1. RECENT READING Tom Peters/11 July 2013

2. FILTER BUBBLE

3. The Filter Bubble: How the New, Personalized Web Is Changing What We Read and How We Think Eli Pariser The Filter Bubble: How the New, Personalized Web Is Changing What We Read and How We Think Eli Pariser

4. bonding capital vs. bridging capital Eli Pariser, The Filter Bubble: How the New, Personalized Web Is Changing What We Read and How We Think Eli Pariser, The Filter Bubble: How the New, Personalized Web Is Changing What We Read and How We Think

5. If youre not paying for something, you are the product being sold. Andrew Lewis, MetaFilter.com (from Eli Pariser, The Filter Bubble: How the New, Personalized Web Is Changing What We Read and How We Think)

6. How much time you take between the moment you enter your query and the moment you click on a result sheds light [for Google] on your personality. Eli Pariser, The Filter Bubble: How the New, Personalized Web Is Changing What We Read and How We Think

7. It is hardly possible to overrate the value of placing human beings in contact with persons dis-similar to themselves, and with modes of thought and action unlike those with which they are familiar. Such communication has always been, and is peculiarly in the present age, one of the primary sources of progress. John Stuart Mill (1806-1873)

8. I believe this is the quest for what the quest for what a personal computer really is. It is a personal computer really is. It is to capture ones entire life. Gordon Bell to capture ones entire life. Gordon Bell

9. Psychologists have a name for this fallacy: fundamental attribution error. We tend to attribute peoples behavior to their inner traits and personality rather than to the situations in which theyre placed. Eli Pariser, The Filter Bubble: How the New, Personalized Web Is Changing What We Read and How We Think

10. Some people rush for a deal, others think that the deal means the merchandise is subpar. Just by eliminating the persuasion styles that rub people the wrong way [as deduced from prior Web behavior patterns], [the marketer] found he could increase the effectiveness of marketing materials from 30 to 40 percent. Eli Pariser, The Filter Bubble: How the New, Personalized Web Is Changing What We Read and How We Think

11. With new forms of sentiment analysis its now possible to guess what mood ones in. People use substantially more positive words when theyre up … Eli Pariser, The Filter Bubble: How the New, Personalized Web Is Changing What We Read and How We Think

12. LinkedIn offers a career trajectory prediction by comparing your resume to other peoples who are in your field but further along. LinkedIn can forecast where youll be in five years. … As a service to customers, its pretty useful. But imagine if LinkedIn offered the data to corporate clients to weed out people who are forecast to be losers. … It seems unfair for banks to discriminate against you because your high school buddy is bad at paying his bills or because you like something that a lot of loan defaulters also like. And that points to a basic problem with induction, the logical method by which algorithms use data to make predictions. Eli Pariser, The Filter Bubble: How the New, Personalized Web Is Changing What We Read and How We Think

13. Technodeterminism is alluring and convenient for newly powerful entrepreneurs because it absolves them of responsibility for what they do. Eli Pariser, The Filter Bubble: How the New, Personalized Web Is Changing What We Read and How We Think

14. ROBOT FUTURES ROBOT FUTURES

15. Robot Futures Illah Reza Nourbakhsh, Illah Reza Nourbakhsh, Professor of Robotics, Carnegie Mellon

16. Analytics can yield literally hundreds of millions of data pointsfar too many for human intuition to make any sense of the data. So in conjunction with the ability to store very big data about online behavior, researchers have developed strong tools for data mining, statistically evaluating correlations between many types and sources of data to expose hidden patterns and connections. The patterns predict human behaviorand even hidden human motivations. Illah Reza Nourbakhsh, Professor of Robotics, Carnegie Mellon, Robot Futures

17. [Very successful websites send 99% of their traffic to tried-and-true designs, but risk 1% of their traffic on new variations to discover ever better conversion rates from visits to dollars. When Google was choosing the right shade of blue for a navigation bar, the company famously performed A/B split testing across 41 shades of blue. … When numbers are large and hundreds of millions of people are in play, the tiniest improvements translate into breathtaking levels of profit improvement. Illah Reza Nourbakhsh, Professor of Robotics, Carnegie Mellon, Robot Futures

18. Robotics will drive this very innovation. Landing page tuning will bust out of the Internet and become interaction tuning. Companies will apply their analytics engines to all interaction opportunities with people everywhere: online, in the car, in a supermarket aisle, on the sidewalk, and of course in your home. Illah Reza Nourbakhsh, Professor of Robotics, Carnegie Mellon, Robot Futures

