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When we consider the subway, its often for reasons that have to do with decay and deterioration. The switches are outdated. The elevators are broken. The train is late (again). Of course it could be better, but rarely do we pause to take in what the system does right. Its 25 lines, 472 stations, and 665 miles of track traverse the city and offer a tremendous amount of mobility. And now, a new digital installation at the Fulton Street subway station by the information designer Giorgia Lupi and her team at Pentagram pays tribute to the system. [Photo: courtesy Pentagram] Sometimes adults lose the ability to see magic in mundane things and to treat what we experience every day with a bit of wonder and romance, Lupi says. She translated those feelings into the installation, a two-minute animation of the New York City Transit lines. [Image: courtesy Pentagram] Inspired by Craigslist Missed Connections and the citys open data portal, A Data Love Letter to the Subway, as its titled, appears on 50 screens throughout the station, which are normally used for advertising, and plays every hour on the hour through December. Theres such an incredible world if you think about the subway, Lupi says. I wanted to create a story and to almost give a bit of a personality, like a character in a childrens book, to those lines. They thread this beautiful system that sits underneath us and that we use every day. [Photos: courtesy Pentagram] The graphics show where the trains travel, converge, and go their own ways as well as various facts about the system, from the age and length of lines to the ones that go above ground or never see the sun. Lupi has turned this information into a charming animation that makes visible what most New Yorkers take for granted. I have this little bit of a curse that I see data everywhere, Lupi says. [Image: courtesy Pentagram] Since the screens are of various sizes, Lupi and her team created slightly different animations to fit the frames. At a few moments during the film, they all converge. Lupi compares the experience to dance choreography where individuals have their solos, but then become synchronized. She and her team stuck to a mostly black-and-white palette and minimalist graphics to depart from the cacophonous images that usually show up on the stations screens. To stop someone when everything is shouting for their attention, simplicity can be remarkably effective. The installation also commemorates the MTA Arts & Design programs 40th anniversary; three additional four-month digital installations will appear across Fulton Center over the next 12 months. [Image: courtesy Pentagram] So far, the installation has been received warmly. A former coworker just wrote to me: Oh my gosh, am I crying thinking about trains, spending time together?! Lupi says. Its niceand not because we need more tears or more moments of hard feelingsto remind ourselves that there are different ways of seeing pretty much everything.
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E-Commerce
Ever had a song you couldnt get out of your head? That happened to me the other day. Pink Pony Club. Its everywhere right now; I cant escape it. And even though I really dont like that song, its catchy. And as youve probably experienced, once you get a song like that stuck in your head, it can feel impossible to get out. What you might not know is theres a scientific reason for this: Its called ironic process theory. Or, you may have heard it by its more common name: The white bear problem. But theres a tried and tested brain hack that helps you to get a song out of your head. Whats more, you can use it to replace negative or harmful thoughts with positive, helpful ones. With enough practice, you can change your entire mindset. I like to call this method the Blue Dolphin Rule. What is the Blue Dolphin Rule, and why is it so helpful? How can you use it to hack your brain and change your thinking from harmful to helpful? To answer those questions, lets go back to the white bear problem. The White Bear Problem The white bear problem was popularized by Harvard psychologist Daniel Wegner in the late 1980s. Also known as ironic process theory, Wegners problem stated that attempts to suppress thoughts can actually increase their frequency. Wegner based the name on a quote in an essay by Russian writer Fyodor Dostoevsky from over a century ago: Try to pose for yourself this task: not to think of a polar bear, and you will see that the cursed thing will come to mind every minute. Over the course of a decade, Wegner discovered that at least part of the reason why this happens. While we try our best to avoid a thought with one part of the mind, another part of us keeps checking in to make sure the thought isnt coming up. Wegner described this as an ironic process. That helps explain why I cant get Pink Pony Club out of my head. Also, why you may struggle to push out anxious thoughts or limiting beliefs. But theres a way to conquer your white