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Many consumers look at their car insurance choices and see an MC Escher drawing of mazes leading into the unknown. Using advanced artificial intelligence, however, Insurify is streamlining the historically convoluted process. Winner of the 2016 ACORD Insurance Innovation Challenge Startup Disruptor, the company has wowed industry traditionalists and customers alike with its reinvention of the client experience.

Entrepreneurs have attempted to tackle the insurance industry before, but no new venture in this space has taken off as robustly as Insurify. “Insurance—the industry that nobody wanted to touch for generations—is now super hot,” says Snejina Zacharia, SF ’13, founder and CEO. “Because it’s a data-driven industry, it can be transformed by the inspired use of artificial intelligence.”

Only four-years old, the company is now the largest insurance marketplace in the US, growing profitably with two million customers and a 42% increase in closed policies month after month. Its virtual insurance agent uses AI and natural language processing to simplify the shopping experience, creating a virtual insurance agent who delivers a quote in under three minutes—by far, the fastest tool in the industry.

Zacharia and her team opted not to develop an app, given the infrequency with which people make decisions about insurance. Instead, customers simply text a photo of their license plate and converse with a well-informed bot. Messaging is personal and asynchronous. Consumers can initiate and complete the transaction while watching television or waiting in line for take-out.

Educating robots to become super agents

Insurify has partnered with the largest agencies in the country and is available in 48 states. Its bots are able to quote 102 insurance carriers in real time with more than 800 agents working on the platform. The advanced recommendation engine helps customers select the best coverage for their needs given their personal risk profiles.

Insurify’s mobile-first platform is powered by advanced analytics that continuously optimize the user experience. That platform is the work of a remarkably adept and experienced team, which includes key talent from top tech companies. Cofounder Giorgos Zacharia, for example, holds a handful of MIT degrees and was the chief technology officer at Kayak.

“The goal of this technical dream team,” says Zacharia, “is to educate our robots so well that they can take—and ace—the insurance licensing exam. Basically, we are developing the brain of a super agent, a super agent who is getting smarter every day.”

Read more about Insurify in Disruptor Daily.

The post Navigating the car insurance maze appeared first on Leadership Blog.

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More women are entering science and tech-related fields than ever before, but the number occupying the executive suite still lags far behind men. The Massachusetts Life Sciences Center (MLSC) and Takeda Pharmaceuticals have launched a new initiative to help right the balance. MassNextGen is a five-year program that will fund and support early stage biotech companies run by women.

A recent report by the Massachusetts Biotechnology Council (MassBio) and the executive recruiting firm Liftstream found growing gender disparities in the state’s life-sciences industry. The report integrated the responses of 70 companies and more than 900 professionals and revealed that while women enter the industry in equal proportion to men, their numbers decline in the early stages of their careers. As a result, they account for just 24 percent of C-suite executives in biotech—the gap is even greater at the board level. Between 2011 and 2013, only 15% of the companies receiving venture capital investment included a woman on the executive team.

A support system for women founders and leaders

The cause of this disparity? The report notes fewer opportunities to advance, a perceived bias in evaluations and promotions, and a paucity of opportunities for mentoring and career development. Jennifer Griffin, Vice President for Industry Programs and Relations at MLSP, says MassNextGen will “encourage and support more women entrepreneurs in the life sciences industry and provide them with the skills, the tools, and the network they need to go out and successfully raise funds for their small, innovative companies.”

Seed stage money is the hardest for women executives to come by. Only 3% of the total venture capital dollars in the U.S. went to companies with a woman CEO, according to “Women Entrepreneurs 2014: Bridging the Gender Gap in Venture Capital,” a report produced by Babson College in 2014. To address this issue, MassNextGen will support annually two women-owned companies with $50,000 and executive coaching that will include mentoring and access to a network of entrepreneurs, investors, and industry experts.

Catalyst for change

Takeda was the first private partner to support the program. The pharma giant provided $250,000 in support to match MLSC’s $250,000. “It’s one initiative,” Takeda CEO Christophe Weber noted at the launch of the initiative, “but it creates some visibility and allows us to express our willingness to improve the situation.”