19. Human level capability has not turned out to be a special stopping point from an engineering perspective. …. Source: Illah Reza Nourbakhsh, Professor of Robotics, Carnegie Mellon, Robot Futures

20. BIGDATA

21. Big Data: A Revolution That Will Transform How We Live, Work, and Think Viktor Mayer-Schonberger and Kenneth Cukier

22. As humans, we have been conditioned to look for causes, even though searching for causality is often difficult and may lead us down the wrong paths. In a big data world, by contrast, we wont have to be fixated on causality; instead, we can discover patterns and correlations in the data that offer us novel and invaluable insights. The correlations may not tell us precisely why something is happening, but they alert us that it is happening. And in many situations, this is good enough. If millions of electronic medical records reveal that cancer sufferers who take a certain combination of aspirin and orange juice see their disease go into remission, then the exact cause for the remission in health may be less important than the fact that in health may be less important than the fact that they lived. they lived. Source: Big Data: A Revolution That Will Transform How We Live, Work, and Think, by Viktor Mayer-Schonberger and Kenneth Cukier

23. Correlations let us analyze a phenomenon not by shedding light on its inner workings, but by identifying a useful proxy for it. Source: Big Data: A Revolution That Will Transform How We Live, Work, and Think, by Viktor Mayer-Schonberger and Kenneth Cukier

24. Predictions based on correlations lie at the heart of big data. Source: Big Data: A Revolution That Will Transform How We Live, Work, and Think, by Viktor Mayer-Schonberger and Kenneth Cukier

25. There is a philosophical debate going back centuries over whether causality even exists. Source: Big Data: A Revolution That Will Transform How We Live, Work, and Think, by Viktor Mayer-Schonberger and Kenneth Cukier

26. Unfortunately, Kahneman argues [Nobel laureate Daniel Kahnemans masterpiece Thinking, Fast and Slow], very often our brain is too lazy to think slowly and methodically. Instead, we let the fast way of thinking take over. As a consequence, we often see imaginary causalities, and thus fundamentally misunderstand the world. Source: Big Data: A Revolution That Will Transform How We Live, Work, and Think, by Viktor Mayer-Schonberger and Kenneth Cukier

27. Walmart: [Using big data], the company noticed that prior to a hurricane, not only did sales of flashlights increase, but so did sales of Pop-Tarts. … Walmart stocked boxes of Pop-Tarts at the front of the store [and dramatically boosted sales]. Source: Big Data: A Revolution That Will Transform How We Live, Work, and Think, by Viktor Mayer-Schonberger and Kenneth Cukier

28. Aviva, a large insurance firm, has studied the idea of using credit reports and consumer- marketing data as proxies for the analysis of blood and urine samples for certain applicants. The intent is to identify those who may be at higher risk of illnesses like high blood pressure, diabetes, or depression. The method uses lifestyle data that includes hundreds of variables such as hobbies, the websites people visit, and the amount of television they watch, as well as estimates of their income. Avivas predictive model, developed by Deloitte Consulting, was considered successful at identifying health risks. Source: Big Data: A Revolution That Will Transform How We Live, Work, and Think, by Viktor Mayer-Schonberger and Kenneth Cukier

29. Editor-in-chief Chris Anderson authored a Wired cover story titled The Petabyte Age. The use of big data (more or less everything, not a sample) and the attendant primacy of correlation over causation as the basis for discovery was described thusly: The data deluge makes the scientific method obsolete. He also called the phenomenon the end of theory. Source: Big Data: A Revolution That Will Transform How We Live, Work, and Think, by Viktor Mayer-Schonberger and Kenneth Cukier

30. AUTOMATE THIS: HOW ALGORITHMS CAME TO RULE THE WORLD

31. Automate This: How Algorithms Came to Rule Our World Christopher Steiner

32. April 2011. Prof Michael Eisen goes to Amazon to buy book The Making of a Fly. Expects price to be $35-$40. Follows bid war for 3 days: Price hits $23,698,655.93. Culprit: Unsupervised [pricing] algorithm. (Parallels 5/6/10 Wall Street flash crash: Market dropped 1K points in about 5 minutes.) From: Christopher Steiner, Automate This: How Algorithms Came to Rule Our World

33. Algorithms have already written symphonies as moving as those composed by, picked through legalese with the deftness of a senior, diagnosed patients with more accuracy than a, written news articles with the smooth hand of a seasoned, and driven vehicles on urban highways with far better control than a human. Algorithms have already written symphonies as moving as those composed by Beethoven, picked through legalese with the deftness of a senior law partner, diagnosed patients with more accuracy than a doctor, written news articles with the smooth hand of a seasoned reporter, and driven vehicles on urban highways with far better control than a human driver. Christopher Steiner, Christopher Steiner, Automate This: How Algorithms Came to Rule Our World

