Artificial intelligence (AI) has permeated every aspect of our lives. From major advancements in medicine to transforming the way business is conducted, machine learning shows great potential to improve the quality of our lives in a variety of ways. A behind-the-scenes look into different companies' AI ventures shows that certain aspects of machine learning even aid in making the world a safer place. Manufacturing problems can have serious negative impacts on a business. From cars to home appliances, product safety is of utmost importance when it comes to customer satisfaction.

The digital secretary has said he will question Grindr and Tinder about how they protect children after an investigation claimed they are put at risk of sexual exploitation. More than 30 cases of child rape have been investigated by police since 2015 after victims evaded age checks on such apps, the Sunday Times found. Jeremy Wright described it as "truly shocking". Grindr and Tinder said they have measures to prevent minors using them. A Freedom of Information request by the Sunday Times also showed 60 further instances of child sex offences - including grooming, kidnapping and violent assault - through online dating services.

The culture secretary Jeremy Wright is to question Tinder and Grindr about measures used to protect children after police records showed they are at risk of grooming and sexual exploitation on the dating apps. The Secretary of State for Digital, Culture, Media and Sport (DCMS) said he was "truly shocked" to discover the perpetrators of child sex offences had used online dating services. Mr Wright said: "I will be writing to these companies asking what measures they have in place to keep children safe from harm, including verifying their age. "If I'm not satisfied with their response, I reserve the right to take further action." Police have investigated more than 30 incidents of child rape since 2015 where victims were sexually exploited after evading age checks on dating apps, according to The Sunday Times. Dwain Chambers made his sprint comeback in the 60m event at the British Indoor Championships. The 40-year-old came in second during his heat with a time of 6.78 however after a ...

Artificial intelligence (AI) could contribute up to $15.7 trillion to the global economy by 2030, according to PwC. Meanwhile, Forrester has warned that cybercriminals can weaponize and exploit AI to attack businesses. And we've all seen the worrisome headlines about how AI is going to take over our jobs. Toss in references to machine learning, artificial neural networks (ANN), and multilayer ANN (aka deep learning), and it's difficult to know what to think about AI and how CISOs can assess whether the emerging technology is right for their organizations. Gartner offers some suggestions on how to fight the FUD, as do Gartner security analysts Dr. Anton Chuvakin and Augusto Barros, who help demystifying AI in their blogs (not without a good note of sarcasm).

What's New: Non-profit RESOLVE's* new TrailGuard AI* camera uses Intel-powered artificial intelligence (AI) technology to detect poachers entering Africa's wildlife reserves and alert park rangers in near real-time so poachers can be stopped before killing endangered animals. TrailGuard AI builds on anti-poaching prototypes funded by Leonardo DiCaprio Foundation and National Geographic Society. "By pairing AI technology with human decision-makers, we can solve some of our greatest challenges, including illegal poaching of endangered animals. With TrailGuard AI, Intel's Movidius technology enables the camera to capture suspected poacher images and alerts park rangers, who will ultimately decide the most appropriate response." How It Works: TrailGuard AI uses Intel Movidius Vision Processing Units (VPUs) for image processing, running deep neural network algorithms for object detection and image classification inside the camera.

What is the law but a series of algorithms? Sounds a lot like computer programming, right? The legal system, on the other hand, is not as straightforward as coding. Just consider the complicated state of justice today, whether it be problems stemming from backlogged courts, overburdened public defenders, and swathes of defendants disproportionately accused of crimes. So, can artificial intelligence help?

But the ambiguity of human decision-making often makes it extraordinarily hard for the legal system to know whether anyone has actually discriminated. To understand how algorithms affect discrimination, we must therefore also understand how they affect the problem of detecting discrimination. By one measure, algorithms are fundamentally opaque, not just cognitively but even mathematically. Yet for the task of proving discrimination, processes involving algorithms can provide crucial forms of transparency that are otherwise unavailable. These benefits do not happen automatically. But with appropriate requirements in place, the use of algorithms will make it possible to more easily examine and interrogate the entire decision process, thereby making it far easier to know whether discrimination has occurred. By forcing a new level of specificity, the use of algorithms also highlights, and makes transparent, central tradeoffs among competing values. Algorithms are not only a threat to be regulated; with the right safeguards in place, they have the potential to be a positive force for equity.

Little by little, newspapers are revealing the bright future that Artificial Intelligence (AI) is building. Intelligent machines will help everywhere. However, this bright future may have a possible dark side: a dramatic job market contraction before its unpredictable transformation. Hence, in a near future, large numbers of job seekers may need financial support while catching up with these novel unpredictable jobs. This possible job market crisis has an antidote inside. In fact, the rise of AI is sustained by the biggest knowledge theft of the recent years. Many learning AI machines are extracting knowledge from unaware skilled or unskilled workers by analyzing their interactions. By passionately doing their jobs, many of these workers are shooting themselves in the feet. In this paper, we propose Human-in-the-loop Artificial Intelligence (HitAI) as a fairer paradigm for AI systems. Recognizing that any AI system has humans in the loop, HitAI will reward these aware and unaware knowledge producers with a different scheme: decisions of AI systems generating revenues will repay the legitimate owners of the knowledge used for taking those decisions. As modern Merry Men, HitAI researchers should fight for a fairer Robin Hood Artificial Intelligence that gives back what it steals. This article is part of the special track on AI and Society.

Republican Rep. Mike Henderson introduced a bill that would make it a misdemeanor for anyone to knowingly fly a drone within 300 vertical feet (90 meters) and near the furthest perimeter of prisons, the St. The legislation would also add felony charges for attempting to drop contraband into state prison grounds.

A report from the recent conference on Computers, Privacy and Data Protection suggested that the European Commission is "considering the possibility of legislating for Artificial Intelligence." Karolina Mojzesowicz, Deputy Head, Data Protection Unit at the European Commission, said that the Commission is "assessing whether national and EU frameworks are fit for purpose for the new challenges." The Commission is exploring, for instance, whether to specify "how big a margin of error is acceptable in automated decisions and machine learning." The vehicle for this regulatory effort seems to be the draft Ethics Guidelines developed by a high-level expert group. The comment period on this draft closed on February 1, and a final report is due in March.