Apple on Thursday announced a long-awaited update for the MacBook Pro, giving the laptops a much-needed performance bump but not any meaningful change in design. Most notably, Apple has not fully changed the design of the laptops' keyboards, which have drawn serious complaints from consumers who find them unreliable. The new models -- one 13-inch model and one 15-inch model, both with Apple's Touch Bar -- have new chips that Apple said should dramatically increase performance. The company said in a press release that the 15-inch model is up to 70 percent faster, while the 13-inch model is twice as fast. Both have more storage than before: The 15-inch model can go up to a four-terabyte solid-state drive, while the smaller model maxes out at two terabytes. The laptops will also have a new "Hey Siri" capability that allows people to trigger Apple's voice assistant without having to hit a combination of keys beforehand.

Unleashing a legal and ethical debate worldwide, AI (artificial intelligence) is progressing with leaps and bounds as it portends to change human society forever. For example, if a driverless car meets with an accident involving fatalities, it is the algorithm operator who faces "product liability" rules. In the case of AI used in conventional war, machines killing humans is an ethically chilling concept. Carrying major implications, it is feared that the proto-AI technologies of today are going to evolve into true AI super-intelligence very rapidly without giving enough time for research into the pros and cons. As apprehensions of a "hyper-war scenario" build up, the main challenge remains: how to place the human factor in AI and prevent a drastic downgrade in military security as combat involving the technology changes the dimensions of warfare.

Future Tense is a partnership of Slate, New America, and Arizona State University that examines emerging technologies, public policy, and society. Starting in 2012, the Supreme Court's approach to digital privacy has undergone a seismic shift. In a series of recent cases on location tracking and cellular phone searches, the court has recognized that, when it comes to big data, old rules about our expectations of privacy may not apply. Because information can now be gathered, stored, and analyzed cheaply, the Supreme Court has recently found that Fourth Amendment protections must be carefully recalibrated to prevent unchecked police power. Supreme Court nominee Brett Kavanaugh, however, has exhibited a contrasting and outdated understanding of privacy. As important questions come before the court in the future--on police drone surveillance, on the use of facial recognition software, on government access to the vast troves of different kinds of digital data companies hold on us--it's crucial to understand where Kavanaugh stands.

Computer programs can, in some cases, predict chemical toxicity as well as tests done on rats and other animals.Credit: Coneyl Jay/SPL Machine-learning software trained on masses of chemical-safety data is so good at predicting some kinds of toxicity that it now rivals -- and sometimes outperforms -- expensive animal studies, researchers report. Computer models could replace some standard safety studies conducted on millions of animals each year, such as dropping compounds into rabbits' eyes to check if they are irritants, or feeding chemicals to rats to work out lethal doses, says Thomas Hartung, a toxicologist at Johns Hopkins University in Baltimore, Maryland. "The power of big data means we can produce a tool more predictive than many animal tests." In a paper published in Toxicological Sciences1 on 11 July, Hartung's team reports that its algorithm can accurately predict toxicity for tens of thousands of chemicals -- a range much broader than other published models achieve -- across nine kinds of test, from inhalation damage to harm to aquatic ecosystems. The paper "draws attention to the new possibilities of big data", says Bennard van Ravenzwaay, a toxicologist at the chemicals firm BASF in Ludwigshafen, Germany.

LONDON – The rise of robots in manufacturing in Southeast Asia is likely to fuel modern-day slavery as workers who end up unemployed due to automation face abuses competing for a shrinking pool of low-paid jobs in a "race to the bottom," analysts said Thursday. Drastic job losses due to the growth of automation in the region -- a hub for many manufacturing sectors from garments to vehicles -- could produce a spike in labor abuses and slavery in global supply chains, said risk consultancy Verisk Maplecroft. More than half of the workers in Cambodia, Indonesia, Thailand, Vietnam and the Philippines -- at least 137 million people -- risk losing their jobs to automation in the next two decades, the United Nations' International Labour Organization says. The risk of slavery tainting supply chains will spiral because workers who lose their jobs due to increased robot manufacturing will be more vulnerable to workplace abuses as they jostle for fewer jobs at lower wages, said Alexandra Channer of Maplecroft. "Displaced workers without the skills to adapt or the cushion of social security will have to compete for a diminishing supply of low-paid, low-skilled work in what will likely be an increasingly exploitative environment," she said.

HMRC's use of AI and big data to gather evidence in tax investigations has led to a 30% drop in property raids, according to law firm Pinsent Masons. The firm explained that HMRC has leveraged sophisticated algorithms and big data sources to gather evidence with greater ease and efficiency than costly and time-consuming property raids. Steven Porter, Partner at Pinsent Masons, said: "HMRC's big brother-style data collection on taxpayers is giving it the material it needs to ramp up its tax investigations and at the same time, is reducing the need for it to actually raid properties." The figure has dropped from 669 property raids in 2016/17 to 471 last year. In particular, tax inspectors have been using the state-of-the-art Connect database, an analytical system worth £80m and designed by BAE Systems, to carry out preliminary investigative work within seconds.

I had two really important AI ethics paper come out last year. The Science paper on semantics and prejudice I blogged about at least four times, but I just realised that I've never really blogged about the paper on legal personhood that I wrote with two leading law professors in legal personality, Tom Grant of Cambridge and Mihailis E. Diamantis of Iowa. Since they had way more influence on the paper than I did, I can sincerely and humbly say that it is just a great paper and everyone should read it. Long term, I think it may have more impact than the Science paper, to be honest. I just had an email about that paper, and it offered me a chance to write about the paper more succinctly.

While America struggles to retain net neutrality protections on a piecemeal state-by-state level, India just adopted its own seemingly-strong set of rules that largely ban artificial slowing or blocking of content. The Telecom Regulatory Authority of India (TRAI) proposed the rules back in November, and the country's official Telecommunications Commission (TC) approved them today, resolving a movement to update internet protections that began in 2015. From today onward, ISPs cannot perform actions involving "blocking, degrading, slowing down or granting preferential speeds or treatment to any content," per The Wire's report. Providers are also prohibited from providing zero-rated content. These include remote surgery or autonomous vehicles, which Sundarajan compared to laws allowing ambulances to ignore traffic rules.

GDPR (The General Data Protection Regulation) is a very significant EU law that offers major new data and privacy protection for all individuals within the European Union (EU) and the European Economic Area (EEA). GDPR took effect on May 25, 2018. You probably have all received countless emails from companies updating their privacy policies to comply with GDPR. These were written prior to the introduction of the new regulations, when the ambiguity of the new regulations had everyone second-guessing as to what affect the machine learning field would feel. So, two months on, has it become clearer?

Most of you will have interacted with several algorithms already today. Algorithms are of course simply sets of rules for solving problems, and existed long before computers. But algorithms are now everywhere in digital services. An algorithm decided the results of your internet searches today. If you used Google Maps to get here, an algorithm proposed your route. Algorithms decided the news you read on your news feed and the ads you saw.