Griffin’s intention is that MassNextGen will prove to be a catalyst for change over time. “We’re targeting young entrepreneurs, but certainly those women entrepreneurs will someday become board members of larger companies and advise those companies.”

MassNextGen begins taking applications in early 2018.

The post Boosting the ranks of women in biotech appeared first on Leadership Blog.

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What are the stumbling blocks of blockchain? How can AI strengthen cybersecurity?  Are cryptocurrencies the future of the marketplace? Members of the MIT Sloan faculty bring in-depth discussion of these pivotal fintech issues—and a good many more—to Buenos Aires at the end of this month. The MIT Sloan Latin America Office in collaboration with the Institute for Business Development of Argentina (IDEA) will hold a summit called “Transforming the Fintech Revolution” at the Hilton Buenos Aires on Tuesday, May 29.

The all-day conference will spotlight emerging trends in financial technology and examine how fintech inventions are turning global commerce upside down. MIT Sloan Professor of Applied Economics, Roberto Rigobon, faculty director of the MIT Sloan Latin American Office, has been a key force in organizing the event. “Over the past decade,” he says, “fintech has emerged as one of the fastest-growing sectors in the technology industry and today is at the forefront of innovation.” The goal of the conference, he added, is to “shine a light on the promise of fintech to lead to more transparent, secure, and inclusive financial services for millions around the world.”

Rigobon and his team expect the conference to draw hundreds of business leaders, policymakers, regulators, academics, and entrepreneurs from across Latin America. The event will include presentations and workshops led by leading economists, computer scientists, and development experts. The faculty contingent from MIT includes Rigobon, applied economics professor Tavneet Suri, engineering professor Silvio Micali, information engineering professor John Williams, and Christian Catalini from MIT Sloan’s Technological Innovation, Entrepreneurship, and Strategic Management (TIES) Program.

The evolution of fintech

The conference, Rigobon says, will showcase “the most current and cutting-edge fintech applications and charts a course for its future evolution in Latin America and beyond.” Fintech, he notes, “is about using technology to solve pressing financial problems. This includes everything from helping investors make better decisions on where to put their money, to employing data analytics to drive business efficiency, to accelerating entrepreneurship through blockchain, to expanding the use of mobile payments in the developing world to make the economic system more fair.”

Transforming the Fintech Revolution’s packed agenda includes such topics as Cyber Security and The Future Web; AI Applied Now; Fintech and Argentina; Some Simple Economics of Blockchain; Digital Finance and Economic Lives in Africa; Fintech and Financial Regulation; Why Blockchain is the Key for Financial Inclusion; and Fin Tech: Solving the Macro Development Problems.

Learn more about the conference or register.

Read about the conference.

The post MIT Sloan conference in Buenos Aires explores fintech advances appeared first on Leadership Blog.

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According to the National Kidney Foundation, thirteen people die every day while awaiting a kidney transplant. More than 3,000 new patients are added to the waiting list every month—a new name every 14 minutes. But the length of the waiting list and the insufficient supply aren’t the only issues in those deaths. The entire system is slowed by a time-consuming decision-making process that relies on individual discernment. “Who might be best suited to this kidney?” “Is this kidney the best possible match?” “Will a better match be coming in the next few months?”

Dimitris Bertsimas

Dimitris Bertsimas, the Boeing Leaders for Global Operations Professor of Management and the co-director of the MIT Sloan Operations Research Center, is cutting through red tape with an elegant algorithm designed to streamline the waiting list process, getting the right kidney to the right recipient in the shortest amount of time. In a new paper, he and MIT Sloan Assistant Professor of Operations Management Nikos Trichakis describe a pioneering model that applies machine-learning to historical data about all kidney transplants over the last decade to guide future donations.

Nikos Trichakis

At present, when a kidney is offered to a wait-listed candidate, the decision to accept or decline the organ relies primarily upon a surgeon’s experience and intuition. The physician might take into consideration the location and condition of the kidney. And might there be a higher-quality kidney or a better match available in the future? The authors maintain that the current experience-based paradigm lacks scientific rigor and is subject to the inaccuracies that plague anecdotal decision-making. As a result, as many as 20% of all kidneys obtained are discarded as unsuitable—when, in fact, they might well have been the best option.

