Thank You for Being Late

by Thomas L. Friedman

  The Khan–College Board collaboration is really worth studying because it’s a microcosm of how we can beat the bots—how we can make the transition to a different education-to-work-to-lifelong-learning social contract in the age of accelerations. There are three basic ingredients of the Khan–College Board revolution: (1) More will be on you, and you’d better take ownership of that fact and seek out intelligent assistants and assistance everywhere that you can; (2) precisely because more is on you, government and social organizations need to get serious about providing you not just any tools, but much better tools—informed by artificial intelligence tailored exactly for you and your needs and reinforced by a caring adult or coach, wherever possible; and (3) technology can take you only so far. Concentration also matters. Coleman likes to say that today the “technology of interruption has outpaced the technology of concentration.” Students need to learn the discipline of sustained concentration more than ever and to immerse themselves in practice—without headphones on. No athlete, no scientist, no musician ever got better without focused practice, and there is no program you can download for that. It has to come from within.

  If you come, they will build it—turning AI into IA is only going to get more efficient every year. “In the old days someone would publish a calculus textbook and get no data and no feedback on what is working for people and what is not,” explained Sal Khan. So they spent the next five years just changing page numbers. Today, he said, Khan Academy can put up a set of calculus tutorials and see within hours which ones are the most effective in helping students come up with the right answers, iterate immediately, and start scaling the best tutorials globally within a few more hours. The ability to refine content and make it better at scale is staggering.

  “Having high literacy rates was an accelerant for growth of the developed world, but now imagine we have an accelerant for the developing world”—where instead of 5 percent being able to participate and then contribute, you have 50 percent, Khan added. Young people who are motivated to learn can now go to Khan’s platform and go as fast as they want, and some have started to go very, very fast.

  Said Khan: “There is no ceiling anymore.”

  The Brilliant Janitor

  Intelligent assistants are not simply websites you can access. They are also portable tools that can turn AI into IA in remarkable new ways so that so many more people, no matter how educated or dexterous, can live above the average adaptability line—and even thrive there.

  Consider what it is to be a janitor today at the Qualcomm campus in San Diego. Hint: thanks to intelligent assistants, it’s become a knowledge worker job. Ashok Tipirneni, director of product management for Qualcomm’s Smart Cities project, explained to me why: Qualcomm has created a business in showing companies how they can retrofit wireless sensors to every part of their buildings in order to generate a real-time, nonstop sort of EKG or MRI of what is going on deep inside every one of their buildings’ systems. To create a demonstration model, Tipirneni started with six buildings at Qualcomm’s Pacific Center Campus in San Diego, which included parking garages, office spaces, and food courts; the area was about a million square feet in total and used by about 3,200 people. They retrofitted small, self-powered, clip-on sensors to transmit all their data—from doors, trash cans, bathrooms, windows, lighting systems, heating systems, wires, chillers, and pumps—to a receiver on the campus. The receiver sends all the data up to the supernova to be stored, analyzed, and turned into intelligent advice for the building maintenance men. “We didn’t have to break open a single wall,” said Tipirneni.

  The first result was significant savings. Labs started competing with one another over who could save the most. “We discovered that a lot of the energy use was coming out of PCs in labs, and just by putting the PCs in hibernate mode in six buildings when they were not being used is projected to save roughly a million dollars a year—it was shocking [to find] such an easy fix,” said Tipirneni. “This data is giving us those insights—it’s amazing.”

  But the fun part is that they started to stream all the data into icons on a tablet and then outfitted each of their maintenance men with one. The minute a leak or short happens or a valve is left open, it shows up on the tablet. And if something breaks the tablet will immediately display the repair manual. If something breaks or leaks that the maintenance team doesn’t know how to fix, they take a picture of it with their tablet. “The system will know that this part in this building is connected to a pipe on the fourth floor and that floor is assigned to this technician, and it automatically sends a ticket to him to fix it,” said Tipirneni. “The device will know exactly where the pipe is behind the drywall,” so there is no need to guess where to make the hole. “You save time and money and use only what you need in the most efficient way. And then you use the time saved from treating symptoms to fix root causes.”

  Qualcomm is putting these sensor clips on all forty-eight buildings in San Diego. Suddenly the building maintenance guys “got converted to data engineers, which is exciting for them,” added Tipirneni. They made sure the data was “distilled in a way that is easy for them to understand and be actionable. In the old days, when a facilities manager looked at a building, he would say: “If there is a leak someone will call me or I will see it.” They were reactive. Now, says Tipirneni, “We trained them to look at signals and data that will point them to a leak before it happens and causes destruction. They did not know what data to look at, so our challenge was [to] make sensor data easy for them to make sense of, so we don’t overwhelm them with too much data and just say ‘You figure it out.’ Our goal was, ‘We will give you information you can use.’”

