Captain Sullenberger Hudson

Fly by Wire: The Geese, the Glide, the Miracle on the Hudson
by William Langewiesche
Published 10 Nov 2009

They knew that the airplane’s flight-control computers had performed remarkably well, seamlessly integrating themselves into Sullenberger’s solutions and intervening assertively at the very end to guarantee a survivable touchdown. The test pilots believed that the airplane’s functioning was a vindication of its visionary design. But they were not going to bring it up. They were going to get through this hearing and be done. Their front man said, “Good morning, Captain Sullenberger, but all of our questions have been answered by Captain Sullenberger, the technical panel, and the other party members. Thank you, sir.” Sullenberger said, “Thank you.” The engine manufacturer had no questions.

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Forty-five seconds had passed since the airplane’s liftoff. Skiles called for a flap retraction from position two to position one. Sullenberger said, “Flaps one.” They flew in silence for twenty seconds. It was a beautiful day. The Hudson River stretched upstream, below and to the left, on the far side of the Bronx. Looking outside, Sullenberger said, “What a view of the Hudson today.” “Yeah.” But Skiles was all business. He said, “Flaps up, please. [Do the] after-takeoff checklist.” Sullenberger said, “Flaps up.” The checklist was short. He said, “After-takeoff checklist complete.” They had been airborne for a minute and a half.

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The Frenchman probed no further. He said, “Thank you, Captain.” Dr. Wilson echoed his gratitude. She said, “Thank you, Captain Sullenberger.” To Robert Sumwalt, she said, “Mr. Chairman, we have no more questions at this time.” It was the turn now for the officially designated parties to ask their own questions. A woman from the flight attendants’ union led off. She suggested to Sullenberger that rather than announcing, “Brace for impact,” as he had over the cabin address system, he should have announced, “Brace for water impact.” Sullenberger easily batted this aside. She then led him through a series of questions pertaining to the fact that only two of the four life rafts in the airplane had been usable, and that even if they had been loaded to their maximum capacity, forty-five people would have been unaccommodated.

The Checklist Manifesto: How to Get Things Right
by Atul Gawande
Published 2 Jan 2009

As it happened, the very next day, US Airways Flight 1549 took off from La Guardia Airport in New York City with 155 people on board, struck a large flock of Canadian geese over Manhattan, lost both engines, and famously crash-landed in the icy Hudson River. The fact that not a single life was lost led the press to christen the incident the “miracle on the Hudson.” A National Transportation Safety Board official said the flight “has to go down as the most successful ditching in aviation history.” Fifty-seven-year-old Captain Chesley B. “Sully” Sullenberger III, a former air force pilot with twenty thousand hours of flight experience, was hailed the world over. “Quiet Air Hero Is Captain America,” shouted the New York Post headline. ABC News called him the “Hudson River hero.” The German papers hailed “Der Held von New York,” the French “Le Nouveau Héros de l’Amérique,” the Spanish-language press “El Héroe de Nueva York.”

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Zaslow, Highest Duty: My Search for What Really Matters (New York: William Morrow, 2009). 179 “Skiles managed to complete”: Testimony of Captain Terry Lutz, Experimental Test pilot, Engineering Flight Operations, Airbus, National Transportation Safety Board, “Public Hearing in the Matter of the Landing of US Air Flight 1549 in the Hudson River, Weehawken, New Jersey, January 15, 2009,” June 10, 2009. 180 “ ‘Flaps out?’ ”: D. P. Brazy, “Group Chairman’s Factual Report of Investigation: Cockpit Voice Recorder DCA09MA026,” National Transportation Safety Board, April 22, 2009. 180 “For, as journalist and pilot”: W. Langewiesche, “Anatomy of a Miracle,” Vanity Fair, June 2009. 181 “After the plane landed”: Testimony of Captain Chesley Sullenberger, A320 Captain, US Airways, National Transportation Safety Board, Public Hearing, June 9, 2009.

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Olshan and I. Livingston, “Quiet Air Hero Is Captain America,” New York Post, Jan. 17, 2009. 174 “As Sullenberger kept saying”: M. Phillips, “Sully, Flight 1549 Crew Receive Keys to New York City,” The Middle Seat, blog, Wall Street Journal, Feb. 9, 2009, http://blogs.wsj.com/middleseat/2009/02/09/. 174 “ ‘That was so long ago’ ”: “Sully’s Tale,” Air & Space, Feb. 18, 2009. 178 “Once that happened”: C. Sullenberger and J. Zaslow, Highest Duty: My Search for What Really Matters (New York: William Morrow, 2009). 179 “Skiles managed to complete”: Testimony of Captain Terry Lutz, Experimental Test pilot, Engineering Flight Operations, Airbus, National Transportation Safety Board, “Public Hearing in the Matter of the Landing of US Air Flight 1549 in the Hudson River, Weehawken, New Jersey, January 15, 2009,” June 10, 2009. 180 “ ‘Flaps out?’

Future Perfect: The Case for Progress in a Networked Age
by Steven Johnson
Published 14 Jul 2012

The mass media quickly offered up two primary explanations, both of which turned out to be typical interpretations of good news. First there was the hero narrative: Captain Chesley “Sully” Sullenberger, who had indeed brilliantly navigated his plane into the river with great poise under unthinkable pressure. And then there was the quasi-magical rhetoric that quickly became attached to the event, the Miracle on the Hudson. Those were the two options. That plane floating safely in the Hudson could be explained only by superheroes or miracles. There was no denying Sullenberger’s achievement that day, but the fact is, he was supported by a long history of decisions made by thousands of people over the preceding decades, all of which set up the conditions that made that perfect landing possible.

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Inspired by the NASA model, engineers at Airbus in the early 1980s built an exceptionally innovative fly-by-wire system into the Airbus A320, which began flying in 1987. Twenty-one years later, Chesley Sullenberger was at the controls of an A320 when he collided with that flock of Canada geese. Because his left engine was still able to keep the electronics running, his courageous descent into the Hudson was deftly assisted by a silent partner, a computer embodied with the collective intelligence of years of research and planning. William Langewiesche describes that digital aid in his riveting account of the flight, Fly by Wire: While in the initial left turn [Sullenberger] lowered the nose . . . and went to the best gliding speed—a value which the airplane calculated all by itself, and presented to him as a green dot on the speed scale of his primary flight display.

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Most non-pilots think of modern planes as possessing two primary modes: “autopilot,” during which the computers are effectively flying the plane, and “manual,” during which humans are in charge. But fly-by-wire is a more subtle innovation. Sullenberger was in command of the aircraft as he steered it toward the Hudson, but the fly-by-wire system was silently working alongside him throughout, setting the boundaries or optimal targets for his actions. That extraordinary landing was a kind of duet between a single human being at the helm of the aircraft and the embedded knowledge of the thousands of human beings that had collaborated over the years to build the Airbus A320’s fly-by-wire technology. It is an open question whether Sullenberger would have been able to land the plane safely without all that additional knowledge at his service.

The Elements of Choice: Why the Way We Decide Matters
by Eric J. Johnson
Published 12 Oct 2021

If I had been home and not on my flight, I could have watched the aircraft descend into the Hudson from my living room window. Choice architecture is all around us, influencing even the pilots whom we rely on to deliver us safely to our destinations. They are trained to make choices and, as the chair of one flight-training program put it, “We’re not building pilots. . . . I like to tell our students we’re training them to be decision-makers who happen to know how to fly an airplane.”1 Captain Chesley “Sully” Sullenberger’s decision about where to land the plane was made simply and quickly. There were only 208 seconds, just over three minutes, between the time the blades of both engines were stopped by striking a flock of errant Canada geese and the moment the plane touched down.

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Sully reported that he did not have time to do a careful analysis of his three options: going back to LaGuardia, an airfield whose runways are infamously short, especially for an emergency landing; flying over a densely populated area across the river to the smaller general aviation airfield at Teterboro; or splashing down in the Hudson. The first thing Sullenberger had to do was make a decision about how he would decide. He did this quickly and automatically, and according to transcripts of the accident report, he was very aware of the decision he made but not as aware of how he chose to make that decision. There simply wasn’t time. He was in total control, but his mind was working automatically, as if he was on autopilot.

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What did the gauge enable Sullenberger to think about, and what did it enable him to ignore? How did it help him load-shed? He says that in the midst of everything, he considered the location for a water landing. The Hudson is cold in mid-January. The water temperature was 41 degrees Fahrenheit, and the air a chilly 19 degrees. Hypothermia was a real risk. Even if they successfully landed, the plane might float for only a short time. Sullenberger knew that there were many boats along Manhattan’s west side, and a ferry terminal nearby. Because he was able to load-shed, he considered not only where he could safely land the plane but rescue possibilities as well, thinking about what would happen next.

Speed
by Bob Gilliland and Keith Dunnavant

Crossfield died on impact. And the so-called Miracle on the Hudson was still fresh in the minds of all. Just fifteen months before the famous aviators took flight, the U.S. Airways A320 that struck a flock of Canadian geese immediately after takeoff from LaGuardia Airport served as a reminder of all the little things that could go wrong—and, ultimately, offered a powerful object lesson about how one skilled and quick-thinking pilot could avert disaster. By carefully guiding the fast-sinking jetliner onto the Hudson River, Captain Chesley “Sully” Sullenberger saved the lives of 155 passengers and crew. In the otherwise comparatively monotonous life of an airline pilot, the decision to try to land or divert during dangerous weather always looms large, and this particular situation was embroidered with an additional level of pressure.

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The founder of Solovox Publishing, Dunnavant has also been an award-winning writer and newsroom executive for The National, Adweek, Atlanta, and BusinessWeek and a featured historian on ESPN, CBS, HBO, Showtime, Epix, and SEC Network. About Chesley “Sully” Sullenberger Chesley “Sully” Sullenberger is a retired U.S. Air Force fighter pilot and airline captain who became world famous after the so-called Miracle on the Hudson. He is the coauthor of the New York Times best seller Highest Duty: My Search for What Really Matters. 1. Frank Gilliland Sr. was a hero in World War I but rarely talked about his service. Courtesy of Gilliland family. 2.

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Bob with Andrew Green, Eric Brown, and Neil Armstrong Foreword Chesley “Sully” Sullenberger Over the last century, thanks to the work of some very dedicated and gifted professionals who learned to harness the wonders of science, air travel has evolved from risky to routine. Most of the passengers who regularly cruise from city to city at 600 miles per hour, six miles above the earth, do so with a confidence approaching certitude. After all, flying in an airliner is now much safer than other forms of transportation. Of course, sometimes things go wrong. On January 15, 2009, when I was sitting in the captain’s seat of an Airbus A320 climbing away from New York’s LaGuardia Airport, multiple bird strikes caused the loss of both engines.

The Crash Detectives: Investigating the World's Most Mysterious Air Disasters
by Christine Negroni
Published 26 Sep 2016

“I wanted enough altitude so we could glide back to Changi,” he reasoned. Nine months earlier, Captain Sullenberger found himself in a similar situation with even less altitude. He was at three thousand feet following takeoff from New York’s LaGuardia Airport when geese flew into the engines, knocking them out. The A320 began a one-thousand-feet-per-minute descent. In his book Highest Duty, Sullenberger said he and Skiles knew in less than a minute that they were not going to get to any of the nearby airports. “We were too low, too slow, too far away and pointed in the wrong direction,” he wrote. The Hudson River was “long enough, wide enough and on that day, smooth enough to land a jetliner.”