Bertsimas’ and Trichakis’ data-driven analytics-based model predicts whether a patient will receive an offer for a deceased-donor kidney at KDPI thresholds of 0.2, 0.4, and 0.6, and at time frames of 3, 6, and 12 months. The model accounts for OPO, blood group, wait time, DR antigens, and prior offer history to provide accurate and personalized predictions. They tested datasets spanning various lengths of time to understand the adaptability of the method.

The pair is working with surgeons at Massachusetts General Hospital to create a support tool that leverages their model. They hope to give surgeons a reality check about kidneys, providing them with hard evidence of whether they can realistically expect a better donation if they decline a kidney—ultimately reducing the number of kidneys that are discarded because physicians are pessimistic about the match.

Find out more about their research.

Read the abstract.

The post Kidney-matching by algorithm appeared first on Leadership Blog.

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MIT Sloan Leadership Blog by Deepashree Patil - 2M ago

Erik Brynjolfsson, Schussel Family Professor of Management and director of the MIT Initiative on the Digital Economy, and Andrew McAfee, principle research scientist at the MIT Center for Digital Business, urge us to move beyond questions of what technology will do to us and instead ask: What do we want to do with technology? What matters more than ever before, they say, is thinking deeply about what we want the future to be. Having more choices means that our values are more important than ever.

The post Test 4-24-2018 appeared first on Leadership Blog.

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Fredric Abramson, SF ’77, has an extensive background in genetics, biology, entrepreneurship, and the law. All paths converge at his most recent startup, Digital Nutrition, which is using AI and genetics to revolutionize the concept of illness prevention.

Abramson is building Digital Nutrition, still in its startup phase, to be a $100 million-dollar-business that taps the very latest genetic science and technology to promote wellness and wellbeing. “With advanced AI and machine learning analytics,” he says, “we can deliver genetic data tools that will improve the life of anyone who uses our app.”

The idea: shape preventive health behavior with DNA-based personal nutrition feedback using a simple phone app. Well, maybe not so simple—at least in what’s behind the firewall—but the app itself, as Abramson’s team is creating it, will be second nature for the consumer. “The world is moving more and more toward personalization, and that’s not going to change—nor should it. Digital Nutrition is the ultimate in personalization. It puts consumers in touch with their genetic roots and coaches them on how to make choices based on that information.”

The mobile app is designed to be a sort of digital nutritionist, allowing users to identify the foods and supplements that are optimal for their own genetic makeups based on a simple swab DNA test. They will be able to scan bar codes from food, beverage, or supplement packages and receive an instant AI-generated score that reflects how well the ingredients match their genetic profile in terms of metabolism, physiology, and neurology.

A very personal nutrition app

What will set this platform apart is the science behind the app’s affable interface. Digital Nutrition will tap the massive amount of published genetic science to map areas where genetic data can have a positive impact on a user’s quality of life. “In effect, we are using technology to deliver deep science to the average person. The app will be an exceptionally brainy weight-loss coach, fitness guru, and counselor rolled into one. Eventually, as the Digital Nutrition app is adopted on a global scale, we envision that the marketplace will respond by developing nutritional products that work in concert with it, strengthening and broadening its ability to serve consumers.”

The company is actually a business unit of Abramson’s other enterprise AlphaGenics, the first bio-consumer company to exclusively use non-medical genetic data to provide lifestyle solutions. The field has been a driving interest of Abramson’s for nearly two decades. In 2002, he was the sole U.S. representative invited to participate in the European Union’s first framework meeting on nutrigenomics.

Digital Nutrition will allow consumers on a much larger scale to leverage their genetic blueprint for optimal health. “We’re talking about a low-cost scalable app that can improve the nutritional and health status of people worldwide, including populations in developing economies,” Abramson says. “It’s time we employ science to deliver better health, wellness, and wellbeing for everyone on this planet. That goal is just a DNA app away from reality.”