bears, and it involves emotional intelligence, the ability to understand and manage emotions. Enter the blue dolphin. Using Blue Dolphins to Stop Negative Thoughts Over time, Wegner and other researchers found a trick to reduce the rebound of unwanted thoughts. Instead of trying not to think of something, you have to intentionally focus your mind on a completely different thought. For example, instead of a white bear, try to think of a blue dolphin. A blue dolphin is a substitute thought. Its a replacement, or go-to, something you can immediately focus attention on if your white bear comes to mind. In psychology, this emotional regulation technique is known as thought replacement or thought substitution. For example, if Pink Pony Club is ringing around in my head, Ive got to start singing another catchy song. As I shift my attention and go all in with my new song, Pink Pony Club fades into the background . . . and eventually disappears. You can do the same with your negative thoughts. Before a presentation, do you keep thinking to yourself: Im so nervous? Try telling yourself repeatedly: This is going to be over in 30 minutes, and by next week I wont even be thinking about it. Or maybe youre down because a product launch did much lower numbers than you expected. Remind yourself: Products take time to get right. Lets work on improving this version and try again. See how it works? Every time you think of a blue dolphin, write it down or record it in a note on your phone. Eventually, youll have a collection of replacement thoughts you can use whenever you need them. Use your dolphins Remember, white bears have a tendency to keep coming back. But emotional intelligence means recognizing that, while you dont have control over a thought entering your mind, you can do something about it. So, the next time a white bear rears its ugly head, you can pull out your list. Focus on one of your blue dolphins. Read it out loud if you like. As you practice, youll start to do this more naturally. And eventually, youll find youre keeping those nasty white bears at bayand singing the tune you want, instead of the one that got stuck in your head. Justin Bariso This article originally appeared on Fast Companys sister publication, Inc. Inc. is the voice of the American entrepreneur. We inspire, inform, and document the most fascinating people in business: the risk-takers, the innovators, and the ultra-driven go-getters that represent the most dynamic force in the American economy.
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E-Commerce
In the 1960s, IBM embarked on what Fortune called the $5 billion gamble. It was a bet-the-company investment on a scale nobody had seen before. The payoff was the legendary System/360 mainframes, which revolutionized computing and set the stage for two decades of IBM dominance. That $5 billion would be roughly the equivalent of $50 billion today, but even that princely sum is dwarfed by the $364 billion that tech giants are expected to invest in artificial intelligence this year. And the spending wont stop there. McKinsey projects that building AI data centers alone could demand $5.2 trillion by 2030. Today, the AI investment boom is probably the single biggest factor propping up the US economy. However, there is cause for concern. Throughout our history, great technological advances have led to overinvestment, the crowding out of traditional industries, and, eventually, a collapse triggering economic upheaval. Indicators suggest thats where were headed now. The booms and busts of railroad barons In terms of economic impact, the closest comparison to the AI boom was the railroads in the 19th century. Then, like now, there was a revolutionary technology with unprecedented potential for impact. The railroads promised to connect production to markets like never before in human history. Another striking parallel was government support and subsidy for investment. The Pacific Railroad Acts of 1862 and 1864 authorized vast land grants and the issue of government bonds to finance the construction of railroad infrastructure. These effectively guaranteed profits for private investors, while the public bore the risks. Railroad barons such as Cornelius Vanderbilt, Jay Gould, and Leland Stanford made enormous fortunes and came to dominate the era. They created huge monopolies that stifled competition and squeezed farmers and small businesses. If the local railroad wouldnt give you a rate, you couldnt get your goods to market. Greed, arrogance, and overinvestment fueled massive and repeated boom-and-bust cycles. The panics of 1873 and 1893 led to massive financial crises followed by years-long economic depressions and political instability. As historian Richard White explains in Railroaded, while eventually railroads would be valuable for America, the corruption, monopoly power, public cost, and repeated crashes were unnecessary and avoidable. The Second Industrial Revolution After the panic of 1893, hundreds of railroads went bankrupt, which created an opportunity