Future of Work

How Artificial Intelligence Will Impact The Insurance Industry



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If you’re like most people, calling an insurance company isn’t among your favorite activities. That’s because the insurance industry is one of the least innovative areas for customer experience, meaning that customers typically come away from their interactions disappointed and dissatisfied. However, things are definitely changing, and artificial intelligence is playing a large role. The fast-growing technology has the potential to disrupt the entire industry and greatly improve the insurance customer experience.

Artificial Intelligence In The Claims Process

The insurance agency is notorious for its outdated processes. Filing a claim often looks the same today as it did decades ago because the industry isn’t consistently leveraging new technologies that are available to them. If an employee is busy or on vacation, a claims request could sit still until the right person is back. The outdated processes make it harder for agents by increasing the workload and forcing them to work with antiquated systems and frustrated customers.

However, AI can be applied to improve the claims process. Claims currently are touched by multiple employees. However, a new process of “touchless” claims doesn’t require any human intervention. This process uses artificial intelligence and other technology to report the claim, capture damage, audit the system, and communicate with the customer. The potential here is huge, as the process could allow clients the chance to file claims without having to wade through red tape.

Companies that have already automated some aspects of their claims process have seen a significant reduction in processing times and quality. AI-powered claims could also fight against one of the most costly elements of the insurance industry: fraudulent claims, which cost the industry more than $40 billion a year. Instead of relying on humans to manually comb through reports to catch inaccurate claims, AI algorithms can identify patterns in the data and recognize when something is fraudulent.

Future Of AI And Insurance

The industry is definitely ripe for AI disruption. Customers expect to be able to interact with companies through modern technology; a recent survey found that 74% of consumers say they would be happy to get computer-generated insurance advice.

Many insurance companies are already using artificial intelligence to some degree, and the number of companies following in their footsteps is sure to increase dramatically over the coming years. Artificial Intelligence has never been less expensive or more accessible, which means most companies don’t have a reason not to adopt it in at least some form.


Chatbots work through messaging apps many customers already have on their phones, which makes them a natural next step in customer interaction. In order to truly be effective, chatbots must have natural language processing and sentiment analysis so they can understand what customers are really asking. Effective chatbots can process concerns that are either typed or spoken from customers and provide personalized service. In the insurance space, chatbots can be used to answer basic questions and resolve claims, as well as sell products, address leads, or make sure customers are properly covered by their insurance. (Read More...)

How AI Is Taking the Scut Work Out of Health Care



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When we think of breakthroughs in healthcare, we often conjure images of heroic interventions — the first organ transplantation, robotic surgery, and so on. But in fact many of the greatest leaps in human health have come from far more prosaic interventions — the safe disposal of human excrement through sewage and sanitation, for example, or handwashing during births and caesarians. 

We have a similar opportunity in medicine now with the application of artificial intelligence and machine learning. Glamorous projects to do everything from curing cancer to helping paralyzed patients walk through AI have generated enormous expectations. But the greatest opportunity for AI in the near term may come not from headline-grabbing moonshots but from putting computers and algorithms to work on the most mundane drudgery possible. Excessive paperwork and red-tape is the sewage of modern medicine. An estimated 14% of wasted health care spending — $91 billion — is the result of inefficient administration. Let’s give AI the decidedly unsexy job of cleaning out the administrative muck that’s clogging up our medical organizations, sucking value out of our economy, and literally making doctors illwith stress.

Here’s just one example of the immediate opportunity: Each year, some 120 million faxes still flow into the practices of the more than 100,000 providers on the network of athenahealth, the healthcare technology company where I’m CEO. That’s right: faxes. Remember those?

In healthcare, faxes remain the most common method that practitioners use to communicate with each other, and therefore often contain important clinical information: lab results, specialist consult notes, prescriptions and so on. Because most healthcare fax numbers are public, doctors also receive scores of pizza menus, travel specials, and other “junk faxes.” Faxes don’t contain any structured text — so it takes medical practice staff an average of two minutes and 36 seconds to review each document and input relevant data into patient records. Through a combination of machine learning and business-process outsourcing that has automated the categorizing of faxes, we’ve reduced time-per-fax for our practices to one minute and 11 seconds. As a result, last year alone we managed to eliminate over 3 million hours of work from the healthcare system. (Read More...)