34. When you ask [Cloudera founder Jeffrey] Hammerbacher what he sees as the most promising field that could be hacked by people like himself, he responds with two words: Medical diagnostics. And clearly doctors should be watching their backs, but they should be extra vigilant knowing that the smartest guys of our generationpeople like Hammerbacher---are gunning for them. The targets on their backs will only grow larger as their complication rates, their test results and their practicesare scrutinized by the unyielding eyeof algorithms built by smart engineers. Doctors arent going away, but those who want to ensure their employment in the future should find ways to be exceptional. Bots can handle the grunt work, the work that falls to our average practitioners. Christopher Steiner, Automate This: How Algorithms Came to Rule Our World

35. Shades of Ned Ludd … When Emmy [algorithm] produced orchestral pieces so impressive that some music scholars failed to identify them as the work of a machine, [Prof. David] Cope instantly created legions of enemies. … At an academic conference in Germany, one of his peers walked up to him and whacked him on the nose. … his peers walked up to him and whacked him on the nose. … Christopher Steiner, Automate This: How Algorithms Came to Rule Our World

36. … The audience then voted on the identity of each composition.* [Music theory professor and contest organizer] Larsons pride took a ding when his piece was fingered as that belonging to the computer. When the crowd decided that [algorithm] Emmys piece was the true product of the late musician [Bach], Larson winced. Christopher Steiner, … The audience then voted on the identity of each composition.* [Music theory professor and contest organizer] Larsons pride took a ding when his piece was fingered as that belonging to the computer. When the crowd decided that [algorithm] Emmys piece was the true product of the late musician [Bach], Larson winced. Christopher Steiner, Automate This: How Algorithms Came to Rule Our World *There were three: Bach/Larson/Emmy-the-algorithm.

37. … Which haiku are human writing and which are from a group of bits? Sampling centuries of haiku, devising rules, spotting patterns, and inventing ways to inject originality, Annie [algorithm] took to the short Japanese sets of prose the same way all of [Prof David] Copes. algorithms tackled classical music. In the end, its just layers and layers of binary math, he says. … Cope says Annies penchant for tasteful originality could push her past most human composers who simply build on work of the past., which, in turn, was built on older works. … Christopher Steiner, Automate This: How Algorithms Came to Rule Our World … Which haiku are human writing and which are from a group of bits? Sampling centuries of haiku, devising rules, spotting patterns, and inventing ways to inject originality, Annie [algorithm] took to the short Japanese sets of prose the same way all of [Prof David] Copes. algorithms tackled classical music. In the end, its just layers and layers of binary math, he says. … Cope says Annies penchant for tasteful originality could push her past most human composers who simply build on work of the past., which, in turn, was built on older works. … Christopher Steiner, Automate This: How Algorithms Came to Rule Our World

38. Legal industry/Pattern Recognition/Discovery (e- discovery algorithms): 500 lawyers to … ONE Source: Race AGAINST the Machine, Erik Brynjolfsson and Andrew McAfee

39. Lionbridge/IBM: GeoFluent Evaluated as successful in customer-service transactions; medical diagnosis Medical knowledge from labs, descriptions, via pattern recognition/intuition in customer-service transactions; medical diagnosis Medical knowledge from labs, descriptions, via pattern recognition/intuition Watson/IBM: Beats human Jeopardy players w/ puns, other idiosyncratic word play Source: Race AGAINST the Machine, Erik Brynjolfsson and Andrew McAfee

40. StatsMonkey: Sports writing (Readers cannot tell difference) Source: Race AGAINST the Machine, Erik Brynjolfsson and Andrew McAfee

41. REALITY IS BROKEN: WHY GAMES MAKE US BETTER AND HOW THEY CAN CHANGE US BETTER AND HOW THEY CAN CHANGE THE WORLD THE WORLD

42. Reality Is Broken: Why Games Make Us Better and How They Can Change Us Better and How They Can Change the World Jane McGonigal the World Jane McGonigal

43. MMORPG/Massively Multiplayer Online Role-Playing Game Source: Jane McGonigal, Reality Is Broken: Why Games Make Us Better and How They Can Change the World Us Better and How They Can Change the World

