Health insurers and providers are increasingly using machine learning to flag the subset of patients likely to rack up the most costly …

Health systems are using machine learning to predict which patients will have the highest health care costs.

Once feared as a job-erasing technology devoid of clinical nuance, autonomous artificial intelligence in medicine is growing up.

Recent surveys, studies, forecasts and other quantitative assessments of the impact and progress of AI highlighted the strong state of AI surveillance worldwide, the lack of adherence to common privacy principles in companies' data privacy statement, the growing adoption of AI by global businesses, and the perception of AI as a major risk by institutional investors. Using just the first fifteen minutes of a patient's raw electrocardiogram (ECG) signal, the tool produces a score that places patients into different risk categories. Patients in the top quartile were nearly seven times more likely to die of cardiovascular death when compared to the low-risk group in the bottom quartile. U.S. AI and machine learning startups raised $6.62 billion so far in 2019, and international startups raised $6.79 in the same period. The global total for all of 2018 was $19.5 billion [Crunchbase News] The North America AI chip market is estimated to reach $30.62 billion in 2027, up from $2.5 billion in 2018 [ResearchAndMarkets] The Asia Pacific AI chip market is estimated to reach $22.27 billion in 2027, up from $1.03 billion in 2018 [ResearchAndMarkets] "An AI-equipped surveillance camera would be not a mere recording device, but could be made into something closer to an automated police officer"--Edward Snowden "When you get into the millions, you can really start to generate the levels at which humans stop understanding the correlations, and the machines start to understand the correlations"--Ricky Knox, co-founder and CEO, Tandem Bank "As AI gets better at performing the routine tasks traditionally done by humans, only the hardest ones will be left for us to do. But wrestling with only difficult decisions all day long is stressful and unpleasant"--Fred Benenson, former vice president of data, Kickstarter "AI can do things previously unimaginable with the volume, velocity, variety and veracity of big data. It can deliver an edge given the information intensity of all of the processes in asset management"--Amin Rajan, CEO, Create-Research "By 2025, a quarter of all miles driven will be driven by on-demand services"--Amy Wyron, vice president of business solutions, Gett

Recent surveys, studies, forecasts and other quantitative assessments of the impact and progress of AI highlighted the need to retrain many workers, improving AI's score from F to A on 8th-grade science exam, and the $97.9 billion the AI market will reach in 2023. In the next three years, as many as 120 million workers in the world's 12 largest economies may need to be retrained or reskilled as a result of AI and intelligent automation; only 41% of CEOs surveyed say that they have the people, skills and resources required to execute their business strategies; the time it takes to close a skills gap through training has increased from 3 days on average in 2014 to 36 days in 2018 [IBM] Top drivers for investing in robotics and automation: Reduced cost (80%), improved quality (55%), increased productivity (54%), improved capabilities of robots (54%). L'Oréal's recruiters believe they saved 200 hours of time to hire 80 interns out of a pool of 12,000 candidates, using a chatbot that saves significant time in the early stages of the recruiting process by handling questions from candidates, and Seedlink, AI software that assesses their responses to open-ended interview questions [Forbes]

Recent surveys, studies, forecasts and other quantitative assessments of the impact and progress of AI highlighted the need to retrain many workers, improving AI's score from F to A on 8th-grade science exam, and the $97.9 billion the AI market will reach in 2023. In the next three years, as many as 120 million workers in the world's 12 largest economies may need to be retrained or reskilled as a result of AI and intelligent automation; only 41% of CEOs surveyed say that they have the people, skills and resources required to execute their business strategies; the time it takes to close a skills gap through training has increased from 3 days on average in 2014 to 36 days in 2018 [IBM] Top drivers for investing in robotics and automation: Reduced cost (80%), improved quality (55%), increased productivity (54%), improved capabilities of robots (54%). "I was at MIT for another fifteen years after I graduated…twenty years after I went and asked to do my bachelor's thesis [with Victor Zue on speech recognition], Siri comes out… twenty years ago, we [wanted to] have a device where you can talk to it and it gives you answers and twenty years later there it was. So, that, for me, that was a cue that maybe it's time to go where the action is, which was in companies that were building these things. Once you have a large company like Microsoft or Google throwing their resources behind these hard problems, then you can't compete when you're in academia for that space. You know, you have to move on to something harder and more far out… So, I joined Microsoft to work on Cortana…"--T.J. Hazen The worldwide market for AI systems will reach $97.9 billion in 2023, up from $37.5 billion in 2019.