Big Companies Are Embracing Analytics, But Most Still Don’t Have a Data-Driven Culture



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For six consecutive years NewVantage Partners has conducted an annual survey on how executives in large corporations view data. Each year the response rate increases, and the reported urgency of making effective use of data increases as well. This year the results are both more encouraging and more worrisome than in the past.

Six years ago, the primary focus of questions and answers in the survey was big data, which was relatively new on the business scene. In the 2018 survey, the primary attention has moved to artificial intelligence. AI is now a well-established focus at these large, sophisticated firms. There is both a stronger feeling that big data and AI projects deliver value and a greater concern that established firms will be disrupted by startups.

The survey includes senior executives from 57 large corporations. The industry group with the most firms represented in the survey is one of the most data-intensive: financial services. Companies from the life sciences, manufacturing, telecom, and online industries also participated. The actual respondents are changing somewhat from the first surveys: It has always involved a high proportion of C-level executives responsible for data, but this year chief data officers are 56% of the respondents, up from 32% last year. Only 12% of firms in the 2012 survey had even appointed a chief data officer.

While AI gets the headlines here and elsewhere in the world, the survey addresses both big data and AI. Terminology comes and goes, but the constant is a data explosion and the need to make sense of it. Big data and AI projects have become virtually indistinguishable, particularly given that machine learning is one of the most popular techniques for dealing with large volumes of fast-moving data. It’s also the case that statistical approaches to AI — deep learning, for example — are increasingly popular. Therefore, we view traditional data analytics, big data, and AI as being on a continuum. Virtually all of the respondents (97%) say they are investing in these types of projects.

Perhaps the best news in this survey is that companies continue to believe they are getting value from their big data and AI projects. 73% of respondents said they have already received measurable value from these initiatives. That number is half again higher than in the 2017 survey, which suggests that more value is being achieved as companies grow familiar with the technologies. (Read More...)

How AI Can Keep Accelerating After Moore’s Law



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Google CEO Sundar Pichai was obviously excited when he spoke to developers about a blockbuster result from his machine-learning lab earlier this month. Researchers had figured out how to automate some of the work of crafting machine-learning software, something that could make it much easier to deploy the technology in new situations and industries.

But the project had already gained a reputation among AI researchers for another reason: the way it illustrated the vast computing resources needed to compete at the cutting edge of machine learning.

A paper from Google’s researchers says they simultaneously used as many as 800 of the powerful and expensive graphics processors that have been crucial to the recent uptick in the power of machine learning (see “10 Breakthrough Technologies 2013: Deep Learning”). They told MIT Technology Review that the project had tied up hundreds of the chips for two weeks solid—making the technique too resource-intensive to be more than a research project even at Google.

A coder without ready access to a giant collection of GPUs would need deep pockets to replicate the experiment. Renting 800 GPUs from Amazon’s cloud computing service for just a week would cost around $120,000 at the listed prices.

Feeding data into deep learning software to train it for a particular task is much more resource intensive than running the system afterwards, but that still takes significant oomph. “Computing power is a bottleneck right now for machine learning,” says Reza Zadeh, an adjunct professor at Stanford University and founder and CEO of Matroid, a startup that helps companies use software to identify objects like cars and people in security footage and other video.

The sudden thirst for new power to drive AI comes at a time when the computing industry is adjusting to the loss of two things it has relied on for 50 years to keep chips getting more powerful. One is Moore’s Law, which forecast that the number of transistors that could be fitted into a given area of a chip would double every two years. The other is a phenomenon called Dennard scaling, which describes how the amount of power that transistors use scales down as they shrink. (Read More...)

Big Data and Search: The Time for Artificial Intelligence Is Now


Businesses have been relying on search and big data analytics for many years to gain insight into their data. In recent years, these technologies have evolved rapidly and now incorporate machine learning and artificial intelligence, and they increasingly allow enterprises to more fully integrate their big data results into business action, whether it be for customer service, assembly line production, precision medicine or any of a number of other business use cases.

Big data applications today must be built to provide real-time results for businesses to compete in today’s fast-moving marketplace. Powered by search and big data, artificial intelligence (AI), machine learning, natural language processing (NLP) and cognitive (or “intelligent”) search are leading the way.

As we enter this new age, the time is near for1 businesses to incorporate these technologies — though they must be cognizant of the challenges that exist and the resources that will be required.

