Westworld is a hell of a show, but the sense of dread it elicits is nothing new. Pygmalion sculpted a woman who came to life. Same goes with the Golem, only with mud. The amalgamated Frankenstein jolted awake to get all murderous. Humans creating life in their own image is a cornerstone of the realm of fiction.

Apple describes its mobile devices as designed in California and assembled in China. You could also say they were made by the App Store, launched a decade ago next month, a year after the first iPhone. Inviting outsiders to craft useful, entertaining, or even peurile extensions to the iPhone's capabilities transformed the device into the era-defining franchise that enabled Uber and Snapchat. Craig Federighi, Apple's head of software, is tasked with keeping that wellspring of new ideas flowing. One of his main strategies is to get more app developers to use artificial intelligence tools such as recognizing objects in front of an iPhone's camera. The hope is that will spawn a new generation of ideas from Apple's ecosystem of outsourced innovation.

The democratization of mass surveillance is upon us. Insanely cheap tools with the power to track individuals en masse are now available for anyone to use, as exemplified by a Forbes test of an Amazon facial recognition product, Rekognition, that made headlines last month. Jeff Bezos' behemoth of a business is seen by most as a consumer-driven business, not a provider of easy-to-use spy tech. But as revealed by the American Civil Liberties Union (ACLU) last week, Amazon Web Services (AWS) is shipping Rekognition to various U.S. police departments. And because Rekognition is open to all, Forbes decided to try out the service. Based on photos staff consensually provided, and with footage shot across our Jersey City and London offices, we discovered it took just a few hours, some loose change and a little technical knowledge to establish a super-accurate facial recognition operation.

The US government is deploying a new facial recognition system at the southern border that would record images of people inside vehicles entering and leaving the country. The pilot program, scheduled to begin in August, will build on secretive tests conducted in Arizona and Texas during which authorities collected a "massive amount of data", including images captured "as people were leaving work, picking up children from school, and carrying out other daily routines", according to government records. The project, which US Customs and Border Protection (CBP) confirmed to the Guardian on Tuesday, sparked immediate criticisms from civil liberties advocates who said there were a host of privacy and constitutional concerns with an overly broad surveillance system relying on questionable technology. Already the largest and most funded federal law enforcement agency in its own right, the border patrol is part of the umbrella agency US Customs and Border Protection (CBP). CBP's approximately 60,000 employees are split in four major divisions: officers who inspect imports; an air and marine division; agents who staff ports of entry – international airports, seaports and land crossings; and the approximately 20,000 agents of the border patrol, who are concentrated in the south-west, but stationed nationwide.

Apple's Siri has fallen behind its virtual assistant competition. Google's Assistant expertly surfaces information, while Amazon's Alexa works with a staggering number of third-party apps for a broad variety of capabilities. Apple isn't admitting defeat, though: Siri played a prominent role at WWDC, the company's "Worldwide Developers Conference," on Monday. Specifically, Apple is finally tackling the issue of customization with its personal digital assistant: Making Siri do more, proactively, to make your day easier. Apple is primarily accomplishing this with a new tool called Siri Shortcuts, a sort of IFTTT built straight into iOS for personalizing and automating Siri commands and functions.

As much as fully autonomous vehicles are in the news, none of us will be commuting to work in a self-driving car for at least two decades. Meanwhile, Toyota says it will use technology, called V-2-V, in all its cars within a few years with claims it will save thousands of lives each year -- as cars talk to each other on the highway.

With today's unveilling of iOS 12 at WWDC, Apple hinted at an upgraded Siri worthy of 2018. The news: On opening day of its annual developer conference, Apple announced plans to make its AI-powered digital assistant Siri more robust in iOS 12 with a new property called "shortcuts." Users will be able to create voice commands that let Siri help more effectively with day-to-day tasks, from ordering coffee to finding lost keys. Catching up on AI: The launch of Siri in 2011 was a breakout moment for voice-activated smart assistants, but competitors like Google's Assistant and Amazon's Alexa have since caught up, if not surpassed, Apple's technology. The news in April that the firm poached Google's AI chief confirmed that it was doubling down to get back on pace.

Microsoft is building a tool to automatically identify bias in a range of different AI algorithms. It is the boldest effort yet to automate the detection of unfairness that may creep into machine learning--and it could help businesses make use of AI without inadvertently discriminating against certain people. Big tech companies are racing to sell off-the-shelf machine-learning technology that can be accessed via the cloud. As more customers make use of these algorithms to automate important judgements and decisions, the issue of bias will become crucial. And since bias can easily creep into machine-learning models, ways to automate the detection of unfairness could become a valuable part of the AI toolkit.

University of Toronto researchers have designed an algorithm to disrupt facial recognition technology. The past few months have witnessed a mainstream groundswell around security and data privacy, embodied most notably in news of Cambridge Analytica's data-collection tactics and the Facebook CEO Mark Zuckerberg's testimony before the U.S. senate. One major form of data emerges from facial recognition technology, which uses algorithms to identify us based on facial feature points. Every time you upload a photo to Facebook, Instagram, or otherwise, you give these learning systems another data point around your face -- and anybody else in the picture with you -- as well as metadata such as phone type and location. To address this problem, researchers at University of Toronto, led by Professor Parham Aarabi and graduate student Avishek Bose, have developed an algorithm to dynamically disrupt this technology.

Spanish police are introducing an artificial-intelligence system to detect liars.Credit: SubstanceP/Getty If you live in southern Spain, last June was not a good time to lose your smartphone and, as a way of getting an insurance payout, falsely claiming that you had been mugged. Ten police forces in Murcia and Malaga had some extra help in spotting your deceit: a computer tool that analysed statements given to officers about robberies and identified the telltale signs of a lie. According to results published in the journal Knowledge-Based Systems, the algorithm was so good at pointing officers towards false claimants that detection of such offences in one week was an impressive 31 and 49 for the respective regions, up from an average of 3 and 12 closed cases over the entire month (L. The government in Madrid is now rolling the system out across the country, and its developers are trying to apply its machine-learning methods to help detect other types of crime. In this case, the algorithm flagged up suspicious wording (based on a training set of statements known to be true and false), and left it up to the police to question suspects and get them to confess.