  “The cognitive load is too much,” he added, “and technology has to reduce that cognitive load on the user. Everyone will need and everyone will have a personal assistant.”

  The maintenance team now feel more like building technicians, not just janitors. “They feel it is a step up,” said Tipirneni. “They got very excited about the interfaces.”

  And the best part, he added: “We had forty officials from four different cities in for a demo, and some of the maintenance people here presented it and they showed what they learned, and it struck a chord with the city officials. They were confident enough to talk about these things in a matter of a few months.”

  That is what an intelligent assistant can do.

  Intelligent Algorithms

  I could tell you why intelligent algorithms are so valuable for the world of work in the age of accelerations, but I would rather just tell you the story of how LaShana Lewis, a computer server engineer with MasterCard, got her job. I got to know Lewis at a panel discussion on how to “re-wire the U.S. labor market,” organized by Opportunity@Work.

  Lewis, an African American woman, now age forty, was born to a single mom (who was herself just fifteen years old when she had LaShana) in East St. Louis, Illinois. “My mom was on welfare, and we lived in public housing. Everyone around us was on welfare. We did not have many resources at home; there were no computers in the schools, which were funded with property taxes.” But Lewis discovered early in life that she “had a knack for fixing things.” So whatever broke around the house—from toasters to sinks—she would repair herself. Once she hit high school, where they had computers, she dived into the computer science course; she ended up tutoring other students and catching the eye of the teacher, who told her: “You need to go to college and study computers.” She got a scholarship to attend Michigan Tech, but even with the scholarship she did not have enough to support herself and dropped out after three and a half years—without a degree. She would have graduated in 1998.

  “So I came back home and tried to get a job in computing, but I was blocked every time,” said Lewis. “People asked if I had graduated, and I would not lie and said ‘no,’ so I got a job driving black kids back and forth to a supplemental tutoring program from the high school I went to in East St. Louis to the local community college. So I am driving the van, a
nd one day the computer science tutor at this tutoring program quits. So they asked me to fill in, which I did. And at the end of the month, I asked if I could do the job full-time and they said, ‘No, you don’t have a degree.’ So after that frustration, I went to a hiring firm and they got me into a help desk.” She worked at help desks for ten years, helping knuckleheads like me reset their passwords and the like.

  Her break came while she was working at the help desk at Webster University in St. Louis, when a colleague and faculty member saw just how talented she was. (She was constantly hanging around with the IT team, working as a backup technician.) One day, while Lewis was taking a refresher course on computing at Webster, her professor, who’d learned about a new intelligent assistant—LaunchCode.org—told Lewis to check it out. LaunchCode’s aim is to help “you find the best resources online and in your community to prepare yourself for a job in tech.” Its promise is: “Don’t sweat your credentials, just show us what you can do. Apply online for a LaunchCode apprenticeship and we will help you grow your skills and passion for tech, while matching you with mentors and providing feedback on your progress. LaunchCode matches you with one of our 500 employer partners for a paid apprenticeship, typically twelve weeks long. Hone your skills on the job, learning from experienced developers. Nine out of ten apprentices are converted to full-time hires.”

  Lewis signed on with LaunchCode in June 2014 and was hired by MasterCard in St. Louis as an apprentice in September of that year and promoted to full-time assistant systems engineer by November, helping the credit card company manage its giant server network. In March 2016, she was promoted to systems engineer.

  And as Lewis told me with a twinkle in her eye, “I still don’t have my BA.”

  Roughly estimated, there are about thirty-five million LaShana Lewises in America today who started college but never finished. Imagine how much more productive we could be as a country if we could find ways to value and capture the learning those thirty-five million have. We simply cannot continue with this binary system of degree or no degree, where the key to inclusion is pedigree and not what you actually know and can actually do. The emergence of intelligent algorithms and networks such as LaunchCode, which can be used by employers as trusted validators to sow people into the system and not weed them out of it, holds the promise of unlocking a lot of wasted talent.

  Says Lewis: “If you can do the job, you should get the job.”

  Fortunately, intelligent algorithms and intelligent networks are emerging and enabling a new social contract. There are actually a lot of people who have the skills certain employers are seeking, but may not have the traditional credentials to be appreciated. There are many people who would be happy to learn those skills but don’t have the information on what they are or access to learning platforms, some of which are unconventional and not covered by traditional government loans. There are employers who have employees with the skills—or the aspiration to acquire the skills—for new jobs, but the employers don’t know who they are or are not currently set up to offer them online training opportunities. And there are schools that are actually great at teaching those skills, but no one knows which schools do that the best.

  As we develop more intelligent algorithms “to overcome these labor market failures,” argued Byron Auguste, we can put so many more people to work—work better aligned to their talents that contributes more to our economy and society—no matter how many machines and robots are out there. These intelligent algorithms or networks are called “online talent platforms.”