The post Eat–or shun–that apple pie? Check your DNA appeared first on Leadership Blog.

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Companies that know how to harness machine learning and artificial intelligence are clear winners in the 21st century economy. And, arguably, few companies on Earth rival Google for its ingenuity in unlocking their powers. Suzanne Frey, SF ’06, Director of Security, Trust, and Privacy at Google, says, in fact, that every area in which Google is advancing relies on the progress of AI and ML.

DeepMind

Frey says that a game-changer was Google’s 2014 acquisition of the London-based AI pioneer DeepMind. Now a world leader in artificial intelligence research, DeepMind is developing programs that can learn to solve complex problems without necessarily needing to be taught how. Working closely with subject experts, DeepMind researchers are building tools that augment advances in fields such as healthcare and energy. And, of course, it’s tapping its late-breaking knowledge to enhance Google’s own products and services.

Frey says that DeepMind’s capabilities were best demonstrated recently on the virtual playing field. “The work we’ve done with DeepMind really went big when we won a pivotal GO match against the #1 champion in the world, an accomplishment that most thought was a decade out on the computer science horizon.” Big deal…just a game? Frey explains why not. “In winning that match, DeepMind illustrated the ability to run an exceptional number of deeply complex scenarios in parallel, at scale, and select the best outcome. And that capability is applicable to so many domains—the biosciences, in particular, allowing biotech researchers to do drug testing and create genetic scenarios at scale without testing on animals. Bottom line: the implications of that winning game of GO could have enormous positive impacts on society.”

Productivity apps

As a time-challenged tech executive, Frey is understandably somewhat obsessed with time-saving apps. “My twin passions for AI and time collide heavily at Google. Anything that saves time and optimizes energy is important. Google, she says, is using AI to create a suite of indispensable apps like Smart Reply in Gmail, which offers you quick responses to choose from so that you don’t have to compose a message from scratch. Another app will note a meeting on your calendar and queue up related documents in preparation. All these little inventions, Frey says, can save a minute here, five minutes there, minutes that add up by the end of a given day. “Nothing is more precious than time; just think about the total area under the curve saved by each of these features, and I’m excited to say that there’s much more time savings to come.”

Voice-activated searches

On the educational horizon, Frey reports that Google’s search functions have advanced to such an extent that a Google search is almost akin to having a research assistant. Google Scholar helps students find relevant resources across the world of academic research, pulling in articles, theses, books, and abstracts from publishers, universities, professional societies, and other online repositories. Google Scholar ranks documents the way researchers do, weighing the full text of each document, where it was published, who it was written by, as well as how often and how recently it has been cited in other scholarly literature. “The quality of the search,” Frey points out, “is directly correlated to the quality of the AI.”

Google Home Assistant

“Hey, Google. Is Johnny’s Pie in the Sky open? Order me a pizza with pepperoni and mushrooms. And tell me how to get there. Is it on Front Street?” Frey gives this example of a series of tasks that Google Home Assistant could handle for someone returning home from a stressful workday. Again, she says, it’s about conserving that most valuable of all commodities—time. And as the AI becomes more sophisticated, so does the Home Assistant. “One of the most exciting developments in voice-assisted searches is that the ‘trail of thought’ problem has been solved,” Frey says. “We’re teaching AI to realize that your prior query is related to your next query. It understands the pronouns within a string of questions. After you asked if the restaurant was open and you followed it with the phrase ‘How do I get there?’ the Home Assistant knows that you’re asking how to get to the restaurant, even though you haven’t specifically used those words.”

The Home Assistant, Frey says, is an illustration of Google’s intention to reposition itself as a personal assistant rather than a comparatively aloof search function. “There is no part of Google that isn’t directly investing in machine learning and AI,” Frey says. “It’s all connected to our mission to move from searching to assisting. It’s a thrilling space to be working in right now, even in security and data protection, and I’m enjoying every minute of it.

The post Deep mind thinking about AI and ML appeared first on Leadership Blog.

