Technology Cannot Hug a Customer

The New York Times: “Technology, some hotels are finding, has its limits. ‘Technology cannot hug a repeat guest,’ said George Aquino, the vice president and managing director of AHC+Hospitality … That is the reason his company, which manages several hotels, has been running a training program for some of its managers and other staff members to improve their hospitality skills, connect with local business leaders and learn more about local tourist offerings.”

“Similar programs are sprouting in other cities, involving not just hotels but also restaurants and even cities themselves, which see the personal touch as giving them a competitive edge. For business travelers, in particular, talking to someone knowledgeable about a city can lead to a good restaurant. And it can also help expand business leads.”

“A consulting program based in Tucson, Certified Tourism Ambassadors, trains hospitality workers. Mickey Schaefer, the chief executive and founder, said she had developed the idea in 2006 while working for the American Academy of Family Physicians to plan its conventions. Hospitality workers sometimes did not know their own cities, leading to bad experiences, she said … The program, she said, ‘is more than just helping the customer. It is helping them find the richness of whatever they are interested in.’ She added that the program also instills civic pride.”


Is Ecom a Jobs Engine?

The New York Times: Michael Mandel, an economist, “asserts that the move toward e-commerce is creating more jobs than are being lost in the brick-and-mortar retailing industry — and that these new jobs are paying much higher wages than traditional retail jobs … He says that government numbers and conventional industry classifications don’t properly count all the jobs associated with e-commerce — in particular, the numbers miss large parts of the industry like fulfillment centers and distribution warehouses.”

“Mr. Mandel has combed through the job statistics on a county-by-county basis and come to this counterintuitive view: From December 2007 to May 2017, by his count, the e-commerce industry has created 397,000 jobs in the United States, and this compares with the loss of 76,000 jobs in the traditional retail industry. And those jobs related to e-commerce, he says, pay about 30 percent more than the brick-and-mortar ones.”

“To Mr. Mandel, it’s not that e-commerce jobs are directly replacing traditional retail jobs. Rather, he describes a world in which some of what he calls ‘unpaid household labor’ that we all do when we drive to the mall, park, shop and bring the goods home has been transferred into the labor market.” As for automation and robots, he thinks “it will take longer for them to replace humans than we think.”


Deep Thinking: ‘Artificial’ Trumps ‘Intelligence’

LARB: From a review of Deep Thinking, by Garry Kasparov, the chess champion defeated by Deep Blue, a machine, in 1997: “The history of computer chess is the history of artificial intelligence. After their disappointments in trying to reverse-engineer the brain, computer scientists narrowed their sights. Abandoning their pursuit of human-like intelligence, they began to concentrate on accomplishing sophisticated, but limited, analytical tasks by capitalizing on the inhuman speed of the modern computer’s calculations.”

“This less ambitious but more pragmatic approach has paid off in areas ranging from medical diagnosis to self-driving cars. Computers are replicating the results of human thought without replicating thought itself. If in the 1950s and 1960s the emphasis in the phrase ‘artificial intelligence’ fell heavily on the word ‘intelligence,’ today it falls with even greater weight on the word ‘artificial’ … If a machine can search billions of options in a matter of milliseconds, ranking each according to how well it fulfills some specified goal, then it can outperform experts in a lot of problem-solving tasks without having to match their experience or insight.”

Also: “A bit of all-too-human deviousness was also involved in Deep Blue’s win. IBM’s coders, it was later revealed, programmed the computer to display erratic behavior — delaying certain moves, for instance, and rushing others — in an attempt to unsettle Kasparov. Computers may be innocents, but that doesn’t mean their programmers are.”


Machine Platform Crowd: The Future Today

The Wall Street Journal: Machine Platform Crowd, a new book by Andrew McAfee and Erik Brynjolfsson, “is a book for managers whose companies sit well back from the edge and who would like a digestible introduction to technology trends that may not have reached their doorstep—yet … In the authors’ terminology, ‘Machine’ is shorthand for computers running software that, with new AI techniques called ‘deep learning,’ essentially teaches itself how to make judgments superior to those of humans. ‘Machine’ also encompasses the disappearance of employees in the services sector, leaving only the customer, robots and software—what the authors refer to as ‘virtualization.'”