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After all, it was an ordinary flight—under the command of an experienced and well-regarded captain—that suddenly turned baffling. The Boeing 777 departed Kuala Lumpur International Airport on March 8, 2014, on an overnight trip to Beijing. There were 227 passengers and 12 crew members on board. In the cockpit, Capt. Zaharie Ahmad Shah, a thirty-three-year employee of the company, was in command. He had eighteen thousand flight hours. As a point of reference, that’s just fifteen hundred hours fewer than Chesley Sullenberger had in his logbook when he successfully ditched a disabled US Airways airliner into New York’s Hudson River, and Zaharie was five years younger than Sully.

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“Thank God,” Norhisham said when Flight 124 landed safely with no injuries, though everyone on board the airplane was shaken. Only then did Norhisham stop and think about the “very thin margin of survival.” He had joined a fraternity of pilots who had knowingly broken the last link in the chain to calamity. Three and a half years later, Chesley Sullenberger and Jeff Skiles ditched an Airbus A320 in New York’s Hudson River after geese flew into the engines following takeoff from LaGuardia Airport. In September 2010, Andrei Lamanov and Yevgeny Novoselov landed on an abandoned runway in northwestern Russia that was half as long as their aircraft required. A total power failure on a the Tupelov TU-154 caused all the fuel pumps to fail, starving the engines and leading to the loss of all navigation and radio equipment on what should have been a five-hour flight to Moscow.

Air Crashes and Miracle Landings: 60 Narratives
by Christopher Bartlett
Published 11 Apr 2010

US AIRWAYS FLIGHT 1549 (Hudson River 2009) Sully the Saint Just as we were saying how difficult it is to ditch an airliner successfully in the sea, there has been the widely publicized case of an Airbus suffering a bird strike on taking off from New York’s La Guardia Airport and ditching in the nearby Hudson River with no fatalities. See photo on back cover of the printed edition. [US Airways Flight 1549] No commercial airline pilot has been quite as sanctified[26] as 58-year-old Captain Chesley B. Sullenberger III (nicknamed Sully) who ditched his Airbus A320 in New York’s Hudson River without a single loss of life, except for some hapless birds.

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Incidentally, he had been hijacked twice before. 5. Captain Sullenberger’s (page 19) ‘perfect’ ditching of his Airbus in New York’s Hudson River after its engines ingested Canadian geese just after takeoff. It was a great achievement based on good judgment in deciding to ditch in the river and not least on switching on the Auxiliary Power Unit (APU) to provide electricity for the aircraft’s computers thus enabling him to fly the aircraft optimally. However, it was not against all odds in that such an ideal—water temperature apart—ditching site was at hand. 6. Captain Moody’s (page 9) successful landing of his Boeing 747 after all four engines had flamed out (stopped) on entering a cloud of volcanic ash most certainly seemed a miracle to the passengers.

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‘Hero’ and ‘Fighting to Save the Aircraft’ We have to accept the media’s tendency (for want of a better word) to label pilots heroes when the qualities that save a situation are usually competence and clear thinking. Granted some pilots may have to force themselves to stay calm and collected as Captain Sullenberger frankly admitted in an interview following the ditching of his aircraft in the Hudson River. Rather than quibble over the use of the word hero, one should have more qualms about the phrase ‘the pilot was fighting desperately to save the aircraft,’ often used immediately after a crash when the press has little hard information and where many if not all the occupants have died.

Black Box Thinking: Why Most People Never Learn From Their Mistakes--But Some Do
by Matthew Syed
Published 3 Nov 2015

It was dropping too fast. At 3:29 p.m. Sullenberger uttered the words that would create headlines around the world: “We’re going to be in the Hudson.” • • • In the opening part of this book we have focused on failure in two safety-critical areas: aviation and health care. We have looked at responses, attitudes, and investigations into failure. Now we will have a brief look at success, and our responses to that. By shining a light on how we get things right we will discover a little more about why we get things wrong. Sullenberger ultimately landed the plane, all 70 tons of it, on the Hudson River. It was a brilliantly judged maneuver.

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But aviation experts took a different view. They glimpsed a bigger picture. They cited not just Sullenberger’s individual brilliance but also the system in which he operates. Some made reference to Crew Resource Management. The division of responsibilities between Sullenberger and Skiles occurred seamlessly. Seconds after the bird strike, Sullenberger took control of the aircraft while Skiles checked the quick-reference handbook. Channels of communication were open until the very last seconds of the flight. Skiles called out airspeeds and altitudes to provide his captain as much situational awareness as possible as the aircraft dropped.

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Anderton, two outstanding doctors, in an operating theater near North Marston more than twenty-five years later. The irony is that Sullenberger, feted by presidents, might have made precisely the same mistake under those circumstances. The fact that he didn’t, and emerged a hero, was for a simple but profound reason: the industry in which he operates had learned the lessons. It is both apt and revealing that Sullenberger, a modest and self-evidently decent man, has made exactly this point. In a television interview months after the miracle landing on the Hudson, he offered this beautiful gem of wisdom: Everything we know in aviation, every rule in the rule book, every procedure we have, we know because someone somewhere died . . .

Cockpit Confidential: Everything You Need to Know About Air Travel: Questions, Answers, and Reflections
by Patrick Smith
Published 6 May 2013

The severity of a maneuver, whether perceived or actual, is not always a crewmember’s whim or lack of finesse. What are your thoughts on the alleged heroics of Captain “Sully” Sullenberger and the so-called Miracle on the Hudson? Chesley “Sully” Sullenberger was the US Airways captain who guided his suddenly engineless Airbus into the Hudson River on January 15, 2009, after striking a flock of Canada geese. Together with the majority of my colleagues, I have the utmost respect for Captain Sullenberger. But that’s just it: respect. It’s not adoration or a false, media-fattened misunderstanding of what he and his crew faced that day.

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As it happened, it was daylight and the weather was reasonably good; there off Sullenberger’s left side was a 12-mile runway of smoothly flowing river, within swimming distance of the country’s largest city and its flotilla of rescue craft. Had the bird-strike occurred over a different part of the city, at a lower altitude (beyond gliding distance to the Hudson), or under more inclement weather conditions, the result was going to be an all-out catastrophe, and no amount of talent or skill was going to matter. Sullenberger, to his credit, has been duly humble, acknowledging the points I make above.

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Any time a pilot changes airlines, he starts over at the bottom of the list, at probationary pay and benefits, regardless of experience. The long, slow climb begins again. This is industry standard, and there are no exceptions—not for Chesley Sullenberger, not for a former NASA astronaut, not for anybody. When the pilots of Eastern, Braniff, Pan Am, and a hundred other belly-up carriers suddenly found themselves on the street, their choice was an ugly one: start over as a rookie, as it were, or find another career. If business is bad and airlines are contracting, seniority moves in reverse: captains become first officers; and junior first officers become cab drivers. In the rickety profit/loss roller coaster that is the airline industry, layoffs—furloughs, as we call them—come and go in waves, displacing thousands at a time.

The Eureka Factor
by John Kounios
Published 14 Apr 2015

And I needed to touch down just above our minimum flying speed but not below it. And I needed to make all these things happen simultaneously.” Three and a half minutes after the bird strike, flight 1549, with its complement of 155 passengers and crew members, landed safely in the Hudson River. All were saved. Why did Captain Sullenberger succeed where virtually all pilots had previously failed? Sullenberger learned to fly at sixteen. When he enrolled in the U.S. Air Force Academy, he received glider training and became an instructor pilot. In the air force, he spent five years as a fighter pilot, where he became a flight leader, a training officer, and a member of the aircraft accident investigation board.

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The quick wits of experts can even save lives. On January 15, 2009, US Airways flight 1549 took off from New York’s LaGuardia Airport bound for Charlotte, North Carolina. While ascending, the plane struck a flock of birds. Captain Chesley (“Sully”) Sullenberger smelled burning—birds had been sucked into the engines. Then the engines went dead. Within thirty seconds, Captain Sullenberger concluded that the engines couldn’t be restarted. The plane’s altitude was three thousand feet and decreasing rapidly. He communicated the situation to the air traffic control tower and looked for a place to land. Decades of training and experience were brought to bear in an instant: “I quickly determined that due to our distance from LaGuardia and the distance and altitude required to make the turn back to LaGuardia, it would be problematic reaching the runway, and trying to make a runway I couldn’t quite make could well be catastrophic to everyone on board, and persons on the ground.

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Regarding Bent Larsen’s approach to playing chess, see query.nytimes.com/gst/fullpage.html?res=9403E0DD1638F931A2575AC0A9669D8B63. Quick Think 1 The information about, and quotes from, Captain Chesley Sullenberger are derived from www.airspacemag.com/flight-today/Sullys-Tale.html/; www.cbsnews.com/news/flight-1549-a-routine-takeoff-turns-ugly/; and Wikipedia, s.v. “Chesley Sullenberger,” last modified June 26, 2014, en.wikipedia.org/wiki/Sullenberger. CHAPTER 4: ALL OF A SUDDEN … * * * 1 The idea that creativity does not differ from “ordinary” thought is discussed in R. W. Weisberg, Creativity: Understanding Innovation in Problem Solving, Science, Invention, and the Arts (Hoboken, N.J.: John Wiley and Sons, 2006). 2 The anagram study by R.

Team of Teams: New Rules of Engagement for a Complex World
by General Stanley McChrystal , Tantum Collins , David Silverman and Chris Fussell
Published 11 May 2015

The lack of fuel meant there was no fire and the houses the plane struck happened to be empty, but eight passengers, a flight attendant, and the flight engineer were killed; twenty-four people suffered serious injuries. • • • Compare the tragedy of United Flight 173 to the story of US Airways Flight 1549—the plane that Captain Chesley Sullenberger ditched in the Hudson River in 2009. Shortly after the flight took off from LaGuardia Airport, a flock of Canada geese in the midst of their annual migration flew into both engines, causing immediate engine failure. Barely two thousand feet above the ground, the crew had only moments to respond. All emergency checklists and technical training designed to confront engine failures were premised on the assumption that such failure would transpire at cruising altitude above twenty thousand feet—an incapacitating event so low was unprecedented.

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• • • The accident report deconstructing the success of Flight 1549 noted that Sullenberger’s crew’s technical training had been completely irrelevant to the solution they achieved. No procedure for low-altitude dual-engine failure existed anywhere in the industry. It was their interactive adaptability, the report found, that proved crucial: Because of time constraints, they could not discuss every part of the decision process; therefore, they had to listen to and observe each other . . . [the captain] and the first officer had to work almost intuitively in a close-knit fashion. The report concluded, “The captain credited US Airways CRM training for providing him and the first officer with the skills and tools that they needed to build a team quickly and open lines of communication, share common goals, and work together.”

