All posts by Rowan Byrne

[Un]hyping AI

This article previously appeared in Healthcare Business Today.  Check it out here.

Artificial intelligence has been one of the most important — and perhaps most jarring — technological advances of the 21st century. Lines of code have been trained to drive cars, detect faces, and decode complex radiological images, and the recent explosion of AI utilizations has created a jagged divide in societal perception. On the one hand, there are those who fear the robot apocalypse, with entrepreneur Elon Musk himself claiming that “AI is a fundamental risk to the existence of civilization.” Conversely, there are those who overzealously point to AI as a panacea, a cure-all for everything from weight loss to higher education.

Yet despite these prodigious claims, the marketing hype around today’s AI seems to be, in many ways, surpassing reality. A brief interaction with Apple’s Siri, for example, reveals how easily the clever programming can be fooled, or how often it tends to be completely inaccurate. And IBM’s supercomputer Watson, while impressive, is less magic than manual labour. In a recent STAT article, one reporter noted that although Watson can digest massive amounts of data, “its treatment recommendations are not based on its own insights…. Instead, they are based exclusively on training by human overseers, who laboriously feed Watson information.”

Marketing hype is dangerous, both for AI technology itself and for the humans that could benefit from it. Beyond just risking a complete misunderstanding, overhyping AI imperils its very progress — much like what occurred in the “AI winter” of the 1970s and 1980s, during which the technology had been so sensationalized that, when it could not fulfill every unfeasible expectation, it was met with a period of deep disenchantment that resulted in a lack of popularity, funding, and technological advancement.

Once again, AI finds itself reaching the end of the second stage of the Gartner Hype Cycle, the peak of inflated expectation — and if we’re not careful, it may slope back into what Gartner calls “the trough of disillusionment,” prompting yet another lack of public interest and capital investment.

To avoid the pit, it’s important to properly understand AI and its limitations so that we may use it more effectively in areas where AI particularly excels. Artificial intelligence essentially allows machines to “learn” from experience and adjust to new inputs, in order to accomplish tasks by synthesizing enormous amounts of data and analyzing that data to find patterns. While it’s true that AI can accomplish a variety of tasks more efficiently than us — due to a machine’s ability to store and compute far more data than a single human mind (or even a team of human minds) — it does have its limitations.

For instance, deep learning, one of the more complicated branches of AI, mimics the human mind by utilizing an artificial neural network, wherein layers of mathematically simulated neurons are trained to respond to certain inputs. This method of training, known as supervised learning, is not automatic — it requires varying degrees of attention from engineers, who feed pieces of information into a machine (such as IBM’s Watson) until the machine is able to draw out the most likely conclusion from those data.

Additionally, AI is unable — as of yet — to handle abstract reasoning. Manually-trained programs comb through historical data in order to construct patterns upon which they can make predictions. Although these programs are exceedingly useful when solving problems of categorization, they possess no true understanding in the way that a human does.

Acknowledging AI’s limitations has not impeded its progress — in fact, it’s quite the opposite. Companies from a broad range of fields have been effectively utilizing AI not in spite of its limitations, but because they have found ways to capitalize on them. Currently, FICO uses neural networks to predict fraudulent banking transactions, a process that involves high-volumes of data that are exceedingly arduous to manually sift through. The agricultural industry is also benefiting from AI, with companies using autonomous robotics, machine vision, and predictive analytics to reduce labor costs and maintain soil and crop health. In education, AI is already assisting teachers with menial tasks such as grading and has even proven useful in tutoring students. And in healthcare, Watson Paths, a research collaboration with the Cleveland Clinic designed to assist medical professionals, enables “a more natural interaction between physicians, data and electronic medical records.” Designed to mimic the decision-making process physicians use when diagnosing, the software doesn’t need to be manually programmed to find the correct answer, and it has been so successful that it’s currently being used to teach med students.

Viewing AI either as a catalyst for the apocalypse or as a panacea of all of mankind’s difficulties is a hindrance to further advancement in the field. We at Aspire Ventures take full advantage of the benefits of AI, weaving adaptive, personalized algorithms into all of our technologies in order to glean the most valuable outcomes. Only by understanding both the capabilities and limitations of these very technologies can we unlock their true potential.

Watch: Smart Health Innovation Lab Grand Opening

As a venture lab that deals regularly with healthcare startups, we at Aspire Ventures understand how healthcare silos can stymie new technologies by creating a sluggish and unpredictable path to market adoption, even after the product has been tested and is market ready.

