While artificial intelligence promises to create actionable insights for clinicians to make better care decisions for patients, the regulations and standards for evaluating AI-based algorithms are lacking. Writing in the February 22 issue of the journal Science, they make the case that evaluations of AI-based algorithms are not held to traditional clinical trial standards--and, as a result, there has been little prospective evidence that predictive analytics improve patient care. "Several commercial algorithms have received regulatory approval for broad clinical use. But the barrier for entry of new advanced algorithms has been low," charge the authors. "To unlock the potential of advanced analytics while protecting patient safety, regulatory and professional bodies should ensure that advanced algorithms meet accepted standards of clinical benefit, just as they do for clinical therapeutics and predictive biomarkers."

The core business of healthcare organizations is to care for the medical needs of patients. Yet information security is a key component of any healthcare organization. There are electronic healthcare records (EHRs) and HIPAA privacy regulations, both of which make your average hospital or big healthcare practice an enticing target for hackers looking to steal data. "We are attacked about a million times a day," said Jennings Aske, chief information security officer at NewYork-Presbyterian Hospital. Aske joined the organization in 2015 to create a cyber security strategy for the organization, and he used platforms from Splunk which he said was "basically a security analytics platform."

In its latest annual report, filed with the Securities and Exchange Commission, tech giant Alphabet warned investors against the many challenges of artificial intelligence, following the lead of Microsoft, which issued similar warnings last August. Recent advances in deep learning and neural networks have created much hope about the possibilities that AI presents to various domains that were previously thought to be off the limits for computer software. But there's also concern about new threats AI will pose to different fields, especially where bad decisions can have very destructive results. We've already seen some of these threats manifest themselves in various ways, including biased algorithms, AI-based forgery and the spread of fake news during important events such as elections. The past few years have seen the development of a growing discussion around building trust in artificial intelligence and creating safeguards that prevent abuse and malicious behavior of AI models.

SAN DIEGO--A novel smartphone app that uses artificial intelligence (AI)-based algorithms significantly reduced pain and pain-related hospital admissions in a group of patients with various metastatic, solid-organ cancers, according to results from a randomized clinical trial reported at the 2018 Palliative and Supportive Care in Oncology Symposium sponsored by ASCO (Abstract 76). The ePAL is a smartphone app that regularly monitors pain and uses AI to differentiate urgent from non-urgent issues in real time. It also collects and assesses patient-reported pain severity three times each day while providing daily tips on pain-reduction strategies. It is one of the first apps to utilize both patient-reported outcomes and AI clinical algorithms, according to the researchers. The app was developed and tested in 56 pain patients and a matched group of 56 control patients who received regular pain management care by investigators at the Massachusetts General Hospital (MGH) Cancer Center, the hospital's Division of Palliative Care, and Partners HealthCare Pivot Labs, which is a new center of excellence that focuses on human-centered preventive care and chronic pain management.

What eventually becomes cutting-edge in retail and payments often originates in places that are dedicated to security, not commerce. New technology often starts out at the U.S. Department of Defense (DOD) or NATO, for instance. Former Israeli intelligence agents or military members have taken the knowledge they gained during their service and contributed to artificial intelligence (AI), fraud prevention and other efforts that do make -- or can end up making -- a difference in the daily lives of consumers. Now, the time might be right to at least consider adding prisons to that mix. Let's not get ahead of ourselves -- there is little chance that any prison system will become a miniature Silicon Valley.

A recent decision by research lab OpenAI to limit the release of a new algorithm has caused controversy in the AI community. The nonprofit said it decided not to share the full version of the program, a text-generation algorithm named GPT-2, due to concerns over "malicious applications." But many AI researchers have criticized the decision, accusing the lab of exaggerating the danger posed by the work and inadvertently stoking "mass hysteria" about AI in the process. The debate has been wide-ranging and sometimes contentious. It even turned into a bit of a meme among AI researchers, who joked that they've had an amazing breakthrough in the lab, but the results were too dangerous to share at the moment.

Reported by the New York Times, new tests of facial recognition technology suggest that Amazon's system has more difficulty identifying the gender of female and darker-skinned faces compared with similar facial recognition technology services provided by IBM and Microsoft. Amazon's Rekognition is a software application that sets out to identify specific facial features by comparing similarities in a large volume of photographs. The study is of importance, given that Amazon has been marketing its facial recognition technology to police departments and federal agencies, presenting the technology as an additional tool to aid those tasked with law enforcement to identify suspects more rapidly. This tendency has been challenged by the American Civil Liberties Union (See: "Orlando begins testing Amazon's facial recognition in public"). The new study comes from Inioluwa Deborah Raji (University of Toronto) and Joy Buolamwini (Massachusetts Institute of Technology) and it is titled "Actionable Auditing: Investigating the Impact of Publicly Naming Biased Performance Results of Commercial AI Products."

Smart assistants could come with a'moral AI' to decide whether to report their owners for breaking the law. That's the suggestion by academics at the University of Bergen, Norway, who touted the idea at the ACM conference on Artificial Intelligence, Ethics and Society in Hawaii. They suggest that domestic bots such as Amazon Echo and Google Home should be enhanced with moral AI. This would enable them to weigh-up whether to report illegal activity to the police, effectively putting millions of people under constant surveillance. Marija Slavkovik, Associate Professor the Department of Information Science and Media Studies, led the research behind the idea.

A lot has been said, and much has been discussed about the upcoming effects of GDPR – like how the organization is collecting the data and in what other ways they are making use of the data, and many more discussions are ongoing. Amongst these, all machine learning has become a key player and has gained traction amongst prominent role across organizations, and a key question is emerging and mystifying amongst regulators, researchers and lawyers alike; How will the GDPR impact on machine learning applications? If you are actively living on this planet, then I am pretty sure that you must have heard about the Facebook and Cambridge Analytica Scandal and Mark's statement on Facebook is making in response to European Union's GDPR – General Data Protection Regulation. If you do not belong to Europe, then you would have heard the statement from U.S. Senator Brain Schatz that all the technology partners, as well as platforms, will adopt the EU approach for data protection. GDPR is indeed a big deal, and since it has become a law in the European Union, it has undeniably improved the data protection for EU citizens and the people around the world.

The European Council adopted last 18 Febreary conclusions on the Coordinated Plan on the development and use of Artificial Intelligence Made in Europe.