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But for groups like the SEALs, the oneness imbued by trust and purpose is a prerequisite to deployment. Entering the battlefield as a group of individuals without those characteristics would be like walking into a firefight without wearing body armor. The SEAL team in Abbottabad had not planned for the helicopter crash, just as Captain Sullenberger’s crew had not planned for the bird strike, and the Carty-Caterson team had not planned for the marathon bombing, but all were capable of adjusting to the unexpected with creative solutions on the spot, coherently and as a group. Their structure—not their plan—was their strategy. EMERGENT INTELLIGENCE In his book Emergence, Steven Johnson debunks “the myth of the ant queen.”

When to Rob a Bank: ...And 131 More Warped Suggestions and Well-Intended Rants
by Steven D. Levitt and Stephen J. Dubner
Published 4 May 2015

But I have to admit there is something particularly creative about affixing a value to time itself, especially if you can capture that value for your own benefit. Maybe I will write more about that tomorrow™. What Captain Sullenberger Meant to Say (But Was Too Polite to Do So) (BY “CAPTAIN STEVE”) Captain Steve is a seasoned international pilot for a major U.S. carrier and a friend of Freakonomics. (Given the sensitivity of what he writes, he prefers anonymity.) This post was published on June 24, 2009, six months after the “The Miracle on the Hudson,” in which Captain Chesley Sullenberger safely landed an Airbus A320-200 in the Hudson River. Both the plane’s engines had failed, due to a bird strike, shortly after takeoff from LaGuardia Airport in New York.

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Both the plane’s engines had failed, due to a bird strike, shortly after takeoff from LaGuardia Airport in New York. After reading some of the excerpts of Captain Sullenberger’s various speeches, especially those of a few weeks ago with the National Transportation Safety Board, I would like to add my editorial. Captain Sullenberger has been a class act all the way. He’s not been petty, pious, or egotistical. He is, however, like most of the captains I know and, more broadly, most of the pilots I know. Why? He doesn’t need to be otherwise. When someone has accomplished what he and the scores of men and women like him have accomplished, why do we need to boast? He implies that what he did while serving as the “skipper” of US Airways flight 1549 was simply his job.

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Wade, 288 Romer, David, 208 Rooney family, 214 Rose, Charlie, 274 Rose, Pete, 80–81 Rossi, Martin, 33–34 Rossotti, Charles O., 12 Rubinstein, Yona, 9–10 rugby, blood injuries in, 148–49 Sadoff, Sally, 338 Saffer, Henry, 116 Sandusky, Jerry, 121 satisfaction, 122–23 scientific ideas, legitimacy of, 123 security overkill, 106–7 security screening, 108–9 self-consciousness, 123–24 self-reporting, 137–40 INS Form N-400, 237–38 Seltzer, Margaret, 146 Sen, Amartya, 336–37 September 11 attacks, 212–13, 252 sex: casual, 261 high-end call girl, 261–67 more, 259–61 prostitution, 255–56, 265–67 tax on, 256–59 Sexton, Alison and Steve, 184–85 shark attacks, 113 Shin-Yi Chou, 116 shrimp, 341–44 Siberry, Jane, 69–71 Silvertooth, Eugene “Chip,” 47 Simmons, Matthew, 114–16 Simon, Julian, 114 60 Minutes, 61–62 skin color, in the marketplace, 319–22 Smith, Adam, 315 Smith, Noah, 26–27 soccer, 209, 211, 212, 256 Somali pirates, 314–19 songs, prices of, 69–71 specialization, efficiency of, 172 sports: autographed baseballs, 80–81 betting on teams, 125–26 bowling, 204–6 cheating in, 148–50 doping, 151–52, 153 football, 206–9, 212–19, 239–41 golf, 198–204 home field advantage, 209–12 horseback riding, 101–3 horse racing, 191, 220–22 loss aversion, 206–9 players carrying concealed weapons, 240–41 soccer, 209, 211, 212, 256 steroids, 152–53 taxes on athletes’ incomes, 72–74 statistics: and medicine, 280–82 misinterpretation of, 345 Stein, Luke, 320–22 Steinem, Gloria, 51 Stenger, Victor, 286 steroids, 152–53 Stevenson, Betsey, 344–47 Stewart, Jon, 273–74 Stewart, M. R., 38–39 stock markets, capitalization of, 67 strangers, fear of, 130–33 street gangs, 229–36, 246–47, 248–49 street handouts, 328–37 Stubbs, Bob, 46 subjectivity, 170 Sullenberger, Chesley “Sully,” 82–83 SuperFreakonomics (Levitt & Dubner), 54, 101, 105, 119, 121, 261 supply and demand, 78–80, 110, 112, 115, 128, 341–44 Swift, Jonathan, 258–59 Taleb, Nassim Nicholas, 329, 334–37 tax code, 159–60 taxes: on athletes’ incomes, 72–74 cheating on, 158–60 on sex, 256–59 war on, 11–14 Taylor, Brian, 253 Taylor, Sean, 241 teachers, cheating by, 103–4, 160–61 Tejada, Miguel, 149 tenure, 16–19 Terrible Towel, 215 terrorism, 5–11, 108–9, 252 Thaler, Richard, 68, 308–9 Think Like a Freak (Levitt & Dubner), 26, 27 350.org, 178–84 ticketless travel, 141 Tierney, John, 114–16 Tinker, David, 40 tipping, and flight attendants, 19–20 Tomlin, Mike, 218 tooth decay, 275–76 Tour de France, 151–52 Travolta, John, 306 Tropicana, 174–75 TSA, 5–6, 11, 108–9, 251–53 Tversky, Amos, 206 TV viewing habits, 322–24 Twitter contest, 94–96 umbrellas, dangers of, 108–9 United States, six-word motto for, 96–99 Unlawful Internet Gambling Enforcement Act (UIGEA), 129–30 US Airways flight 1549, 82–83 Veblen, Thorstein, 184 veganism, 179–84 Velde, François, 62 Venkatesh, Sudhir, 229–36, 246–47 Vermeil, Dick, 207–8 Virgin Mobile, 63–64 voting mechanisms, 29–31 wages: and markets, 24, 25 of politicians, 32–36 and quality of applicants, 34 walking drunk, 101 Wayne (middle name), 38–40 Weber, Christopher L., 171, 172 Weller, Mark, 62–63 Werner, James, 40 Wertheim, Jon, 209–12 Weyl, Glen, 30–31 White, Byron “Whizzer,” 214 Williams, Tom, 148–49 Wilson, A.N., 282 Winfrey, Oprah, 51 Wire, The, 229–33 Witt, Robert, 225–26 Wolf, Cyril, 51–53 Wolfers, Justin, 344–47 women: feminist movement, 346–47 and happiness, 344–47 work: incentives in, 339–40 leisure vs., 168 World Preservation Foundation, 179–82, 192–95 World Series of Poker, 187–88, 192–95 Worthy, Paige, 44–45 Zelinsky, Aaron, 152–53 About the Authors STEVEN D.

The Digital Doctor: Hope, Hype, and Harm at the Dawn of Medicine’s Computer Age
by Robert Wachter
Published 7 Apr 2015

He shows us that it’s not just the technology but how we manage it that will determine whether the computerization of medicine will be for good or for ill. And he reminds us that the promise of technology in healthcare will be realized only if it augments, but does not replace, the human touch.” —Captain Chesley “Sully” Sullenberger speaker; consultant; author of Highest Duty and Making a Difference; pilot of US Airways 1549, the “Miracle on the Hudson” “With vivid stories and sharp analysis, Wachter exposes the good, the bad, and the ugly of electronic health records and all things electronic in the complex settings of hospitals, physician offices, and pharmacies. Everyone will learn from Wachter’s intelligent assessment and become a believer that, despite today’s glitches and frustrations, the future computer age will make medicine much better for us all.”

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She thought for a moment and then said, “If the alarms went silent. That would be scary.” Medicine, of course, is not the only industry in which professionals need to perform their tasks in a swirling, often confusing, high-stakes environment, nor the only one that has to grapple with the matter of computerized alerts. I spoke to Captain Chesley “Sully” Sullenberger, the famed “Miracle on the Hudson” pilot, about how aviation handles the matter of alerts. “The warnings in cockpits now are prioritized so you don’t get alarm fatigue,” he told me. “We work very hard to avoid false positives because false positives are one of the worst things you could do to any warning system.

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Mitchell, et al., “Mortality and Morbidity in Patients Receiving Encainide, Flecainide, or Placebo: The Cardiac Arrhythmia Suppression Trial,” New England Journal of Medicine 324:781–788 (1991). 146 “Based on what I can extract from the data” Interview of Shahram Ebadollahi by the author, August 18, 2014. 146 “Missing a real event is much more costly” Quoted in L. Kowalczyk, “Patient Alarms Often Unheard.” 147 I spoke to Captain Chesley “Sully” Sullenberger Interview of Sullenberger by the author, May 12, 2014. 147 So I spent a day in Seattle with several of the Boeing engineers Interviews of Bob Myers, Alan Jacobsen, and Mark Nikolic by the author, June 4, 2014. 150 and a 2010 Australian study confirmed that it is J. I. Westbrook, A. Woods, M. I.

The Glass Cage: Automation and Us
by Nicholas Carr
Published 28 Sep 2014

In early 2009, just a few weeks before the Continental Connection crash in Buffalo, a US Airways Airbus A320 lost all engine power after hitting a flock of Canada geese on takeoff from LaGuardia Airport in New York. Acting quickly and coolly, Captain Chesley Sullenberger and his first officer, Jeffrey Skiles, managed, in three harrowing minutes, to ditch the crippled jet safely in the Hudson River. All passengers and crew were evacuated. If the pilots hadn’t been there to “babysit” the A320, a craft with state-of-the-art automation, the jet would have crashed and everyone on board would almost certainly have perished.

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The Airbus sidesticks, in contrast, are not in clear view, they work with much subtler motions, and they operate independently. It’s easy for a pilot to miss what his colleague is doing, particularly in emergencies when stress rises and focus narrows. Had Robert seen and corrected Bonin’s error early on, the pilots may well have regained control of the A330. The Air France crash, Chesley Sullenberger has said, would have been “much less likely to happen” if the pilots had been flying in a Boeing cockpit with its human-centered controls.32 Even Bernard Ziegler, the brilliant and proud French engineer who served as Airbus’s top designer until his retirement in 1997, recently expressed misgivings about his company’s design philosophy.

