It's been estimated that China's government has detained as many as a million members of the country's Muslim population in so-called "re-education camps," in part of a campaign that has alarmed human rights activists across the world. This week, drawing on 403 pages of leaked government documents, The New York Times published new details of how the ongoing crackdown took shape under Chinese President Xi Jinping and other leadership in the Communist Party of China, how government workers who resisted the plan were sidelined, and what officials were instructed to tell young people whose families had been detained. "They're in a training school set up by the government to undergo collective systematic training, study and instruction," the talking points read, adding, "You have nothing to worry about." The Chinese government's campaign against those it says have been exposed to extremism is centered on an autonomous region, Xinjiang, where nearly half of the 25 million residents are a Muslim people called the Uighurs. Earlier in November, a FRONTLINE documentary called In the Age of AI examined how, as part of its crackdown involving the Uighurs, China's government has made Xinjiang a test project for forms of extreme digital surveillance.

Discussions on the interplay of humans and Artificial Intelligence tend to pose the issue in the language of opposition. However, according to the thinking of evolutionary biologist Richard Dawkins, tools such as AI can be better thought of as part of our extended phenotype. A phenotype refers to the observable characteristic of an organism, and the idea of the extended phenotype is that this should not be limited to biological processes, but include all of the effects that the genes have upon their environment, both internally and externally. We are used to defining ourselves strictly by the space we occupy in the physical world. The numbers of non-human cells that occupy our own body outnumber the number of human cells and vast colonies of bacteria swarm within the interior of our digestive tract. Author Robert Svoboda compares the human to a minority government ruling a primarily non-human population.

A few short years ago, personal digital assistants like Amazon's Alexa, Apple's Siri and Google Assistant sounded futuristic. Now, the future is here and this future is embedded, augmented and ubiquitous. Digital assistants can be found in your office, home, car, hotel, phone and many other places. They have recently undergone massive transformation and run on operating systems that are fuelled by artificial intelligence (AI). They observe and collect data in real-time and have the capability to pull information from different sources such as smart devices and cloud services and put the information into context using AI to make sense of the situation.

Life sciences companies are likely to begin experimenting further with AI in their workflows in the coming years, but they face challenges in AI adoption due to strict regulations. Machine learning has a "black box" problem, meaning that it's in many cases impossible to know how a machine learning algorithm comes to its conclusions. An AI application that detects cancer, for example, may not be able to show an oncologist how it determined the presence of cancer in a patient's body. As a result, if the oncologist used the application to diagnose a patient, they wouldn't be able to explain to the patient what makes them sure they have cancer. This issue relegates AI applications in life sciences to experiments and pilots, and widespread adoption, although likely inevitable, may not come for a while as public opinion shifts toward accepting that its diagnoses are informed by decision-making artificial intelligence and regulations evolve to match.

JPMorgan Chase sees artificial intelligence (AI) as critical to its future success. And the mega-bank has a big advantage over many of its smaller rivals: the massive amount of data it gathers from sources such as the 50% of U.S. households with which it has some form of relationship and the $6 trillion worth of payment flows it handles daily. But until recently, identifying and pulling in relevant data to train AI models was taking up around 60% of the time of the bank's growing army of data scientists. That was an inefficient use of an expensive and relatively scarce resource. Now a new data platform the bank has developed, called OmniAI, is helping it to get relevant data into its models much faster.

Marketing today is on the threshold of change. In the past, marketing as we knew it was largely dominated by 30-second TV spots and other mass media such as print, outdoor, radio and so on. The number-crunching only came into play while deciding which medium to back in the advertising campaign and for what price to buy the media. But, look around today and there are the likes of Google, Facebook, Twitter and others who apply complex algorithms such as Page Rank, Adsense, marketing mix modelling, content marketing and so on along with technology (analytics, digital marketing, search engine optimisation (SEO) and search engine marketing (SEM) to make marketing a lot more data-driven. Similarly, in music the magic of maths plays a huge role.

Technology is ever-changing, and with every new decade it accelerates at a pace that is often difficult for us humans to keep up with. We now live in a world in which we rely heavily on technology on a daily basis, regardless of which field we belong to. However, few industries have been changed by technology as much, or as positively, as healthcare. Although the healthcare industry has often lagged behind others when it comes to deploying advanced technology, new discoveries and improvements are always being made. The technology that we know today has opened countless doors and opportunities to improve our lives, and it's almost impossible to imagine life without it now.

FRONTLINE investigates the promise and perils of artificial intelligence, from fears about work and privacy to rivalry between the U.S. and China. The documentary traces a new industrial revolution that will reshape and disrupt our lives, our jobs and our world, and allow the emergence of the surveillance society.

Think lawsuits involving humans are tricky? Try taking an intelligent robot to court. While autonomous robots with humanlike, all-encompassing capabilities are still decades away, European lawmakers, legal experts and manufacturers are already locked in a high-stakes debate about their legal status: whether it's these machines or human beings who should bear ultimate responsibility for their actions. The battle goes back to a paragraph of text, buried deep in a European Parliament report from early 2017, which suggests that self-learning robots could be granted "electronic personalities." Such a status could allow robots to be insured individually and be held liable for damages if they go rogue and start hurting people or damaging property.