Mobile phone technology has progressed at an astonishing pace, with advanced technologies like fingerprint scanners and artificial intelligence now becoming a common sight on handsets. Yet it appears we're a stickler for tradition, with alarm clocks and maps topping out in a list of our favourite smartphone features in a survey by uSwitch. In a study of 2,000 UK adults, 42% cited GPS technology – used for map and navigation apps – as the most useful feature on their phone. This came above even mobile messaging apps such as Facebook and WhatsApp, which ranked highest with 36% of respondents. Alarm clock apps – which have largely replaced clock radios to become the default method for getting us out of bed every morning – were considered the most useful mobile phone feature by 35% of UK adults.

Artificial intelligence can predict better than real doctors when patients with serious heart disorders are likely to die. That's according to a paper published this week in Radiology. A team of medics and computer scientists, led by the MRC London Institute of Medical Sciences (LMS) at Imperial College London, created what is claimed to be the first computer program that uses machine learning to study heart disease. Pulmonary hypertension, a condition that increases the level of pressure exerted on the arteries that supply oxygen to the lungs, is dangerous if left untreated. It affects up to 7,000 people in the UK, and a third of patients die of heart failure within five years of diagnosis.

Artificial intelligence that can understand and answer any work-related question it is asked has been made available in the UK for the first time. The computer software, called Starmind, uses machine learning to understand queries, then source answers from previous staff conversations on a subject or track down experts within the company who are able to help. Its creators refer to it as'brain technology', adding its aim is to become a central knowledge bank within any company, an instant database of information that can be accessed by anyone. AI software which understands and answers work-related questions has been made available in the UK. Starmind is an artificial intelligence software for the workplace, designed in Switzerland.

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The development of problem solvers for configuration tasks is one of the most successful and mature application areas of artificial intelligence. The provision of tailored products, services, and systems requires efficient engineering and design processes where configurators play a crucial role. For more than 25 years the application of constraint-based methods has proven to be a key technology in order to realize configurators at Siemens. This article summarizes the main aspects and insights we have gained looking back over this period.

Spoken dialog researchers have recently demonstrated highly-interactive systems in several domains. This paper considers how to build on these advances to make systems more robust, easier to develop, and more scientifically significant. We identify key challenges whose solution would lead to improvements in dialog systems and beyond.

One particular challenge is to ground human language to robot internal representation of the physical world. Although copresent in a shared environment, humans and robots have mismatched capabilities in reasoning, perception, and action. A robot not only needs to incorporate collaborative effort from human partners to better connect human language to its own representation, but also needs to make extra collaborative effort to communicate its representation in language that humans can understand. This article gives a brief introduction to this research effort and discusses several collaborative approaches to grounding language to perception and action.

The Association for the Advancement of Artificial Intelligence, in cooperation with Stanford University's Department of Computer Science, presented the 2016 Spring Symposium Series on Monday through Wednesday, March 21-23, 2016 at Stanford University. The titles of the seven symposia were (1) AI and the Mitigation of Human Error: Anomalies, Team Metrics and Thermodynamics; (2) Challenges and Opportunities in Multiagent Learning for the Real World (3) Enabling Computing Research in Socially Intelligent Human-Robot Interaction: A Community-Driven Modular Research Platform; (4) Ethical and Moral Considerations in Non-Human Agents; (5) Intelligent Systems for Supporting Distributed Human Teamwork; (6) Observational Studies through Social Media and Other Human-Generated Content, and (7) Well-Being Computing: AI Meets Health and Happiness Science.

The 29th International Florida Artificial Intelligence Research Society Conference (FLAIRS-29) was held May 16-18, 2016, at the Hilton Key Largo Resort in Key Largo, Florida, USA. The conference events included invited speakers, special tracks, and presentations of papers, posters, and awards. The conference chair was Bill Eberle from Tennessee Technological University. The special track were coordinated by Vasile Rus from University of Memphis.

This issue of AI Magazine brings together a collection of articles on challenges, mechanisms, and research progress in turn-taking and coordination between humans and machines.