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F., 179n Slamecka, Norman, 72–73, 74 slavery, slaves, 20, 21, 25, 26, 224–26 slot machines, 179n Small, Willard, 88 smartphones, 12–13, 33, 91, 136, 199–202 smartwatch, 201, 202 Smith, Adam, 21–22, 106–7 social decision-making, 122 social networks, 181–82 society, 159–60, 161, 172, 173, 176 automation’s changing of nature of, 193–99, 202 trade-offs made by, 207–8 sociologists, 109, 158–59 software, 1, 7–8, 12, 27, 28, 30, 33, 40, 52, 66, 67, 90, 108, 114–16, 119, 136, 151–52 architecture and design, 135, 138–47, 167, 229–30 cognitive processes and, 74–77, 80 compelling urgency of, 194 decision support, 70–71 ergonomics and, 164 ethics and, 184, 204 hidden assumptions of, 206 human- vs. technology-centered, 156, 160, 172–76 limits of, 9, 205 medical, 97–100, 114–15 planes and, 52, 54, 57, 168 social adaptations to, 202–8 trust in, 69 video games as model for design of, 178–82 software programmers, 157, 159, 174, 175 space, 129–30, 133–36, 205 Specialmatic, 174–75 speed, 17, 20, 35, 38, 51, 88, 159, 181, 207 of computers, 118–22, 139, 156, 164, 173, 219 of robots, 186 spell checkers, 180–81 Spence, Michael, 30 Sperry, Elmer A., 47 Sperry, Lawrence, 46–47, 50, 53, 232 Sperry autopilot, 47–49 Sperry Corporation, 49, 58 Spinoza, Baruch, 216 spy agencies, 120 Stanton, Neville, 90–91 Star Trek, 232 steamships, 36–37 stick shift, 3–6, 13 Street View, 136 substitution myth, 67, 97, 98, 129, 193 Sullenberger, Chesley, 154, 170 supersystem, development of, 196 Sutherland, Ivan, 138 tablets, 153, 199, 202 tacit (procedural) knowledge, 9–11, 83, 105, 113, 144 talents, 12, 27, 61, 74, 83, 85, 112, 216, 217, 219 of doctors, 105 human, limits to replication of, 9 Talisse, Robert, 85 Tango (mapping technology), 136 Taylor, Frederick Winslow, 107, 108, 114, 158, 207 teachers, teaching, 10, 12, 32, 153 technical arrogance, 175 technological momentum, 172–75, 196 technological unemployment, 26, 27, 198 technology, 1–2, 150–51, 215–32 health information, 93–106 invisibility of, 203–4, 208–10 labor-saving, 17, 20, 28, 67 long history of ambivalence to, 21–41 master-slave metaphor and, 224–26 progress and, see progress, technological TED conference (2013), 199–201 Tesla Motors, 8 tests, medical, 70–71, 99, 102, 245n–46n Thiel, Peter, 227 thinking, thought, 65, 67, 147–51 artificial intelligence and, 119 drawing as, 142–43, 144 Thinking Hand, The (Pallasmaa), 145 Thomis, Malcolm, 23 THOR (software program), 171 Thrun, Sebastian, 6, 207 tools, 150–51, 158, 174, 185, 195, 215–19, 221–26 To Save Everything, Click Here (Morozov), 225 traders, trading, 77, 115, 171 Tranel, Ben, 167 transport, 48, 49, 132, 173 “Tuft of Flowers, The” (Frost), 221 Turing, Alan, 119–20 Turkle, Sherry, 69 unconscious mind, 121, 148–49 unemployment, 20, 25–29, 38 technological, 26, 27, 198 United Kingdom, 95 University College London, 133 UPS, 117 U.S.

Alchemy: The Dark Art and Curious Science of Creating Magic in Brands, Business, and Life
by Rory Sutherland
Published 6 May 2019

A fielder would, of course, have no time to perform mathematical calculations, even if a calculator were available, and moreover, even if he had enough time and calculating power, he simply wouldn’t have enough data without knowing the velocity or the angle at which the ball was hit to calculate its trajectory to any level of accuracy. The batsman who hit the ball probably wouldn’t know, either.* 5.4: He’s Not Stupid, He’s Satisficing On 15 January 2009, in an incident now known as the ‘Miracle on the Hudson’, Captain Chesley Sullenberger demonstrated the value of heuristics when, after his aircraft had both its engines disabled by a bird strike, he reacted quickly and safely landed on the Hudson River. It is possible to listen to Sullenberger’s conversations with air traffic control on YouTube: between attempts to restart the engines, he communicates with the departure airport. Having immediately rejected the possibility of returning to LaGuardia, correctly as it turns out, he is offered the possibility of landing at Teterboro Airport, which is in New Jersey over to his starboard side.

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A former US Air Force fighter pilot, Sullenberger was a glider pilot in his spare time, and all glider pilots learn a simple instinctive rule which enables them to tell whether a possible landing site on the ground is within their reach. They simply place the glider in the shallowest possible rate of descent and look through the windshield: any place which appears to be moving downwards in the field of view is somewhere they can safely land, while anywhere on the ground that appears to be moving upwards is too far away. It was by deploying this rule that he was able to decide within seconds that the Hudson River was the only feasible landing site.

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The main value of having a swimming pool at home is not that you swim in it, but that it allows you to walk around your garden in a bathing costume without feeling like an idiot. A friend who had been invited to spend a week on a luxury yacht explained why they are so popular with megalomaniacs: ‘You can invite your friends to join you on holiday, then spend the week treating them like you are Captain Bligh.’ If you have the most magnificent villa in the world, there is still the risk that your friends and rivals might hire a car and wander off on their own: on a megayacht, however, they are your captives.* One problem (of many) with Soviet-style command economies is that they can only work if people know what they want and need, and can define and express their wants adequately.

Our Robots, Ourselves: Robotics and the Myths of Autonomy
by David A. Mindell
Published 12 Oct 2015

De Crespigny marshaled his remaining resources, focused his attention, and the crew landed flight QF32 safely back in Singapore with no injuries. Every time lives are lost due to human error, we can think of other times when they have been saved by human judgment and skill. QF32, and the “miraculous” 2009 US Airways landing on the Hudson River at the hands of Captain Chesley Sullenberger, seem to show that experienced, skilled, calculating humans are critical safety features of these systems on which our lives depend, the last line of defense when the machines fail. Air France 447 and others undermine those hopes. In the summer of 2013, pilots of Asiana Airlines flight 214 failed to successfully land their modern Boeing 777 in San Francisco on a perfectly clear day; the crash landing killed three and injured scores.

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“The twentieth century was born yearning for a new type of hero,” writes aviation historian Robert Wohl, “someone able to master the cold, inhuman machines that the nineteenth century bequeathed and at the same type transforming them into resplendent art and myth.” From Charles Lindbergh to Neil Armstrong to “Sully” Sullenberger, the cultural icon of the pilot embodied the human on the cutting edge of technology and social change. Analogies flowed freely—the adventurer of the sky, the aerial artist, the athlete of the third dimension. World War I offered new identities, particularly the “knight of the air” flying fighter ace, reviving ancient mythologies to rescue heroism from an anonymous war of trenches and random death.

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F., 38 Skynet (driverless car), 204–5 SM4 Hubble repair mission on STS-125, 173, 174–75 Southwest Airlines, 92–93 spaceflight and exploration, 159–90 autoland and, 159–63 heads up display (HUD) and, 159 Hubble Space Telescope service and repair missions and, 163–75 Mars Exploration Rover (MER) missions and, 163, 164, 175–90 space shuttles, 161–63 Spirit (mobile robot), 181, 184–86 Squyres, Steven, 175, 183–84, 185 SR-71 spy plane, 123 Star Wars (movie), 161, 217 STS-61 (first Hubble repair mission), 167–72 Sullenberger, Chesley, 72, 77 supervisory control, 38, 62 synthetic vision, 108–9, 225 systems managers, pilots as, 80 Talos (driverless car), 204–5 telepresence, 26, 43, 57 Teller, Seth, 200 Thornton, Kathy, 170, 171–72 Three Mile Island nuclear accident, 38 Thresher (submarine), 27, 36, 42 Thronson, Harley, 188–89 Thrun, Sebastian, 199–200 Time, 50–51 Titanic (movie), 51 Titanic (ship), 40, 42–43, 45–51 Toscano, Michael, 219–20 Trieste (bathyscaphe), 35, 44 trimming of aircraft, 116 Turkish Airlines crash, in Amsterdam, 105 U-2 spy plane, 123 Uber, 199 Uchuppi, Al, 43 unmanned aerial vehicles (UAVs).

Deep Sea and Foreign Going
by Rose George
Published 4 Sep 2013

He tried to call the barge and got no response, then watched in disbelief as the barge hit his ship, fracturing all three cargo tanks. Suddenly there he was in the middle of an environmental disaster ‘with hydrocarbons all around us’. Imagine that the ship was an aeroplane. Imagine, for example, that it was US Airways Airbus A320, landed on New York’s Hudson River by Captain Chelsey Sullenberger in 2009. Although fuel oil was discharged into the river, Captain Sullenberger was an immediate hero, because all lives were saved. No-one died either in the collision between the barge and Hebei Spirit. Yet Jasprit Chawla and his first officer were immediately thrown in jail. Chawla had been at sea for 16 years without incident.

