The “most advanced transit city in the west” is having growing pains.
The Mile High city punches above its weight when it comes to mass transit: Denver boasts the eighth-largest rail system in the United States, radiating out of what’s only the 19th most populous town.
That’s because of FasTracks. In 2004, with the hopes to cool congestion and brace for growth, Denver and communities in seven surrounding counties voted to expand public transit to the tune of $4.7 billion, adding 122 miles of commuter, light rail, and bus rapid transit lines across the region by 2018.
Since then, the Regional Transportation District has undergone a transformation: Where once only a few rail lines served a handful of suburbs, train tracks and BRT corridors now extend in all directions, from Boulder (28 miles northwest from Denver’s downtown) to Aurora (11 miles east) to Jefferson County (26 miles west), with Denver’s downtown Union Station serving as the central hub. Seven projects are complete, and five are still on the way.
But the expansion plan, which caused CityLab to once dub Denver “the most advanced transit city in the west,” has yet to translate into greater transit ridership, or even reduced use of cars. In 2006, then-mayor of Denver John Hickenlooper described a hope that the city would reach 20 percent ridership by 2020. But in 2016, only 6 percent of people in Denver used public transit as part of their commute to work.
In her powerful new book, “Nomadland,” award-winning journalist Jessica Bruder reveals the dark, depressing and sometimes physically painful life of a tribe of men and women in their 50s and 60s who are — as the subtitle says — “surviving America in the twenty-first century.” Not quite homeless, they are “houseless,” living in secondhand RVs, trailers and vans and driving from one location to another to pick up seasonal low-wage jobs, if they can get them, with little or no benefits.
The “workamper” jobs range from helping harvest sugar beets to flipping burgers at baseball spring training games to Amazon’s AMZN, -0.33% “CamperForce,” seasonal employees who can walk the equivalent of 15 miles a day during Christmas season pulling items off warehouse shelves and then returning to frigid campgrounds at night. Living on less than $1,000 a month, in certain cases, some have no hot showers. As Bruder writes, these are “people who never imagined being nomads.” Many saw their savings wiped out during the Great Recession or were foreclosure victims and, writes Bruder, “felt they’d spent too long losing a rigged game.” Some were laid off from high-paying professional jobs. Few have chosen this life. Few think they can find a way out of it. They’re downwardly mobile older Americans in mobile homes.
Last weekend, in the hours after a deadly Texas church shooting, Google search promoted false reports about the suspect, suggesting that he was a radical communist affiliated with the antifa movement. The claims popped up in Google’s “Popular on Twitter” module, which made them prominently visible — although not the top results — in a search for the alleged killer’s name. Of course, the was just the latest instance of a long-standing problem: it was the latest of multiple similar missteps. As usual, Google promised to improve its search results, while the offending tweets disappeared. But telling Google to retrain its algorithms, as appropriate as that demand is, doesn’t solve the bigger issue: the search engine’s monopoly on truth.
Surveys suggest that, at least in theory, very few people unconditionally believe news from social media. But faith in search engines — a field long dominated by Google — appears consistently high. A 2017 Edelman survey found that 64 percent of respondents trusted search engines for news and information, a slight increase from the 61 percent who did in 2012, and notably more than the 57 percent who trusted traditional media. (Another 2012 survey, from Pew Research Center, found that 66 percent of people believed search engines were “fair and unbiased,” almost the same proportion that did in 2005.) Researcher danah boyd has suggested that media literacy training conflated doing independent research with using search engines. Instead of learning to evaluate sources, “[students] heard that Google was trustworthy and Wikipedia was not.”
Americans are wary of driverless cars — 56 percent, according to the Pew Research Center, would prefer not to ride in one — and when I talked to Brewer, it occurred to me that some part of that hesitation might stem from who we assume will be producing them: Silicon Valley tech giants, the same stateless behemoths that have spent the last few decades barging into old-line industries like the Kool-Aid Man, destroying working-class jobs and leaving behind cold, modern efficiency. But maybe these skeptics could be persuaded to trust Detroit. After all, Brewer is right — self-driving cars aren’t smartphones. They’re two-ton projectiles that take your parents to the grocery store and your kids to soccer practice, that will need to make billions of computational decisions per second while moving at 65 miles per hour, that contain within them the power to extinguish human life. You kind of want them to take a while.
