The Court of Appeals in the 3^rd District has issued a blockbuster opinion on apportionment in City of Jackson v W.C.A.B. (Rice) regarding the requirements for substantial medical evidence in worker’ compensation cases. In reversing the W.C.A.B., the court laid out its analysis of why a QME’s apportionment to genetic factors was well supported and legally sufficient. The applicant in this case was a 29-year-old, police officer who developed cervical spine pain, resulting in the need for surgery. He was evaluated by QME Sloan Blair MD on multiple occasions. Dr. Blair apportioned applicant’s disability to multiple factors, including 17% each to his employment with the city, to prior employment and to personal activities. The remaining 49% was apportioned to his personal history, including “genetic issues." In response to a request for supplemental report from the applicant attorney, Dr. Blair further clarified the basis for her opinion: “…“to a reasonable degree of medical probability that genetics has played a role in Mr. Rice’s injury,” despite the fact that there is no way to test for genetic factors. Citing the referenced medical studies, Dr. Blair stated that one of them said “heritability was . . . 73 percent in the cervical spine. . . . [S]moking, age, and work are only a small percentage of disc disease and most of it is familial.” Another source cited the role of heritability in disc degeneration as 75 percent, and the other stated it was 73 percent. Dr. Blair cited a fourth article that claimed, “ ‘[t]win studies demonstrate that degeneration in adults may be explained up to 75 percent by genes alone.’ ” The same study found environmental factors to contribute little or not at all. Dr. Blair stated that while these studies supported an apportionment of 75 percent to personal history, she decided to err on the side of the patient in case there was some unknown “inherent weakness” in the study, and decided that 49 percent was the “lowest level that could reasonably be stated…” The WCJ accepted Dr. Blair’s apportionment to genetic factors but rejected the other apportionment awarding PD based on 51% industrial causation. On reconsideration, the W.C.A.B. reversed, asserting Dr. Blair’s apportionment to genetic factors resulted in an allocation of disability to impermissible immutable factors and not to “specific identifiable factors” and was therefore not substantial evidence. See also: 3rd District Upholds Validity of IMR   The 3^rd District took issue with the W.C.A.B.’s entire analysis of this apportionment issue. Noting the specific intent of SB 899 to allow apportionment to “other factors,” the court went through multiple W.C.A.B. and appellate court decisions on apportionment and could find little to distinguish apportionment on the basis of degenerative joint disease, asymptomatic prior conditions etc. The court specifically rejected the W.C.A.B.’s reference to “impermissible immutable factors,”  commenting as follows: “…Precluding apportionment based on “impermissible immutable factors” would preclude apportionment based on the very factors that the legislation now permits, i.e., apportionment based on pathology and asymptomatic prior conditions for which the worker has an inherited predisposition.  The Court pointed to several instances where medical evidence relied on apportionment to genetic dispositions to develop medical conditions, citing the Kos v W.C.A.B., Escobedo and Acme Steel cases and further noting: “…We perceive no relevant distinction between allowing apportionment based on a preexisting congenital or pathological condition and allowing apportionment based on a preexisting degenerative condition caused by heredity or genetics.” The court also rejected the W.C.A.B.’s analysis that Dr. Blair’s reliance on the applicant’s genetic makeup resulted in apportionment to the causation of injury rather than the causation of disability. The court pointed out the cause of the injury was repetitive motion, not genetics. Rather, Dr. Blair commented that the applicant’s disability was caused by a combination of factors, including a significant contribution from his genetic makeup.. The court was also not put off by the QME’s reliance on medical literature to support her conclusion rather than on a specific history from the applicant of his genetic makeup or background. As noted by the court, the doctor’s conclusion was supported by significant, unrebutted medical literature that found degenerative disc disease was influenced significantly by genetic factors and only minimally to environmental factors such as work activity. The court points out that the research relied upon by Dr. Blair supported the conclusion that as much as 75% of all DDD was related to genetics, and the issue was not whether one could prove that the genetic factor existed; the existence of significant DDD established the genetic factor as present. “Dr. Blair’s reports meet all of the requirements of Escobedo. Dr. Blair expressly stated that confidence in her opinion was predicated on reasonable degree of medical probability. Dr. Blair gave the reasoning behind her opinion--the published medical studies--and even named the studies and the pages relied upon. Her opinion disclosed familiarity with the concept of apportionment. Labor Code section 4663 states that apportionment is based on causation, and that “[a] physician shall make an apportionment determination by finding what approximate percentage of the permanent disability was caused by the direct result of injury arising out of and occurring in the course of employment and what approximate percentage of the permanent disability was caused by other factors . . . .”  (Lab. Code, § 4663, subd. (c).)” The case was remanded to the W.C.A.B. to issue an opinion based upon the QME’s conclusions. Comments and Conclusions: Assuming this decision holds up -- it is certainly likely to be appealed further -- it dramatically reinforces the rules on apportionment to any relevant factors that a physician can identify with reasonable medical probability. There are some unusual circumstances in this case that may have played a role in the ultimate outcome. First, the applicant was relatively young to have significant DDD, only 29 years old. That fact probably tipped Dr. Blair off that there was something about the condition that could not be attributed to environmental factors, including work. Second, the length of employment as a peace office was not lengthy; the applicant had worked less than five years in a full-time capacity. There had not been a lot of time to attribute causation to work activity. There is also fairly strong support in the medical literature that DDD is not really activity-related. Other than studies that suggest whole body vibration is a significant factor, there is little to suggest that bending, lifting and stooping, without significant trauma, plays any role in the development of disc disease. The situation is much like carpal tunnel syndrome, where the medical literature overwhelming fails to demonstrate a relationship between computer usage and the disease process, and yet we still routinely get compensable reports without any real support in the medical literature. Spine pain is constantly related to even relatively benign work activities as a matter of course. Clearly, defense attorneys need to start appearing at doctor depos armed with the literature cited by Dr. Blair and challenge physicians to provide a basis for their unapportioned or minimally apportionment spine CT claims, especially in younger individuals. See also: Intelligent WC Medical Management   This decision may have even broader applications in non-orthopedic cases. We have a wealth of literature about causation of various internal medicine conditions and even psychiatric conditions attributable to genetic, historical and environmental factors that now can more carefully be considered to support apportionment where previously the W.C.A.B. had been rejecting such opinions. The issue of whether there can be apportionment to genetic factors or predispositions would appear to be resolved in the affirmative in this case.

The Global Insurance Accelerator, based in Des Moines, Iowa, has just participated in the fourth Global Insurance Symposium. Two of the big takeaways are that the insurtech movement is maturing, and there is indeed convergence happening between the traditional industry and the entrepreneurial startups that have new ideas and business models. For the insurance industry to advance, there must be a great deal of collaboration between all types of participants in the marketplace. The GIA represents a great example of how this collaboration can be facilitated.

