There's a chance it could bring the mood down. Having chosen your shiny new driverless car, only one question remains on the order form: whether your spangly, futuristic vehicle be willing to kill you? To buyers more accustomed to talking models and colours, the query might sound untoward. But for manufacturers of autonomous vehicles (AVs), the dilemma it poses is real. If a driverless car is about to hit a pedestrian, should it swerve and risk killing its occupants?

In catch-22 traffic emergencies where there are only two deadly options, people generally want a self-driving vehicle to, for example, avoid a group of pedestrians and instead slam itself and its passengers into a wall, a new study says. But they would rather not be travelling in a car designed to do that. The findings of the study, released on Thursday in the journal Science, highlight just how difficult it may be for auto companies to market those cars to a public that tends to contradict itself. Related: Statistically, self-driving cars are about to kill someone. "People want to live a world in which everybody owns driverless cars that minimize casualties, but they want their own car to protect them at all costs," Iyad Rahwan, a co-author of the study and a professor at MIT, said.

Self-driving car technology is advancing at a rapid pace, thanks to work by technology and automotive companies ranging from Google to Ford. While still years from being widely adopted, driverless cars are increasingly capable of handling a wide variety of driving conditions. With the basic technical hurdles out of the way, driverless car experts now face a different set of problems -- namely, ethical issues. Among the most pressing questions: What should a driverless car do if it faces a choice between putting its passengers at risk or harming someone outside the vehicle? New research reveals that people are conflicted about such a dilemma.

Would you buy a driverless car that is programmed to kill you? Ok, how about a car programmed to kill you if it's the only way to avoid plowing into a crowd of dozens? That's one of the conundrums an international group of researchers put to 2,000 US residents through six online surveys. The questions varied the number of people that would be sacrificed or saved in each instance--if you want to try it for yourself, see if you'd make a good martyr here. The study, just published in the journal Science is the latest attempt to answer ethics' classic "trolley problem"--forcing you to choose between saving one life and saving many more.

Self-driving cars have a lot of learning to do before they can replace the roughly 250 million vehicles on U.S. roads today. They need to know how to navigate when their pre-programmed maps are out of date. They need to know how to visualize the lane dividers on a street that's covered with snow. And, if the situation arises, they'll need to know whether it's better to mow down a group of pedestrians or spare their lives by steering off the road, killing all passengers onboard. Once self-driving cars are logging serious miles, they're sure to find themselves in situations where an accident is unavoidable.

The FBI has access to nearly 412 million facial photos in its facial recognition system--perhaps including the one on your driver's license. But according to a new government watchdog report, the bureau doesn't know how error-prone the system is, or whether it enhances or hinders investigations. Since 2011, the bureau has quietly been using this system to compare new images, such as those taken from surveillance cameras, against a large set of photos to look for a match. That set of existing images is not limited to the FBI's own database, which includes some 30 million photos. The bureau also has access to face recognition systems used by law enforcement agencies in 16 different states, and it can tap into databases from the Department of State and the Department of Defense.

Dublin-based Text and Image Analysis startup, AYLIEN, is looking to hire Research Fellows, Postdoctoral Researchers and Lecturers to conduct novel and significant research in the fields of Artificial Intelligence, Machine Learning and Natural Language Processing. This is a unique opportunity to work with a team of talented Scientists and Engineers at AYLIEN to push the boundaries of AI research. Please send a brief introduction about yourself, your CV and links to GitHub, Google Scholar, papers and articles if applicable to jobs@aylien.com AYLIEN is a leading Text and Image Analysis solution provider in Europe, helping tens of thousands of developers and data scientists in more than 500 cities globally to extract meaning and insights from unstructured data, such as news articles, social media updates and customer reviews. We are a team of 13 people spread across Science, Engineering and Sales & Marketing, based near the beautiful River Liffey in the heart of Dublin.

As part of a strategic initiative for large for-profit and non-profit organizations, Microsoft has included data science as a key component of the "Data Insights" initiative. Key technologies also associated with this initiative are now bundled and presented as "Cortana Intelligence". This presentation will cover how you can learn more about the key elements of Cortana Intelligence (a subset of Azure), and highlight the already-known elements for data science. Independent of Microsoft, this talk makes the case for why any data science solution beyond a single computer would want to include the types of elements within Cortana Intelligence. Mark Tabladillo is a specialist in data science and analytics.

University of Skövde is seeking a post-doc in machine learning for a project where the main application scenario will be text analytics. The post-doc will have an unique opportunity to develop new machine learning algorithms, e.g., from the field of deep learning, to detect and predict how text flows from the internet evolve over time based on over 700 000 different sources on the open web (through an API provided by our partner company Recorded Future). The post-doc will be affiliated with the Skövde Artificial Intelligence Lab (SAIL), which is one of the oldest and most prominent research groups in artificial intelligence (AI) in Sweden. At the University of Skövde Informatics is defined as the science that addresses how information is represented, processed and communicated in artificial and natural systems, and how such systems are used and developed in order to achieve usable and effective applications and solutions for individuals, organizations or society. The post-doc is positioned at the School of Informatics, which is a school in expansion.

WIRE)--Ipswitch, the leader in easy to try, buy and use IT management software, today announced the findings of an independent global study, carried out by analyst firm Freeform Dynamics. The survey examines the attitudes and readiness of IT decision makers with regard to intelligent machines and business systems (machines with decision making and learning capabilities). Exploring the fast-paced adoption of these systems, the report looks at the positive impacts already being observed in the commercial world and the potential barriers to even further mainstream adoption over the next decade. According to the research, investment in intelligent business systems and automation is well underway across the globe. Top current application deployment areas cited by respondents include digital customer engagement systems (55 percent), process automation and workflow systems (52 percent) and automated risk monitoring and management solutions (50 percent).