The Smart Health Innovation Lab brings together healthcare providers, insurers, and tech entrepreneurs in order to expedite integration, help health technologies gain faster market adoption and payor reimbursement, and transform healthcare. The lab, of which we are a founding member, recently opened its doors to its first class of residents, and the grand opening event was an enormous success, drawing excitement not only from attendees, but also from both regional and national news outlets.

Check out the video from the event below.

How We Plan to Broaden the Impact of Precision Medicine

Last week, we announced the launch of the Aspire Ventures Precision Medicine Fund (AVP), a $300 million fund co-managed with Penn Medicine Lancaster General Health (LG Health) to fast-track precision medicine ventures and practices that transform care with AI and IoT. Together with LG Health we’ve seeded the fund with $30 million cash and in-kind investment and will be fundraising for the remainder over the next two years. We believe precision medicine is the future of healthcare, and we’re excited to be working with a top-tier partner to accelerate its realization.

Precision medicine matches each individual with the right treatment according to their unique biochemistry, genetics, environment, and lifestyle, instead of offering one-size-fits-all solutions for the “average” patient. This approach could have profound impacts on cost, experience, and outcomes in a healthcare system that today is wasteful, slow, and expensive. By some counts, more than $1 trillion of U.S. healthcare spending is wasted every year, 40 percent of which can be attributed to unnecessary treatments, and another 12% to medical errors. Imagine if we could eliminate that waste while making treatments more effective.

Precision medicine has been gaining a lot of momentum recently, and it’s no surprise — already it has had an exciting impact on both clinical research and patient care. Since the Obama administration launched the Precision Medicine Initiative in January 2015, the notion of precision medicine has expanded from next generation gene sequencing and pharmacogenomics to a much broader definition that has attracted a lot more investment. In fact, the global precision medicine market is expected to reach $141 billion in just eight years, driving an enormous uptick in research and development.

For precision medicine to be successful, it must address not only genetic data, but also account for other health variables, such as environmental factors, clinical narratives, or behavior analyses — essentially, it must rely on comprehensive data regarding the whole person. The challenge in doing so is that without the right technological tools, collecting and analyzing comprehensive data for each patient is often cost-prohibitive.

That’s why artificial intelligence (AI) and the Internet of Things (IoT) play a key role in the realization of a practical, scalable approach to precision medicine that can be used not only to monitor cancer treatments and tame the human genome, but also to assist the larger population with a wide variety of health conditions.

Data Power

Technology like IoT makes it possible to acquire both the quantity and quality of data needed to effectively broaden the scope of precision medicine. There is a growing number of data collection devices, from consumer-level fitness trackers to Continuous Glucose Monitors and portable EEGs, that monitor a patient’s condition constantly, aiding physicians in making more accurate diagnoses. There are also a variety of apps and wearables that can help patients to manage their diet, record their medications, and monitor their own mental health status. Yet the benefits of these devices do more than merely assist patients in managing their own health — they can provide physicians the data they need for individualized treatments and even extend to the emergency room.

AI Efficiency

One of the major hurdles precision medicine solutions face is finding a way to create individualized solutions that can be scaled affordably. To that end, AI plays a vital role in achieving cost-effectiveness and lowering healthcare costs overall. In pharmaceuticals alone, AI data mining algorithms have made it faster and easier to obtain and organize large quantities of accurate information, thereby decreasing the cost of drug development and replication. Finding significant patterns and making meaningful use of massive data sets to provide personalized treatments for every patient is a nearly impossible task for humans alone. However, sifting through data is precisely the type of work that artificial intelligence can do quickly and cheaply.

The Aspire Ventures Precision Medicine Fund

The Aspire Ventures Precision Medicine Fund will focus investments on devices and practices that leverage AI and IoT to overcome precision medicine’s scalability challenges and maximize impact on population health. Aspire and LG Health will also help to fast-track technologies by contributing technological and clinical expertise along with intellectual property like health system data and Aspire’s proprietary adaptive artificial intelligence platform, A2I.

A big part of the cost related to precision medicine solutions stems from the time, resources, and risk it takes to fully develop, deploy, and integrate health technologies into health systems. Our fund’s unique structure helps ventures overcome these challenges by leveraging an ecosystem of strategic partnerships that accelerate each step of the venture development process — from ideation, to clinical trials, to FDA approval, to market adoption, to insurance reimbursement. In this way we can maximize our capital efficiency and rapidly advance new precision medicine technologies to market that will have the broadest possible impact.