Since its inception, the GIA has promoted collaboration instead of disruption. There is a clear focus on insurtechs and their potential to bring transformative ideas to the industry, but not with the objective of displacing the existing industry players. The model is designed to look for mutual benefit for insurers and insurtech startups. Insurance companies, regulators, investors, academia and other industry experts like SMA are actively involved with insurtechs to guide and support them as they mature.

See also: Insurance Coverage Porn  

The idea is that there is a win-win situation when the strengths of the traditional industry (capital, regulatory experience, scale, risk knowledge, etc.) can be blended with the strengths of insurtechs. The startups bring an entrepreneurial spirit, speed, innovation and new business models to the game. The best ways to partner and take advantage of these combinations require hard work and are enhanced by facilitating organizations like the GIA.

As the transformation of the insurance industry continues, more and more insurers are seeking to actively partner with insurtechs, leverage emerging technologies and institutionalize innovation. At the same time, the insurtech community in general is maturing and has a greater understanding of the insurance industry and the need to collaborate than it had a couple of years ago. This evolving formula creates the potential to provide new ways to deliver the customer experience, improve operational efficiencies and assist customers in risk management and wealth accumulation, resulting in success for insurers, insurtechs, and other market participants.

In my completely and totally unbiased view of the world, the most important news of this past week is that Guy Fraker joined us at ITL as our chief innovation officer. I've been a fan of Guy's for many years—in fact, for years before I even met him. The admiration began because my frequent co-author, Chunka Mui, had identified Guy as one of the leading thinkers on driverless cars and had quoted him in a book we did on the topic. Chunka and I felt like we were very early in identifying the importance of autonomous vehicles—we published the book more than four years ago—yet I realized that Guy was ahead of us in many ways. Then I saw Guy speak at an industry conference and was totally sold.

Guy's long history of identifying winners in the insurance industry will help us greatly as we at ITL, in turn, help you figure out which of the more than 1,000 insurtechs we track at the Innovator's Edge will be important and which will not. 

He will address an even bigger problem, too—many companies think that identifying winning technologies and companies is their biggest issue with insurtechs these days, but there's actually a bigger problem out there. That problem is: Once you identify a promising technology or company, how do you bring that inside your company in a way that produces an important new product or even a new business model?

Every successful business is practically designed to stifle innovation brought in from the outside, and, even if you somehow neutralize those corporate antibodies that let existing business units protect their interests, there are many, many ways to fail at innovation. Guy has seen them all and has often even overcome them. Although he doesn't name names, he has consulted on some of the most successful innovation programs I've seen in the industry. 

He will share his expertise through a program we're calling the Innovator's Studio, as part of the Innovator's Edge. Please join me in welcoming Guy to the ITL team. (His email is here, in case you want to contact him directly.) And please share this note with anyone you think might benefit from a conversation with Guy.

Cheers,

Paul Carroll,
Editor-in-Chief 

Most insurers are using some form of predictive modeling, but it can be difficult to know if it will remain effective over time. Evaluating a predictive model can be tricky because, while there are many ways data can be measured, there is no accepted standard. With the considerable investment that’s involved in predictive analytics, the C-suite understandably wants to hold certain yardsticks to the models and see if they are performing well, and to make sure every stakeholder is using it correctly. Having a forward-looking evaluation can make all the difference when making key decisions, especially if there is trust in the measuring mechanism. Below are three new ways that insurers can evaluate the impact of predictive models, based on a model currently in production for a regional workers’ compensation insurer. The graphs below provide real-time insights that can help predictive modeling avoid becoming a black box, meaning that you can only see the output of the predictive model, not the input or how that output came to exist. The first two graphs separate out 10 equal portions of either premium or policy count, with each portion referred to as a "bin." 1. Monitoring that a model is still current and accurate You need to be able to regularly check if the model you have in production is still up-to-date and providing accurate scores. This graph illustrates the overall model lift on the book for a regional workers’ comp insurer in 2015 and 2016. The insurer’s model is generating a low score on business that’s running very profitably -- the lower-risk bins 1, 2, 3 are approximately 30% better than average. Policies getting a score in the higher-risk bins 8, 9, 10 are all running at twice the average loss ratio. This provides a clear indication of what to target and what to avoid. Bottom line: This model is still current and accurate. See also: Top 6 Myths About Predictive Modeling   2. Tracking the impact of a model on decision-making To realize the benefits of analytics, your staff needs to leverage the insights to make more informed decisions that create improved results. This is a graph of “decision data” from Valen’s InsureRight Manage application. Orange represents policies that were declined, red is quoted and lost, green is quoted and bound and yellow represents non-renewals. It’s evident that declinations are low on the good business -- less than 10% -- and high on the other end, approaching 50% for bin 10. The insurer is not renewing policies in bins 9 and 10 and, most importantly, retaining more than 50% of business in bins 1, 2, 3. Bottom line: Underwriters at this insurer are using the model to make more profitable risk selection and pricing decisions. 3. Measuring if the overall risk quality of a portfolio is improving with a model in production. If you’ve established that your model is accurate and your people are using it, the next question is what kind of impact it’s making to the quality of your portfolio. Are we lowering the risk of our book of business? This view shows the insurer’s risk-selection trends, with an overview of how risk-selection decisions have been influenced by a model and the resulting change to the portfolio. The blue bars represent premium volume by month, and the orange line represents average risk score (i.e., loss ratio prediction) by month. Though there is some variability from month to month, the overall downward trend indicates improvement over the course of the year. There is a small uptick in December 2016, which provides an indication that further analysis is needed. Bottom line: The risk quality of this portfolio is improving, though still requires careful monitoring. See also: Survey: Predictive Modeling Lifts Profits   Not only is it crucial to measure before an implementation takes place, it’s vital to do so both during and after, as well. Predictive modeling only works well if it is aligned with stated business goals, and knowing how to measure that is key to an insurer’s bottom line. With these three new ways to measure, insurers now will have different yardsticks to see whether it is successful and if they are using the actionable insights.