Using Search to Deliver Big Data Analytics

As the result of the growing demand for AI, machine learning and NLP applications, a tremendous amount of data is being pulled into big data platforms at massive scale. And, as the volume of data grows rapidly, organizations are increasingly seeking intelligent information discovery and analytics platforms. Navigating a traditional SQL database or typing in keywords is no longer enough! (Read More...)


The Age of Artificial Intelligence – Can AI Really Transform the Future of Businesses?


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Think about this – today, there are millions of smartphones, internet users, connected devices, and the number is just increasing by the hour. There is a historic shift in the way digital is becoming a part of our lives – from digital payments, to the way we shop or even interact with each other. Fueled by technologies such as Artificial Intelligence (AI), Cloud, Internet of Things (IoT) and Blockchain – this new era of digitization is producing data which is outstripping human capacity to understand the meaning and value hidden within that data.

Data, in all forms, is expanding as a resource to be utilized. Industries and professions are exploring several new possibilities and the potential value of this data is boundless. The next wave of technology – Artificial Intelligence – is already helping us make sense of the deluge of data out there, providing systems that are able to adapt and learn.

Once the preserve of science fiction, Artificial Intelligence (AI) has now become ubiquitous. From transforming healthcare to improving public safety, from enhancing the quality of education to bringing us into a world of connected devices- Artificial Intelligence is helping businesses reinvent and rethink.

A Gartner report predicts that AI will create 2 million net new jobs by 2025. Advances in virtual assistants and deep learning will foster adoption of artificial intelligence, according to the market research firm.

As one of the technology pioneers that helped establish the industry, IBM has been exploring AI and Machine Learning technologies for close to a decade with the launch of Watson in 2011. Little did the world know that the technology would very soon be touching more than one billion lives across the world?

Today, early adopters are using AI to position themselves as innovators and those that haven’t yet leveraged AI - are missing out on insights and opportunities that could help transform their businesses. (Read More...)

The Business of Artificial Intelligence


Authored By

Erik Brynjolfsson and Andrew McAfee


For more than 250 years the fundamental drivers of economic growth have been technological innovations. The most important of these are what economists call general-purpose technologies — a category that includes the steam engine, electricity, and the internal combustion engine. Each one catalyzed waves of complementary innovations and opportunities. The internal combustion engine, for example, gave rise to cars, trucks, airplanes, chain saws, and lawnmowers, along with big-box retailers, shopping centers, cross-docking warehouses, new supply chains, and, when you think about it, suburbs. Companies as diverse as Walmart, UPS, and Uber found ways to leverage the technology to create profitable new business models.

The most important general-purpose technology of our era is artificial intelligence, particularly machine learning (ML) — that is, the machine’s ability to keep improving its performance without humans having to explain exactly how to accomplish all the tasks it’s given. Within just the past few years machine learning has become far more effective and widely available. We can now build systems that learn how to perform tasks on their own.

Why is this such a big deal? Two reasons. First, we humans know more than we can tell: We can’t explain exactly how we’re able to do a lot of things — from recognizing a face to making a smart move in the ancient Asian strategy game of Go. Prior to ML, this inability to articulate our own knowledge meant that we couldn’t automate many tasks. Now we can.

Second, ML systems are often excellent learners. They can achieve superhuman performance in a wide range of activities, including detecting fraud and diagnosing disease. Excellent digital learners are being deployed across the economy, and their impact will be profound.

In the sphere of business, AI is poised have a transformational impact, on the scale of earlier general-purpose technologies. Although it is already in use in thousands of companies around the world, most big opportunities have not yet been tapped. The effects of AI will be magnified in the coming decade, as manufacturing, retailing, transportation, finance, health care, law, advertising, insurance, entertainment, education, and virtually every other industry transform their core processes and business models to take advantage of machine learning. The bottleneck now is in management, implementation, and business imagination. (Read More...)

Alumni networks allow ex-staff to still work for a company


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Corporate alumni networks are growing in importance as employees spend less and less time at a single company.

Mainstream employment is gradually giving way to a gig economy, where temporary or freelance positions and short-term contracts are rapidly becoming commonplace. Last year, millenials — those born between 1981 and 1997 — became the largest generational group in the US labour-force, according to the Pew Research Center. The demographic shift is helping create this broader employment model and a mobile generation where connectivity is key.