For more information about our precision medicine fund, check out a few of the articles in the links below.

Silicon Valley Exodus

Last month, The New York Times published a story on the growing discontent among innovators in Silicon Valley and their search for greener pastures elsewhere. Although it’s probably an overstatement to say that “Silicon Valley is Over” — as the NYT sensationally wrote in the headline of their story — the case for leaving the Valley is becoming more compelling than ever, and it appears that some entrepreneurs and investors are catching on.

The idea that true innovation can’t succeed outside of Silicon Valley has become accepted as the holy truth. To be sure, the link between Silicon Valley and venture success is difficult to deny. According to a recent report, the Silicon Valley area still receives the most venture investment, accruing over $27 billion in 2015 alone, which accounts for nearly half of the total venture capital invested in the U.S. that year.

Harvard Business Review attributes the success of Silicon Valley companies to cultural qualities such as audacity, “grit,” strong leadership, collaboration, flexible work schedules, and strict attention to user-centered design. Yet these qualities are not limited to geography and can ultimately be reproduced anywhere. This realization that the Valley doesn’t have a monopoly on innovation has driven many — from high-profile investors to engineers in the field — to search out new frontiers for building the next technologies for the 21st century. But what’s wrong with the Valley?

Certainly, the most obvious answer is the cost of living. Business leaders and residents alike are increasingly buckling under longer traffic commutes, inflated property costs, and a steep housing shortage. While companies such as Facebook and Google have attempted to address the housing crisis by expanding their campuses to include low-income complexes, the move has largely been blocked so far by regulatory battles with local government and has been met with dissatisfaction from community residents who see it as an inadequate response from the culprits of the housing crunch.

The increasing pay scale has also proven difficult for employers to keep up with. Programmers and engineers might earn a median salary of $50,000 on average in the United States, but at companies in the Valley, like Facebook or Google, it could reach “triple or quadruple that amount.” As a result, many employers have expressed the desire to outsource to satellite offices in more affordable areas.

Another common complaint is the increasingly “homogenous” culture in the Bay Area. “There is a mono-conversation of tech that is near impossible to avoid,” says Tim Ferris, author and angel investor who recently relocated to Austin. Ferris and others are finding that although engineers, venture capitalists, and entrepreneurs are commonplace, little else is represented in the way of diverse employment.

There is growing dissatisfaction with a lack of intellectual diversity in what some call a “left-wing echo chamber that stifles opposing views.” Many in the Bay Area are “feeling increasingly squeezed by what they perceive to be liberal groupthink,” writes one reporter for The Guardian. This at least partly contributes to why some investors, such as Peter Thiel, have elected to leave the Valley to seek a broader range of mindsets.

Whatever the reasons, Glenn Kelman, chief executive of Seattle-based Redfin, believes that the exodus from expensive coastal cities to cheaper inland locations is actually good for the country as a whole. “You shouldn’t have that many people making so much money in just a few cities. It should spread to the rest of the country.”

Alternative tech hubs offer a way of living that lends itself to innovation. Smaller, more intimate communities tend to drive deeper support structures, breeding excitement for each new success. While much of Silicon Valley is racing to be part of a unicorn, innovators elsewhere are simply hungry to make a difference.

The allure of tech jobs in the Bay Area is still undeniably strong. But, as blockchain engineer and entrepreneur Preethi Kasireddy reminds us: “Silicon Valley is just one way of living… [T]echnology is global, engineering is global, innovation is global and entrepreneurship is global.”

4 Thought Leaders on Tech in Healthcare

Modern healthcare is continuously being shaped by big data, artificial intelligence, and a slew of other digital technologies. As these technologies mature, they will transform the patient experience by enabling personalized treatments and reduce the workload for physicians with automation, affecting everything from medical imaging, to management of chronic diseases, to primary care. Today’s thought leaders from across industries agree that technology is poised to make a huge impact on healthcare. Here are what leaders from payor systems, technology companies, and healthcare providers are saying about the latest technology in healthcare today.

On Machine Learning & Artificial Intelligence

“[D]eployed systems from our team and from AI efforts by colleagues employ machine learning and reasoning to help doctors to understand patient outcomes—in advance of poor outcomes. There’s a great deal of low-hanging fruit where even today’s AI technologies are well positioned to help. Sticking with healthcare for a bit, a recent study showed that nearly 1,000 people per day are dying in the US because of preventable errors being made in hospitals. I believe that AI technologies could be employed to provide new kinds of safety nets, via error detection, alerting, and decision support, that could save hundreds of thousands of lives per year.”