More than a half century ago, Ted Levitt transformed the strategic marketing agenda by asking a seemingly simple question. In his classic Harvard Business Review article "Marketing Myopia," Levitt declared that truly effective executives needed the courage, creativity and self-discipline to answer, "What business are we really in?" Were railroads, he asked, in the railroad business or the transportation business? Are oil companies in the oil business or hydrocarbon or energy business? The distinctions aren’t subtle, Levitt argued, and they subverted how companies saw their futures. Marketing myopia blinded firms to both disruptive threats and innovation opportunities. Levitt’s provocative question remains both potent and perceptive for marketers today. But my research in human capital investment and "network effects" suggests that it, too, needs a little visionary help. Increasingly, successful market leaders and innovators – the Amazons, Apples, Googles, Facebooks, Netflixs and Ubers– also ask, "Who do we want our customers to become?" That question is as mission-critical for insurance and financial services innovators as for Silicon Valley startups. The digitally disruptive influence of platforms, algorithms and analytics comes not just from how they transform internal enterprise economics but from their combined abilities to transform customers and clients, as well. Successful innovators transform their customers. See also: The 7 Colors of Digital Innovation   The essential insight: Innovation isn’t just an investment in product enhancement or better customer experience; innovation is an investment in your customer’s future value. Simply put, innovation is an investment in the human capital, capabilities, competencies and creativity of one’s customers and clients. This is as true for professional services and business-to-business industries as for consumer products and services companies. History gives great credence to this “human capital” model of innovation. Henry Ford didn’t just facilitate “mass production,” he enabled the human capital of “driving.” George Eastman didn’t just create cheap cameras and films; Kodak created photographers. Sam Walton’s Walmart successfully deployed scale, satellite and supply chain superiority that transformed "typical" shoppers into higher-volume, one-stop, everyday-low-pricing customers. Similarly, Steve Jobs didn’t merely “reinvent” personal computing and mobile telephony; he reinvented how people physically touched, stroked and talked to their devices. Google’s core technology breakthrough may appear to be “search,” but the success of the company’s algorithms and business model is contingent upon creating more than a billion smart “searchers” worldwide. The essential economic takeaway is that sustainable innovation success doesn’t revolve simply around what innovations “do”; it builds on what they invite customers to become. Simply put, making customers better makes better customers. Successful companies have a “vision of the customer future” that matters every bit as much as their products and services road maps. Insurance, fintech and insurtech industries should be no different. The same digital innovation and transformation dynamics apply. That means financial services firms must go beyond the "faster, better, cheaper" innovation ethos to ask how their innovations will profitably transform customer behaviors, capabilities and expectations. In other words, it’s not enough to answer Levitt’s question by declaring, "We’re in the auto/property/life insurance business." The challenge comes from determining how insurance companies want their new products, innovative services and novel user experiences to transform their customers. How can insurance companies invest in their customers in ways that make them more valuable? Who are they asking their customers to become? So when insurers innovate in ways that give customers and prospects new capabilities -- like Progressive’s price-comparison tools and Snapshot vehicle-usage plug-ins or Allstate’s mobile-phone-enabled QuickFoto claims submission option -- they’re not just solving problems but asking customers to engage in ways they never had before. Who are these companies asking their customers to become? People who will comparison shop; allow themselves to be monitored in exchange for better prices and better service; collaboratively gather digital data to review and expedite claims. These are but the first generation of innovation investments that suggest tomorrow’s customers will do much more. This is of a piece with how a Jeff Bezos, Steve Jobs, Mark Zuckerberg or Reed Hastings innovates to make their customers -- not just their products -- more valuable. Today’s Web 2.0 "network effects" business model — where a service becomes more valuable the more people use it — are superb examples of how smart companies recognize that their own futures depend on how ingeniously they invest in the future capabilities of their customers. Their continuous innovation is contingent on their customers’ continuous improvement. Call it “customer kaizen.” How rigorously and ruthlessly fintech, insurtech and insurance companies champion this innovation ethos will prove crucial to their success. Being in "the blockchain business" is radically and fundamentally different than asking who we want our blockchain users to become. See also: ‘Digital’ Needs a Personal Touch   Giving better, faster and cheaper advice on risk management via digital devices is different than fundamentally transforming how customers perceive and manage risk. It’s the difference between “transactional innovation” and innovation based on more sustainable relationships of mutual gain. The insurance industry needs to transform its innovation mindset. Start thinking how innovations make customers and clients more valuable. If your innovations aren’t explicit, measurable investments in your customers’ futures, then you are taking a myopic view of your own. Today’s strategic marketing and innovation challenge is how best to align "What business are we in?" with "Who do we want our customers to become?"

The insurance industry is currently going through an incredible amount of change. This is largely because developments in insurtech are making insurance solutions faster, better and more effective than ever. In the first quarter of 2016 alone, more than $650 million of funding was given to insurtech companies. The result of insurtech progression is that insurance companies now have more data and insight to work with than at any point in history -- but also face a challenge. This challenge is the need to become nimble -- quickly. See also: Fast and Slow: the Changing Landscape   The importance of swiftness Cognitive computing, robotic process automation, Internet of Things applications, the gig economy and even self-driving cars are all now issues that insurers must consider. All these developments mean that methods and practices that insurers have been using for decades are changing rapidly. Also contributing to the need to be nimble is the fact that America has recently experienced a cataclysmic housing market crash and has elected a president who seems dedicated to shaking up the insurance world. President Trump has already attempted to repeal Obamacare and has stated his intention to remove state lines for insurance company operations. The political uncertainty means that law and regulations could change quickly. Staying on the cutting edge One way that insurers are staying on the cutting edge is by looking for ways to speed up processes, and to operate more efficiently. I would know, because my company, WeGoLook, helps insurance companies to do just that. WeGoLook provides insurance solutions, financial services, auto and fleet inspections, and heavy equipment verifications for companies. Our innovative mobile application facilitates inspections and data collection that help in insurance claims processing. We have 30,000 on-demand agents in the field, who collect 65,000 data points on a daily basis. Gig companies such as ours plug into supply chains easily with innovative technology, which is why traditional insurers are taking notice. In fact, this is exactly why Crawford & Co. took an 85% stake in WeGoLook. Partnering with digitally powered gig economy startups can make insurers more nimble. See also: How to Embrace Workforce Flexibility   For insurers that can adapt to the swiftness that is now required, substantial profits can be made. Those that cannot may find that their companies suffer dramatically. Being nimble is the new standard for insurers.