Tony Audino founded the Microsoft alumni network 20 years ago and is now chief executive and founder of Conenza, a company that builds and manages alumni networks. He sees companies facing a loyalty challenge as they compete for global talent. He believes an effective alumni network offers huge benefits to both the organisation and the alumni. An organisation’s former workers can act as promoters for its “talent brand as well as its overall corporate brand”, says Mr Audino.

Companies also can use alumni networks as a resource for recruiting former employees. Annabel Rake, chief marketing officer at Deloitte UK, refers to returning workers as “boomerangs”. “These are people who come back with a new set of skills and experiences that we find very beneficial,” she says. About 20 per cent of Deloitte’s hires each year are boomerangs. Returning employees are a proven benefit of the Credit Suisse alumni network, too, says Markus Simon, global head of the bank’s talent development shared services and online academy, as well as its alumni network. Like Deloitte, roughly 20 per cent of Credit Suisse recruits are rehires, he says. Companies can save money in recruiting using alumni networks. Further savings are made when an alumni network generates referrals of talent and business. (Read More...)

Leading Across Boundaries: Respect, Leadership And The Future Of Work

By Hal Gregersen

Incivility – in the community, in politics, in the workplace – is on the rise. In one survey, nearly everyone (79%) believes it’s creating a serious problem in society. It’s whittling away at people’s health, performance and souls. It’s affecting business. It’s compromising the American Dream for future generations. How we treat one another matters. It centers on respect – something we, as a society, don’t seem to respect.

Many place blame for our plethora of problems at the feet of two camps: parents and leaders. It’s a fiery debate. But regardless of where the worst of our issues originate, leaders have the distinct responsibility – and greatest opportunity – to be the solution.

Tom Kochan, MIT Sloan School of Management Professor and author of Shaping the Future of Work, shares both my concern and my optimism. As he explained in our recent interview, “There’s such a deep need to bring people together. We have so many divisions in our society, in our workplaces and in our personal lives that we need leaders who can bring people together to resolve problems, to build consensus, to mobilize action, and then to actually make progress in dealing with the difficult challenges we face every day.” (Read More...)

Policy Solutions Needed in Cities to Support Future of Work

By Brooks Rainwater

Fundamental shifts in society are upending the current nature of work. With automation and artificial intelligence already permeating nearly every sector of the economy, disruption is happening at an accelerated pace.

Our recent presidential election made clear that workforce shifts are felt by a broad swath of the American public. People are looking to elected officials at every level of government for a new response to these changes.

We have to move the policy discussion away from job retraining towards job rethinking.

The National League of Cities newest report, The Future of Work in Cities, examines the rapid changes happening in the workforce. Here are 8 suggestions from that report on how city leaders — the most responsive level of government — can approach the rapidly shifting future of work. (Read More...)


Build On-Demand Teams Instead of Hiring Employees



With the pace of change ever escalating, entrepreneurs today can’t afford to acquire talent through traditional hiring alone, and need to revise the perception that “talent” is only full-time employees. At the same time, more people in the workplace don’t want to be “employees.” According to an Intuit study, that number is quickly rising and will approach 40 percent by 2020.

The answer to both is a new fast and flexible talent strategy based on freelancers, consultants, experts, and specialists, who are part of the new “1099 economy” including Baby Boomers and Millennials. I just finished a new book, “Navigating the Talent Shift,” with convincing arguments for this approach by Lisa Hufford, Founder of Simplicity Consulting talent solutions.

The author outlines eight necessary steps for every business and entrepreneur to capitalize on this movement to on-demand project teams, versus permanent hires. These steps are the new keys to driving business innovation, controlling costs, staying nimble, and getting better results:

  • Build teams to meet goals rather than organization charts. Too many entrepreneurs, as they grow their business, are focused on hiring to fill a traditional organization chart, rather than acquiring skills and talents to meet their current goals and needs. They use generic job descriptions and plan for long-term business stability, which rarely happens. (Read More...)

    The digitally disrupted workplace

    By Thomas Brown


    The fourth industrial revolution is creating prospects of a future that few fully comprehend, but the implications for the world of work are already taking shape

    Trying to make sense of the future, in the face of such significant change and disruption, can leave you sympathising with Alice of Lewis Carroll’s 19th-century writings.