Eric Horvitz, Technical Fellow & Director at Microsoft Research Labs

On Wearables

“Thanks to technologies such as remote monitoring and telehealth, we’ll see people get a lot more care from home… [This will] offer patients greater independence, improved convenience, and new opportunities to tailor treatments to their personal needs…The technology also empowers doctors to prescribe a personalized set of tools for each individual’s needs. Patients now can manage their health at home and in the workplace, while caregivers and care coordinators are armed with critical information that can help people stay healthy.

The next step in wearables will be to make them relevant to people who wouldn’t normally use them. The opportunity lies in how wearables, big data and artificial intelligence come together to offer solutions that improve the quality of care, and how we as marketers can foster greater adoption of these tools.”

David Edelman, Chief Marketing Officer at Aetna

On Digitization & Precision Medicine

“During my conversations with customers and partners about healthcare, precision medicine and SAP’s connected health strategy continue to be top of mind. Digitization in healthcare addresses the need to run simple (by turning big data into smart data), the need to run with data (by breaking down the information silos) and the need to run in real-time (through the capacity to visualize relevant results within seconds, instead of hours).”

Dr. C. Suter Crazzolara, VP Product Manager for Health and Precision Medicine at SAP

On Big Data

“Over the last decade, there has been growing enthusiasm for data analytics as well as growing appreciation of the potential usefulness of so-called big data in transforming personal care, clinical care and public health, and related research. Both the public and private health sectors are investing in the technologies and analytical capabilities needed to unlock the full value of big data. For governments that are interested in using such data, a natural starting point is to link national health-care data sets, to facilitate in-depth analysis of the performance and utilization of health service. At the institutional level, the analysis of electronic health records map greatly expand the capacity to generate new knowledge by creating an observational evidence base to help resolve clinical questions. Analysis of big data is already proving critical in building accurate models of disease progression and providing personalized medicine in clinical practice. It has also facilitated the evaluation of the impact of health policies and improved the efficiency of clinical trials. By encouraging patients to participate in their own care, delivering personalized information and integrating medicine with behavioural determinants of health, the integration of electronic health records with personal data from other sources, e.g. medical devices, wearable devices, sensors and tools based on virtual reality, could also be very beneficial.

John Brownstein, Chief Innovation Officer at Boston Children’s Hospital

Cross-Functional Collaboration with Design Sprints

Turning great ideas into elegant, engaging solutions that people will actually want to use isn’t easy. Companies spend exorbitant amounts of time and resources creating a market-ready product, only to discover months down the road that the product isn’t user-friendly, or worse still, that it simply isn’t useful. To avoid that costly mistake, an iterative design process that favors speed, early user feedback, and collaboration are necessary ingredients for any successful venture.

A design sprint is a comprehensive tool companies can use to rapidly carry an initial design idea through prototyping and user testing in just five days. A concept originally formulated by Jake Knapp and the design team at Google Ventures, a design sprint is a condensed process that orients a team of diverse minds around a single design solution and aims their efforts at hitting clearly defined goals.

At Aspire, we use design sprints regularly to build rapid prototypes and get early feedback on the first iterations of our products. We recently conducted a design sprint, in a period of four days rather than the usual five, to develop a prototype for our venture MedStatix’s new consumer-facing doctor search app, M-Path. The app takes a new approach to the doctor search process by enabling cost transparency and leveraging MedStatix’s huge patient experience dataset to let users match with the right provider based on experience preferences, book an appointment, pay, and rate their experience, all from one tool.

The design sprint helped us build a rapid prototype without investing too many resources, and helped us gain early consumer feedback vital to future development of the product. But while user testing and time constraints are often recognized as the primary benefits to sprints, we’ve found that perhaps the most important (and often overlooked) benefit is the utilization of a diverse, cross-functional team.

Design sprints call for a group of key players from a variety of factions within the business, including executives, stakeholders, product managers, technology engineers, designers, marketers, or anyone else with a vested interest in the project. Developing a cross-functional team can dramatically speed up the design process by breaking down silos and building early consensus around a solution. A sprint strongly encourages equal participation from across the departmental spectrum, which helps to build a stronger community that’s focused on solving the problem at hand, and ensures that the project is less likely to be derailed by dissenting viewpoints in the future.