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Brown, 1 noise, underwater, 1 North West Evening Mail, 1 Northeast Passage, 1 NRP Vasco da Gama, 1, 2, 3, 4 Oakie, Jack, 1 Obama, President Barack, 1 O’Brien, Bob, 1 Observer, 1 ocean gyres, 1 oceanic dead zones, 1 oil crisis (1973), 1, 2 oil spills, 1, 2, 3 oil tankers, 1, 2, 3, 4 oil traffic, 1, 2 O’Kennedy, Wing Commander Paddy, 1, 2, 3 Oman, 1 outboard motors, 1 Ouzo (yacht), 1, 2, 3 Oxford Companion to Ships and the Sea, 1 Pakistani seafarers, 1 Pamir (sail-training ship), 1, 2 Panama Canal, 1, 2 Parker, Tony, 1 Parkes, Susan, 1 particulate emissions, 1 Pattaya, 1 Paul, Roy, 1 Pelton, Robert Young, 1 Penang, 1 people traffickers, 1 Philadelphia, 1 Philipse, Colonel Frederick, 1 Phillips, Captain Richard, 1 pig iron, cargoes of, 1 pigeons, 1, 2 Pillars of Hercules, 1, 2 Pillay, Navi, 1 pilots, 1, 2 piracy and pirates anti-piracy measures, 1, 2 and armed security, 1 arrests and prosecutions, 1, 2 compassion for Somalis, 1 deemed haram, 1 division of labour, 1 earnings, 1 economic consequences, 1 economic model, 1 EU-NAVFOR counter-piracy operations, 1, 2 fishermen mistaken for pirates, 1, 2 in history, 1, 2 in Malacca Straits, 1 myths about Somali pirates, 1 nationalities, 1 negotiations, 1, 2 planning and targeting, 1 ransoms, 1, 2 statistics, 1, 2 and torture, 1 ‘tripwires’, 1 victims of, 1 Pirates of Somalia, The (film), 1 Plutarch, 1, 2 Poon Lim, 1 porpoises, 1, 2 Port Klang, 1, 2, 3, 4 Port of London Mission, 1 privateers, 1 prostitutes, Brazilian, 1 Provincetown, Cape Cod, 1 Puerto Cortes, 1 Puget Sound, 1 Puntland, 1, 2, 3, 4 Qasim, 1 Quantrill, Dr Douglas, 1 Quest (yacht), 1, 2 Race Point, 1, 2 rape, 1 rats, 1 Redl, Joan, 1 reefs, artificial, 1 RFA Wave Knight, 1 Richardson, Pam, 1 Riggle, Bob, 1 RMS Laconia, 1 RMS Queen Elizabeth II, 1 RMS Titanic, 1, 2, 3 Roberts, Bartholomew, 1 Rogerson, Captain William, 1 Rolland, Roz, 1 Romanian seafarers, 1 Romney, Mitt, 1 Roosevelt, President Franklin D., 1, 2 Roper, Janet (Mother Roper), 1 Rotterdam, 1 Rousmaniere, Leah Robinson, 1, 2 Royal Navy, 1, 2, 3 RRS Ernest Shackleton, 1 Russian Navy, 1, 2 Russian seafarers, 1, 2 RV Shearwater, 1, 2, 3 Safe Port Act, 1, 2 St Augustine, 1 Salalah, 1, 2, 3, 4, 5, 6 Oasis Club, 1 Samsung Heavy Industries, 1 San Francisco, 1 Sandi, Jakku Suleiman, 1 Sanghar, Captain Akbarali Mamad, 1 sanitation, on-board, 1 Saunders, Rupert, 1 Savarese, Giuseppe, 1 Saved from the Sea (film), 1 Schettino, Francesco, 1 sea turtles, 1 seafarer certificates, 1 seafarers American hostility to, 1 blamed for accidents, 1 exploitation of, 1 fatalities among, 1 loneliness, 1 medical needs, 1 mortality rates, 1, 2, 3 nationalities, 1 working hours, 1 Sea-Land Service, Inc., 1 Seamen’s Church Institute (SCI), 1, 2, 3, 4 seamen’s missions, 1, 2 searchlights, 1 seasickness, 1, 2 seawater, effects of drinking, 1 Securewest, 1 security and terrorism, 1 seismic airguns, 1 Sekula, Allan, 1 Semenov, Waldemar, 1 Semide, Commander, 1 Senusret III, Pharaoh, 1 Sesay, Issa, 1 Seve, J.A., 1 sewage sludge, discharge of, 1, 2 sextants, 1, 2, 3 sharks, 1, 2, 3, 4, 5 Shibin, Mohammed Saaili, 1 ship-building, 1 shipping industry and environment, 1 recession in, 1 secrecy and invisibility, 1, 2, 3 and whale strikes, 1 shipping news, 1 ships abandoned, 1 laid-up, 1 naming of, 1, 2 ships’ agents, 1, 2 ships’ bridges, 1 ships’ captains earnings, 1 in port, 1 and shipwrecks, 1, 2 social isolation, 1 ships’ cats, 1, 2 ships’ chandlers, 1, 2, 3 ships’ godmothers, 1 ships’ propellers, 1 Shipwrecked Mariners’ Society, 1 shore leave, 1, 2, 3 Short, John, 1 Shortland, Dr Anja, 1 Sierra Leone, civil war, 1, 2 Silva Barata, Lieutenant-Commander Pedro, 1, 2 Simon, Able Seaman (cat), 1, 2 Singapore, 1, 2, 3 Slabbekoorn, Hans, 1 ‘slow steaming’, 1 Smuggling Precautions, 1 sniffer bees, 1, 2 sniffer dogs, 1 Soladiesel, 1 Somali fishermen, 1 Somali pirates, see piracy and pirates sonar, 1 South Shields, 1 Southampton, 1, 2 Southend Pier, 1 Sovereign Ventures, 1, 2 Special Boat Service, 1 SPS Infanta Cristina, 1 SS Alcoa Guide, 1 SS Amazone, 1 SS Anglo Saxon, 1, 2 SS Ashby, 1 SS Athenia, 1 SS Benvrackie, 1 SS Calchas, 1 SS Cingalese Prince, 1 SS City of Cairo sinking, 1, 2 SS Culworth Hill, 1 SS Halsey, 1 SS Rakhotis, 1 SS Soekaboemi, 1 SS Storaa, 1 SS Svendborg, 1 SS Warrior, 1 Stena Lines, 1 Stephen, King, 1 stevedores, 1 Stobbart, Frank, 1 Stockholm International Peace Research Institute (SIPRI), 1, 2 storms, 1 stowaways, 1 Strait of Gibraltar, 1 Strait of Hormuz, 1, 2 Straits of Malacca, 1, 2, 3 and piracy, 1 Strangers’ Rest Mission, 1 Strickler, Homer, 1 Strong, L.A.G., 1 Suez Canal, 1, 2, 3, 4, 5, 6 construction, 1 crews, 1 pilots, 1 transit costs, 1 Sullenberger, Captain Chelsey, 1 sulphur content, in fuel, 1, 2 Sumatra, 1, 2 Sunday Times (South Africa), 1 supply vessels, 1, 2, 3 Tapscott, Robert, 1 Taskar, Dr, 1, 2 Taylor, ex-President Charles, 1, 2 tea clippers, 1, 2 Tebbutt, David, 1 Thames, River, 1 Thomas, Captain Richard, 1 thunderboxes, 1 Tilbury, 1 Titanic (film), 1 Toki, Bryan, 1 trade, value of sea-borne, 1 transport costs, 1, 2 Trinh Vinh Thang, 1 tugs, 1 U-boats, 1, 2, 3, 4, 5, 6 UK Hydrographic Office, 1, 2 UK Marine Accident Investigation Branch, 1, 2 UK Maritime and Coastguard Authority, 1 UK Maritime Trade Operations Centre, 1 Ukrainian seafarers, 1, 2 Umenhofer, Walter, 1 UN Convention on the Law of the Sea (UNCLOS), 1, 2 UN Offices on Drugs and Crime, 1 United States of America and container security, 1 decline of seafaring, 1 hostility to seafarers, 1 merchant marine and wartime, 1, 2, 3 piracy prosecutions, 1 Prohibition era, 1 sea-borne trade, 1, 2 and seafarers’ welfare, 1 uranium, shipping of, 1 Urban Whale, The, 1, 2 US Coast Guard, 1 US Customs and Border Agency, 1, 2 US Department for Homeland Security, 1, 2 US Marines, 1, 2, 3, 4 US National Oceanic and Atmospheric Association (NOAA), 1, 2 US Navy, 1, 2, 3, 4 anti-piracy patrols, 1 US Navy Seals, 1 US Office for Naval Research, 1 USCG cutter Campbell, 1 USS Cole, 1 USS Indianapolis, 1, 2 USS Nicholas, 1 USS Vella Gulf, 1 Vessel Data Recorders, 1 VHF radio, 1, 2, 3, 4 wages, unpaid, 1, 2 Wallis, Barnes, 1 war graves, 1 Watts, Norman, 1 Watts, Tiny, 1 whale-watching, 1 whales, 1 communication among, 1 disentanglement, 1, 2 Eubalaena glacialis, 1 exploding, 1 fasting, 1 identification of, 1 and noise, 1 ‘sagging’, 1 scat collecting, 1 skimming, 1 stranded, 1 whaling industry, 1 Widdicombe, Wilbert, 1, 2 Wilson, R.

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Kendal shone searchlights on them, a passing US helicopter did a fly-by, and the suspect craft flashed lights back. Marius thinks they were friendly; the captain is more sceptical. Sometimes they pretend to be friendly. They lure you in. The captain’s daily orders, written instructions that are kept on the bridge, require his officers to stay four miles away from small craft if possible. He has written, ‘Trust no-one.’ Once, the captain was having dinner when the first officer made an announcement over the PA. ‘Captain to the bridge.’ This is not an announcement a captain ever likes to hear. He thought, ‘Oh, shit,’ displayed no outward alarm, and took the lift up to the wheelhouse.

Prediction Machines: The Simple Economics of Artificial Intelligence
by Ajay Agrawal , Joshua Gans and Avi Goldfarb
Published 16 Apr 2018

While it does not take a tremendous amount of training to begin a job as a crew member at McDonald’s, new employees are slower and make more mistakes than their more experienced peers. They improve as they serve more customers. Commercial airline pilots also continue to improve from on-the-job experience. On January 15, 2009, when US Airways Flight 1549 was struck by a flock of Canada geese, shutting down all engine power, Captain Chesley “Sully” Sullenberger miraculously landed the plane on the Hudson River, saving the lives of all 155 passengers. Most reporters attributed his performance to experience. He had recorded 19,663 total flight hours, including 4,765 flying an Airbus A320. Sully himself reflected: “One way of looking at this might be that for 42 years, I’ve been making small, regular deposits in this bank of experience, education, and training.

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The judgment is the simple recognition that the objective is to score the most points. Teaching a machine to play a sandbox game like Minecraft or a collection game like Pokemon Go would require more judgment, since different people enjoy different aspects of the games. It isn’t clear what the goal should be. 8. Chesley “Sully” Sullenberger quoted in Katy Couric, “Capt. Sully Worried about Airline Industry,” CBS News, February 10, 2009; https://www.cbsnews.com/news/capt-sully-worried-about-airline-industry/. 9. Mark Harris, “Tesla Drivers Are Paying Big Bucks to Test Flawed Self-Driving Software,” Wired, March 4, 2017, https://backchannel.com/tesla-drivers-are-guinea-pigs-for-flawed-self-driving-software-c2cc80b483a#.s0u7lsv4f. 10.