    We’re confronted with such a dizzying array of shifting macro-environmental forces and rapid technological advances that most of us struggle to keep up with, let alone decipher. We read of countless innovations and new possibilities that not too long ago would have been written off as the result of an overactive imagination or simply material for a Hollywood plot.

    Rethinking Work

    The reality, however, is that the relationship between technology and humanity is changing – fast. And it’s no longer a distant future but already here, shaping not just the way in which we live, but the way we work.

    As Klaus Schwab, founder and executive chairman of the World Economic Forum (WEF), opens in his book The Fourth Industrial Revolution: “Of the many diverse and fascinating challenges we face today, the most intense and important is how to understand and shape the new technology revolution, which entails nothing less than a transformation of humankind.” (Read More...)

    2016 Future of Work Trends Report

    We at Bluespace believe the Future of Work will significantly change the global corporate landscape, and offers companies and talent new and beneficial ways of interacting. In our view, there are three major guiding pillars that will shape how firms engage with talent and vice versa, with critical implications for firms:

    1. People increasingly want fluidity in managing work and life, and companies need the mechanisms to accommodate these goals and preferences. This is even more critical especially as talent segments such as returning moms, parents with special needs kids, veterans looking for transition, knowledgeable near-retirees, mobile millennials, etc. increasingly become a larger untapped and concentrated talent segment.
    2. As business complexity increases, companies need access to a more diverse mix of talent and expertise - often in an on-demand, short-duration, or other non-traditional arrangement. And many such experts prefer to work - and thrive - as independents, providing their specialized talents to a variety of companies rather than a single employer. Traditional employment models and processes need to adapt.
    3. As the business ecosystem continues to become more interconnected, companies will increasingly find value moving from the transactional, binary “in-or-out” relationship with employees to a longer-term ongoing relationship, in which value flows in both directions periodically over the span of people’s careers.


    US Bureaus of Labor statistics show there are tremendous pockets of untapped talent in the industry and companies that need skills including state and city governments (refer to WSJ article "Cities, States Need Top Financial Talent, but Fall Short on Pay"). These and other Future of Work trends continue to emerge at varying speeds in different industries. To better understand how companies across industry segments expect these trends to impact their business, how they are planning for this future, and what new services and models are needed to take best advantage of these changes, we are conducting this seminal cross-industry assessment jointly with Global Federation of Competitiveness Councils (GFCC) and assistance from NYU Stern School of Business.

    If you are interested in participating in this effort and/or receiving the finished report, please reach out to us.

    Does Future of Work = Less Collaboration?

    By Lisa Baird

    Something’s afoot in the future of work, but it’s hush-hush. People don’t like talking about it. "I know it is ugly to say ‘unicorn,’ but yeah, you kinda do have to be the unicorn," Chris Noessel, head of design for IBM’s transportation group, tells me. Before joining the tech giant, Mr. Noessel spent a decade at the design and strategy firm Cooper.

    His former boss, Alan Cooper, who invented (and later sold to Microsoft) the core design for Visual Basic, is even more cautious around the subject. "I think we in the design profession do ourselves and our colleagues a disservice by even recognizing the argument that ‘unicorns’ exist."

    Noessel and Cooper aren't talking about tech unicorns—startups valued at over $1 billion—they're talking about people. I asked them both about the type of person whose professional expertise is both deep and wide in multiple subject areas, and whether such a worker's already high value has risen in recent years. Cooper seems to reject the notion of such a person outright; Noessel doesn't but is uncomfortable with the notion of a "unicorn" worker in his field—somebody with vast experience in business, technology, and design. Yet both men are clearly more than a little polymathic themselves. (Read More..)

    Why High-Skilled Freelancers Are Leaving Corporate Life Behind

    Photos: Rawpixel.com via Shutterstock

    Photos: Rawpixel.com via Shutterstock

    By Lisa Baird


    On a sunny November day in San Francisco’s Mission District, inside the offices of Stamen Design (a studio known for cool-looking maps), I met what you might call a unicorn of the modern knowledge economy. Her name is Nicolette Hayes.

    She and I sat down, and she walked me through her latest two client projects. The first was an interactive model of the Amazon rainforest designed for a popular geography magazine. The second was a visual design language for human emotion, where sadness was represented as a deep ultramarine blob with soft blurry edges. These disparate projects called upon a range of visual, interactive, spatial, and psychological concepts that many would struggle to understand, let alone weave together cogently.