"I think it’s particularly important for business today to take an active role in trying to fix the problems that this country does have." – Jamie Dimon, chairman and CEO, JP Morgan Chase- April 5, 2017

Since the global financial crisis of 2008, concerned business leaders, government officials, thinkers and a wide group of stakeholders have spawned a new discourse on the future of modern capitalism. The Coalition for Inclusive Capitalism was inaugurated in 2014 to encourage businesses to make changes and expand their investment and management practices to regain public trust. Primarily composed of business leaders, the coalition advocates for corporations to be managed for the long term and for the benefit of stakeholders as well as shareholders. Thomas Piketty’s “Capital in the 21^st Century” became an international best seller by highlighting the challenges facing capitalist economies and how rising inequality is leading to discontent and undermining democratic values. In January 2017, the G20 finance ministers called on members to pursue inclusive growth. Innovation and global commerce have traditionally been tremendous forces for progress. Capitalism has demonstrated a consistent ability to adapt to changing circumstances and drive technological change. According to the latest available data, the global economy is more than five times larger than it was half a century ago, and global per capita GDP has more than doubled over the same period. These numbers represent more than higher profits for corporations: They also amount to millions of jobs created and billions of lives improved. In 2015, the World Bank estimated that the share of the global population living in extreme poverty had fallen below 10% for the first time – down from more than 40% barely three decades ago. Networks and connections are playing an increasingly dominant role in all aspects of our lives. As Joshua Cooper Ramo has described in his book “The Seventh Sense: Power, Fortune and Survival in the Age of Networks” -- financial webs, DNA databases, currency platforms, medicine and research labs are all increasingly operating through both concentrated and diffuse networks. Networks have compressed time and space, accelerated the speed of commerce and trade and enabled the creation of vast wealth. But it is also evident that the market economy that has worked so well is not serving everyone equally. Growing income inequality and a rapidly evolving job market have left many people behind. In July 2016, the McKinsey Global Institute released an extensive report on incomes in 25 advanced economies worldwide, finding that between 65% and 70% of households were in income segments whose average incomes stagnated or declined between 2005 and 2014. The growth of artificial intelligence, big data and machine learning is having a profound impact on skilled labor, eliminating many positions and also undermining steady, secure employment opportunities and with it sources of income. This precipitous rise in income equality is having a direct impact on the way many see the capitalist system as a whole. According to a recent study by the Harvard Kennedy School, only 19% of Americans aged 18-29 identify themselves as “capitalist,” and only 42% of Americans 18-29 say they even support capitalism at all. Some have gone so far as to question whether these trends are insurmountable and if the world is entering a “post-capitalist” phase of economics. The World Economic Forum’s (WEF) 2017 Global Risk Report shows in detail how rising income inequality and the polarization of societies pose a risk to the global economy in 2017 and will shape the world for at least a decade unless urgent action is taken. The WEF’s 2017 Inclusive Growth and Development Report shows that the U.S. ranked 23rd among the most advanced economies in that regard, one spot above Japan. According to the report, the U.S. ranked 29th out of 30 in net income inequality, 29th in wealth inequality and 28th in poverty rate. Growing inequality, technological changes and the rise of digital networks are creating new economic paradigms. These disruptions are clear and potentially dangerous. These challenges also present the U.S. with an opportunity to show the world how a new American and inclusive capitalism can work, thrive and ultimately serve as a model for American leadership around the world. See also: 6 Tech Rules That Will Govern the Future   American Inclusive Capitalism – An agenda An American inclusive capitalism agenda should be both transformational and empower businesses, governments and non-profits to effectively respond to both the short- and long-term challenges. Government at the state, local and federal level will need to provide an appropriate legal and regulatory framework, but executing the agenda should be led by business and be built on a broader rethinking of the role of businesses and capital markets and their ability to generate public goods. Some of this rethinking is on the notion that financial value can be created by business in addressing social challenges. This view – most famously championed by Harvard Business School (HBS) Professor Michael Porter – is that businesses through a “shared value” model present the best opportunity to scale and solve these problems. And Porter’s HBS colleagues Gary Pisano and Willy Shih have argued for a manufacturing renaissance through the expansion of a new “industrial commons” where research and development (R&D) and production among companies can be co-located and serve as an innovative platform for growth. Enactment of an American inclusive capitalism agenda could also provide the U.S. with an opportunity to address urgent domestic economic challenges, unlock business creativity and create a blueprint for other countries to address similar issues within their own economies. The implementation of the agenda within the U.S. could begin with the following initiatives:

• Reduce incentives for short-term financial engineering. Over the past few decades, businesses have increasingly become unable to plan and execute for the long term. The private equity industry has accelerated these trends by buying companies, restructuring the businesses (often accompanied by layoffs) and then selling the businesses. Financial engineering has been central to private equity-led leveraged buyouts (LBOs) fueled by debt laid upon the companies themselves. While appropriate financial engineering can provide opportunities for failing companies to thrive, in many cases the results are less than optimal for the companies, their workers and the communities where these businesses operate. In addition, private equity owners are both the investors and the managers of their portfolio companies, which creates incentives for owners to manage operational decisions – such as union contracts, plant closings and use of capital – for short-term gains to owners. Partly as a result of these realities, private equity-owned companies are twice as likely to file for bankruptcy as compared with public companies, which lead to significant job losses at individual companies. Policymakers should reduce the incentives for indiscriminate and harmful financial engineering. An initial step could be to address what some refer to as the “carried interest loophole.” Carried interest refers to income flowing to the general partner of a private investment fund that is currently treated for tax purposes as capital gains as opposed to wage or salary income. Instead of fund managers typically paying a federal personal income tax on these gains at about 23.8%, by eliminating the carried interest loophole these same managers would be taxed at a top rate of 43.4% (not including any relevant state and local taxes). Taxing carried interest at ordinary rates would generate $180 billion over 10 years and provide a disincentive to harmful financial engineering.
• Enact a Universal Basic Income (UBI). Universal Basic income is a transfer payment in an amount sufficient to secure basic needs as a permanent earnings floor no one could fall beneath, and would replace many of today’s temporary benefits, which are given only in case of emergency and only to those who meet highly specific criteria. Rising inequality, decades of stagnant wages, the end of career employment and technology and networks disrupting the labor force have resulted in unprecedented income instability. Price Waterhouse Coopers (PWC) has concluded in March 2017 that as much as one-third of the U.S. workforce is at risk of being lost to automation. An Oxford University study goes even further, concluding that as many as 47% of jobs in the U.S. are at risk of being wiped out due to automation within the next 20 years. Some countries are already experimenting with a UBI system. Finland launched a UBI pilot program in 2017 where 2000 people are collecting approximately $587 per month for two years without having to report whether they are seeking employment or how they are spending the money. This supplement will be deducted from any benefits they are currently receiving. The program was created by KELA, the Finnish agency responsible for the country’s social benefits. Finnish official believe the UBI will help to streamline a bloated welfare system, and because participants will continue to receive benefits even when they find work there are no disincentives to seeking employment while on the program. A partial UBI already exists in Alaska, and pilot programs are being discussed in Canada, Brazil, Iceland and Uganda. A UBI system would serve as an effective mechanism to fight poverty while providing a floor where citizens could take risks in the job market without fear of losing all of their income. A growing chorus from all sides of the political spectrum – from Charles Murray to Robert Reich to Labor leader Andrew Stern – to business titans such as Pierre Omidyar and Elon Musk – all now support a UBI for Americans. There are various estimates regarding the costs of implementing a UBI program, but the UBI should be considered in tandem with full or partial consolidation of other programs and tax credits that would immediately be made redundant by the new transfer.
• Encourage Environmental Social and Governance (ESG) and Impact Investment as core parts of asset management. Impact investments are made into companies, organizations and funds with the intention to create measurable social and environmental impact along with financial returns. Research has shown that currently the majority of institutional investors actively consider ESG criteria when making alternative investment allocations. ESG analysis has moved beyond ethical concerns and has found a firm footing as a risk and investment management topic. Surveys now show most institutional investors are confident that ESG improves risk-adjusted returns and is an important aspect of risk and reputation management. It is estimated that investors committed at least $15 billion globally to impact-related projects in 2015, and that number is anticipated to grow exponentially as impact funds develop a track record and millennials demand more accountability as to how their savings are invested. Large impact investment funds with more than $250 million of assets under management (AUM) include Bridge Ventures, the Calvert Foundation and Turner Impact Capital. These funds and many others invest in sustainable agriculture, global health, water and sanitation, clean technology and affordable housing, among many others. In 2016, the largest asset management company in the world (BlackRock) launched its impact mutual fund to invest in companies seeking triple bottom line returns (profit, social and environmental returns), and the Department of Labor revised its Employee Retirement Income Security Act (ERISA) guidelines to allow pension fund managers to incorporate ESG criteria into investment allocation decisions. Impact investment can serve as a critical future channel to solve problems while generating returns for businesses and investors. The federal government could help to jump start this growing market by creating an ESG-related fund for the federal government’s defined contribution savings plan (Thrift Savings Plan, or TSP) for civil service employees, retirees and members of the military. There are nearly 5 million current participants in TSP, with total assets of at least $468 billion.
• Grant special purpose national bank charters for financial technology (fintech) companies. Fintech companies include businesses focused on payments, blockchain, wealth management, crowdfunding, digital currencies, peer-to-peer lending, clearance and settlement. Technology has made "financial products and services more accessible, easier to use and much more tailored to individual consumer needs." The power of fintech to accelerate financial inclusion and provide greater financial security to the marginal and the unbanked is one of the greatest potential impacts of this segment of finance. Fintech can help address this growing program of “capital deserts” by providing citizens tools to access capital particularly in underserved rural and urban areas. Many U.S. fintech companies consistently cite the lack of a clear and coherent regulatory structure within the U.S. as a major impediment to further growth and expansion. Policymakers currently find it difficult to support fintech innovation while upholding consumer and financial system protections.