  At the high end of the labor ladder, professionals already have a global intelligent algorithm to draw on: LinkedIn, the career professional social networking site. But its founders now want to extend that intelligent algorithm to the whole world of work by creating a global “economic graph.” Here is how LinkedIn’s CEO, Jeff Weiner, describes it on his company blog:

  Reid Hoffman and the other founders of LinkedIn initially created a platform to help people tap the value of their professional networks, and developed an infrastructure that could map those relationships up to three degrees. In doing so, they provided the foundation for what would eventually become the world’s largest professional graph.

  Our current long-term vision at LinkedIn is to extend this professional graph into an economic graph by digitally manifesting every economic opportunity [i.e., job] in the world (full-time and temporary); the skills required to obtain those opportunities; the profiles for every company in the world offering those opportunities; the professional profiles for every one of the roughly 3.3 billion people in the global workforce; and subsequently overlay the professional knowledge of those individuals and companies onto the “graph” [so that individual professionals could share their expertise and experience with anyone].

  Anyone will be able to access intelligent networks such as LinkedIn’s global graph, see what skills are in demand or available, and even offer up online courses. You might teach knitting or editing or gardening or plumbing or engine repair. So many more people will be incentivized to offer their expertise to others, and the market for it will be vastly expanded.

  Added Weiner:

  With the existence of an economic graph, we could look at where the jobs are in any given locality, identify the fastest growing jobs in that area, the skills required to obtain those jobs, the skills of the existing aggregate workforce there, and then quantify the size of the gap. Even more importantly, we could then provide a feed of that data to local vocational training facilities, junior colleges, etc., so they could develop a just-in-time curriculum that provides local job seekers the skills they need to obtain the jobs that are and will be, and not just the jobs that once were.

  Separately, we could provide current college students the ability to see the career paths of all of their school’s alumni by company, geography, and functional role.

  For instance, go to linkedin.com/edu. LinkedIn has studied its hundred-million-worker database to determine which schools seem to be launching more graduates into the top companies in various professional fields. You might be surprised: Accounting? Villanova and Notre Dame. Media? New York University and Hofstra. Software developers? Carnegie Mellon, Caltech, and Cornell. Whether you want to be a plumber or a surgeon, it is valuable to know which schools’ alums keep rising at the leading companies.

  LinkedIn is already busy building its graph, starting with several pilot cities, and if it succeeds in creating such an intelligent algorithm for the whole world one day, it will be a hugely valuable achievement. But how do we offer an intelligent tool like that for the half of the labor market not yet networked like LinkedIn professionals? That question is a reason LinkedIn’s cofounder Reid Hoffman is one of the main backers of the intelligent algorithm Opportunity@Work, headed by Auguste and Karan Chopra, which is trying to fix the lower end of the labor market, from whence LaShana Lewis emerged, and where there are even bigger “talent arbitrage” opportunities to be found.

  There are too many people like Lewis who have developed skills on their own but don’t necessarily have the certificates, badges, or degrees that employers have grown accustomed to relying upon in hiring—way too accustomed in an era when people have so many more options to learn on their own.

  Opportunity@Work is trying to solve this problem by working at the community level to create intelligent networks that help employers who are ready—even desperate—to hire anyone who can effectively do the tech jobs that they need filled. Many employers say that college degrees don’t come with the skills they need—yet the screening tools they use for hiring mean that many people who have those skills are currently overlooked because they lack the diplomas or degrees or badges to prove it.

  If someone has the skills—but not the academic pedigree or professional résumé—to be an IT systems administrator or web developer, Opportunity@Work tests them out on its TechHire.org platform, certifies their mastery of skills for various tech occupations, then connects them with the right employers
or the right training to earn or learn more.

  “We have to move to more hiring based on mastery, not history,” argued Chopra. “We can steepen the slope of the learning curve, but if that learning and those skills are not recognized in the labor market, there is no incentive and no payoff.” Too many companies today are investing in screening software to keep people out, based on pedigrees, rather than learning and matching software that could tap everyone’s highest and best use.

  How crazy is that? Here’s an interesting data point from a 2015 labor survey by Burning Glass Technologies: 65 percent of new job postings for executive secretaries and executive assistants now call for a bachelor’s degree, but “only 19% of those currently employed in these roles have a B.A.” So four-fifths of secretaries today would be barred from being considered for two-thirds of the job postings in their own field because they don’t have a degree to do the job they’re already doing.

  Message from employers: if you’re a working secretary today without a BA and want to change jobs, another employer will consider you, but first you need to quit, go into debt for eighty thousand dollars to get a BA, and then interview for another opening for the exact job you are already doing. Welcome to the American job market today, where, Burning Glass notes, an “increasing number of job seekers face being shut out of middle-skill, middle-class occupations by employers’ rising demand for a bachelor’s degree” as a job-qualifying badge, even though it may be irrelevant to the job or your true capabilities.