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See autonomous vehicles sensors, 15, 44–45, 105 Shevchenko, Alex, 96 signal vs. noise, in data, 48 Simon, Herbert, 107 simulations, 187–188 skills, loss of, 192–193 smartphones, 129–130, 155 Smith, Adam, 54, 65 The Snows of Kilimanjaro (Hemingway), 25–26 society, 3, 19, 209–224 control by big companies and, 215–217 country advantages and, 217–221 inequality and, 212–214 job loss and, 210–212 Solow, Robert, 123 Space Shuttle Challenger disaster, 143 sports, 117 camera automation and, 114–115 sabermetrics in, 56, 161–162 spreadsheets, 141–142, 163, 164 Standard & Poor’s, 36–37 statistics and statistical thinking, 13, 32–37 economic thinking vs., 49–50 human weaknesses in, 54–58 stereotypes, 19 Stern, Scott, 169–170, 218–219 Stigler, George, 105 strategy, 2, 18–19 AI-first, 179–180 AI’s impact on, 153–166 boundary shifting in, 157–158 business transformation and, 167–178 capital and, 170–171 cheap AI and, 15–17 data and, 174–176 economics of, 165 hybrid corn adoption and, 158–160 judgment and, 161–162 labor and, 171–174 learning, 179–194 organizational structure and, 161–162 value capture and, 162–165 strokes, predicting, 44–46, 47–49 Sullenberger, Chesley “Sully,” 184 supervised learning, 183 Sweeney, Latanya, 195, 196 Tadelis, Steve, 199 Taleb, Nassim Nicholas, 60–61 The Taming of Chance (Hacking), 40 Tanner, Adam, 195 task analysis, 74–75, 125–131 AI canvas and, 134–139 job redesign and, 142–145 Tay chatbot, 204–205 technical support, 90–91 Tencent Holdings, 164, 217, 218 Tesla, 8 Autopilot legal terms, 116 navigation apps and, 89 training data at, 186–187 upgrades at, 188 Tesla Motor Club, 111–112 Thinking, Fast and Slow (Kahneman), 209–210 Tinder, 189 tolerance for error, 184–186 tools, AI, 18 AI canvas and, 134–138 for deconstructing work flows, 123–131 impact of on work flows, 126–129 job redesign and, 141–151 usefulness of, 158–160 topological data analysis, 13 trade-offs, 3, 4 in AI-first strategy, 181–182 with data, 174–176 between data amounts and costs, 44 between risks and benefits, 205 satisficing and, 107–109 simulations and, 187–188 strategy and, 156 training data for, 43, 45–47 data risks, 202–204 in decision making, 74–76, 134–138 by humans, 96–97 in-house and on-the-job, 185 in medical imaging, 147 in modeling skills, 101 translation, language, 25–27, 107–108 trolley problem, 116 truck drivers, 149–150 Tucker, Catherine, 196 Tunstall-Pedoe, William, 2 Turing, Alan, 13 Turing test, 39 Tversky, Amos, 55 Twitter, Tay chatbot on, 204–205 Uber, 88–89, 164–165, 190 uncertainty, 3, 103–110 airline industry and weather, 168–169, 170 airport lounges and, 105–106 business boundaries and, 168–170 contracts in dealing with, 170–171 in e-commerce delivery times, 157–158 reducing, strategy and, 156–157 strategy and, 165 unknown knowns, 59, 61–65, 99 unknown unknowns, 59, 60–61 US Bureau of Labor Statistics, 171 US Census Bureau, 14 US Department of Defense, 14, 116 US Department of Transportation, 112, 185 Validere, 3 value, capturing, 162–165 variables, 45 omitted, 62 Varian, Hal, 43 variance, 34–36 fulfillment industry and, 144–145 taming complexity and, 103–110 Vicarious, 223 video games, 183 Vinge, Vernor, 221 VisiCalc, 141–142, 163, 164 Wald, Abraham, 101 Wanamaker, John, 174–175 warehouses, robots in, 105 Watson, 146 Waymo, 95 Waze, 89–90, 106, 191 WeChat, 164 Wells Fargo, 173 Windows 95, 9–10 The Wizard of Oz, 24 work flows AI tools’ impact on, 126–129 decision making and, 133–140 deconstructing, 123–131 iPhone keyboard design and, 129–130 job redesign and, 142–145 task analysis, 125–131 World War II bombing raids, 100–102 X.ai, 97 Xu Heyi, 164 Yahoo, 216 Y Combinator, 210 Yeomans, Mike, 117 YouTube, 176 ZipRecruiter, 93–94, 100 About the Authors AJAY AGRAWAL is professor of strategic management and Peter Munk Professor of Entrepreneurship at the University of Toronto’s Rotman School of Management and the founder of the Creative Destruction Lab.

Visual Thinking: The Hidden Gifts of People Who Think in Pictures, Patterns, and Abstractions
by Temple Grandin, Ph.d.
Published 11 Oct 2022

William Langewiesche, in a New York Times Magazine story about the Boeing crash, contends that “these pilots couldn’t decipher a variant of a simple runaway trim . . . leading their passengers over an aerodynamic edge into oblivion.” The problem was Boeing’s flawed software system, which repeatedly and aggressively forced the nose of the plane down. It was a perfect storm: a pilot uninformed about the new computer systems, poorly designed software, and a malfunctioning sensor. Captain Chesley Sullenberger, the pilot who successfully landed a plane on the Hudson River, piloted a full-motion flight simulation that replicated the Boeing MAX malfunction. In a letter to the editor of The New York Times, he called the automated system a death trap. Pilot error is cited in 80 percent of all plane crashes. Lion Air was known for poor maintenance and for promoting pilots prematurely to meet the demands of a growing travel market.

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Special issue “10th International Conference on Air Transport—INAIR 2021, towards Aviation Revival.” Transportation Research Procedia 59 (2021): 310–18. https://doi.org/10.1016/j.trpro.2021.11.123. Sparks, J. “Ethiopian Airlines Crash, Anguish and Anger at Funeral for Young Pilot.” Sky News, 2019. Sullenberger, C. “What Really Brought Down the Boeing MAX?” Letter to the Editor, New York Times Magazine, October 13, 2019, 16. Swaminathan, N. “What Are We Thinking When We (Try to) Solve Problems?” Scientific American, January 25, 2008. https://www.scientificamerican.com/article/what-are-we-thinking-when/.

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See also NASA SpaceX, 138–39, 194 spatial visualizers, 47, 61 collaborations of, 121–24, 126, 131, 135, 151 description of, 3, 90–91, 146 excellence at chess, 232 excellence at mathematics, 3, 31–32, 37, 45, 62, 74, 91, 95, 114, 133, 147, 149 future needs for, 152–53 identifying test for, 18–19 versus object visualizers, 90–91, 131 studies on, 30–34, 37–39 traits/skills of, 17, 36–39, 45–46, 105, 107, 143, 175 work with object visualizers, 137–38, 142–43, 146–48, 153 work with verbal thinkers, 151 special education, 4, 55, 107, 277 Species of Mind: The Philosophy and Biology of Cognitive Ethology (Allen and Bekoff), 245 speech and autistic children, 25, 43–44, 77, 79–80, 98, 101 and the brain, 22, 25 therapy for, 9, 77, 80, 100, 170 Sperry, Elmer, 122 Sperry, Roger, 27 Sperry Corporation, 123–24 Spielberg, Steven, 174–75 Spikins, Penny, 161 Stacho, Martin, 256 standardized tests dropped as college admission requirement, 73–74 and inequities, 72–73 for intelligence, 64 and mathematics, 59, 64, 74–75 to measure creativity, 184–85 qualities not found on, 76, 81 stripping school curricula, 51 and visual thinkers, 73–74, 81 See also specific tests Stanford University, 46, 77, 116, 125, 139, 142, 170 Stedman’s Medical Dictionary, 199 Stein, Gertrude, 176 STEM, 69, 95 Steve Jobs Theater (Apple headquarters), 4–5 Stone Age Origins of Autism, The (Spikins), 161 StreamYard, 149 Suh, Joori, 37 Sullenberger, Chesley, 217 Sušac, Ana, 61 Suskind, Owen, 44 Sussex Centre for Neuroscience (UK), 239 Sutton, Mike, 46 Swaminathan, Nikhil, 207 Sweden, 169, 176, 231 Swift cattle plant, 114, 149 Swiss apprenticeship model, 112–14, 117 Syntactic Structures (Chomsky), 1–2 T Tacoma Narrows Bridge (Washington state), 207–8 talking to oneself, 10, 13–14.

Ghost Road: Beyond the Driverless Car
by Anthony M. Townsend
Published 15 Jun 2020

Finally, the delegation of driving to computers may make operating a vehicle more complex, not less. This has long been the case in aviation. Pilots of today’s aircraft now require much more training. “Technology does not eliminate error, but it changes the nature of errors that are made, and it introduces new kinds of errors,” argues Captain Chesley Sullenberger, the US Airways pilot who safely landed an airliner in the Hudson River in 2009. The further the spread of automation in the cockpit, the thicker the machines’ manuals have become. OUR PRESENT TERMINOLOGY for the journey ahead is deeply problematic. The proof is in the public attitude. According to annual surveys by the American Automobile Association, a motorists’ advocacy group, in 2017, 63 percent of US drivers reported they “would be afraid to ride in a fully self-driving vehicle.”

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See driverless shuttles Shyp, 133 Sidewalk Labs, 209, 210, 211, 222, 232 Silverdome (Pontiac, MI), 196n SilverRide, 95 Singapore, 97, 167, 169, 177, 209, 211 singletons, 237–38 Singularity predictions, 234–35, 236–38 Skype, 56 smartphones, 13, 64, 89, 90, 139, 169 see also mobile phones SoftBank, 176, 176–78, 238 software trains, 70–71, 70–72, 197, 200–201, 202, 204, 206 Son, Masayoshi, 176, 178 Space10 (IKEA), 72–73 specialization overview, 16 shifts in daily travel patterns, 53–54 of taxibot rides, 95–97 of traditional automobiles, 52, 80 vehicular variety increase, 16, 18, 52–55 see also specific types of AVs Speedostat, 24 Sprinter delivery vans (Mercedes), 125 Stae, 247 Standard Oil, 174 Starship conveyors, 55–56, 57, 125, 192 Starship Technologies, 56, 57, 124–25 Starsky Robotics, 46 status quo bias, 49–50, 52 steering wheel introduction, 4 Steffens, Lincoln, 180 store closures in US, 117–18, 121 streetcars, 58, 59, 88–89, 106, 174–75, 180–81, 186 “street furniture,” 77 suitcases, semi-autonomous, 125 Sullenberger, Chesley, 45 Superintelligence (Bostrom), 236–37 supermarket, origins of, 116 Superpedestrian, 66 surge pricing, 17, 87, 181 Swift Nick, 161 task model for computerization of work, 150–54, 151, 155 taxibots (AV cabs) computer models of growth, 97–98, 99 doubts about cost-effectiveness, 97–98 impact on taxi business, 94–95 overview, 60–61, 94–95 price savings, 94, 96 rides for pregnant women, 96–97 specialization of rides, 95–97 traffic congestion and, 99 Waymo self-driving taxi service, 8, 46, 97, 230, 240–41 see also mobility as a service taxis automation predicted by 2030, 10–11 impact of taxibot takeover, 94–95 meters in, 169 number of vehicles, 10 ride-hail push to deregulate the taxi business, 40 Waymo self-driving taxi service, 8, 46, 97, 230, 240–41 Teague, 127 TECO Line streetcar (Tampa, FL), 58, 59 Teetor, Ralph, 24, 26 Tel Aviv’s traffic gridlock, 85–87, 88 Tesla, 26–29, 44, 60, 62, 231 three big stories of the driverless revolution, 16–20, 187–88, 238, 248, 253 see also financialization of mobility; materialization; specialization Thrun, Sebastian, xiv, 7, 8 ticketing in transit systems, 89, 90–91, 93, 109, 110–11 time wasted on commuting, 9, 12, 30–31 Toffler, Alvin, 120 toll roads in Great Britain, 162–63 Toronto, Canada, 209–10, 213–14, 222 traction monopolies investors, 176–78, 182–83 in New York City, 174, 174, 180 in Philadelphia, 180 SoftBank, 176, 176–78, 238 in streetcar era, 174, 174–75, 180 traffic congestion cost of time wasted, 9, 12, 30 driverless shuttles and, 106 predicted effects of AVs, 9 ride-hail and, 168 taxibots and, 99 see also congestion pricing trafficgeddons, 85–86 Trafi, 109, 216 transects of the driverless city, 187–88, 188–89, 194–95, 198–99, 200–201, 206–7, 208 transit oriented development (TOD), 200, 202, 203–4 transit systems autonomist contempt for, 214–15 impact of ride-hail, 215–16 as mobility integrators, 216 response to driverless revolution, 214–17 ticketing in, 89, 90–91, 93, 109, 110–11 as transportation utilities, 216 workforce changes, 216–17 TransMilenio (Bogotá), 69 Trikala, Greece, 102–3 trip chaining, 54 Tron (film), 137 trucks and trucking accident risks, 156 automated fleets impact on economic risks, 156–58 automation and types of truck drivers, 153–54 freight AVs and, 125–26 industrial sprawl and, 12–13 investment in self-driving truck startups, 152 “land trains” and “road trains,” 69 last-mile delivery, 121–29, 154, 218 platoons and platooning, 68–69, 70–71 self-driving tractor-trailers, 68, 122 software trains, 70–71 volatile energy costs, 157 Tsukuba, Japan, 6, 8, 216 turnpike trusts in Great Britain, 162–63 Turpin, Dick, 161 Uber betrayal of cities, 181 Careem purchase by, 177 competition with Lyft, 177–78, 179 congestion pricing, 179, 181 dynamic pricing, 181 fatal AV–pedestrian accident, 231 Greyball program, 178 initial public offering, 97, 177, 181 Jump bike-share platform, 202 limited global footprint, 98 market cap, 97 Micromobility Robotics, 67 number of vehicles, 10 partnerships with public transit, 110–11 relationship with transit, 215 SoftBank and, 177 specialization and variety of rides, 95, 96, 110–11 subscriptions, 244 surge pricing, 17, 87, 181 taxibots, 97 traffic congestion and, 168 Uber Eats, 124 vertically integrated urban-mobility empire, 98 Udelv, 57–58 unmanned aerial vehicles (UAVs), 246 UPS, 116, 120, 127, 130 urban design and driverless cities automation and urban concentration, 186–87 automobiles and urban expansion, 185 complete streets (shared streets), 208–9 core, 187, 188, 188–96, 194–95 desakota, 187, 189, 205–8, 206–7 freight tunnels, 211 fulfillment zone, 187, 188, 196–99, 198–99 infill housing, 204, 253–55 legibility, 229–30, 231 megablocks, 209–10 microsprawl, 187, 189, 200–201, 200–205, 243 parking, 189–93 population growth and home building, 253–54 separation of people and vehicles, 208–12, 210 transects, 187–88, 188–89, 194–95, 198–99, 200–201, 206–7, 208 transit oriented development (TOD), 200, 202, 203–4 urban growth since 1950, 186 Urbanetic, 58 Urban Mobility in a Digital Age, 88 urban ushers, 76–77, 77–79 Vélib system (Paris), 63 VeoRide, 67 Via, 107 Vickrey, William, 165–67, 168, 169, 172 Vinge, Vernor, 233–34 Vision Fund, 176, 178 Vitruvius, 169 von Neumann, John, 234 “Walking City” (Herron), 74 warehouseless distribution systems, 157–58 Waste Management, 142 wayfinding, 229–30 Waymo improvement in rate of disengagement, 42 lidar cost reduction, 35 market cap, 97 market share goal for 2030, 11 remote human safety monitors, 46, 98 self-driving taxi service, 8, 46, 97, 230, 240–41 see also Google Waze, 86–87 Webb, Kevin, 233 Where Do Cars Go at Night?