“‘Platform’ refers to digital environments that bring economic actors together, exploiting free, or nearly free, online access, reproduction and distribution. Uber and Airbnb are examples of new platforms. ‘Crowd’ refers to information resources created by the uncredentialed, the nonexpert and, with rare exceptions, the unpaid. Wikipedia and the Linux operating system comprise the two most impressive achievements of the crowd.”

​”Messrs. McAfee and Brynjolfsson argue that, in the latest phase of the second machine age, incumbent businesses will be pushed aside if they fail to understand how new machines and software, platforms, and the crowd enlarge the scope of digital technologies—just as manufacturers that had appeared and thrived in the first phase of the first machine age were displaced when electricity supplanted steam power in the early 20th century.”


Quantumobiles: VW Catches D-Wave

The New York Times: “Efforts by Volkswagen, trying to remake itself as a technology leader as it recovers from an emissions scandal, show how far into exotic realms of technology carmakers are willing to go. Volkswagen, a German company, recently joined the handful of large corporations worldwide that are customers of D-Wave Systems, a Canadian maker of computers that apply the mind-bending principles of quantum physics.”

“While some experts question their usefulness, D-Wave computers — housed in tall, matte black cases that recall the obelisks in the science fiction classic 2001: A Space Odyssey — can in theory process massive amounts of information at unheard-of speeds … While classical computers are based on bits with a value of either 1 or 0, the qubits in a quantum computer can exist in multiple states at the same time. That allows them, in theory, to perform calculations that would be beyond the powers of a typical computer.”

“This year Volkswagen used a D-Wave computer to demonstrate how it could steer the movements of 10,000 taxis in Beijing at once, optimizing their routes and thereby reducing congestion … Such claims are met with skepticism by some experts, who say there is no convincing proof that D-Wave computers are faster than a well-programmed conventional supercomputer … Volkswagen executives say they will publish the results of their work with D-Wave computers, allowing outsiders to try to debunk them.”


Robo-Shop: Will Cashiers Cash Out?

The New York Times: Our mental image of job-killing automation is robots in factories or warehouses. But the next jobs to disappear are probably ones that are a much bigger part of most people’s daily lives: retail workers and cashiers in stores and restaurants … Half the time worked by salespeople and cashiers is spent on tasks that can be automated by technology that’s currently in use, according to a recent McKinsey Global Institute report. Two-thirds of the time on tasks done by grocery store workers can be automated, it said.”

“Retailers say automating certain tasks doesn’t necessarily displace employees, but frees them to do other things that are more valuable to customers. Lowe’s, for instance, said its customer service robot answered simple questions so employees could provide more personalized expertise, like home project planning … But shoppers often prefer to save time by interacting with fewer people, especially when they just need coffee or paper towels.”

Erik Brynjolfsson, director of the M.I.T. Initiative on the Digital Economy, comments: “The bigger and more profound way that technology affects jobs is by completely reinventing the business model. Amazon didn’t go put a robot into the bookstores and help you check out books faster. It completely reinvented bookstores. The idea of a cashier won’t be so much automated as just made irrelevant — you’ll just tell your Echo what you need, or perhaps it will anticipate what you need, and stuff will get delivered to you.”


‘Amazon Charts’ Re-Define ‘Best Seller’

The New York Times: Amazon now tracks “not only the top-selling digital and print books on Amazon, but the ones that customers spend the most time reading … With its lists, Amazon aims to redefine the notion of a best seller, expanding it to include books that are ‘borrowed’ from its e-book subscription service, and ones that are streamed on Audible. As a result, the lists give increased visibility to books that might not typically appear on other best-seller lists.”