The M-path app in particular revealed the importance of involving diverse perspectives and disciplines, because the problem the app tries to solve is a complex one that involves numerous stakeholders. Building an app that appeals to doctors, everyday consumers, insurers, and hospital administrators requires a broad range of expertise. It was necessary to understand the everyday healthcare consumer’s user story; how insurance and pay structures work; how to receive buy-in from doctors; and how the intricacies of healthcare, technology, and design might work together to address the problem.

Obtaining diverse perspectives at the outset of the project allowed the entire team to benefit from access to unique, on-the-ground insights specific to the product. Instead of filling the room with designers and developers only, our M-Path sprint team members included a Human Resources manager, an accountant, two software engineers, an artist, and a creative manager.

The result of putting such a diverse group together not only led to better design results, it became an important way to build invaluable working relationships that advance the company as a whole.

“It was just a fabulous team-building experience,” says Renee Rahe, Human Resources Manager at Aspire. “It was phenomenal to see how people from completely different departments can come together to make something work. Everyone brought something to the table.”

Rahe, with over 20 years of experience in healthcare administration, was able to offer intimate insights into health insurance reimbursement models and practice-centered questions like: How will it affect people? Who will pay for it? What if it changes the workflow?

“You always want to have industry experts in the room for a project like this,” says Don Locker, one of the Aspire software engineers whose traditional knowhow helped guide the sprint to a buildable solution. “All of the resources we needed were in that room.”

Design sprints have become an integral part of our venture development process. The benefits of efficiency, early user feedback, and collaboration have revealed themselves not only with M-path, but with many of our other ventures as well — and we look forward to the progress we will make with other design sprints in the future.

HIMSS 2018 Conference

The annual Healthcare Information and Management Systems Society (HIMSS) conference — health IT’s leading exhibit — is in Las Vegas this week, and members from our Smart Health Innovation Lab are attending to take part in the national conversation on improving healthcare.

Previous HIMSS conferences have been centered around healthcare legislation reform, medical banking, and mobile health solutions, but this year the buzz has been all about artificial intelligence and its potential to transform care. Our ventures have been focused on developing new impactful AI applications in healthcare, and we have written extensively on how AI can transform care — we are happy the industry is finally catching on. HIMSS this year also focused on important themes such as interoperability, cybersecurity, analytics, and federal health IT.

“[Now] we have dense, robust algorithms, tons of data and the ability to handle it computationally,” said Pamela Peele, chief analytics officer at University of Pittsburgh Medical Center Health Plan and UPMC Enterprises, in a recent TechTarget article. “It’s the perfect storm.”

We couldn’t agree more.

Connexion Health Announces Sacramento Kings as Early Customer

Last May, we sent a group to Chicago during the NBA Combine to showcase a prototype Connexion kiosk the Aspire team had developed in a span of 6 weeks, along with its first application, Fusionetics+. Taken together, the technology generates AI-powered, touchless health screenings and personalized training programs for athletes. The result of the debut was even more positive than we had imagined.

Now, only 9 months later, Connexion is a full-fledged company and they’re winning some headline-grabbing customers. Yesterday, Connexion Health announced that the Sacramento Kings was among the first of two NBA teams that would utilize the Connexion kiosk.

“The Sacramento Kings will use Connexion to measure and analyze their players’ key physical attributes including their posture, lateral balance, and body movement, in order to prevent injuries, improve their on-court performance and fitness levels, and lengthen their playing careers,” the press release reads.

SportsTechie also published an article on the Kings announcement, lauding some of the potential benefits the kiosk can provide the team.

“Many, if not all, professional sports teams conduct regular or even daily check-ups on each athlete to gauge rest and recovery levels while checking for early signs of asymmetries or weaknesses that could lead to injury risk,” writes sports journalist Joe Lemire.  “The Connexion kiosk helps detect deviations from each player’s regular patterns.”

But this is just the beginning.  With a host of other third-party health applications already in the works, Connexion is expected to affect far more than just the sports science industry. They’re poised to transform health and wellness across a broad range of industries and are already in talks with healthcare systems, physical therapy practices, major retail companies, insurers, fitness centers, and self-insured employers. We’re thrilled to see what’s next for Connexion Health. For more information, check out their website, or follow their progress on Twitter, Facebook, and LinkedIn.