Studies suggest that relying on your smartphone heart monitor may not be the wisest move. The widespread use of smartphones to collect healthcare data has been thrown into doubt by a couple of recent studies. In some fields -- such as the management of chronic diseases and mental health monitoring smartphones have enabled a greater level of patient self-control, and personalised clinical intervention. Success in one area, however, does not imply success in all – especially as smartphone health apps are often rolled out before evidence of their effectiveness has been rigorously analysed. A major study into the use of mobile phone data as a tool for predicting clinical decisions, released in June, came to a scathing conclusion, characterising the practice as "voodoo machine learning".

The United States Air Force wants robots and service members to be best buds on the battlefield. Last Friday, the Air Force announced a grant of 7.5 million for research on ways to make humans trust artificial intelligence (AI) so that people and machines can collaborate on missions. Soon service members in every branch of the Armed Forces will be working with AI on a daily basis--be it unmanned ariel vehicles, underwater drones, or robot soldiers (the U.S. Military had to shelve the Boston Dynamic L3 "robotic mule" because it was too loud, but last week the company revealed the much stealthier SpotMini). On November 1, 2014, (one week after Elon Musk compared developing AI to "summoning the demon") Undersecretary of Defense Frank Kendall issued a memo asking the Defense Science Board to study what issues must be solved in order to expand the use of AI "across all war-fighting domains." But robotic weapons and soldiers wont be as effective if their human counterparts don't trust them.

A new study by Kevin Warwick and Huma Shah, published by Taylor & Francis, purports to uncover a flaw in the classic artificial intelligence test developed by Alan Turing. The paper summarizing their findings is called "Taking the fifth amendment in Turing's imitation game." The announcement states, "A serious problem in the Turing test for computer intelligence is exposed in a study published in the Journal of Experimental and Theoretical Artificial Intelligence. If a machine were to'take the Fifth Amendment' – that is, exercise the right to remain silent throughout the test – it could, potentially, pass the test and thus be regarded as a thinking entity, authors Kevin Warwick and Huma Shah of Coventry University argue. However, if this is the case, any silent entity could pass the test, even if it were clearly incapable of thought."

S. Somasegar is a venture partner at Madrona Venture Group and the former head of Microsoft's Developer Division. Daniel Li is an investor with Madrona Venture Group. You can hardly talk to a technology executive or developer today without talking about artificial intelligence, machine learning or bots. Madrona recently hosted a conference on ML and AI, bringing together some of the biggest technology companies and innovative startups in the Intelligent Application ecosystem. One of the key themes for the event emerged from a survey of the attendees.

With over 2 million apps in Apple's App Store, it can be hard to find the ones that suit you best. We're here to take the tedium out of your search. If you're a politics junkie, you know there are a lot of polls to keep up with in the heat of the presidential campaign. TPM (Talking Points Memo) has released an app that lets you "follow" the races you're interested in and sends a push notification to your device every time a new poll comes out. If you don't want to wait until dinner to learn the latest poll results, this app is for you.

SUMMARY: Artificial intelligence (AI) technologies offer great promise for creating new and innovative products, growing the economy, and advancing national priorities in areas such as education, mental and physical health, addressing climate change, and more. Like any transformative technology, however, AI carries risks and presents complex policy challenges along a number of different fronts. The Office of Science and Technology Policy (OSTP) is interested in developing a view of AI across all sectors for the purpose of recommending directions for research and determining challenges and opportunities in this field. The views of the American people, including stakeholders such as consumers, academic and industry researchers, private companies, and charitable foundations, are important to inform an understanding of current and future needs for AI in diverse fields. The purpose of this RFI is to solicit feedback on overarching questions in AI, including AI research and the tools, technologies, and training that are needed to answer these questions.

Machine learning is a type of artificial intelligence that allows computer programs to learn when exposed to new data without being programmed. Now, researchers in The Netherlands have coupled machine learning methods with a special MRI technique that measures the perfusion, or tissue absorption rate, of blood throughout the brain to detect early forms of dementia, such as mild cognitive impairment (MCI), according to a new study published online in the journal Radiology. "MRI can help with the diagnosis of Alzheimer's disease," said principal investigator Alle Meije Wink, Ph.D., from the VU University Medical Centre in Amsterdam. "However, the early diagnosis of Alzheimer's disease is problematic." Scientists have long known that Alzheimer's disease is a gradual process and that the brain undergoes functional changes before the structural changes associated with the disease show up on imaging results.

AI could be a game changer for securing IoT environments, an article in Forbes posits. In-brief: Artificial intelligence will be a critical ingredient as enterprises struggle to secure an exploding population of connected devices in the coming years, an article on Forbes argues. Forbes has an interesting article that looks at whether artificial intelligence might be a critical ingredient in the Internet of Things security paradigm. "Between six and 15 billion IoT devices are already connected, and the pace will only quicken. By 2020, Gartner IT 0.25% predicts we'll top 20 billion web-connected'things'. In that same year – just four years from now – Gartner expects more than 25% of enterprise security attacks will involve IoT. But currently enterprises are investing only 10% of their security budgets to deal with this growing threat."

Machine learning is a branch of artificial intelligence concerned with the design of data-driven programs which autonomously demonstrate intelligent behavior in a variety of domains. Machine learning systems are all around us. When you deposit a check, scan your fingerprint, or post a picture on social media, autonomous algorithms are deployed on the spot to sift through and make sense of your constant interactions with our technology. Machine learning silently underpins the fabric of our digital infrastructure, discriminating spam e-mail and banking fraud, making light-speed transactions in the global financial market, recommending music and films for customers to buy, deciding what search results are relevant to your queries, and countless more of the daily interactions with electronic media that we take for granted. Machine learning is the backbone that powers self-driving cars, content recommendation in social media, face identification in digital forensics, and countless other high-level tasks.

The Turing test, developed by legendary computer scientist Alan Turing and used to test the artificial intelligence of computers, has a major flaw. A new study, published in the Journal of Experimental and Theoretical Artificial Intelligence, points out that the test, which was devised in the 1950s, could be successfully passed if the computer pleaded the Fifth Amendment and remained silent. Authors Kevin Warwick and Huma Shah from Coventry University argue that a machine could plausibly pass the test by saying very little, or nothing at all. Previous attempts at defeating the Turing test have seen computers pretend to be children, but no matter how great their general knowledge, they are often unable to convince a human interacting with them (over typed messages) that they are also a human. A critical point raised by the study is how the Turing test is based around a machine being discovered as a human based on what it does wrong, rather than what it does right.