44. Why exactly are we competing with each other to do the dirty work? Were playing a free online game called Chore Wars and it just so happens that ridding our real-world kingdom of toilet stains is worth more experience points, or XP, than any other chore in our apartment. … A mom in Texas describes a typical Chore Wars experience: We have three kids, ages 9, 8, and 7. I sat down with the kids, showed them their characters and the adventures, and they literally jumped up and ran off to complete their chosen task. Ive never seen my 8- year-old son make his bed. I nearly fainted when my husband cleaned out the toaster oven. … Jane McGonigal, Reality Is Broken: Why Games Make Us Better and How They Can Change the World and How They Can Change the World

45. You get a sense of the scale and intricacy of the task by considering the sound effects alone: The game contains 54,000 pieces of audio and 40,000 lines of dialogue. There are 2,700 different noises for footsteps alone depending on whose foot is stepping on what.Sam Leith on Halo 3, from Jane McGonigal, Reality Is Broken: Why Games Make from Jane McGonigal, Reality Is Broken: Why Games Make Us Better and How They Can Change the World Us Better and How They Can Change the World

46. The popularity of an unwinnable game like Tetris completely upends the stereotype that gamers are highly competitive people who care more about winning than anything else. Competition and winning are not defining traits of gamesnor are they defining interests of the people who love to play them. Many gamers would rather keep playing than win. In high-feedback games, the state of being intensely engaged may ultimately be more pleasurable than the satisfaction of winning. Jane McGonigal, Reality Is Broken: Why Games Make Us Better and How They Can Change the World

47. When we are playing a well-designed game, failure doesnt disappoint us. It makes us happy in a very peculiar way: excited, interested, and most of all optimistic. Studies from M.I.N.D. Lab, Helsinki, in Jane McGonigal, Reality Is Broken: Why Games Make Us Better and How They Can Change the World

48. It may have once been true that computer games encouraged us to act more with machines than with each other. But if you still think of gamers as loners, then youre not playing games. Jane McGonigal, Reality Is Broken: Why Games Make Us Better and How They Can Change the World

49. World of Warcraft is the singlemost powerful IV drip of productivity ever created. Brian, friend, in Jane McGonigal, Reality Is Broken: Why Games Make Us Better and How They Can Change the World

50. 3-D PRINTING/ FAB LABS 3-D PRINTING/ FAB LABS

51. Fab Labs/Fabrication Labs/Fabulous Labs/digital fabrication machine/parts themselves are digitalized/3-D printer/MIT Center for Bits and Atoms/ Prof Neil Gershenfeld/ $5K: large-format computer- controlled milling machine can make all the parts in an IKEA flat-pack box customized for the individual/Etc./Etc. Source: How to Make Almost Anything, Beil Gershenfeld, Foreign Affairs/11-12.2012

52. Its Getting a Little Weird Out* Bradescos biometric ATM sensors/blood flow (Economist 0519) Oscar Pistorius sprinting acumen/approved for London (WSJ 0602) London (WSJ 0602) DelFly/lighter than your wedding ring (Economist 0602) *Kurzweils Singularity is nigh?!

53. RACE AGAINST THE MACHINE

54. Race AGAINST The Machine: How the Digital Revolution Is Accelerating Innovation, Driving Productivity, and Irreversibly Transforming Employment and the Economy Erik Brynjolfsson and Andrew McAfee

55. The root of our problem is not that were in a Great Recession that were in a Great Recession or a Great Stagnation, but rather or a Great Stagnation, but rather that we are in the early that we are in the early throes of a. Our technologies are racing ahead, throes of a Great Restructuring. Our technologies are racing ahead, but our skills and organizations but our skills and organizations are lagging behind. are lagging behind. Source: Race AGAINST the Machine, Erik Brynjolfsson and Andrew McAfee

56. Explanations for Slow Recovery CyclicalStagnation Rise of BRICS+ End of Work/ Accelerated Pace* of Technological Change *The second half of the chessboard Source: Race AGAINST the Machine, Erik Brynjolfsson and Andrew McAfee

57. Worst in 30 Years! The number of Americans in the labor force those who have a job or are looking for one fell by nearly half a million people from February to March [2013], the government said Friday. And the percentage of working-age adults in the labor force what's called the participation rate fell to 63.3 percent last month The number of Americans in the labor force those who have a job or are looking for one fell by nearly half a million people from February to March [2013], the government said Friday. And the percentage of working-age adults in the labor force what's called the participation rate fell to 63.3 percent last month. It's the lowest such figure since May 1979. Source: AP/0407.13

