My father was an accountant, and in 1965, he decided to explore the emerging field of information technology (IT). He joined an IBM training program and went to work selling their System 360 mainframe computers. That year's model would set you back $2-3 million, for which you got a room full of refrigerator-sized cabinets supporting a central processor with about a megabyte of memory. These machines were used by businesses to automate accounting, and for billing and tracking inventory. Looking back these tasks now seem simple, straightforward, even trivial, but at the time these capabilities were revolutionary, automating tasks that took people enormous amounts of time and effort. What does this reflection have to do with applying artificial intelligence and machine learning (AI/ML) to healthcare?

On 1st October 2019, the UKRI Centre for Doctoral Training in Artificial Intelligence for Healthcare opens its doors to their first cohort. The United Kingdom Research and Innovation Centre for Doctoral Training in Artificial Intelligence for Healthcare (AI4Health) will open its doors to the first cohort of PhD students in October. Director Dr Aldo Faisal and the whole AI4Health Team are looking forward to getting started and turning vision into practice. Imperial College London understand the term "AI" as meaning the development of intelligent systems that embody a practical solution. However, practical solutions involving AI will require a broader approach and the College will drive technical innovation by providing broad training for exploitation of multiple technological strategies within the broader realm of AI.

What a rough few weeks it's been for AI and healthcare. In just the last ten days, we've seen the publication of a number of commentaries that collectively express a significant degree of caution, if not outright concern, about the extravagant expectations around the application of AI to healthcare and drug discovery. Let's start with the two peer-reviewed publications, both in the journal Digital Medicine. The first DM paper centers around "The'inconvenient truth' about AI in healthcare" – basically, the disconnect between promising research algorithms and the activity of frontline clinicians. In addition, Panch is the CMO of the company Wellframe, Mattie is affilitated with Welframe, and Celi is also associated with MIT.) Panch et al argue the disconnect stems from two factors: The authors highlight the potential of cloud computing, and argue the opportunity to benefit from this capability is thwarted by EMRs.

Keeping all of this in mind, let's take a step back and examine AI for what it is: a powerful technology that can play a role in improving individual and population health when implemented judiciously. In the wrong hands, it's clear that AI tools could be misused, but with the right strategies and careful use of AI aligned with an organization's goals, AI can be used to generate insights based on data and analytics that may have been otherwise missed. AI has the potential to improve the quality of care and reduce cost by preventing unnecessary tests and procedures, while accelerating diagnoses and improving access by better utilizing resources. In the current healthcare climate, adding value while improving patient outcomes and access is not only a stated goal but also an imperative for survival of health systems in the emerging value-based integrated care environment.

AI and Healthcare is a peer-reviewed academic journal providing a forum for technological advancements in healthcare. Its mission is to accelerate analysis and discussion on the improvement of health and health care through the application of artificial intelligence technology. The inaugural issue will be launched in mid-2019. AI and Healthcare seeks to disseminate original research, analyses, surveys, and perspectives. The journal focuses on the technologies and healthcare topics listed below, but welcomes all topic submissions. For questions and comments, please contact hello@aiandhealthcare.org

From hospital care to clinical research, drug development and insurance, AI applications are revolutionizing how the health sector works to reduce spending and improve patient outcomes. The total public and private sector investment in healthcare AI is stunning: All told, it is expected to reach $6.6 billion by 2021, according to some estimates. Even more staggering, Accenture predicts that the top AI applications may result in annual savings of $150 billion by 2026. These benefits will accrue incrementally, from automated operations, precision surgery, and preventive medical intervention (thanks to predictive diagnostics), but within a decade they will fundamentally reshape the healthcare landscape as we know it. "It's going to take years to get the full promise, but it does bring a particular tool into the dialogue that was never before available," says Kaveh Safavi, head of Accenture's global health practice.

The use of artificial intelligence (AI) in healthcare is finally becoming a reality. According to CB Insights, from 2012 to 2017 more than $2 billion was invested specifically in healthcare AI with companies that leverage machine learning algorithms. Additionally, technology giants Apple, Microsoft and Google are investigating entering the healthcare market, and Amazon's secret health tech team 1492 is exploring a platform for electronic medical record data, telemedicine and health apps. You're not quite going to find doctor Amazon Alexa diagnosing patients in homes – yet, but we are excited by the many advancements in AI to help detect diseases earlier and analyze vast data streams to identify risks and outcomes. AI in this capacity can truly change the healthcare delivery and diagnosis model in the future.

The use of artificial intelligence (AI) in healthcare is finally becoming a reality. According to CB Insights, from 2012 to 2017 more than $2 billion was invested specifically in healthcare AI with companies that leverage machine learning algorithms. Additionally, technology giants Apple, Microsoft and Google are investigating entering the healthcare market, and Amazons secret health tech team 1492 is exploring a platform for electronic medical record data, telemedicine and health apps.

Because artificial intelligence (AI) has become so buzzy, and applied so indiscriminately–AI for pot, AI for beer brewing, AI for horse care, AI for sex ed (all examples courtesy of CB Insights)–it's easy to dismiss as just another passing trend, like slap bracelets, Fitbits or a dignified presidency. I get pitched at least two companies per day claiming to have AI. I always ask them, "Tell me what AI is," and they have yet to say the same thing. I have not seen one [product] that is truly learning or is truly intelligent. That's the bear view, and fairly representative of how many in healthcare see AI–just the latest bright, shiny object that's unlikely to meaningfully impact their daily work.

Earlier this year I was fortunate to once again participate in one of Arc Fusion's Jeffersonian-style dinner talks, this time with a constellation of tech and design luminaries, such as Ray Kurzweil (Google), Lorie Fiber (IBM Watson), Paul Saffo (Stanford), and Bruce MacGregor (IDEO). Arc Fusion's mission is to convene top scientists, entrepreneurs, investors, engineers, artists, and doers to explore the frontiers of health, IT, and biomedicine. This "recipe for dialogue" worked incredibly well, and the overall tone of conversation was very positive, focusing on the potential power and impact of exponential information technologies. Led by insights from Ray Kurzweil, who has exhaustively studied the growth curves of various digital technologies, we discussed how the next two or three "doublings" of computing power are about to unleash completely astonishing breakthroughs--including the possibility of extending the human lifespan indefinitely. Even before these coming leaps in computing power arrive, we're already seeing some of the ways in which artificial intelligence (AI) has impacted healthcare, as cloud-based systems, such as IBM Watson, turn their vast computing power on fast-moving fields like oncology: It's clear that AI appears poised to increase patient safety, drive early prevention by predictive modeling, and, eventually, maybe even extend human lifespans to unimaginable lengths.