See also: The Sharing Economy and Accountability   In December 2016, the Office of the Comptroller of the Currency (OCC) published and solicited comments for a paper exploring special purpose bank charters for U.S. fintech companies engaged in “receiving deposits, paying checks or lending money.” There would be numerous benefits to the OCC granting special purpose national bank charters to fintech companies. Special purpose charters would help ensure that these companies operate in a safe and sound manner while effectively serving the needs of customers, businesses, and communities. They would promote consistency in the application of the law and regulation across the country and ensure that consumers are treated fairly. The growth of new fintech companies with national charters would also expand access to finance for SMEs and make the federal banking system much stronger. Special purpose national bank charters for fintech companies would represent a crucial step in modernizing the banking system, fostering innovation and demonstrating U.S. leadership throughout the world in the rapidly evolving intersection of technology and finance.

• Continue to enact legislation at state level to support alternative corporate forms such as Benefit Corporations. Benefit corporations are legally designated for-profit corporate entities whose mission includes generating a positive impact on society, employees, the community and the environment, in addition to profit. Benefit corporations give entrepreneurs the freedom to consider stakeholders in addition to shareholders and net profit. Shareholders of such corporations, in turn, enjoy all the same protections and powers found in traditional corporate law but also have more freedom to hold the company accountable for remaining true to its stated mission. Benefit corporations create a no-cost economic development opportunity for states by establishing new pathways for social entrepreneurs to scale. Thirty-two states including the District of Columbia have passed benefit corporation legislation. “B” Corporations are businesses privately certified by B Lab, a non-profit organization founded in the U.S. but with offices throughout the world. Companies are granted “B” Corporation status by B Lab upon completion of an assessment and satisfying requirements that the company integrate B Lab commitments into its core business. There are now 4,000 legally constituted Benefit Corporations and 2,000 certified “B” Corporations in the U.S.. Some examples of well-known benefit or “B” corporations include Patagonia, Kickstarter, Solberg Manufacturing and Etsy.

Benefit Corporations and “B” corporations create tremendous branding opportunities for businesses seeking to highlight their positive impact on their communities. States and the federal government can expedite a process to provide incentives to businesses to declare as Benefit Corporations. More U.S. states can pass legislation to help facilitate a new market so that current shareholders, consumers and potential investors can make informed decisions based on companies’ missions and performance. And as the federal government downsides and more work is granted to federal contractors and subcontractors, government procurement guidelines could be reviewed and revised as a pilot project to include preferences for benefit corporations.

• Eliminate Anonymous Corporate Ownership. Nearly one year after the Panama papers exposed the offshore banking activities of clients of the Panamanian firm Mossack Fonseca, it is still legal for corporations in the U.S. to be anonymously owned. Anonymous ownership directly facilitates the ability of shell companies to hide assets and obscure illegal activity. But in addition to tax evasion and money laundering, anonymous ownership is also contributing to accelerating housing prices in major U.S. cities. According to the New York Times, streams of foreign wealth shielded by shell corporations are already used to purchase more than half of all individual properties in New York City that cost more than $5 million. In a three-block stretch in Midtown Manhattan, 57% of apartments are vacant for at least 10 months every year, and absentee homeownership has grown by 70% in Manhattan since 2000. In South Florida, money linked to wrongdoing abroad is helping to power the new condos rising on its waterfront and pushing home prices far beyond what locals can afford. These investments often result in skyrocketing home prices not only in luxury units but also more affordable housing – ultimately pricing out the ability of American citizens to live in their own cities. Cities also routinely encounter difficulties in identifying who actually owns slum properties and ensuring accountability for those owners and corporate entities that allow residential properties to become dangerous and deadly.