…

There could be a half dozen or more to choose from, including private cars, private bikes, taxis, buses, trains, trams, shared bikes, shared cars, and simply walking. Layer in all the different pricing options—pay-as-you-go, daily passes, monthly passes, and so on—and deciding how to get to work suddenly requires a master’s degree in economics. Consider my morning commute crossing the Hudson River into Manhattan, for instance. On any given day I can choose between a subway, a bus, or a ferry. Deciding which to take is a complex calculus of cost, comfort, and convenience that changes depending on work and family schedules, the weather, and service disruptions. Thankfully, there are loads of apps to help tame this tangle of consumer choice—it’s one of the busiest bits of reprogramming mobility going on today.

Utopia Is Creepy: And Other Provocations
by Nicholas Carr
Published 5 Sep 2016

Computers are wonderful at following instructions, but they’re lousy at improvisation. They resemble, in the words of computer scientist Hector Levesque, “idiot savants” who are “hopeless outside their area of expertise.” Their talents end at the limits of their programming. Human skill is less circumscribed. Think of Captain Sully Sullenberger landing that Airbus A320 on the Hudson River after its engines were taken out by a flock of geese. Born of deep experience in the real world, such intuition lies beyond calculation. If computers had the ability to be amazed, they’d be amazed by us. While our own flaws loom large in our thoughts, we view computers as infallible.