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How much artificial intelligence (AI) can you pack into a Manhattan apartment? How much could it improve your life? When digital expert Pieter Nel, SF ’14, moved into his new place in 2017, he decided to find out. His Amazon Alexa is now fully networked with the space, and he controls everything from the lights to the Roomba vacuum cleaner with voice commands. “The technology has come a long way,” Nel says, “but it still has a long way to go. Don’t get me wrong. I’m glad I don’t have to do the vacuuming myself, but voice-command capability right now feels more like a novelty than a revolutionary time- or labor-saving feature.”

Nel spent several years as a COO and strategic advisor in the social media and social networking space before joining McKinsey & Company in 2017. “I moved on from the social networking sector because I felt I was doing more to help people waste an hour a day than to solve real problems,” explains Nel. “These platforms were envisioned as tools for enhancing exchanges among people, but mostly they have made our interactions more shallow.”

Nel believes that AI has enormous potential to transform the way we live, but certain pitfalls and distractions lie in wait. “AI could go the way of social media,” he says. “If it’s easier to talk to your virtual assistant than to another human being in a pub, we could end up more isolated from one another. We need great resolve and expertise to make AI productive in people’s lives and in society as a whole.”

Wikipedia plus-plus

If you’re eagerly anticipating your first sophisticated conversation with a robot, Nel says not to get your hopes up. “I ask my Amazon assistant to give me a flash briefing every morning, but we can’t have what most of us would consider an intelligent exchange. The technology isn’t smart enough or fast enough to genuinely converse, and it’s possible that voice interfaces will never be as quick as a Google search.”

The strength of the technology is its ability to process an immense amount of data related to any given topic rather than to replicate human traits. “When you combine massive information crunching with the distinct learning capabilities of AI, you get Wikipedia plus-plus,” he says. Not only will we be able to call up answers to any number of esoteric questions, personalized learning will take a giant leap forward. “Because AI will deduce what you already know, it should be able to customize your course of study in any area of interest,” says Nel. “Every 12-year-old in the world with a high-speed internet connection and a desire to learn will have a personal digital tutor with unlimited capacity to guide curiosity-driven knowledge acquisition.”

Gaining—and preserving—trust

The ability of technology providers to respect and protect privacy will make or break the future of these innovations, Nel says. “To reap the potentially profound benefits of AI in areas such as education and healthcare, public users must be willing to reveal a great deal of confidential information to networked machines.”

Nel believes that encryption technology is up to the task as long as the incentives to prevent breaches exist. “Right now, however, bad actors don’t suffer any real consequences,” he says. “And big social networking platforms such as Facebook pay only enough attention to privacy protection as is absolutely necessary to satisfy the typical user. Most companies’ energies are devoted to growth and market penetration. Security breaches are more of a public relations problem than a business catastrophe.”

Proceed with caution, Nel says, but definitely proceed. If we go forward with full knowledge of the pitfalls of AI, we may well be able to avoid at least a few of them.

Pieter Nel contributed to the recent McKinsey Quarterly article “What AI can and cannot do (yet) for your business.”

The post The light and shade of AI appeared first on Leadership Blog.

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Erik Brynjolfsson, Schussel Family Professor of Management and director of the MIT Initiative on the Digital Economy, and Andrew McAfee, principle research scientist at the MIT Center for Digital Business, urge us to move beyond questions of what technology will do to us and instead ask: What do we want to do with technology? What matters more than ever before, they say, is thinking deeply about what we want the future to be. Having more choices means that our values are more important than ever.

In their celebrated 2017 book Machine, Platform, Crowd: Harnessing Our Digital Future, the duo firmly expresses optimism about the future benefits of artificial intelligence for the way we live. Not because that outcome is predestined, but because the technology at our disposal is more powerful than ever before. “Fundamentally, we have more freedom to do things that simply could not have been done by earlier generations. Rather than being locked into any one future, we have a greater ability to shape the future,” they say.

The AI in our lives

McAfee and Brynjolfsson take particular interest in the growth of virtualization and its long-term implications for how we live. Virtualization—as distinct from full automation—refers to processes in which digital technologies play leading roles but do not completely exclude people. Automated teller machines (ATMs) and self-checkout retail kiosks are examples of virtualized processes that many of us interact with routinely.

