What To Do When Machines Do Everything. Roehrig Paul

known as the FANG vendors) seem to have established themselves as the presumptive and eternal winners in this space, history will likely remember them as the precursors to a much more momentous and democratic economic shift. The next wave of digital titans probably won't be characterized by start-ups from Silicon Valley; instead, it will be made up of established companies in more “traditional” industries – in places like Baltimore, Birmingham, Berlin, and Brisbane – that figure out how to leverage their longstanding industry knowledge with the power of new machines.

      We're starting to see this play out as we collectively work to apply systems of intelligence to help address some of our most vexing societal ills in areas where digital technology is not just entertaining or convenient but also life-altering. Certainly, many of our institutions – the pillars of our society and our everyday lives – are ripe for improvement.

      For example, worldwide we lose 1.2 million lives to car accidents annually, with more than 94 % of these accidents a result of human error.7 In the United States alone, these wrecks cost society over $1 trillion. This is nearly one-third the amount the U.S. federal government collects in individual income taxes.8 Driverless cars promise to save countless lives and heartache.

      One-third of all food produced in the world goes to waste. The food wasted in rich countries alone is almost enough to feed all of sub-Saharan Africa.9 By instrumenting the supply chain and applying AI, we could literally feed the world.

      Medical misdiagnoses could also plummet. Right now, 5 % to 10 % of trips to the ER results in a misdiagnosis.10 More than 12 million diagnostic mistakes contribute to 400,000 deaths caused by preventable errors each year, and that's just in the United States.11 Applying data to the diagnostic process could dramatically improve patient outcomes.

      The United States spends more per student on secondary education than most other countries in the world but generates mediocre results. In a recent international study, American students achieved scores far below those in many other advanced industrial nations in science, reading, and math.12 By tailoring lessons to the individual learning style of each student through technology, we could make the education process radically more productive and effective for both students and teachers.

      These are the sorts of big things that we can address with the new machine. It's digital with purpose and digital that matters, and the big brains bringing these innovations forward will not necessarily reside in Silicon Valley or an MIT dorm room. They may well be sitting in an office down the hall at your company.

      For example, McGraw-Hill Education is applying new technology to help teachers and kids improve learning with a system called ALEKS. The artificially intelligent Assessment and LEarning in Knowledge Spaces system uses adaptive questioning to quickly and accurately determine exactly what a student knows and doesn't know in a course. ALEKS then instructs the student on the topics he or she is most ready to learn. As the student works through a course, ALEKS periodically reassesses the student to ensure retention. All of this results in more flexible, one-on-one instruction for students, which boosts student success. And for teachers, ALEKS helps take over some of the more routine – and, let's say it, boring – work to allow them to focus more intently on working with students. Discovery, one of South Africa's leading insurers, uses its Vitality platform to provide economic incentives – discounts on travel, entertainment, healthy food, gym memberships, sports equipment, health products, and the like – to its members based on whether they participate in healthy behaviors. Members earn points by logging workouts with connected fitness devices and purchasing healthy food (also logged by swiping their Vitality card). The insurance sector may not be known as a hotbed of innovation, but Discovery has built a thriving business based on the value derived from the new machine.

      Playing the New Game

      Another area ripe for reinvention is managing our money. Jon Stein doesn't look like a Wall Street Master of the Universe – just the opposite, in fact. In his mid-30s, dressed in blue jeans and a mildly tattered shirt, he works not in a financial citadel but in a relaxed loft-like space. His language is not full of bravado and bombast but is casual, considered, and humble.

      Figure 1.1 Jon Stein, CEO and founder of Betterment

      Yet Stein is turning his corner of the banking world, personal wealth management, on its head. His company, Betterment, has rapidly become one of the world's leading “robo-advisors,” leveraging AI platforms to rewrite the rules of the financial advisory business. Betterment provides highly personalized, curated wealth management services 24x7. His system of intelligence is doing the work of hundreds of people and is doing it better, at a fraction of the cost.

      Millions of investors – millennials, Gen-Xers, and baby boomers alike – are flocking to the platform. From the beginning of 2015 to mid-2016, Betterment's assets under management grew from $1.1 billion to $5.0 billion13,14 and for good reason. Betterment has created a bigger pie for wealth management services because it can attract new customers that traditional banks wouldn't touch. Traditional “bulge-bracket” investment banks (e.g., Goldman Sachs, Morgan Stanley, Credit Suisse, etc.) often do not offer personalized wealth management services to anyone with less than $1 million in assets; the margin isn't there, given their one-to-one advisory business model. So where does that leave the other 99.9 % of the population that is interested in having their money professionally managed?

