Some argue that Apple's more conservative approach is damaging to the development of core products like Siri, especially in the face of fierce competition from Amazon's Alexa. But Cook reiterated to Vice the company's "collect as little data as possible" stance, saying he considers privacy "one of the most important issues of the 21st century." The tech CEO added that he is not typically a "pro-regulation kind of person," but he would be willing to work with lawmakers to educate them and ensure that tech companies create products that are "great for society." "I think some level of government regulation is important to come out on that," Cook told Vice.

Over the weekend, a Google intern and two researchers from Google's DeepMind division released a paper, currently under review for a 2019 conference, featuring AI-generated images that blow everything else out of the water. Based on the small thumbnails, it's almost impossible to tell that they're not real images: There's a chestnut-colored dog with his tongue hanging out, a beautiful ocean vista, a monarch butterfly, and a juicy hamburger complete with melted cheese and a bun that looks like it was brushed with butter. The textures of the images, from the dog's fur to the hamburger's juices, are incredibly realistic, with careful study revealing only tiniest of tells that the image isn't a real one. The research is making waves in the research community, where some expressed shock at the image quality. Oriol Vinyals, a research scientist at DeepMind, wondered if the images were the "best GAN samples ever." "I want to live in a #BIGGAN generated world!" wrote Meltem Atay, a neurotechnology PhD student who focuses on machine learning.

Combining big data and machine learning algorithms, the power of automatic decision tools induces as much hope as fear. Many recently enacted European legislation (GDPR) and French laws attempt to regulate the use of these tools. Leaving aside the well-identified problems of data confidentiality and impediments to competition, we focus on the risks of discrimination, the problems of transparency and the quality of algorithmic decisions. The detailed perspective of the legal texts, faced with the complexity and opacity of the learning algorithms, reveals the need for important technological disruptions for the detection or reduction of the discrimination risk, and for addressing the right to obtain an explanation of the auto- matic decision. Since trust of the developers and above all of the users (citizens, litigants, customers) is essential, algorithms exploiting personal data must be deployed in a strict ethical framework. In conclusion, to answer this need, we list some ways of controls to be developed: institutional control, ethical charter, external audit attached to the issue of a label.

A Qatar-based sports TV network is seeking $1 billion in damages from Saudi Arabia for the kingdom's alleged involvement in the "most widespread piracy of sports broadcasting that the world has ever seen." BeIN Corporation claims that the pirate network beoutQ has received State support in order to grow into an advanced piracy operation that serves content to potentially millions of viewers through illegal set-top boxes. Global sporting events have been broadcast through the beoutQ network – including the 2018 Fifa World Cup, the Formula One World Championship and the Premier League – after the pirate nework hijacked the feeds of legitimate broadcasters. "Piracy is a major problem facing the sports and broadcasting industries. By supporting beoutQ's widespread and notorious infringement of the intellectual property rights of beIN and its partners, Saudi Arabia is setting a dangerous new precedent," said David Roney, a lawyer at Sidley Austin LLP who is leading the arbitration on behalf of beIN.

From using artificial intelligence (AI) to determine credit scores to using AI to determine whether a defendant or criminal may offend again, AI-based tools are increasingly being used by people and organizations in positions of authority to make important, often life-altering decisions. But how do these instances impact human rights, such as the right to equality before the law, and the right to an education? A new report from the Berkman Klein Center for Internet & Society (BKC) addresses this issue and weighs the positive and negative impacts of AI on human rights through six "use cases" of algorithmic decision-making systems, including criminal justice risk assessments and credit scores. Whereas many other reports and studies have focused on ethical issues of AI, the BKC report is one of the first efforts to analyze the impacts of AI through a human rights lens, and proposes a new framework for thinking about the impact of AI on human rights. The report was funded, in part, by the Digital Inclusion Lab at Global Affairs Canada.

A senior Google research scientist has quit the company in protest over its plan to launch a censored version of its search engine in China. Jack Poulson worked for Google's research and machine intelligence department, where he was focused on improving the accuracy of the company's search systems. In early August, Poulson raised concerns with his managers at Google after The Intercept revealed that the internet giant was secretly developing a Chinese search app for Android devices. The search system, code-named Dragonfly, was designed to remove content that China's authoritarian government views as sensitive, such as information about political dissidents, free speech, democracy, human rights, and peaceful protest. After entering into discussions with his bosses, Poulson decided in mid-August that he could no longer work for Google.

Artificial intelligence is transforming the traditional delivery of legal services. In general terms, the set of tools broadly called "legal analytics" promises to do two things: increase the efficiency of tasks that once required substantial time and human effort, and mine masses of data to discover new insights that were previously inaccessible. As legal scholars, we're excited about the promise of applying these tools to legal research questions. Students are involved too, so that we can educate the next generation of lawyers to leverage these tools in their own practices. Suppose that a company wants to forecast which employee complaints lead to lawsuits.

An engineer with no connection to the self-driving industry has spent $6,000 of his own money to stop Alphabet's self-driving car business Waymo from patenting key technology. Following a challenge filed by Eric Swildens, the US Patent and Trademark Office (USPTO) rejected 53 out of 56 claims in Waymo's 936 patent. He just "couldn't imagine the [lidar] circuit [described in the 936 patent] didn't exist prior," Ars Technica reported. Filed in 2013 and granted in 2016, the 936 patent was a cornerstone of Waymo's lawsuit against Uber, which began in December 2016. In a nutshell, Waymo accused the ride-hailing giant of infringing its lidar design patent and using intellectual property allegedly stolen by engineer Anthony Levandowski.

It's now generally accepted that as artificial intelligence (AI) advances into fields of work that were formerly considered skilled labour, a huge number of manual and white collar jobs are likely to disappear. These are the kinds of jobs that require learning and applying patterns, unemotional calculation and mechanistic problem solving. Think: medical diagnosis, legal contracts and engineering. Read more: AI doctors and engineers are coming – but they won't be stealing high-skill jobs Guardian columnist Simon Jenkins recently suggested AI will free us up to focus on the caring work uniquely suited to humans. Currently much care work is low paid, unpaid or invisible – and mostly done by women.

Algorithms are a black box. We can see them at work in the world. We know they're shaping outcomes all around us. But most of us have no idea what they are -- or how we're being influenced by them. Algorithms are invisible pieces of code that tell a computer how to accomplish a specific task.