“All of Amazon’s acquisitions and new features are having a cumulative effect, allowing the company to draw on its vast customer base and troves of data to discover what is popular, and return that information to customers, creating a lucrative feedback loop … Crowdsourcing and data mining are also driving the company’s approach to its bookstores, which act as showcases for books popular with customers on the site. While the stores have traditional categories, like fiction, nonfiction and travel, the most eye-catching shelves feature categories culled from Amazon’s customer data.”

“The first thing customers see when they walk into the store is a large display table, labeled Highly Rated, which includes books with an average rating of 4.8 stars or higher on a scale of 5 … Another display case, labeled Page-Turners, features books that people finish reading on their Kindle in fewer than three days … Another section features the most ‘wished for’ books from Amazon’s website … The books are all displayed face out. Under each book is a card with the average customer rating, the number of reviews and a featured review from an Amazon reader. Displaying the full cover of each book mimics the visual look of Amazon’s website, and might lure customers to unfamiliar titles.”


Not SeeFood: App Apes ‘Shazam for Food’

The Verge: “In a peculiar case of life imitating art imitating life, Pinterest has announced a new recipe-finding feature that makes use of computer vision to tell you about a dish when you point your smartphone camera at it … It sounds an awful lot like SeeFood, the fake ‘Shazam for food’ app from the HBO comedy Silicon Valley. Pinterest, of course, doesn’t use that terminology anywhere, nor does its marketing material even reference the sitcom or its ludicrous parody, which manifested itself as an app that could only tell you whether an object was or was not a hotdog.”

“When reached for comment regarding SeeFood, a Pinterest representative confirmed to The Verge that the Silicon Valley episode was ‘separate and completely coincidental’.”

“This is all part of a broader artificial intelligence push in the tech industry to apply machine learning techniques to everyday life. By training neural networks on huge mounds of data and translating that into a real-time algorithm, tech giants like Google, Facebook, and Microsoft are now developing software products that can digest and understand the world, from text to photos to even videos.”


The Stitch Fix Secret: Make Shopping Easy

The New York Times: Stitch Fix is a mail-order clothing service that offers customers little choice in what garments they receive, and shies away from discounts for brand name dresses, pants and accessories. Despite a business model that seems to defy conventional wisdom, Stitch Fix continues to grow … To the company’s founder, Katrina Lake, success comes down to delivering what consumers want: making it easier to shop … In her view, what was important was helping customers find clothing they liked without taking lengthy shopping trips and returning dozens of items.”

“At the company’s warehouse, Eric Colson, formerly a top data scientist at Netflix, spoke to the role that data science — once the province of high-tech giants — plays in nearly every aspect of the Stitch Fix business. Mr. Colson excitedly illustrated on whiteboards how the company’s systems can narrow down a broad range of women’s pants to a relative few that each individual customer is statistically likely to keep … Algorithms have even cut the number of steps needed for workers to pick out clothes for individual clients.”

“Yet the question remains whether customers who are initially thrilled by receiving a customized box of clothing will remain customers for months or even years … Stitch Fix executives declined to share their retention statistics, but claim that they are above industry averages.”


Algorithmic Retail: Beyond Dynamic Pricing

The Wall Street Journal: “Advances in A.I. are allowing retail and wholesale firms to move beyond ‘dynamic pricing’ software, which has for years helped set prices for fast-moving goods, like airline tickets or flat-screen televisions. Older pricing software often used simple rules, such as always keeping prices lower than a competitor.”

“These new systems crunch mountains of historical and real-time data to predict how customers and competitors will react to any price change under different scenarios, giving them an almost superhuman insight into market dynamics. Programmed to meet a certain goal—such as boosting sales—the algorithms constantly update tactics after learning from experience … The software learns when raising prices drives away customers and when it doesn’t, leading to lower prices at times when price-sensitive customers are likely.”

“Algorithms can also figure out what products are usually purchased together, allowing them to optimize the price of a whole shopping cart. If customers tend to be sensitive to milk prices, but less so to cereal prices, the software might beat a competitor’s price on milk, and make up margin on cereal.”