      Betterment started by focusing on HENRY (high earners, not rich yet). These are young professionals in their 20s and early 30s: lawyers, doctors, and managers starting their careers armed with great educations…and the associated student debt.

      Traditional wealth managers won't touch HENRY, but Betterment welcomes anyone with money to invest. And as each new customer comes on the platform, the system gets smarter, providing better value to each individual participant: on the spot, empirically based, unspun counsel on investment strategy, portfolio allocation, and tax management.

      Robo-advisers, collectively, have more than $50 billion in assets under management today (and are estimated to have over $250 billion under management by 2020) and are taking aim at the $20 trillion worldwide that is currently being managed by 46,000 human financial advisors at traditional banks.15

      Now, we don't know whether Betterment will ultimately emerge as the long-term winner in this new form of financial advisory services, but the company does demonstrate how new machines are disrupting traditional ways of work. Such widespread adoption is creating shock waves in both the financial services and technology industries.

      Stein, and others who have figured out the new game, are nothing short of the Henry Fords of our time. They understand today's new raw materials (big data). They have built and now operate the new machines. And, most important, they have surrounded these new machines with business models that generate remarkable growth and profitability engines while expanding the overall market.

      The story of robo-advisors in wealth management is about to be replayed a thousand-fold across all sectors of our economy. So the question becomes: Will you play, or stand on the sidelines?

      But Will I Be Automated Away?

      We have already proven that we love to consume AI-based products (with our rabid usage of the FANG vendors’ offers on our smartphones). And, through digital that matters, the new machine is poised to transform the primary institutions of our society for the better.

      Yet once we get over our initial awe of the new machine, we start to wonder how it will impact jobs. What will happen to all those bankers, drivers, radiologists, lawyers, and journalists? What will happen to…me? Will a robot take my job?

      Many

7

“Human Error Accounts for 90 % of Road Accidents,” International News, April 2011, http://www.alertdriving.com/home/fleet-alert-magazine/international/human-error-accounts-90-road-accidents.

8

See http://www.rmiia.org/auto/traffic_safety/Cost_of_crashes.asp and http://www.who.int/violence_injury_prevention/publications/road_traffic/world_report/en/ and https://en.wikipedia.org/wiki/United_States_federal_budget.

9

http://www.fao.org/save-food/resources/keyfindings/en.

10

“Surprising Number of Emergency Room Medical Errors,” July 15, 2016, http://philadelphia.cbslocal.com/2016/07/15/surprising-number-of-emergency-room-medical-errors/.

11

http://www.cbsnews.com/news/12-million-americans-misdiagnosed-each-year-study-says/ and http://www.healthcareitnews.com/news/deaths-by-medical-mistakes-hit-records.

12

http://www.cbsnews.com/news/us-education-spending-tops-global-list-study-shows/ and http://www.pewresearch.org/fact-tank/2015/02/02/u-s-students-improving-slowly-in-math-and-science-but-still-lagging-internationally/.

13

“Millennials hire computers to invest their money,” Denver Post, March 4, 2016, http://www.denverpost.com/2016/03/04/millennials-hire-computers-to-invest-their-money/.

14

Julie Verhage, “Robo-Adviser Betterment Hits the $5 Billion Mark,” Bloomberg Markets, July 14, 2016, http://www.bloomberg.com/news/articles/2016-07-14/robo-adviser-betterment-hits-the-5-billion-mark.

15

Melody Hahm, “Robo-advisor Wealthfront is now using AI to manage over $3 billion in assets,” Yahoo! Finance, March 31, 2016, https://beta.finance.yahoo.com/news/robo-advisor-wealthfront-artificial-intelligence-betterment-assets-venmo-205354921.html and Michael P. Regan, “Robo Advisers to Run $2 Trillion by 2020 if This Model Is Right,” Bloomberg, June 18, 2015, http://www.bloomberg.com/news/articles/2015-06-18/robo-advisers-to-run-2-trillion-by-2020-if-this-model-is-right.