Advances in artificial intelligence have created new threats to the privacy of people's health data, a new University of California, Berkeley, study shows. Led by UC Berkeley engineer Anil Aswani, the study suggests current laws and regulations are nowhere near sufficient to keep an individual's health status private in the face of AI development. The research was published Dec. 21 in the JAMA Network Open journal. The findings show that by using artificial intelligence, it is possible to identify individuals by learning daily patterns in step data, such as that collected by activity trackers, smartwatches and smartphones, and correlating it to demographic data. The mining of two years' worth of data covering more than 15,000 Americans led to the conclusion that the privacy standards associated with 1996's HIPAA (Health Insurance Portability and Accountability Act) legislation need to be revisited and reworked.

In 2016, 56% of recruiters said they can't make good hires because of lengthy hiring procedures – MRI Network Survey 2016 Chatbots can initiate the interview process by fielding screening questions and capturing the answers. This helps in automatically screening and shortlisting the right candidates by assessing their potential. Automating screening has an additional benefit of eliminating human bias and identifying the candidates based on merit. HR personnel need to collect basic information like KYC, tax forms and signed non-disclosure agreements or other legal documents from the new employees during onboarding. It would be a rather time-consuming activity for the HR personnel to collect information from every employee.

The European Union has added its voice to the growing call for artificial intelligence (AI) to be regulated, with draft ethics guidelines that underline it must be human-centric and trustworthy to be effective. The European Commission's expert group on AI said that, to be trustworthy, the technology had both to respect fundamental rights and values and be technically reliable so it did not cause unintentional harm. The group claimed its first draft guidelines were different from other attempts to define ethical AI because they set out concrete proposals as well as broad principles. Meanwhile, the EU is due to make policy recommendations on regulating AI in May 2019. The experts said they aimed to foster "responsible competitiveness" and not stifle innovation.

Artificial intelligence has the potential to create trillions of dollars of value across the economy--if business leaders work to understand what AI can and cannot do. In this episode of the McKinsey Podcast, McKinsey Global Institute partner Michael Chui and MGI chairman and director James Manyika speak with McKinsey Publishing's David Schwartz about the cutting edge of artificial intelligence. Today, we're going to be journeying to the frontiers of artificial intelligence. We'll touch on what AI's impact could be across multiple industries and functions. We'll also explore limitations that, at least for now, stand in the way. I'm joined by two McKinsey leaders who are at the point of the spear, Michael Chui, based in San Francisco and a partner with the McKinsey Global Institute, and James Manyika, the chairman of the McKinsey Global Institute and a senior partner in our San Francisco office. Michael Chui: Great to be here. David Schwartz: Michael, where do we see the most potential from AI? Michael Chui: The number-one thing that we know is just the widespread potential applicability. That said, we're quite early in terms of the adoption of these technologies, so there's a lot of runway to go. One of the other things that we've discovered is that one way to think about where the potential for AI is, is just follow the money. If you're a company where marketing and sales is what drives the value, that's actually where AI can create the most value.

Approaching the end of current fiscal year, I take a serene glance at the memorable moments and guess what? I am quick to realize there was hardly any conference, webinar, debate, event or discussion in which there was no mention about Artificial Intelligence and its subset technologies, specifically Machine Learning, Deep Learning, Reinforcement Learning and Neural Networks. In fact, the latest 3-days conference I attended was titled'When Human Becomes Digital' and was centred around artificial intelligence. Analysts, as well as technologists, believe AI has and will continue to reign the world of technology for at least the next 2-3 years. The Ripple Effect created by these emerging technologies will gradually perish.

Summary: Here are our 5 predictions for data science, machine learning, and AI for 2019. We also take a look back at last year's predictions to see how we did. It's that time of year again when we do a look back in order to offer a look forward. What trends will speed up, what things will actually happen, and what things won't in the coming year for data science, machine learning, and AI. We've been watching and reporting on these trends all year and we scoured the web and some of our professional contacts to find out what others are thinking.

A common belief among tech industry insiders is that Silicon Valley has dominated the internet because much of the worldwide network was designed and built by Americans. Now a growing number of those insiders are worried that proposed export restrictions could short-circuit the pre-eminence of US companies in the next big thing to hit their industry: artificial intelligence. In November, the Commerce Department released a list of technologies, including artificial intelligence, that are under consideration for new export rules because of their importance to national security. Technology experts worry that blocking the export of AI to other countries, or tying it up in red tape, will help AI industries flourish in those nations -- China, in particular -- and compete with US companies. "The number of cases where exports can be sufficiently controlled are very, very, very small, and the chance of making an error is quite large," said Jack Clark, head of policy at OpenAI, an artificial intelligence lab in San Francisco.

With new ideas innovation continuing to drive Cambridge's businesses, Stephen Hodsdon – a partner, patent and trade mark attorney in the Cambridge office of J A Kemp – considers what engineering and IT fields may lead the way in 2019. It is a well-known statistic that Cambridge produces significantly more patent applications per head than any other area of the UK and this shows little sign of decreasing. As a patent attorney, this is of course unsurprising, but it doesn't happen by accident. The diversity of Cambridge-based innovation makes it hard to pick even a selection of sectors which will lead the way in 2018. However, gazing into my crystal ball (sadly neither real nor, as far as I can determine, a Cambridge invention), here are a few thoughts on the areas that could drive 2019's innovation output.

Last year, we put together our list of top trends in artificial intelligence for 2018. Those AI trends focused on increasing acceptance and understanding of AI in business, consumer, and legal applications. Those trends largely bore out over the course of the year, and the continued development of those artificial intelligence trends is what to look for in 2019. This year, we've put together another annual post of what to look for in artificial intelligence. As AI becomes more advanced and simultaneously more mainstream, we'll see a proliferation of applications using AI in 2019.

Technology is already in use to help stop poachers. However, it's frequently limited to monitoring poachers when they're already in shooting range, or after the fact. The non-profit group Resolve vows to do better -- it recently developed a newer version of its TrailGuard camera that uses AI to spot poachers in Africa before they can threaten an endangered species. It uses an Intel-made computer vision processor (the Movidius Myriad 2) that can detect animals, humans and vehicles in real-time, giving park rangers a chance to intercept poachers before it's too late. The technology promises to not only be more effective than previous cameras, but more efficient.