The UK, France, Germany, Spain and Italy have all committed to creating a registry for anonymous corporate ownership. In late 2016, the U.S. Justice Department concluded its three-year Swiss Banking program that provided a path for Swiss banks to resolve potential criminal liabilities related to disclosure of cross-border activities, providing detailed information on an account-by-account basis for accounts in which U.S. taxpayers have a direct or indirect interest, providing information as to other banks that have transferred funds from secret accounts and closing accounts of those who have failed to meet U.S. reporting obligations. Despite these efforts, no U.S. state requires the name of anonymous corporate owners. Bipartisan legislation cosponsored by Sens. Charles Grassley and Sheldon Whitehouse and Congressman Peter King and Congresswoman Carolyn Maloney has been introduced to identify money laundering and terrorist financing through the disclosure of anonymous owners. Congress should pass that legislation, and the Trump administration should sign the bill into law to prevent the U.S. from becoming a preferred haven for tax cheats and illicit activity. See also: Changing Business Models, ‘New’ ERM   Conclusion Jamie Dimon, chairman and CEO of JPMorgan Chase, the largest U.S. financial institution with some $2.5 trillion under management, recently released his annual letter to shareholders. His letter included extensive comments on public policy where he opined that “something is wrong” in America and that “we need coherent, consistent, comprehensive and coordinated policies that help fix these problems.” His letter is another example of the urgent need for inaugurating an American inclusive capitalism agenda. While government can provide the framework and a social safety net, the primary responsibility for such an agenda should be with the private sector through a renewed and reinvigorated business activism. Markets have a unique ability to adapt and allocate resources in the most efficient way, but when needless financial engineering results in the abandonment of communities, when middle-class citizens can no longer access capital and when more and more Americans drop out of the labor force with no source of income, the remarkable consensus that has resulted in American economic strength since the end of World War II will become seriously endangered. But there is a path forward. Business activism focused on new corporate forms, impact investing and a regulatory structure that facilitates a shift away from short-termism and toward entrepreneurship and greater access to finance can lead the way in this quest for reform. Such reform can be the harbinger of a new social compact between government, established business, entrepreneurs and the people. And it can give the U.S. an opportunity to assert leadership and address the most important economic challenges of our time.

Managed security services providers, or MSSPs, continue to rise in presence and impact—by giving companies a cost-effective alternative to having to dedicate in-house staff to network defense. In the thick of this emerging market is Rook Security. I spoke with Tom Gorup, Rook’s director of security operations, about this at RSA 2017. A few takeaways: Outsourced SOCs. MSSPs essentially function as a contracted Security Operations Center, or SOC. Most giant corporations, especially in the financial and tech sectors, have long maintained full-blown SOCs, manned 24/7/365. And so the top MSSP vendors, which include the likes of AT&T, Dell SecureWorks, Symantec, Trustwave and Verizon, are aggressively marketing MSSP services to midsize companies, those with 1,000 to 10,000 employees. See also: 7 Key Changes for Insurers’ Cybersecurity   At the other end of the spectrum—catering to very small businesses—you have consulting technicians, operating in effect as local and regional MSSPs. These service providers may have one or two employees. They make their living by assembling and integrating security products developed by others, working with suppliers such as SolarWinds MSP, which packages and white labels cloud-based security solutions for very small businesses. So what about the companies in between, those with, say, 50 to 999 employees? Security vendors recognize this to be a vastly underserved market, one that probably has pent-up demand for MSSP services. What MSSPs provide. For midsize and large enterprises, MSSPs deliver an added layer of expertise that can help bigger organizations actually derive actionable intelligence from multiple security systems already in place, such as firewalls, intrusion detection systems, sandboxing and SIEMs. The top MSSPs tap into all existing systems and provide deeper threat intelligence services, such as device management, breach monitoring, data loss prevention, insider threat detection and incident response. For small businesses, local MSSPs focus on doing the basics to protect endpoints and servers. This relieves the small business operator from duties such as staying current on anti-virus updates, as well as security patches for Microsoft, Apple, Adobe and Linux operating systems and business applications that are continually probed and exploited.  Who needs one? Every business today is starkly exposed to network breaches. So who could use an MSSP? The calculation for midsize and large organizations is straightforward. The goal is to provide more data protection at less cost, based on thoughtful, risk-based assessments. The most successful MSSPs will help company decision-makers build a strong case for their services. See also: Quest for Reliable Cyber Security   At smaller companies, the first question to ask is this: How mature is my security posture to begin with? Gorup observes: “Is security even on the radar right now? In smaller organizations, you might have just one person, part-time, working IT. Security is kind of secondary. I’d recommend seeking more advisory services to help detect phishing attacks, help build some processes, help understand what technologies you should invest in. This will allow growth to occur. And then you can make a natural transition into building an SOC or seeking SOC services.”

I recently had the pleasure of attending #CityChain17 (blockchain conference) at IBM’s SouthBank offices. Chaired by Paul Forrest (chairman of MBN Solutions), the conference was an opportunity to learn about blockchain and how it is being applied. In the past, I viewed the hype about blockchain (following excitement about Bitcoin its most famous user) as just another fad that might pass. However, as more businesses have got involved in piloting potential applications, it’s become obvious that there really is something in this – even if its manifestations are now much more commercial than the hacking by Bitcoin fans. CityChain17 brought together a number of suppliers and those helping shape the industry. It was a great opportunity to hear voices, at times contradictory,and see what progress has been made toward mainstream adoption. There was so much useful content that I made copious notes and will share a series of two blog posts on this topic. So, without further ado, as a new topic for our blog, here is part 1 of my recollections from this blockchain conference. Introducing blockchain and why it matters The first speaker was John McLean from IBM. He reviewed the need that businesses have for a solution to the problem of increasingly complex business and market networks, with the need to securely exchange assets, payments or approvals between multiple parties. He explained that, at core, blockchain is just a distributed ledger across such a network. In such a scenario, all participants have a regulated local copy of the ledger, with bespoke permissions to approve blocks of information. However, he also highlighted that today’s commercial applications of blockchain differ from the famous Bitcoin implementation:

• Such applications can be internal or external.
• Business blockchain has identity rather than anonymity, selective endorsement versus proof of work and wider range of assets vs. a cryptocurrency.
• Blockchain for businesses is interesting because of the existing problems it solves. Broader participation in shared ledger reduces cost and reconciliation workload. Smart contracts offer embedded business rules with the data blocks on the ledger. Privacy improves because transactions are secure, authenticated and verifiable. So does trust because all parties are able to trust a shared ledger – all bought in.
• Several sectors are currently testing blockchain implementations, including financial services, retail, insurance, manufacturing and the public sector.

