Software micromanages call center employees by monitoring their vocal cues

Daily Mail - Science & tech

Artificial intelligence could soon replace the need for office managers - in call centers, at least. According to a recent report from the New York Times, new software by AI firm Cogito can micro-manage workers by monitoring when they talk too fast, lack enthusiasm, or even when their voices aren't conveying enough empathy. Workers are then notified of their performance in real-time via symbolized prompts like a coffee cup or cartoon heart depending on which metrics the program deems are lacking. And the tech is gaining traction: the Times reports that MetLife now uses Cogito - which claims its has 20,000 users, including the health insurance company, Humana - for 1,500 of its call center workers and claims the AI has helped boost customer satisfaction by 13 percent. Call center employees for the insurance giant MetLife are managed by an artificially intelligent boss that can offer tips based on their vocal cues.

Researchers unveil new tool to pinpoint unnatural movements that helps suss out deepfakes

Daily Mail - Science & tech

The fight against videos altered by the use of artificial intelligence just got a new ally. According to researchers at UC Berkeley and the University of Southern California, a new algorithm can help spot whether a video has been manipulated via a process known as'deepfaking.' Counter-intuitively, the tool that scientists say will aid them in their crusade against faked videos happens to be the very same tool that helps make the videos in the first place: artificial intelligence. The fight against videos altered by the use of artificial intelligence just got a new ally. Pictured is a grab from a deep fake video where Steve Buscemi's face is superimposed over Jennifer Lawrence's body Deepfakes are so named because they utilize deep learning, a form of artificial intelligence, to create fake videos.

Japan aims to provide one computer to every student by 2025

The Japan Times

Japan aims to make a computer terminal available to every school student by around fiscal 2025, the education ministry said Tuesday. The target is included in the ministry's new plan to improve the educational environment through the use of technology. A ministry survey in March 2018 found that computers were distributed on average at a rate of 1 terminal per 5.6 students at public elementary and high schools across the country. By prefecture, Saga performed best with a rate of 1 terminal per 1.8 students, while Saitama saw the worst rate of 1 terminal per 7.9 students. To further increase the number of computers at schools, the ministry's plan showed examples of how computers can be procured at lower costs.

I spent a day eating food cooked by robots in America's tech capital

The Guardian

Around the world, an industry has emerged around automating food service through robotics, raising questions about job security and mass unemployment while also prompting praise for streamlining and innovation. In the epicenter of Silicon Valley, where innovation is exalted beyond all else, this industry has played out in various forms, from cafes, burger shops and pizza delivery to odd vending machines. Man cannot survive on bread alone, the saying goes, but in the Bay Area, a woman could conceivably sustain herself on a varied menu of foodstuffs that had not passed the hand of man in preparation at all that day. And that woman is me. I began my day with a coffee at CafeX, where I met Francisco, the dancing and spinning robotic arm.

Neural network vaccinations protect against hacking


A programming technique that works on the same principle as disease-preventing vaccinations could safeguard machine learning systems from malicious cyber-attacks. The technique was developed by the digital specialist arm of Australia's national science agency, the CSIRO, and presented recently at an international conference on machine learning, held in Long Beach, California, US. Machine learning systems, or neural networks, are becoming increasingly prevalent in modern society, where they are pressed into service across a wide range of areas, including traffic management, medical diagnosis, and agriculture. They are also critical components in autonomous vehicles. They operate from an initial training phase, in which they are fed tens of thousands of possible iterations of a given task.

How Will Artificial Intelligence Change Law Schools?


Beyond the classroom curriculum, many law schools are designing experiential modes of introducing law students to artificial intelligence. At Georgia State University School of Law, for instance, the Legal Analytics and Innovation Initiative gives law students a chance to collaborate closely with computer science and business students at the same university to design complex technologies that solve previously unsolvable legal problems (such as predicting to a high degree of accuracy how a particular judge will rule in cases defined by a large set of parameters). This kind of work not only has the potential to be a flow-through to the legal practitioner space, but could over time become a mechanism for law schools to "spin out" the kinds of revenue-generating start-up businesses that are a common facet of life science departments at research universities. These programs have also been shown (according to the programs' own statistics) to help law students land jobs at higher rates than the overall student body, no doubt because the intersection of technology and law is a rare and valuable skillset in the eyes of employers.

Machine learning helps Northside track insurance payments


Northside Hospital in Atlanta is adopting machine learning technology to enable the organization to predict when insurance companies will end payments. The new technology it's using is from The SSI Group, which is providing technology that aggregates all remittance data coming through its clearinghouse to make the predictions. The goal is to enable providers that manually build their own spreadsheets to predict payments to use the SSI technology to determine when they can expect to get paid, down to the day and time, according to the vendor. "Without predictive analytics, hospitals and other providers are left guessing when they will receive payments," says Eric Nilsson, chief technology officer at SSI. Using analytics, SSI can give greater visibility on the payment of institutional, professional, in-patient and out-patient claims.

ML-Driven DevOps: Should You Really Marry the Two? - Squadex


The story of Artificial Intelligence (AI) and Machine Learning (ML) is all about hope and hype. On the one hand, there's a technology that promises to revolutionize fields as diverse as agriculture, manufacturing, education, and healthcare. On the other, there's so much media attention that it gets impossible to cut through the hype and, proverbially speaking, separate the wheat from the chaff. And though making heads or tails of it all is difficult, DevOps is for sure poised to capitalize on the opportunities that AI and ML offer, such as automation of tasks, data analysis, and improvement of efficiency. DevOps generates tons of data.

Deep learning for detecting inappropriate content in text


Today, there are a large number of online discussion fora on the internet which are meant for users to express, discuss and exchange their views and opinions on various topics. In such fora, it has been often observed that user conversations sometimes quickly derail and become inappropriate such as hurling abuses, passing rude and discourteous comments on individuals or certain groups/communities. Similarly, some virtual agents or bots have also been found to respond back to users with inappropriate messages. As a result, inappropriate messages or comments are turning into an online menace slowly degrading the effectiveness of user experiences. Hence, automatic detection and filtering of such inappropriate language has become an important problem for improving the quality of conversations with users as well as virtual agents.

Zendesk Expands Integration Access to Answer Bot


Zendesk, customer service and engagement solutions provider, recently introduced the expansion of its Answer Bot product. Answer Bot is a machine learning tool that helps customers find answers for themselves. It pulls data from the Zendesk Guide knowledge base and suggests articles to help customers solve problems on their own. Answer Bot has been around for a few years. However, Zendesk is expanding the service through integration capabilities through API, SDK, Web Widget, and forms (both email and web).