Leading Ford into this weird new era is Jim Hackett, who was named chief executive in May. Hackett, 62, is an oddity by Detroit standards. A design-minded aesthete in an industry dominated by gearheads and number crunchers, he spent two decades running Steelcase, a Michigan-based office-furniture company whose designers are often credited with — or blamed for — popularizing the open-plan office trend.
At a conference several years ago, Hackett struck up a conversation with Ford’s executive chairman, William Clay Ford Jr., who goes by Bill. He is the great-grandson of Henry Ford, and another auto-world misfit — an outspoken environmentalist who once ruffled feathers at Ford by speaking at a Greenpeace event. The two bonded over their shared vision of “smart mobility,” a fuzzy term, more common among urbanists than businesspeople, for creating a sort of harmony among land use, technology and transportation of all forms. Hackett joined Ford’s board of directors in 2013. In 2016, Bill Ford persuaded Hackett to lead Ford’s newly created smart-mobility unit, and about a year later, he tapped him to run the entire company.
Where are the Keys to the Kingdom?
Here below is a memo written by an auto industry veteran. He is offering special counsel to the US trade negotiators. The seasoned executive believes that getting China to open up requires tough talk. Open up or America will impose the same set of restrictive rules on Chinese firms in America that American firms face in China.
Call it good old-fashioned reciprocity.
This excerpt below comes from American Wheels, Chinese Roads, the book I authored in 2011.
The so-called retail apocalypse has become so ingrained in the U.S. that it now has the distinction of its own Wikipedia entry.
The industry’s response to that kind of doomsday description has included blaming the media for hyping the troubles of a few well-known chains as proof of a systemic meltdown. There is some truth to that. In the U.S., more than 3,000 stores did open in the first three quarters of this year.
Store Openings and Closings
Excluding grocery stores and restaurants
Starting your own business is about creating value for your customers. Technological advances will create massive value for users in every industry. Most of the past 2000 years were the agricultural era, and the development of technology and society was so low that it was impossible for the average person with life expectancy of 50 to 70 years to witness any significant advancement in technology, so it is only reasonable that there have been no waves of start-up in the past.
Few events in history had as much an impact as the Industrial Revolution and the Internet Revolution. So, it is no wonder that both eras witnessed a spate of innovations and start-ups. Right now, there is nothing as influential as the Internet. Artificial intelligence is dominating the second round of the Internet Revolution, and in the future we might see more advancements in life sciences and space technology.
The Internet is meant to connect. Through connections, efficiency is improved, and value is created and distributed through the industries. Taobao stands for connecting people with products, Baidu for connecting people with information, and Tencent for connecting people with one another… And I hope when people talk about connecting people with cars, they will think of DiDi. Connections form platforms, which then collect big data, and as a result we look to artificial intelligence to be more efficient in utilizing these data. This is why AI is the second round of the Internet Revolution.
This research identifies a new source of failure to make accurate affective predictions or to make experientially optimal choices. When people make predictions or choices, they are often in the joint evaluation (JE) mode; when people actually experience an event, they are often in the single evaluation (SE) mode. The “utility function” of an attribute can vary systematically between SE and JE. When people in JE make predictions or choices for events to be experienced in SE, they often resort to their JE preferences rather than their SE preferences and overpredict the difference that different values of an attribute (e.g., different salaries) will make to their happiness in SE. This overprediction is referred to as the distinction bias. The present research also specifies when the distinction bias occurs and when it does not. This research contributes to literatures on experienced utility, affective forecasting, and happiness.