58. +400,000 -2,000,000

59. +400,000*/-2,000,000** new computing technologies that destroy middle-class [white- collar] jobs even as they create jobs for highly skilled workers who can exploit them * Manufacturing jobs added USA 2007-2012 ** White-collar jobs l ost USA 2007-2012 Source: Financial Times, page 1, 0402.13 (Clerical Staff Bears Brunt of US Jobs Crisis)

60. 3 million jobs unfilled/6% unemployment per se/50% companies with shortfall in skilled people/college degree not required: The numbers of the undertrained are staggering./MA: 100K jobs @ $75K; 40% SMEs report difficulty finding skilled craftsmen to replace retirees Source: Nina Easton/ Fortune/11.2012

61. 2 nd Half of the Chessboard Squares 1-32; 4B grains = 1 large field Squares 33-64; pile bigger than Mt Everest Mt Everest Source: Race AGAINST the Machine, Erik Brynjolfsson and Andrew McAfee

62. The median worker is losing the race against the machine. Erik Brynjolfsson and Andrew McAfee, The Race Against the Machine

63. A bureaucrat is an expensive microchip. Dan Sullivan, consultant and executive coach

64. Erik Brynjolfsson and Andrew McAfee, The Race Against the Machine The median worker is losing the race against the machine. Erik Brynjolfsson and Andrew McAfee, The Race Against the Machine A bureaucrat is an expensive microchip. Dan Sullivan, consultant and executive coach

65. … breakage of the historic link between value creation and job creation: The median worker is losing the race against the machine./ Great Recession: lack of hiring rather than increase in layoffs Source: Race AGAINST the Machine, Erik Brynjolfsson and Andrew McAfee

66. 40 Years: Median inflation adjusted wages, men 30-50 with jobs, 1969-2009: $33K, -27% Source: The Slow Disappearance of the American Working Man, Bloomberg Businessweek/08.11

67. Post-Great Recession: Equipment expenditures +26%; payrolls flat/ Great Recession … lack of hiring rather than increase in layoffs/… breakage of the historic link between value creation and job creation The U-shaped Curve Phenomenon: High-skilled Waaaaay Up!!! Low-skilled: Stable/Up Middle: Middle: Down/Down/Down Source: Race AGAINST the Machine, Erik Brynjolfsson and Andrew McAfee

68. Q3 2011/BLS +3.1/ Non-farm productivity growth +3.8/ Non-farm output +0.6/ Non-farm hours worked +5.4/ Manufacturing productivity +4.7 / Manufacturing output / Manufacturing hours worked Source: Bureau of Labor Statistics/03 November 2011 Q3 2011/BLS +3.1/ Non-farm productivity growth +3.8/ Non-farm output +0.6/ Non-farm hours worked +5.4/ Manufacturing productivity +4.7 / Manufacturing output - 0.6 / Manufacturing hours worked Source: Bureau of Labor Statistics/03 November 2011

69. China too /Foxconn: 1,000,000 robots in next 3 years 1,000,000 robots in next 3 years Source: Race AGAINST the Machine, Erik Brynjolfsson and Andrew McAfee

70. SBTC/Skill-Biased Technical Change: race between education and technology Source: Race AGAINST the Machine, Erik Brynjolfsson and Andrew McAfee

71. Fab Labs/Fabrication Labs/Fabulous Labs/digital fabrication machine/ parts themselves are digitalized/ 3-D printer /MIT Center for Bits and Atoms/ Prof Neil Gershenfeld/ $5K: large-format computer-controlled milling machine can make all the parts in an IKEA flat- pack box customized for the individual/Etc./Etc. Source: How to Make Almost Anything, Beil Gershenfeld, Foreign Affairs/11-12.2012

72. Night to Day = 6 Years DARPA Grand Challenge 2004: No dice Google 2010: 140K miles in driverless cars Source: Race AGAINST the Machine, Erik Brynjolfsson and Andrew McAfee

73. Lionbridge/IBM: GeoFluent Evaluated as successful in customer-service transactions; medical diagnosis Medical knowledge from labs, descriptions, via pattern recognition/intuition in customer-service transactions; medical diagnosis Medical knowledge from labs, descriptions, via pattern recognition/intuition Watson/IBM: Beats human Jeopardy players w/ puns, other idiosyncratic word play Source: Race AGAINST the Machine, Erik Brynjolfsson and Andrew McAfee

74. Legal industry/Pattern Recognition/Discovery (e- discovery algorithms): 500 lawyers to … ONE Source: Race AGAINST the Machine, Erik Brynjolfsson and Andrew McAfee

75. Bachelors degree, age 25-34: 40% F; 30% M Graduate degree students: 60% F; 40% M Source: Sydney Morning Herald /26.03.12