Finally, John went on to outline how IBM is currently enabling this use of blockchain technology (including through its participation in the Hyperledger consortium and its Fabric Composer tool). See also: 5 Main Areas for Blockchain Impact   Comparing blockchain to databases, anything new? As someone who was involved in the early days of data warehouses and data mining, I was delighted to hear the next speaker (Dr. Gideon Greenspan from Coin Sciences) talk about databases. Acknowledging that a number of the so-called unique benefits of blockchain can already be delivered by databases, Gideon began by suggesting there had been three phases of solutions to the business challenges of exchanging and coordinating data:

1. Peer-to-peer messaging
2. Central shared database
3. Peer-to-peer databases

He had some great examples of how the "unique benefits" of blockchain could be achieved with databases already:

• Ensuring consensus in data (B-trees in relational databases)
• Smart contracts (the logic in these equal stored procedures)
• Append-only inserts (database that only allows inserts)
• Safe asset exchanges (the ACID model of database transactions)
• Robustness (distributed and massively parallel databases)

Even more entertaining, in a room that was mainly full of blockchain advocates, developers or consultants, Gideon went on to list what was worse about blockchain vs. databases:

• Transaction immediacy (ACID approach is durable, but blockchains need to wait for consensus)
• Scalability (because of checks, blockchain nodes need to work harder)
• Confidentiality (blockchains share more data)

After such honesty and frankly geeky database technology knowledge, Gideon was well-placed to be an honest adviser on sensible use of blockchain. He pointed out the need to consider the trade-offs between blockchain and database solutions. For instance, what is more important for your business application:

• Disintermediation or confidentiality?
• Multiparty robustness or performance?

Moving to more encouraging examples, he shared a few that have promising blockchain pilots underway:

1. An instant payment network (using tokens to represent money, it’s faster, with real-time reconciliation and regulatory transparency)
2. Shared metadata solution (as all data added to the blockchain is signed, time-stamped and immutable – interesting for GDPR requirements, even if the "right to be forgotten" sounds challenging)
3. Multi-jurisdiction processes (regulators are interested)
4. Lightweight financial systems (e.g. loyalty schemes)
5. Internal clearing and settlements (e.g. multinationals)

But a final warning from Gideon was to be on the watch for what he termed "half-baked blockchains." He pointed out the foolishness of:

• Blockchains with one central validator
• Shared state blockchains (same trust model as a distributed database)
• Centrally hosted blockchain (why not a centralized database?)

Gideon referenced his work providing the multichain open platform, as another source for advice and resources. Blockchain is more complex, hence the need for technical expertise A useful complement (or contradictory voice, depending on your perspective) was offered next. Simon Taylor (founder of 11:FS and ex-Barclays innovation leader), shared more on the diversity of technology solutions. Simon is also the founder of yet another influential and useful group working on developing/promoting blockchain, the R3 Consortium. He credits much of what he has learned to a blogger called Richard Brown, who offers plenty of advice and resources on his blog: One idea from Richard that Simon shared is the idea that different technology implementations of blockchain, or platforms for developing, are best understood as being on a continuum, from more centralized applications for FS (like Hyperledger and Corda) being at one end and the radically decentralized Wild West making up the other end (Bitcoin, z-Cash and Ethereum). He suggests the interesting opportunities lie in the middle ground between these poles (currently occupied by approaches like Stellar and Ripple). Simon went on to suggest a number of principles that are important to understand:

• The shared ledger concept offers better automated reconciliation across markets.
• But, as a result, confidentiality is a challenge (apparently Corda et al. are solving this, but at the expense of more centralization).
• No one vendor (or code-base/platform) has yet won.
• It is more complicated than the advertising suggests, so look past the proof of concept work to see what has been delivered (he suggests looking at interesting work in Tel Aviv and at what Northern Trust is doing).

To close, Simon echoed a few suggestions that will sound familiar to data science leaders. There continues to be an education and skills gap. C-Suite executives recognize there is a lot of hype in this area and so are seeking people they can trust as advisers. Pilot a few options and see what approach works best for your organization. He also mentioned the recruitment challenge and suggested not overlooking hidden gems in your own organization. Who is coding in their spare time anyway? In his Q&A, GDPR also got mentioned, with a suggestion that auditors will value blockchain implementations as reference points with clear provenance. See also: Why Blockchain Matters to Insurers   Time for a blockchain panel After three talks, we had the opportunity to enjoy a panel debate. Paul Forrest facilitated, and we heard answers on a number of topics from experts across the industry. Those I agreed with (and thus remembered) were Tomasz Mloduchowski, Isabel Cooke and Parrish Pryor-Williams. I took the opportunity to ask about the opportunity for more cooperation between the data science and blockchain communities, citing that both technology innovations needed to prove their worth to the C-suite and had some overlapping data needs. All speakers agreed that more cooperation between these communities would be helpful. Isabel’s team at Barclays apparently benefits from being co-located with the data science team, and Parrish reinforced the need to focus on customer insights to guide application of both technologies. What panelists appear to be missing is that, in most large organizations, blockchain is being tested within IT or digital teams, with data science left to marketing or finance/actuarial teams. This could mean a continued risk of siloed thinking rather than the cooperation needed. An entertaining, question concerned what to do with all the fakes now rapidly adding blockchain as a buzzword to their CVs and LinkedIn profiles. Surprisingly, panelists were largely positive about this development. They viewed it as an encouraging tipping point of demand and a case that some will need to fake it 'til they make it. There was also an encouragement to use meetups to get up-to-speed more quickly (for candidates and those asking the questions). The panel also agreed that there was still a lack of agreement on terms and language, which sometimes got in the way. Like the earlier days of internet and data science, there are still blockchain purists railing against the more commercial variants. But the consensus was that standards would emerge and that most businesses were remaining agnostic on technologies while they learned through pilots. The future for blockchain was seen as being achieved via collaborations, like R3 and Hyperledger. A couple of panelists also saw fintech startups as the ideal contenders to innovate in this space, having the owner/innovator mindset as well as the financial requirements. It will be interesting to see which predictions turn out to be right. What next for blockchain and you? How do you think blockchain develops, and do you care? Will it matter for your business? Have you piloted to test that theory? I hope my reflections act as a useful contact list of those with expertise to share in this area. Let us know if this topic is something you would like covered more, on Customer Insight Leader blog. That’s it for now. More diverse voices on blockchain in Part 2….