for financiers like J.P. Morgan. As industries consolidated and competition decreased, stability returned and the Gilded Age roared back to life. The locus of power shifted to Wall Street as Morgan and his colleagues organized the American economy into great trusts like U.S. Steel. It was in this environment that the Second Industrial Revolution took hold. Driven by technological breakthroughs in electricity and internal combustion in the 1880s, it fueled the emergence of entirely new industries, such as automobiles and radio. By the 1920s, the electrification of factories powered a productivity boom. Much like today’s AI boom, the Second Industrial Revolution seemed to change everything. The confluence of electricity and internal combustion, along with the secondary innovations they spawned, led to mass manufacturing and mass marketing. Improved logistics reshaped supply chains and factories moved from cities in the northclose to customersto small towns in the south, where labor and land were cheaper. These genuine innovations and the resulting improvements in productivity, combined with lax regulation and easy credit, led to overinvestment and an enormous stock market bubble. The stock market crash of 1929, along with the poorly advised Smoot Hawley tariffs led to the Great Depression of the 1930s. The pattern mirrored the railroad busts of the 1800s: Genuine innovation, poor government regulation, overinvestment, boom, and bust. The dot-com boom and bust I was working on Wall Street in 1995 when the Netscape IPO hit like a bombshell. It was the first big internet stock and, just like that, a tiny company with no profits was worth $2.9 billion. Soon, productivity growthdepressed since the early 1970sbegan to surge. Economists explained that certain conditions, such as negligible marginal costs and network effects, would lead to winner take all markets and ncreasing returns to investment. Companies such as Webvan and Pets.com, with no viable business plan or path to profitability, attracted hundreds of millions of dollars from investors. In a sign of the times, America Online (AOL), merged with Time Warner, the biggest and most prestigious media company on the planet to create a $350 billion megagiant that would straddle both the old and new worlds. By 2000, the market peaked, the bubble burst, and the AOLTime Warner merger became a cautionary tale. While some of the fledgling Internet companies, such as Cisco and Amazon, did turn out well, thousands of others went down in flames. Other more conventional businesses, such as Enron, WorldCom, and Arthur Anderson, got caught up in the hoopla, became mired in scandal, and went bankrupt. Like the railroads and the Second Industrial Revolution, a bust followed a boom, but this time, there was no depression. While some prestigious companies failed, investors lost money, and genuine malfeasance was exposed, the Internet economy wasnt quite big enough to pose a significant systemic risk. The recession that followed was relatively mild by historical standards. Is this the perfect storm? Looking at the AI boom from a historical perspective, the similarities to earlier technological cycles are striking. We see the same excitement, the same calls for government regulators to get out of the way and let the technological and market forces do their work. We also see the same pattern of massive overinvestment. The only part we havent seen is the bust . . . yet. There are also signs that this particular cycle has the potential to be worse than anything in the living memory of anyone under the age of 100. As investor Paul Kedrosky points out, the size of investment in data center infrastructure has already surpassed that of the dot-com boom and is beginning to approach levels last seen during the railroad frenzy of the 19th century. And for all the hype and hoopla, were not seeing much of a boost in productivity growth. A study by the St. Louis Fed suggests a 1.1% increase in aggregate worker productivity, with much of that concentrated in the tech sector. A paper by Nobel laureate Daron Acemoglu, looking at total factor productivity (TFP), a measure which takes use of capital into account, sees a 0.66% increase over 10 years, translating to a 0.064% increase in annual TFP growth. Finally, there are signs of growing systemic risk. Kedrosky notes that, increasingly, tech giants are choosing to finance much of their infrastructure build-outs with Enron-like special purpose vehicles, which cost more but keep the debt off their balance sheets. That risk, in turn, is increasingly being passed to more traditional investors such as real estate investment trusts (REITs). So, whether you like it or not, were all deeply invested in this AI boom and there will surely be rough waters ahead. We need capable governance if were going to navigate the rapids and not end up crashing on the rocks. Who, if anyone, is at the helm?
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E-Commerce
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