76. StatsMonkey: Sports writing (Readers cannot tell difference) Source: Race AGAINST the Machine, Erik Brynjolfsson and Andrew McAfee

77. Standard optimization problem, 1998-2003: 43,000,000-fold speed improvement; 1,000X processor speed; 43,000X algorithms better Source: Race AGAINST the Machine, Erik Brynjolfsson and Andrew McAfee

78. China too /Foxconn: 1,000,000 robots in next 3 years 1,000,000 robots in next 3 years Source: Race AGAINST the Machine, Erik Brynjolfsson and Andrew McAfee

79. Post-Great Recession: Equipment expenditures +26%; payrolls flat +26%; payrolls flat Source: Race AGAINST the Machine, Erik Brynjolfsson and Andrew McAfee

80. USA/Agriculture 1800: 90% 1900: 41% 2000: 2% Source: Race AGAINST the Machine, Erik Brynjolfsson and Andrew McAfee

81. The U-shaped Curve Phenomenon: High-skilled Waaaaay Up!!! Low-skilled: Stable/Up Middle: Down/Down/Down Source: Race AGAINST the Machine, Erik Brynjolfsson and Andrew McAfee

82. SMEs!

83. In the wake of the 2012 presidential election, some political commentators have written political obituaries of the "red" or conservative-leaning states, envisioning a brave new world dominated by fashionably blue bastions in the Northeast or California. But political fortunes are notoriously fickle, while economic trends tend to be more enduring. These trends point to a U.S. economic future dominated by four growth corridors that are generally less dense, more affordable, and markedly more conservative and pro-business: the Great Plains, the Intermountain West, the Third Coast (spanning the Gulf states from Texas to Florida), and the Southeastern industrial belt. Overall, these corridors account for 45% of the nation's land mass and 30% of its population. Between 2001 and 2011, job growth in the Great Plains, the Intermountain West and the Third Coast was between 7% and 8%nearly 10 times the job growth rate for the rest of the country. Only the Southeastern industrial belt tracked close to the national average. Historically, these regions were little more than resource colonies or low-wage labor sites for richer, more technically advanced areas. By promoting policies that encourage enterprise and spark economic growth, they're catching up. Source: Joel Kotkin, Wall Street Journal, 0225.13

84. We are in no danger of running out of new combinations to try. Even if technology froze today, we have more possible ways of configuring the different applications, machines, tasks, and distribution channels to create new processes and products than we could ever exhaust. Erik Brynjolfsson and Andrew McAfee, The Race Against the Machine: How the Digital Revolution Is Accelerating Innovation, Driving Productivity and Irreversibly Transforming Employment and the Economy out of new combinations to try. Even if technology froze today, we have more possible ways of configuring the different applications, machines, tasks, and distribution channels to create new processes and products than we could ever exhaust. Erik Brynjolfsson and Andrew McAfee, The Race Against the Machine: How the Digital Revolution Is Accelerating Innovation, Driving Productivity and Irreversibly Transforming Employment and the Economy

85. Muhammad Yunus: All human beings are entrepreneurs. When we were in the caves we were all self-employed... finding our food, feeding ourselves. Thats where human history began... As civilization came we suppressed it. We became labor because they stamped us, You are labor. We forgot that we are entrepreneurs. Muhammad Yunus: All human beings are entrepreneurs. When we were in the caves we were all self-employed... finding our food, feeding ourselves. Thats where human history began... As civilization came we suppressed it. We became labor because they stamped us, You are labor. We forgot that we are entrepreneurs. Muhammad Yunus/ The News Hour/PBS/1122.2006

86. Human creativity is the ultimate economic resource. Richard Florida

87. USA 1996-2007 Highest rate entrepreneurial activity (firms founded): Ages 55-64 Lowest rate: Ages 20-34 Source: Dane Stangler, Kauffman Foundation (Economist)

88. The average age of a startup founder is 40. And high-growth startups are nearly twice as likely to be launched by people over 55 as by people 20-34. Vivek Wadhwa, Kauffman foundation (Time/0325.13)