It is a warm autumn morning, and I am walking through downtown Mountain View, Calif., when I see it. A small vehicle that looks like a cross between a golf cart and a Jetson-esque, bubble-topped spaceship glides to a stop at an intersection. Someone is sitting in the passenger seat, but no one seems to be sitting in the driver seat. How odd, I think. And then I realize I am looking at a Google car. The technology giant is headquartered in Mountain View, and the company is road-testing its diminutive autonomous cars there. This is my first encounter with a fully autonomous vehicle on a public road in an unstructured setting. The Google car waits patiently as a pedestrian passes in front of it.  Another car across the intersection signals a left-hand turn, but the Google car has the right of way. The automated vehicle takes the initiative and smoothly accelerates through the intersection. The passenger, I notice, appears preternaturally calm. I am both amazed and unsettled. I have heard from friends and colleagues that my reaction is not uncommon. A driverless car can challenge many assumptions about human superiority to machines. Though I live in Silicon Valley, the reality of a driverless car is one of the most startling manifestations of the future unknowns we all face in this age of rapid technology development. Learning to drive is a rite of passage for people in materially rich nations (and becoming so in the rest of the world): a symbol of freedom, of power, and of the agency of adulthood, a parable of how brains can overcome physical limitations to expand the boundaries of what is physically possible. The act of driving a car is one that, until very recently, seemed a problem only the human brain could solve. Driving is a combination of continuous mental risk assessment, sensory awareness, and judgment, all adapting to extremely variable surrounding conditions. Not long ago, the task seemed too complicated for robots to handle. Now, robots can drive with greater skill than humans — at least on the highways. Soon the public conversation will be about whether humans should be allowed to take control of the wheel at all. This paradigm shift will not be without costs or controversies. For sure, widespread adoption of autonomous vehicles will eliminate the jobs of the millions of Americans whose living comes of driving cars, trucks, and buses (and eventually all those who pilot planes and ships). We will begin sharing our cars, in a logical extension of Uber and Lyft. But how will we handle the inevitable software faults that result in human casualties? And how will we program the machines to make the right decisions when faced with impossible choices — such as whether an autonomous car should drive off a cliff to spare a busload of children at the cost of killing the car’s human passenger? See also: Of Robots, Self-Driving Cars and Insurance   I was surprised, upon my first sight of a Google car on the street, at how mixed my emotions were. I’ve come to realize that this emotional admixture reflects the countercurrents that the bow waves of these technologies are rocking all of us with: trends toward efficiency, instantaneity, networking, accessibility, and multiple simultaneous media streams, with consequences that include unemployment, cognitive and social inadequacy, isolation, distraction, and cognitive and emotional overload. Once, technology was a discrete business dominated by business systems and some cool gadgets. Slowly but surely, though, it crept into more corners of our lives. Today, that creep has become a headlong rush. Technology is taking over everything: every part of our lives, every part of society, every waking moment of every day. Increasingly pervasive data networks and connected devices are enabling rapid communication and processing of information, ushering in unprecedented shifts — in everything from biology, energy and media to politics, food and transportation — that are redefining our future. Naturally we’re uneasy; we should be. The majority of us, and our environment, may receive only the backlash of technologies chiefly designed to benefit a few. We need to feel a sense of control over our own lives; and that necessitates actually having some. The perfect metaphor for this uneasy feeling is the Google car. We welcome a better future, but we worry about the loss of control, of pieces of our identity, and most importantly of freedom. What are we yielding to technology? How can we decide whether technological innovation that alters our lives is worth the sacrifice? The noted science-fiction writer William Gibson, a favorite of hackers and techies, said in a 1999 radio interview (though apparently not for the first time): “The future is already here; it’s just not very evenly distributed.” Nearly two decades later — though the potential now exists for most of us, including the very poor, to participate in informed decision-making as to its distribution and even as to bans on use of certain technologies — Gibson’s observation remains valid. I make my living thinking about the future and discussing it with others, and am privileged to live in what to most is the future. I drive an amazing Tesla Model S electric vehicle. My house, in Menlo Park, close to Stanford University, is a “passive” home that extracts virtually no electricity from the grid and expends minimal energy on heating or cooling. My iPhone is cradled with electronic sensors that I can place against my chest to generate a detailed electrocardiogram to send to my doctors, from anywhere on Earth. Many of the entrepreneurs and researchers I talk with about breakthrough technologies such as artificial intelligence and synthetic biology are building a better future at a breakneck pace. One team built a fully functional surgical-glove prototype to deliver tactile guidance for doctors during examinations — in three weeks. Another team’s visualization software, which can tell farmers the health of their crops using images from off-the-shelf drone-flying video cameras, took four weeks to build. The distant future, then, is no longer distant. Rather, the institutions we expect to gauge and perhaps forestall new technologies’ hazards, to distribute their benefits, and to help us understand and incorporate them are drowning in a sea of change as the pace of technological change outstrips them. The shifts and the resulting massive ripple effects will, if we choose to let them, change the way in which we live, how long we live for, and the very nature of being human. Even if my futuristic life sounds unreal, its current state is something we may laugh at within a decade as a primitive existence — because our technologists now have the tools to enable the greatest alteration of our experience of life since the dawn of humankind. As in all other manifest shifts — from the use of fire to the rise of agriculture and the development of sailing vessels, internal-combustion engines, and computing — this one will arise from breathtaking advances in technology. It is far larger, though, is happening far faster, and may be far more stressful to those living through this new epoch. Inability to understand it will make our lives and the world seem even more out of control. A broad range of technologies are now advancing at an exponential pace, everything from artificial intelligence to genomics to robotics and synthetic biology. They are making amazing and scary things possible — at the same time. Broadly speaking, we will, jointly, choose one of two possible futures.  The first is a utopian “Star Trek” future in which our wants and needs are met, in which we focus our lives on the attainment of knowledge and betterment of mankind. The other is a “Mad Max” dystopia: a frightening and alienating future, in which civilization destroys itself. These are both worlds of science fiction created by Hollywood, but either could come true. We are already capable of creating a world of tricorders, replicators, remarkable transportation technologies, general wellness and an abundance of food, water and energy. On the other hand, we are capable too now ofushering in a jobless economy; the end of all privacy; invasive medical-record keeping; eugenics; and an ever worsening spiral of economic inequality: conditions that could create an unstable, Orwellian or violent future that might undermine the very technology-driven progress that we so eagerly anticipate. And we know that it is possible to inadvertently unwind civilization’s progress. It is precisely what Europe did when, after the Roman Empire, humanity slid into the Dark Ages, a period during which significant chunks of knowledge and technology that the Romans had hard won through trial and error disappeared from the face of the Earth. To unwind our own civilization’s amazing progress will require merely cataclysmic instability. See also: Lack of Enthusiasm for Driverless Cars? It is the choices we all make which will determine the outcome. Technology will surely create upheaval and destroy industries and jobs. It will change our lives for better and for worse simultaneously. But we can reach “Star Trek” if we can share the prosperity we are creating and soften its negative impacts; ensure that the benefits outweigh the risks; and gain greater autonomy rather than becoming dependent on technology. The oldest technology of all is probably fire, even older than the stone tools that our ancestors invented. It could cook meat and provide warmth; and it could burn down forests. Every technology since this has had the same bright and dark sides. Technology is a tool; it is how we use it that makes it good or bad. There is a continuum limited only by the choices we make jointly. And all of us have a role in deciding where the lines should be drawn. This is an excerpt from Vivek Wadhwa’s new book, “The Driver in the Driverless Car: How Our Technology Choices Will Create the Future.”