“Virtualization accelerates when networks and convenient digital devices are almost everywhere,” say McAfee and Brynjolfsson. The success of virtualized banking, for example, is made clear by the fact that the total number of bank tellers in the U.S. has decreased by almost 20% since its peak in 2007. And despite the so far underwhelming performance of self-checkout technologies, McAfee and Brynjolfsson predict large-scale adoption in the future. “When it does come, it might look like Amazon Go, an 1,800-square-foot convenience store…with neither cashiers nor self-checkout kiosks.” The store’s environment integrates cameras, sensors, machine-learning technologies, and a smartphone app to track and bill for whatever customers carry out of the store.

Eatsa, the virtualized restaurant concept launched in San Francisco in 2015, and Wealthfront, an AI-driven wealth management company founded in 2011, demonstrate other areas in which automation may change the way many of us conduct our lives. And while Eatsa hasn’t fulfilled expectations quite yet, Wealthfront has attracted more than $3 billion from 35,000+ households since 2011 using a platform of robo-advisers and online forms in place of brick-and-mortar locations and human professionals.

Although McAfee and Brynjolfsson acknowledge that self-selection by patrons and clients has been a key driver for these companies, they also assert that experimentation, iteration, and technical progress will expand automated and digitally mediated processes beyond the market of younger, more tech-savvy consumers. “We believe, in short, that virtualization is a secular trend, where ‘secular’ is used in the way the finance industry uses it: to denote a long-term development that will unfold over several years.”

Stay tuned, McAfee and Brynjolfsson tell us. Life in an AI world is about to get more interesting—and very probably better.

The post What do we [really] want from technology? appeared first on Leadership Blog.

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When we suspend our fears and fantasies of robotic minds replicating or surpassing our own, we increase the likelihood of turning the differences between human intelligence (HI) and AI into productive collaborations. The resulting whole could be much greater than the sum of the parts—a whole that offers a compelling counterpoint to the zero-sum scenarios many technology pessimists envision.

The revolutionary Live Parts™ software in development at Desktop Metal may foreshadow ways in which we will relate to artificial intelligence in a variety of settings. “AI can process ideas for functional parts in ways that humans can’t,” explains Desktop Metal CEO and company cofounder Ric Fulop SF ’06. “Our vision for Live Parts™ is to allow engineers and manufacturers to efficiently capitalize on the full potential of additive manufacturing, including material and cost efficiencies and immense design flexibility.”

Live Parts™ is just one of a collection of ingenious technology solutions emerging from the young company, which was founded in 2015 to address a challenge—how to make 3D printing in metal accessible to engineering teams. Back in 2013, Fulop began collaborating with global experts in materials science, engineering, and 3D printing. Over the course of two years, those collaborations generated multiple inventions that now define Desktop Metal’s printing frontier.

Technology inspired by nature

Desktop Metal’s experimental technology auto-generates part designs in minutes using morphogenetic principles and advanced simulation. “Because Live Parts is driven by nature-inspired algorithms, a part can grow and adapt like a plant or bone without a pre-existing design,” Fulop says. “Components change shape in real time to find the best form for their environment and function. Humans define forces, constraints, and load conditions—linear, radial, rotational, and dynamic—and view the progress in visual simulations.”

Fulop expects his company’s new technology to change the way metal products are designed. Clearly, the tech world agrees. Popular Science just named Desktop Metal’s production system “2017 Best of What’s New” in the engineering category. The magazine’s coveted awards honor “innovations that shape the future, from life-saving technology…to gadgets that are just breathtakingly cool.” Desktop Metal qualifies on both counts. The company was also selected as one of the world’s 30 most promising technology pioneers by the World Economic Forum and was recently named to MIT Technology Review’s list of the “50 Smartest Companies.”

The use of the artificial intelligence in Desktop Metal’s Live Parts™ is tantalizing when considered as a template for how humans can interact with machines going forward. With that frame of reference, we can understand AI as different and complementary—rather than superior to—human intelligence. And with that understanding, we can begin to view robots not as servants or masters but as collaborators in myriad areas of our lives.

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