Driverless vehicles are being tested on public roads in a number of countries.Credit: Prostock/Getty Last month, for the first time, a pedestrian was killed in an accident involving a self-driving car. A sports-utility vehicle controlled by an autonomous algorithm hit a woman who was crossing the road in Tempe, Arizona. The safety driver inside the vehicle was unable to prevent the crash. Although such accidents are rare, their incidence could rise as more vehicles that are capable of driving without human intervention are tested on public roads. In the past year, several countries have passed laws to pave the way for such trials.

The concept of big data can be hard to pin down – how would you define it? Per Nymand-Andersen: Big data can be defined as a source of information and intelligence resulting from the recording of operations, or from the combination of such records. There are many examples of recorded operations – records of supermarket purchases, robot and sensor information in production processes, satellite sensors, images, as well as behaviour, event and opinion-driven records from search engines, including information from social media and speech recognition tools. The list seems endless, with more and more information becoming public and digital as a result – for example, the use of credit and debit payments, trading and settlement platforms, and housing, health, education and work-related records. Should central banks take advantage of big data?

Rather than being fearful of AI replacing human jobs, companies are starting to embrace automation for a more intelligent way of working and providing the highest level of client satisfaction. Below we will explore the different ways in which smart technology has already been or is on its way to being implemented within the property industry. Problems within rented buildings are a constant source of complaint and burden, to which the human element of a property manager also contributes. Things don't always go wrong between the working hours of 9–6, and waiting for something to get fixed till the next working day may be a problem of the past. Companies such as UK-based Pi Labs are already implementing an AI messaging platform called AskPorter to help residents in apartments have issues within their buildings or inquiries they may have solved quickly and efficiently.

Traditional and new-school retailers alike are using AI and robotics to automate various parts of the retail chain, from manufacturing to last-mile delivery. Retail is under pressure to crack the AI code. After all, corporations in every industry are scrambling to adapt and integrate artificial intelligence into their products -- and retail is no exception. Learn how Walmart, Amazon, Sephora, Zara, and other retailers are using AI to reinvent the brick-and-mortar store. For traditional retail giants, this means entering the playing field with the likes of e-commerce behemoths Amazon and Alibaba, both of which are leveraging big data and powerful AI algorithms to transform the retail space. In addition to fierce competition, the need for a change in strategy is being underscored by the record rates at which many US retailers are shutting down. In 2017 alone, 21 retail chains applied for bankruptcy, including high-profile names like RadioShack, Toys R' Us, and Aerosoles.

Video Friday is your weekly selection of awesome robotics videos, collected by your Automaton bloggers. We'll also be posting a weekly calendar of upcoming robotics events for the next few months; here's what we have so far (send us your events!): Let us know if you have suggestions for next week, and enjoy today's videos. Only try this at home on April 1. You might remember the Flowbee hair cutting vacuum device from commercials back in the late 1980s.

Amazon has been working on its voice-enabled virtual assistant, Alexa, for years. It's how the company's Fire TV, its Echo smart speakers, and other Amazon devices are able to answer our questions--and know what we want. While we know Alexa is always listening, how does she think? And how much of what she hears does she "remember?" He's been at Amazon since 2004 and has led the Alexa team since 2011. In our interview, we discussed how Alexa understands our commands, what he makes of users' growing concerns over privacy, and why Alexa was laughing so creepily for some users recently.

The European Union says that Facebook has told it that up to 2.7 million people in the 28-nation bloc may have been victim of improper data sharing involving political data-mining firm Cambridge Analytica. Now the EU says that it will ask the data protection authorities in its various countries to work together and investigate the site for the abuse of data. As the data sharing scandal has spread, estimates of the number of people caught up in it have increased. This week, Facebook said that at least 87 million people across the world had been affected by it. Many of those people are outside of Europe.

It has become clear that AI will affect us all and that there are three main areas to take action in artificial intelligence. Whether you believe, like Stephen Hawking, that it is likely to be humanity's last invention, and the one that abolishes us, or that it will dominate the world, as Vladimir Putin has said, there is no question that things are changing, and we should all be trying to find out more. I spoke to Andreas Gödde at SAS, responsible for presales in the DACH region. Andreas, why is everyone so worried about AI? Whenever people are confronted with big changes, they are always going to be worried. Something known is being replaced by something unknown.

Bottom line: Machine learning algorithms, applications, and platforms are helping manufacturers find new business models, fine-tune product quality, and optimise manufacturing operations to the shop floor level. Manufacturers care most about finding new ways to grow, excel at product quality while still being able to take on short lead-time production runs from customers. New business models often bring the paradox of new product lines that strain existing ERP, CRM and PLM systems by the need always to improve time-to-customer performance. New products are proliferating in manufacturing today, and delivery windows are tightening. Manufacturers are turning to machine learning to improve the end-to-end performance of their operations and find a performance-based solution to this paradox.

New technologies are often touted as the solutions to our problems, as well as decried as the cause of all manner of social ills. We are told that increasing automation of jobs will mean more of us spending less time working, with ever greater responsibility handed over to software, sensors and the cloud. This week we visited some experimental projects that could offer a glimpse of our future, to see how people are grappling with the possibilities and problems of technological innovation. Reducing our working hours, while ensuring sufficient pay and essential services, is often floated as the best model for boosting productivity. It is also a seemingly inevitable byproduct of the rise of the robot worker.