In real life, in the natural course of conversation, it is not uncommon to talk about a person you may know. You meet someone and say, “I’m from Sarasota,” and they say, “Oh, I have a grandparent in Sarasota,” and they tell you where they live and their name, and you may or may not recognize them.
You might assume Facebook’s friend recommendations would work the same way: You tell the social network who you are, and it tells you who you might know in the online world. But Facebook’s machinery operates on a scale far beyond normal human interactions. And the results of its People You May Know algorithm are anything but obvious. In the months I’ve been writing about PYMK, as Facebook calls it, I’ve heard more than a hundred bewildering anecdotes:
The emergence in the United States of large-scale “megaregions” centered on major metropolitan areas is a phenomenon often taken for granted in both scholarly studies and popular accounts of contemporary economic geography. This paper uses a data set of more than 4,000,000 commuter flows as the basis for an empirical approach to the identification of such megaregions. We compare a method which uses a visual heuristic for understanding areal aggregation to a method which uses a computational partitioning algorithm, and we reflect upon the strengths and limitations of both. We discuss how choices about input parameters and scale of analysis can lead to different results, and stress the importance of comparing computational results with “common sense” interpretations of geographic coherence. The results provide a new perspective on the functional economic geography of the United States from a megaregion perspective, and shed light on the old geographic problem of the division of space into areal units.
“Karen,” who prefers that we don’t use her last name, lives in a Silicon Valley Hooverville: a line of Jaycos and Winnebagos, Pace Arrows and Tiogas, parked along the side of El Camino Real. Spanish explorers blazed the trail (its name translates to “the royal highway”) to connect their missions as they were colonizing early Alta California; now the road runs amid the luxe campuses of tech companies, spreading their own kind of cultural hegemony.
In this stretch through Palo Alto, six lanes of suburban traffic whizz by Stanford’s manicured soccer fields, stadium, and wooded jogging paths. Like much of Silicon Valley, the area somehow feels both harried and tranquil, a pastoral pressure cooker that squeezes out anyone who can’t keep pace with its strangulating cost of living. Those inside the RVs are reminded of how they’re being left behind by each passing car that oh-so-slightly jars their home. Whoosh. Whoosh. “It’s like getting hit in the head,” as one resident puts it. “Not real hard—but just hard enough, to where you just want it to stop.”
Over the last year, many companies have ended their liberal work-from-home policies. Firms like IBM, Honeywell, and Aetna joined a long list of others that have deemed it more profitable to force employees to commute to the city and work in a central office than give them the flexibility to work where they want. It wasn’t supposed to be this way—at least according to Norman Macrae.
In 1975, when personal computers were little more than glorified calculators for geeks and the Internet was an obscure project being developed by the United States government, Macrae, an influential journalist for The Economist who earned a reputation for clairvoyant prophesies—including the fall of the Soviet Union and the rise of Japan—made a radical prediction about how information technology would soon transform our lives.
Macrae foretold the exact path and timeline that computers would take over the business world and then become a fixture of every American home. But he didn’t stop there. The spread of this machine, he argued, would fundamentally change the economics of how most of us work. Once workers could communicate with their colleagues through instant messages and video chat, he reasoned, there would be little coherent purpose to trudge long distances to work side by side in centrally located office spaces. As companies recognized how much cheaper remote employees would be, the computer would, in effect, kill the office—and with that our whole way of living would change.
Making a city where most trips are done on bikes requires utterly discarding conventional car-centric ways of thinking about transportation. Over the last 60 years, Amsterdam’s leaders, planners and designers have by trial and error created a template for a city where bikes are the dominant force in transportation planning and design. That template has five essential characteristics; skip or short-change any one of them and your city of bikes won’t work as well.
1. All streets are bike streets
In most cities, the network of bicycle tracks and lanes is far sparser than the overall street network for vehicular traffic. In Amsterdam, the street network map is the bike network map. Almost all streets in the city have excellent bike facilities of one type or another. What is extraordinary is that in Amsterdam you are more likely to need a specialized car map than a bike map, since many streets have limited or no car access.