The recent surveys, studies, forecasts and other quantitative assessments of the health and progress of AI found that Americans are evenly divided over its promise or peril while not entirely sure what it is; that they are increasingly unhappy with technology companies that develop AI; that psychiatrists don't see AI replacing them but ad copywriters may want to consider other vocations; that the data that feeds and nourish AI keeps getting into the wrong hands; and that AI may assist radiologists, cardiologists, and fast-food chains. Glass half full? 50% of American consumers feel "optimistic and informed" about AI while the other half feel "fearful and uninformed" about AI [Blumberg Capital surveys of 1,000 U.S. consumers aged 18 ] Do you trust AI? 67% of Americans believe that self-driving cars will be safer than human-operated cars; 44% say that if a self-driving Uber car picked them up, they would get in; 87% say a licensed driver should be behind the wheel ready to take control if needed; 35% say they would never drive in a self-driving car [DriversED.com Do you trust the companies that develop AI? Only 50% of Americans believe technology companies have a positive impact on their country, down from 71% four years ago. Negative views of technology companies' impact on the U.S. have nearly doubled during this period, from 17% to 33% [Pew Research Center phone survey of 1,502 adults July 2019] AI may not replace psychiatrists: Only 3.8% of 791 psychiatrists surveyed in 22 countries felt that AI/ML was likely to replace a human clinician for providing empathetic care; documenting (e.g.

The recent surveys, studies, forecasts and other quantitative assessments of the health and progress of AI estimated the impact on productivity of human-machine collaboration, the number of jobs that could be automated in major U.S. cities, and the size of the future AI in retail and healthcare markets; and found AI optimism among the general population, algorithms outperforming (again) pathologists, and that our very limited understanding of how our brains learn may improve machine learning. Do you think securing your devices and personal data will become more or less complicated over the next 12 months? DeepMind has developed a machine learning model that can label most animals at Tanzania's Serengeti National Park at least as well as humans while shortening the process by up to 9 months (it normally takes up to a year for volunteers to return labeled photos) [Engadget] In a simulation, biological learning algorithms outperformed state-of-the-art optimal learning curves in supervised learning of feedforward networks, indicating "the potency of neurobiological mechanisms" and opening "opportunities for developing a superior class of deep learning algorithms" [Scientific Reports] The AI in retail market is estimated to reach $4.3 billion by 2024 [P&S Intelligence] [e.g., Nike acquires Celect, August 6, 2019] The AI in healthcare market is estimated to reach $12.2 billion by 2023 [Market Research Future] [e.g., BlueDot has raised $7 million in Series A funding, August 7, 2019] AI companies funded in the last 3 months: 417 for total funding of $8.7 billion Data is eating the world quote of the week: "Although it is fashionable to say that we are producing more data than ever, the reality is that we always produced data, we just didn't know how to capture it in useful ways"--Subbarao Kambhampati, Arizona State University AI is eating the world quote of the week: "We advocate for a new perspective for designing benchmarks for measuring progress in AI. Unlike past decades where the community constructed a static benchmark dataset to work on for the next decade or two, we propose that future benchmarks should dynamically evolve together with the evolving state-of-the-art"--Keisuke Sakaguchi, Ronan Le Bras, Chandra Bhagavatula, Yejin Choi, Allen Institute for Artificial Intelligence and the University of Washington

Do not go gentle into that good night, Old age should burn and rave at close of day; Rage, rage against the dying of the light. Welsh poet Dylan Thomas' famous lines are a passionate plea to fight against the inevitability of death. While the sentiment is poetic, the reality is far more prosaic. We are all going to die someday at a time and place that will likely remain a mystery to us until the very end. Researchers are now applying artificial intelligence, particularly machine learning and computer vision, to predict when someone may die.

IBM's artificial intelligence software, Watson, isn't ready to replace your doctor just yet. Medical experts working with the tech giant on its Watson for Oncology system discovered that it made'often inaccurate' and'unsafe' treatment recommendations, according to internal documents reviewed by Stat News. However, no patients were reportedly harmed despite Watson's missteps. Medical experts working with IBMon its Watson for Oncology system discovered that it made'often inaccurate' and'unsafe' treatment recommendations, internal documents showed The documents were included in two presentations given in June and July 2017 by IBM Watson's former deputy health chief Andrew Norden. In one case, a 65-year-old patient was diagnosed with lung cancer and said he had developed severe bleeding.