89. The prospect of contracting a gofer on an a la carte basis is enticing. For instance, wouldnt it be convenient if I could outsource someone to write a paragraph here, explaining the history of outsourcing in America? Good idea! I went ahead and commissioned just such a paragraph from Get Friday, a virtual personal assistant- firm based in Bangalore. … The paragraph arrived in my in-box ten days after I ordered it. It was 1,356 words. There is a bibliography with eleven sources. … At $14 an hour for seven hours of work, the cost came to $98. … Patricia Marx, Outsource Yourself, The New Yorker, 01.14.2013 (Marx describes in detail contracting out everything associated with hosting her book club including the provision of witty comments on Proust, since she hadnt had time to read the bookexcellent comments only set her back $5; the writer/contractor turned out to be a 14-year-old girl from New Jersey.) la carte basis is enticing. For instance, wouldnt it be convenient if I could outsource someone to write a paragraph here, explaining the history of outsourcing in America? Good idea! I went ahead and commissioned just such a paragraph from Get Friday, a virtual personal assistant- firm based in Bangalore. … The paragraph arrived in my in-box ten days after I ordered it. It was 1,356 words. There is a bibliography with eleven sources. … At $14 an hour for seven hours of work, the cost came to $98. … Patricia Marx, Outsource Yourself, The New Yorker, 01.14.2013 (Marx describes in detail contracting out everything associated with hosting her book club including the provision of witty comments on Proust, since she hadnt had time to read the bookexcellent comments only set her back $5; the writer/contractor turned out to be a 14-year-old girl from New Jersey.)

90. ADDICTION BY DESIGN

91. Machine Gambling 66% revenue 85% profit Source: Natasha Dow Schüll, Addiction By Design: Machine Gambling in Las Vegas

92. Machine Gambling Pleasing odor #1 vs. pleasing odor #2: +45% revenue Source: Effects of Ambient Odors on Slot-Machine Useage in Las Vegas Casinos, reported in Natasha Dow Schüll, Addiction By Design: Machine Gambling in Las Vegas

93. When Friedman slightly curved the right angle of an entrance corridor to one property, he was amazed at the magnitude of change in pedestrians behavior (the percentage who entered increased from one-third to nearly two-thirds). Natasha Dow Schüll, Addiction By Design: Machine Gambling in Las Vegas

94. THE MYTH OF AMERICAN DECLINE AND THE GROWTH OF A NEW ECONOMY NEW ECONOMY

95. Daniel Gross, The Myth of American Decline and the Growth of a New Economy

96. Not Dead Yet Not Dead Yet BRIC/2011: $11T/$4K per capita USA/2011: $16T/$48K per capita USA/2000: 4% population/30% world GDP USA/2010: 4% populattion/28% world GDP USA productivity: 07/1.7%; 08/2.1%; 09/5.4%; 10/2.4%; 11/4.1% FDIC institutions: 4Q/2008/-$38B; 2Q/2011/+$29B 1/2008 to 9/2011: USA consumer savings 0% to 6%/$2.1T saved Foreign Direct Investment: 2003: $64B; 2008: $328B; 2009: $134B; 2011: $200B+ Exports/2009: USA $1.53T ($1.06T goods, $0.47T services); Germany $1.36T; China $1.33T USA/Refined petroleum products/1Q 2011: Imports 2.16M BPD; Exports 2.49M BPD New economy: Apple (>Exxon) + Google + Facebook ~ $1T market cap Source: Daniel Gross, The Myth of American Decline and the Growth of a New Economy

97. iPad/$4 billion of $300 billion negative USA trade balance with China (2011)

98. Cost/Profit Components: Total labor 7% (Chinese labor: 2%) Materials 31% Distribution: 15% Profit: 47% Landed iPad cost: $275 = Imputed USA negative trade balance with China (Actual China cost: $10) Source: Personal Computing Industry Centre (Economist)

99. Cost*/Profit Components: Total labor 7% (Chinese labor: 2%) Materials 31% Distribution: 17% Profit: 47% Landed iPad cost: $275 = Imputed USA negative trade balance with China (Actual China cost: $10) *Biggest non-USA component: Korea Source: Personal Computing Industry Centre (Economist)

100. Q3 2011/BLS +3.1/ Non-farm productivity growth +3.8/ Non-farm output +0.6/ Non-farm hours worked +5.4/ Manufacturing productivity +4.7/ Manufacturing output / Manufacturing hours worked Source: Bureau of Labor Statistics/03 November 2011 Q3 2011/BLS +3.1/ Non-farm productivity growth +3.8/ Non-farm output +0.6/ Non-farm hours worked +5.4/ Manufacturing productivity +4.7/ Manufacturing output - 0.6/ Manufacturing hours worked Source: Bureau of Labor Statistics/03 November 2011

