052014

CreepShield Uses Facial Recognition to Make Online Dating Safer

These days, it seems like nearly every new relationship started online. But for all the well-intentioned online daters out there, a few creeps always threaten to ruin the fun.

Enter CreepShield, new facial recognition software that helps make online dating safer. The technology allows a user to check a dating site member's headshot against a database of nearly 500,000 sex offenders culled from publicly-accessible federal and state registries. CreepShield works with any online dating site; the user simply uploads a photo or pastes a link directly into the search field on the company's homepage.

The facial recognition seems to work fairly well, although CreepShield doesn't claim to achieve exact matches. Instead, it gives percentages based on the similarity of the provided photo to mugshots on file. Now, if only someone will create software that helps you weed out the bad dates.

Thursday
Apr242014

Computer Beats Humans in Face Recognition for the First Time

Labeled Faces in the Wild Credit: LFWFacial recognition technology may be thwarted by photos' variations in pose, illumination, expression and occlusion. But for the first time, a computer algorithm, developed by researchers from Chinese University of Hong Kong, has beat the facial recognition accuracy of humans.

The researchers Chaochao Lu and Xiaoou Tang used the Labeled Faces in the Wild database – a collection of 13,000 faces of 6,000 public figures from the Internet, each labeled with the person's name – as a benchmark. The database provides a range of face images with variations in pose, lighting, expression, race, ethnicity, age, gender, clothing, hairstyles, and other parameters.

The algorithm, named GaussianFace, scored an accuracy rating of 98.52 percent, beating the human average of 97.53 percent. Prior to GaussianFace, the highest score achieved by technology was 97.25 percent. 

According to the Physics arXiv Blog, it works by normalizing each face into a 150x120 pixel image using five image landmarks: the position of both eyes, the nose and the two corners of the mouth. It then divides each image into overlapping patches of 25x25 pixels and describes each patch using a vector, which captures its basic features. Then it compare the images looking for similarities.

GaussianFace was trained by using four databases that contain very different images. One of these is the Multi-PIE database, which consists of face images of 337 subjects from 15 different viewpoints under 19 different conditions of illumination taken in four photo sessions. Another is a database called Life Photos, which contains about 10 images of 400 different people.

Wednesday
Apr232014

Retailers Turn to Facial Recognition to Cut Down on Shoplifting

Smile, shoppers. You're on candid camera equipped with facial recognition software.

Retail stores that are vulnerable to shoplifting criminal activity are about to get a new ally. FaceFirst, a facial recognition software system, recently partnered with a nationally renowned Fortune 500 company to deploy hundreds of cameras in store entrances across the nation in order to curb shoplifting incidences and other criminal activity in the retail market.

FaceFirst's national deployment is the retail industry's largest retail deployment of facial recognition, and the software company anticipates securing additional retailers in the future. The company claims its advanced facial recognition technology will boost customer loyalty by providing shoppers with a peace of mind knowing their shopping experience can be enjoyed without the threat of criminal activity.

The FaceFirst facial recognition system spots known perpetrators entering store locations so retailers can stop criminal activity before they cost the retailer money. The software allows retailers to receive descriptive alerts when pre-identified shoplifters walk through any door at any store across multiple locations and receive alerts when litigious individuals enter store locations.

FaceFirst is just the latest in a string of retail-oriented facial recognition applications. NEC just announced its NeoFace software, which recognizes returning customers and tracks their preferences to provide better customer service. Both FaceFirst and NeoFace are designed to be easily installed and fairly affordable, so retailers of all sizes can take advantage of the technology. As prices on this type of software continue to fall, shoppers should expect facial recognition to become increasingly popular in the retail world.

Thursday
Apr172014

The Seamless Future of Augmented Reality 

With VENTURI's project Très Cloîtres Numérique, residents and visitors in Grenoble, a city in southeastern France, can soon use a tablet or smartphone to see the city in its past. The city scene is overlaid with historical photographs and 3-D reconstructions of ancient buildings. 

Companies like Volkswagen, Audi and IKEA are working with project partner Metaio to create exciting new tools. For example, Audi customers can take a virtual tour of their new vehicle; Volkswagen allows users to customize a car before ordering; and IKEA and Mitsubishi both allow customers to see how their products would look in their homes or offices, before buying.

But VENTURI researchers want people to experience augmented reality without tablets or smartphones. Their goal is to create a seamless augmented reality environment that leverages smart glasses, watches and earpieces. 

"In VENTURI, we have been exploring cutting edge 'reality sensing' through computer-vision and sensor fusion, and have tied this together with intuitive 'world augmentation' through 3D audio, Smartwatch interaction and HMDs like GoogleGlass," says VENTURI Project Coordinator Paul Chippendale. 

VENTURI is working with Metaio and Sony to create the first generation of ubiquitous AR tools. 

"Thanks to Sony's participation in VENTURI, we have had privileged access to their future vision of wearable devices, ranging from smart life logging bands (wrist-worn devices that log a user's activity) to advanced head mounted displaysm," Chippendale said. "We have been using this insight together with Metaio's strong market knowledge, to create personalised AR content according to a user's social profile, the current environmental and what it is that they're currently doing."

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