    Knowledge workers with polymathic competencies in multiple disciplines are still rare, but they're becoming more and more common. Take Hayes—a Berkeley geography grad with a design masters from Pratt. She is a data-visualization designer who regularly handles user interface, user experience, visual design, interaction design, and design research on behalf of clients. What once might’ve been a three- or four-person team is now simply Nicolette.


    Buckminster Fuller might’ve called someone like Nicolette Hayes a "comprehensivist"—the opposite of a specialist. According to constructivist psychologist Spencer McWilliams, "Fuller was highly critical of disciplinary specialization, believing that it was originally instituted to support the interests of a power structure and keep intelligent individuals from knowing too much." (Read More...)

    These 6 Million People Have No Interest in Full-Time Jobs

    Getty Images

    Getty Images

    They want to work—just not 40 hours a week for one company.

    The phrase “part-time worker” comes with some baggage. Assumptions are made about part-time workers—perhaps that their gigs are part-time because they’re students, or retirees whose schedules and needs don’t jibe with full-time employment. Probably the biggest assumption is that employees are working part-time simply because they cannot find full-time gigs with benefits, which could be reflective of something lacking on the behalf of the worker or shifting company policies that emphasize lower-paid part-timers.

    What’s rarely assumed is that workers are part-time employees 100% due to their own choice. In fact, according to U.S. Bureau of Labor Statistics data cited by Bloomberg, there are now 6 million Americans who actively choose to work part-time. And their numbers are on the rise, up 12% since 2007.

    While each individual has a different reason for seeking part-time employment as a first option rather than a fallback position, many of these workers have a few things in common. Namely, they tend to be young and well-educated. Instead of following traditional career paths, they are using part-time pay to help them pursue some version of the popular vision to follow your passion or “do what you love” during the hours they’re not on the clock. (Read More...)

    The Future Of Work: It's Already Here -- And Not As Scary As You Think



    I recently had the opportunity to speak at the Singularity University Summit in San Francisco on The Future of Work. After months of research on the topic, reading dozens of books and articles on AI, robotics, and economics, I came to a simple conclusion: the future of work is already here. And we all have to deal with it.

    The Future Of Work: Why Now?

    The phrase “Future of Work,” has become a buzz word. (I found 48 million Google hits on the phrase.) There are are suddenly hundreds of conferences, books, and articles on the topic, covering everything from artificial intelligence to robotics to income inequality and contingent labor.

    The reason for the interest is simple: we are in an economic cycle where jobs, as we know them, are rapidly changing. In fact, I’d venture to say we are reaching a time when jobs, as we know them, are going away. Here are just a few of the changes:

    • Today, driven by tremendous transparency in the job market, we change jobs often. The average baby boomer will be looking for a job 11.7. times in his or her career, according to a BLS study, and Millennials change jobs every two years or less.

    • Many of us work on a contingent basis. Nearly 40% of US workers are now contingent and platforms like Uber, TaskRabbit and others have made contingent work easier than ever. (Read More...)

    Connecting talent with opportunity in the digital age



    By James Manyika, Susan Lund, Kelsey Robinson, John Valentino, and Richard Dobbs


    Online talent platforms are increasingly connecting people to the right work opportunities. By 2025 they could add $2.7 trillion to global GDP, and begin to ameliorate many of the persistent problems in the world’s labor markets.

    Labor markets around the world haven’t kept pace with rapid shifts in the global economy, and their inefficiencies have taken a heavy toll. Millions of people cannot find work, even as sectors from technology to healthcare struggle to fill open positions. Many who do work feel overqualified or underutilized. These issues translate into costly wasted potential for the global economy. More important, they represent hundreds of millions of people coping with unemployment, underemployment, stagnant wages, and discouragement.

    Online talent platforms can ease a number of labor-market dysfunctions by more effectively connecting individuals with work opportunities. Such platforms include websites, like Monster.com and LinkedIn, that aggregate individual résumés with job postings from traditional employers, as well as the rapidly growing digital marketplaces of the new “gig economy,” such as Uber and Upwork. While hundreds of millions of people around the world already use these services, their capabilities and potential are still evolving. Yet even if they touch only a fraction of the global workforce, we believe they can generate significant benefits for economies and for individuals (exhibit). (Read More...)