In the last several weeks, FDA Commissioner Scott Gottlieb has commented on artificial intelligence and the future of medicine. For nearly a decade, many visionaries and innovators in medicine have believed this to be the case. Finally, the FDA is getting on board by creating an internal data science incubator, called Information Exchange and Data Transformation, or INFORMED. Already this year, the FDA has approved a clinical support software that uses AI algorithms to detect changes in brain function that can alert neurologists much faster than traditional technologies. In addition, the agency also approved an AI-based tool that uses a camera to detect diabetic retinopathy -- a condition that can lead to blindness if not detected and treated early.

The federal government spends as much as $90 billion a year on information technology, but much of that money is wasted on maintaining costly and duplicative legacy systems that are often 10 to 20 years out of date, according to critics on both sides of the aisle. One reason is a lack of funds for modernizing the government's massive technology infrastructure. But another reason is the highly fragmented system that many agencies have traditionally used to oversee their IT. For example, many agencies have numerous chief information officers, not just one, to run their IT. Those CIOs often don't report to agency heads or coordinate effectively, and they sometimes have little incentive or authority to implement comprehensive modernization plans, administration officials said.

How do you spell the future of government IT? While that's not going to get you too many points on the triple word score in Scrabble, the technology and applications will unscramble massive dividends in cost savings, service enhancements, and breakthroughs. Gail Thomas, vice president U.S. public sector, and Kimberly Nelson, executive director state and local government solutions at Microsoft tipped over their AI, IoT, and blockchain toy box of applications running in the Azure cloud for us last month–and it's anything but child's play. Microsoft is building advanced tech services into its cloud offering to help new and disruptive application development partners accelerate into the government space. Let's start with the challenges in managing child adoption–a problem that's been accentuated by the opioid crisis.

Many of you have probably been to France, considering that it's the most visited country in the world. While you were there, you may have noticed that the country is quite large – about the size of Texas, but with far fewer Mexicans. Like Texans, the French are proud of where they come from, and will ramble on about it in their funny little accents much to the chagrin of anyone within earshot. This sense of national pride is what made our article on "The Top-10 French Artificial Intelligence Startups" quite popular, and as we promised, we're going to follow up with an article on some French AI startups in healthcare. None of the top French AI companies we wrote about last month came from the healthcare sector, which happens to be the cornerstone of Monsieur Macron's $1.8 billion AI investment program over the next four years.

The Ontario government will fund the 5-year project with a grant in amount of $3.2M. Jacobs, ON, Canada), as the industrial partner of Kimia Lab, will contribute $500k to the project. The company is the only Canadian manufacturer of digital scanners for pathology. Four professors from the University of Waterloo (Mark Crowley, Ali Ghodsi, Oleg Mikhailovich, and Hamid Tizhoosh), together with the machine learning group at the University of Guelph led by professor Graham Taylor (Vector Institute), and professor Shahryar Rahnamayan (UOIT) will collaborate with three hospitals to design and test an advanced search engine for large pathology archives. Grand River Hospital (Kitchener, ON), Southlake Regional Health Centre (Newmarket, ON) and University of Pittsburgh Medical Center (PA, USA) will not only provide data but also validate the results of the project.

South Korea will invest 2.2 trillion won (US$2 billion) in developing core artificial intelligence (AI) technology over five years with the aim of becoming a global powerhouse in the sector by 2022, the ICT ministry said Tuesday. Under the plan announced by the Ministry of Science and ICT, the South Korean government will spearhead a national program on AI, including research and development (R&D), to join the list of world powers. "The government believes obtaining AI core technologies by joining hands with private corporations will not only achieve global standard but eventually nurture talented people and quality jobs," Chang Byung-gyu, the head of a presidential committee to spearhead the fourth industrial revolution, told reporters in Seoul. "We aim to reach the global top four by 2022." The government said it aims to indigenously develop technologies on par with counterparts, led by the United States and China, and eventually reduce dependence on them.

On December 31, 2015, I published my original call to arms for society's rational regulation of artificial intelligence before it is too late. I explained certain reasons why someone who is against solving problems through regulation would propose precisely that mechanism to help hedge the threats created by AI, and announced my proposed legislation: The Artificial Intelligence Data Protection Act (AIDPA). Since 2015, we have witnessed AI's rapidly evolving national and international growth and adoption that will soon impact every phase of mankind's life, from birth to death, sex to religion, politics to war, education to emotion, jobs to unemployment. Three of many recent developments confirm why now is the time for the AIDPA: (1) a McKinsey study from late 2017 determined that up to 800 million workers worldwide may lose their jobs to AI by 2030, half of contemporary work functions could be automated by 2055 and other recent studies suggest as many as 47 percent of U.S. jobs could be threatened by automation or AI over the next few decades; (2) AI has now created IP with little or no human involvement and continues to be programmed, tested and used to do so; see my Twitter for a library of media reports on AI-created IP; (3) tech giants and regulators are starting to acknowledge that industries that create and use AI should be at least partially responsible for minimizing the impact of AI-displaced workers. Now – and not later -- society must address AI's legal, economic and social implications with regard to IP and employment.

The Tesla Autopilot system was engaged when a Tesla Model S sedan was crushed as it rammed into a stopped truck at 60 MPH in Utah last week, the driver has told police. The driver luckily escaped with only a broken foot, though the car suffered extensive damage. When interviewed by police, the Tesla's 28-year-old driver "said that she had been using the'Autopilot' feature," and was looking at her phone shortly before the accident in South Jordan, near Salt Lake City, according to a statement Monday from South Jordan Police Sgt. Winkler told The Deseret News that the diver, who hasn't been identified by police, had entered an address into the car's GPS and was looking on her phone for possible alternate routes. She "looked up just as the accident was about to happen," he said.

In the history of driverless cars, the Defense Advanced Research Projects Agency's 2004 and 2005 Grand Challenges contributed to improving the tech to the point of viability. The government could play a similar role in the development of artificial intelligence, said Jack Clark, the director of Open AI, at an April 18 congressional hearing focusing on government's role in artificial intelligence. DARPA's 2016 Cyber Grand Challenge concentrated on autonomous systems and is a model other agencies can adopt, Clark said during a hearing of the House Oversight's Subcommittee on Information Technology "Every single agency has … problems it's going to encounter, and it has competitions that it can create to spur innovation, so it's not one single moonshot, it's a whole bunch of them," he told lawmakers during the hearing. "I think every part of government can contribute here." This is the third hearing this subcommittee has held on AI.

The continual increase in security threats combined with an overwhelming amount of data and false positives is creating major headaches for IT security teams. Additionally, the cybersecurity industry faces a colossal shortage of talent, making it nearly impossible to stay on top of the latest threats. According to data from ESG research, 12 percent of enterprise organizations have already deployed AI-based security analytics extensively, while another 27 percent have deployed AI-based security analytics on a more limited basis. The relationship between AI and Machine Learning (ML) is often poorly articulated. Artificial Intelligence is simply concerned with causing machines to perform tasks characteristic of human intelligence. And ML is simply a way in which that AI can be achieved.