101. Its Getting a Little Strange Out* DelFly/lighter than your wedding ring (Economist 0602) wedding ring (Economist 0602) Oscar Pistorius sprinting acumen/approved for London (WSJ 0602) London (WSJ 0602) *See Ray Kurzweil, The Singularity Is Near: When Humans Transcend Biology; key chapter, GNR: Three Overlapping Revolutions (GNR: Genetics, Nanotechnology, Robotics)

102. In some sense you can argue that the science fiction scenario is already starting to happen. The computers are in control. We just live in their world. Danny Hillis, Thinking Machines

103. Unless mankind redesigns itself by changing our DNA through altering our genetic makeup, computer-generated robots will take over the world. – Stephen Hawking

104. THE SHAREHOLDER VALUE MYTH: HOW PUTTING SHAREHOLDERS FIRST HARMS INVESTORS, CORPORATIONS, AND THE PUBLIC

105. Lynn Stout, professor of corporate and business law, Cornell Law school, author The Shareholde,r Value Myth: How Putting Shareholders First Harms Investors, Corporations, and the Public

106. The notion that corporate law requires directors, executives, and employees to maximize shareholder wealth simply isnt true. There is no solid legal support for the claim that directors and executives in U.S. public corporations have an enforceable legal duty to maximize shareholder wealth. The idea is fable. Lynn Stout, professor of corporate and business law, Cornell Law school, in The Shareholder Value Myth: How Putting Shareholders First Harms Investors, Corporations, and the Public

107. Courts uniformly refuse to actually impose sanctions on directors or executives for failing to pursue one purpose over another. In particular, courts refuse to hold directors of public corporations legally accountable for failing to maximize shareholder wealth. Lynn Stout, professor of corporate and business law, Cornell Law school, in The Shareholder Value Myth: How Putting Shareholders First Harms Investors, Corporations, and the Public

108. What about shareholders rights to sue corporate officers and directors for breach of fiduciary duty if they fail to maximize shareholder wealth? Such a right turns out to be illusory. Executives and directors duty of loyalty to the corporation bars them from using their corporate positions to enrich themselves at the firms expense, but unconflicted directors remain legally free to pursue almost any other goal. Lynn Stout, professor of corporate and business law, Cornell Law school, in The Shareholder Value Myth: How Putting Shareholders First Harms Investors, Corporations, and the Public

109. From a legal perspective, shareholders do not, and cannot, own corporations. Corporations are independent legal entities that own themselves, just as human beings own themselves. … Shareholders own shares of stock. A share of stock is simply a contract between the shareholder and the corporation, a contract that gives the shareholder very limited rights under limited circumstances. In this sense, stockholders are no different from bondholders, suppliers, and employees. All have contractual relationships with the corporate entity. None owns the company itself. Lynn Stout, professor of corporate and business law, Cornell Law school, in The Shareholder Value Myth: How Putting Shareholders First Harms Investors, Corporations, and the Public

110. [a corporation] can be formed to conduct or promote any lawful business or purpose from Delaware corporate code (no mandate for shareholder primacy), per Lynn Stout, professor of corporate and business law, Cornell Law school, in The Shareholder Value Myth: How Putting Shareholders First Harms Investors, Corporations, and the Public

111. On the face of it, shareholder value is the dumbest idea in the world. Shareholder value is a result, not a strategy. … Your main constituencies are your employees, your customers and your products. Jack Welch, FT, 0313.09, page 1 are your employees, your customers and your products. Jack Welch, FT, 0313.09, page 1

112. Too Much Cost, Not Enough Value Too Much Speculation, Not Enough Investment Too Much Complexity, Not Enough Simplicity Too Much Counting, Not Enough Trust Too Much Business Conduct, Not Enough Professional Conduct Too Much Salesmanship, Not Enough Stewardship Too Much Focus on Things, Not Enough Focus on Commitment Too Many Twenty-first Century Values, Not Enough Eighteenth-Century Values Too Much Success, Not Enough Character Source: Jack Bogle, Enough! (chapter titles)

113. Managers have lost dignity over the past decade in the face of widespread institutional breakdown of trust and self-policing in business. To regain societys trust, we believe that business leaders must embrace a way of looking at their role that goes beyond their responsibility to the shareholders to include a civic and personal commitment to their duty as institutional custodians. In other words, it is time that management became a profession. Rakesh Khurana & Nitin Nohria, Its Time To Make Management a True Profession, HBR/10.08

114. On the face of it, shareholder value is the dumbest idea in the world. Shareholder value is a result, not a strategy. … Your main constituencies are your employees, your customers and your products. Jack Welch, FT, 0313.09, page 1 are your employees, your customers and your products. Jack Welch, FT, 0313.09, page 1