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(Coupland), 102 Martin, Paul, 335 Marx, Karl, Marxism, xvii, xviii, 26, 83, 174, 308 Marx, Leo, 131 Maslow, Abraham, 117–20 massive open online courses (MOOCs), 133 master-slave metaphor, 307–9 mastery, 64–65 Mayer, Marissa, 268 Mayer-Schönberger, Viktor, 48 McAfee, Andrew, 195 McCain, John, 318 McKeen, William, 13–15 McLuhan, Marshall, 102–6, 183–84, 232, 326 McNealy, Scott, 257 measurement, 182 of experience, 197–98, 211–12 mechanical loom, 77 Mechanical Turk, 37–38 media: as advertorial, 53 big outlets for, 67 changes in, 53–54, 59–60 democratization of, xvi, xviii, 28 hegemony of internet in, 236–37 intellectual and social effects of, 103–6 as invasive, 105–6, 127–30 mainstream, 7–8 pursuit of immediacy in, 79 real world vs., 223 in shaping thought, 232 smartphones’ dominance of, 183–84 tools vs., 226 meditation, 162 Mehta, Mayank, 303 memory: association and cohesion in, 100–101 computer, 147, 231 cultural, 325–28 digital, 327 effect of computers on, 98–101, 234, 240 internet manipulation of, 48 neuroengineering of, 332–34 packaging of, 186 in revivification, 69–70 spatial, 290 time vs., 226 video games and, 94–97 Merholz, Peter, 21 Merleau-Ponty, Maurice, 300 Merton, Robert, 12–13 message-automation service, 167 Meyer, Stephenie, 50 Meyerowitz, Joanne, 338 microfilm, microphotography, 267 Microsoft, 108, 168, 205, 284 military technology, 331–32 Miller, Perry, xvii mindfulness, 162 Minima Moralia (Adorno), 153–54 mirrors, 138–39 Mitchell, Joni, 128 Mollie (video poker player), 218–19 monitoring: corporate control through, 163–65 of thoughts, 214–15 through wearable behavior-modification devices, 168–69 Montaigne, Michel de, 247, 249, 252, 254 Moore, Geoffrey, 209 Morlocks, 114, 186 “Morphological Basis of the Arm-to-Wing Transition, The” (Poore), 329–30 Morrison, Ewan, 288 Morrison, Jim, 126 Morse code, 34 “Most of It, The” (Frost), 145–46 motor skills, video games and, 93–94 “Mowing” (Frost), 296–300, 302, 304–5 MP3 players, 122, 123, 124, 216, 218, 293 multitasking, media, 96–97 Mumford, Lewis, 138–39, 235 Murdoch, Rupert and Wendi, 131 music: bundling of, 41–46 commercial use of, 244–45 copying and sharing technologies for, 121–26, 314 digital revolution in, 293–95 fidelity of, 124 listening vs. interface in, 216–18, 293 in participatory games, 71–72 streamed and curated, 207, 217–18 music piracy, 121–26 Musings on Human Metamorphoses (Leary), 171 Musk, Elon, 172 Musset, Alfred de, xxiii Muzak, 208, 244 MySpace, xvi, 10–11, 30–31 “Names of the Hare, The,” 201 nanotechnology, 69 Napster, 122, 123 narcissism, 138–39 Twitter and, 34–36 narrative emotions, 250 natural-language processing, 215 Negroponte, Nicholas, xx neobehavioralism, 212–13 Netflix, 92 neural networks, 136–37 neuroengineering, 332–33 New Critics, 249 News Feed, 320 news media, 318–20 newspapers: evolution of, 79, 237 online archives of, 47–48, 190–92 online vs. printed, 289 Newton, Isaac, 66 New York Public Library, 269 New York Times, 8, 71, 83, 133, 152–53, 195, 237, 283, 314, 342 erroneous information revived by, 47–48 on Twitter, 35 Nielsen Company, 80–81 Nietzsche, Friedrich, 126, 234–35, 237 Nightingale, Paul, 335 Nixon, Richard, 317 noise pollution, 243–46 Nook, 257 North of Boston (Frost), 297 nostalgia, 202, 204, 312 in music, 292–95 Now You See It (Davidson), 94 Oates, Warren, 203 Oatley, Keith, 248–50 Obama, Barack, 314 obsession, 218–19 OCLC, 276 “off grid,” 52 Olds, James, 235 O’Neill, Gerard, 171 One Infinite Loop, 76 Ong, Walter, 129 online aggregation, 192 On Photography (Sontag), xx open networks, profiteering from, 83–85 open-source projects, 5–7, 26 Oracle, 17 orchises, 305 O’Reilly, Tim, 3–5, 7 organ donation and transplantation, 115 ornithopters, 239 orphan books, 276, 277 Overture, 279–80 Owad, Tom, 256 Oxford Junior Dictionary, 201–2 Oxford University, library of, 269 Page, Larry, 23, 160, 172, 239, 268–69, 270, 279, 281–85 personal style of, 16–17, 281–82, 285 paint-by-number kits, 71–72 Paley, William, 43 Palfrey, John, 272–74, 277 Palmisano, Sam, 26 “pancake people,” 242 paper, invention and uses of, 286–89 Paper: An Elegy (Sansom), 287 Papert, Seymour, 134 Paradise within the Reach of All Men, The (Etzler), xvi–xvii paradox of time, 203–4 parenting: automation of, 181 of virtual child, 73–75 Parker, Sarah Jessica, 131 participation: “cognitive surplus” in, 59 as content and performance, 184 inclusionists vs. deletionists in, 18–20 internet, 28–29 isolation and, 35–36, 184 limits and flaws of, 5–7, 62 Paul, Rand, 314 Pendragon, Caliandras (avatar), 25 Pentland, Alex, 212–13 perception, spiritual awakening of, 300–301 personalization, 11 of ads, 168, 225, 264 isolation and, 29 loss of autonomy in, 264–66 manipulation through, 258–59 in message automation, 167 in searches, 145–46, 264–66 of streamed music, 207–9, 245 tailoring in, 92, 224 as threat to privacy, 255 Phenomenology of Perception (Merleau-Ponty), 300 Philosophical Investigations (Wittgenstein), 215 phonograph, phonograph records, 41–46, 133, 287 photography, technological advancement in, 311–12 Pichai, Sundar, 181 Pilgrims, 172 Pinterest, 119, 186 playlists, 314 PlayStation, 260 “poetic faith,” 251 poetry, 296–313 polarization, 7 politics, transformed by technology, 314–20 Politics (Aristotle), 307–8 Poore, Samuel O., 329–30 pop culture, fact-mongering in, 58–62 pop music, 44–45, 63–64, 224 copying technologies for, 121–26 dead idols of, 126 industrialization of, 208–9 as retrospective and revivalist, 292–95 positivism, 211 Potter, Dean, 341–42 power looms, 178 Presley, Elvis, 11, 126 Prim Revolution, 26 Principles of Psychology (James), 203 Principles of Scientific Management, The (Taylor), 238 printing press: consequences of, 102–3, 234, 240–41, 271 development of, 53, 286–87 privacy: devaluation of, 258 from electronic surveillance, 52 family cohesion vs., 229 free flow of information vs. right to, 190–94 internet threat to, 184, 255–59, 265, 285 safeguarding of, 258–59, 283 vanity vs., 107 proactive cognitive control, 96 Prochnik, George, 243–46 “Productivity Future Vision (2011),” 108–9 Project Gutenberg, 278 prosperity, technologies of, 118, 119–20 prosumerism, 64 protest movements, 61 Proust and the Squid (Wolf), 234 proximal clues, 303 public-domain books, 277–78 “public library,” debate over use of term, 272–74 punch-card tabulator, 188 punk music, 63–64 Quantified Self Global Conference, 163 Quantified Self (QS) movement, 163–65 Quarter-of-a-Second Rule, 205 racecars, 195, 196 radio: in education, 134 evolution of, 77, 79, 159, 288 as music medium, 45, 121–22, 207 political use of, 315–16, 317, 319 Radosh, Daniel, 71 Rapp, Jen, 341–42 reactive cognitive control, 96 Readers’ Guide to Periodical Literature, 91 reading: brain function in, 247–54, 289–90 and invention of paper, 286–87 monitoring of, 257 video gaming vs., 261–62 see also books reading skills, changes in, 232–34, 240–41 Read Write Web (blog), 30 Reagan, Ronald, 315 real world: digital media intrusion in, 127–30 perceived as boring and ugly, 157–58 as source of knowledge, 313 virtual world vs., xx–xxi, 36, 62, 127–30, 303–4 reconstructive surgery, 239 record albums: copying of, 121–22 jackets for, 122, 224 technology of, 41–46 Redding, Otis, 126 Red Light Center, 39 Reichelt, Franz, 341 Reid, Rob, 122–25 relativists, 20 religion: internet perceived as, 3–4, 238 for McLuhan, 105 technology viewed as, xvi–xvii Republic of Letters, 271 reputations, tarnishing of, 47–48, 190–94 Resident Evil, 260–61 resource sharing, 148–49 resurrection, 69–70, 126 retinal implants, 332 Retromania (Reynolds), 217, 292–95 Reuters, Adam, 26 Reuters’ SL bureau, 26 revivification machine, 69–70 Reynolds, Simon, 217–18, 292–95 Rice, Isaac, 244 Rice, Julia Barnett, 243–44 Richards, Keith, 42 “right to be forgotten” lawsuit, 190–94 Ritalin, 304 robots: control of, 303 creepy quality of, 108 human beings compared to, 242 human beings replaced by, 112, 174, 176, 195, 197, 306–7, 310 limitations of, 323 predictions about, xvii, 177, 331 replaced by humans, 323 threat from, 226, 309 Rogers, Roo, 83–84 Rolling Stones, 42–43 Roosevelt, Franklin, 315 Rosen, Nick, 52 Rubio, Marco, 314 Rumsey, Abby Smith, 325–27 Ryan, Amy, 273 Sandel, Michael J., 340 Sanders, Bernie, 314, 316 Sansom, Ian, 287 Savage, Jon, 63 scatology, 147 Schachter, Joshua, 195 Schivelbusch, Wolfgang, 229 Schmidt, Eric, 13, 16, 238, 239, 257, 284 Schneier, Bruce, 258–59 Schüll, Natasha Dow, 218 science fiction, 106, 115, 116, 150, 309, 335 scientific management, 164–65, 237–38 Scrapbook in American Life, The, 185 scrapbooks, social media compared to, 185–86 “Scrapbooks as Cultural Texts” (Katriel and Farrell), 186 scythes, 302, 304–6 search-engine-optimization (SEO), 47–48 search engines: allusions sought through, 86 blogging, 66–67 in centralization of internet, 66–69 changing use of, 284 customizing by, 264–66 erroneous or outdated stories revived by, 47–48, 190–94 in filtering, 91 placement of results by, 47–48, 68 searching vs., 144–46 targeting information through, 13–14 writing tailored to, 89 see also Google searching, ontological connotations of, 144–46 Seasteading Institute, 172 Second Life, 25–27 second nature, 179 self, technologies of the, 118, 119–20 self-actualization, 120, 340 monitoring and quantification of, 163–65 selfies, 224 self-knowledge, 297–99 self-reconstruction, 339 self-tracking, 163–65 Selinger, Evan, 153 serendipity, internet as engine of, 12–15 SETI@Home, 149 sexbots, 55 Sex Pistols, 63 sex-reassignment procedures, 337–38 sexuality, 10–11 virtual, 39 Shakur, Tupac, 126 sharecropping, as metaphor for social media, 30–31 Shelley, Percy Bysshe, 88 Shirky, Clay, 59–61, 90, 241 Shop Class as Soulcraft (Crawford), 265 Shuster, Brian, 39 sickles, 302 silence, 246 Silicon Valley: American culture transformed by, xv–xxii, 148, 155–59, 171–73, 181, 241, 257, 309 commercial interests of, 162, 172, 214–15 informality eschewed by, 197–98, 215 wealthy lifestyle of, 16–17, 195 Simonite, Tom, 136–37 simulation, see virtual world Singer, Peter, 267 Singularity, Singularitarians, 69, 147 sitcoms, 59 situational overload, 90–92 skimming, 233 “Slaves to the Smartphone,” 308–9 Slee, Tom, 61, 84 SLExchange, 26 slot machines, 218–19 smart bra, 168–69 smartphones, xix, 82, 136, 145, 150, 158, 168, 170, 183–84, 219, 274, 283, 287, 308–9, 315 Smith, Adam, 175, 177 Smith, William, 204 Snapchat, 166, 205, 225, 316 social activism, 61–62 social media, 224 biases reinforced by, 319–20 as deceptively reflective, 138–39 documenting one’s children on, 74–75 economic value of content on, 20–21, 53–54, 132 emotionalism of, 316–17 evolution of, xvi language altered by, 215 loom as metaphor for, 178 maintaining one’s microcelebrity on, 166–67 paradox of, 35–36, 159 personal information collected and monitored through, 257 politics transformed by, 314–20 scrapbooks compared to, 185–86 self-validation through, 36, 73 traditional media slow to adapt to, 316–19 as ubiquitous, 205 see also specific sites social organization, technologies of, 118, 119 Social Physics (Pentland), 213 Society for the Suppression of Unnecessary Noise, 243–44 sociology, technology and, 210–13 Socrates, 240 software: autonomous, 187–89 smart, 112–13 solitude, media intrusion on, 127–30, 253 Songza, 207 Sontag, Susan, xx SoundCloud, 217 sound-management devices, 245 soundscapes, 244–45 space travel, 115, 172 spam, 92 Sparrow, Betsy, 98 Special Operations Command, U.S., 332 speech recognition, 137 spermatic, as term applied to reading, 247, 248, 250, 254 Spinoza, Baruch, 300–301 Spotify, 293, 314 “Sprite Sips” (app), 54 Squarciafico, Hieronimo, 240–41 Srinivasan, Balaji, 172 Stanford Encyclopedia of Philosophy, 68 Starr, Karla, 217–18 Star Trek, 26, 32, 313 Stengel, Rick, 28 Stephenson, Neal, 116 Sterling, Bruce, 113 Stevens, Wallace, 158 Street View, 137, 283 Stroop test, 98–99 Strummer, Joe, 63–64 Studies in Classic American Literature (Lawrence), xxiii Such Stuff as Dreams (Oatley), 248–49 suicide rate, 304 Sullenberger, Sully, 322 Sullivan, Andrew, xvi Sun Microsystems, 257 “surf cams,” 56–57 surfing, internet, 14–15 surveillance, 52, 163–65, 188–89 surveillance-personalization loop, 157 survival, technologies of, 118, 119 Swing, Edward, 95 Talking Heads, 136 talk radio, 319 Tan, Chade-Meng, 162 Tapscott, Don, 84 tattoos, 336–37, 340 Taylor, Frederick Winslow, 164, 237–38 Taylorism, 164, 238 Tebbel, John, 275 Technics and Civilization (Mumford), 138, 235 technology: agricultural, 305–6 American culture transformed by, xv–xxii, 148, 155–59, 174–77, 214–15, 229–30, 296–313, 329–42 apparatus vs. artifact in, 216–19 brain function affected by, 231–42 duality of, 240–41 election campaigns transformed by, 314–20 ethical hazards of, 304–11 evanescence and obsolescence of, 327 human aspiration and, 329–42 human beings eclipsed by, 108–9 language of, 201–2, 214–15 limits of, 341–42 master-slave metaphor for, 307–9 military, 331–32 need for critical thinking about, 311–13 opt-in society run by, 172–73 progress in, 77–78, 188–89, 229–30 risks of, 341–42 sociology and, 210–13 time perception affected by, 203–6 as tool of knowledge and perception, 299–304 as transcendent, 179–80 Technorati, 66 telegrams, 79 telegraph, Twitter compared to, 34 telephones, 103–4, 159, 288 television: age of, 60–62, 79, 93, 233 and attention disorders, 95 in education, 134 Facebook ads on, 155–56 introduction of, 103–4, 159, 288 news coverage on, 318 paying for, 224 political use of, 315–16, 317 technological adaptation of, 237 viewing habits for, 80–81 Teller, Astro, 195 textbooks, 290 texting, 34, 73, 75, 154, 186, 196, 205, 233 Thackeray, William, 318 “theory of mind,” 251–52 Thiel, Peter, 116–17, 172, 310 “Things That Connect Us, The” (ad campaign), 155–58 30 Days of Night (film), 50 Thompson, Clive, 232 thought-sharing, 214–15 “Three Princes of Serendip, The,” 12 Thurston, Baratunde, 153–54 time: memory vs., 226 perception of, 203–6 Time, covers of, 28 Time Machine, The (Wells), 114 tools: blurred line between users and, 333 ethical choice and, 305 gaining knowledge and perception through, 299–304 hand vs. computer, 306 Home and Away blurred by, 159 human agency removed from, 77 innovation in, 118 media vs., 226 slave metaphor for, 307–8 symbiosis with, 101 Tosh, Peter, 126 Toyota Motor Company, 323 Toyota Prius, 16–17 train disasters, 323–24 transhumanism, 330–40 critics of, 339–40 transparency, downside of, 56–57 transsexuals, 337–38 Travels and Adventures of Serendipity, The (Merton and Barber), 12–13 Trends in Biochemistry (Nightingale and Martin), 335 TripAdvisor, 31 trolls, 315 Trump, Donald, 314–18 “Tuft of Flowers, A” (Frost), 305 tugboats, noise restrictions on, 243–44 Tumblr, 166, 185, 186 Turing, Alan, 236 Turing Test, 55, 137 Twain, Mark, 243 tweets, tweeting, 75, 131, 315, 319 language of, 34–36 theses in form of, 223–26 “tweetstorm,” xvii 20/20, 16 Twilight Saga, The (Meyer), 50 Twitter, 34–36, 64, 91, 119, 166, 186, 197, 205, 223, 224, 257, 284 political use of, 315, 317–20 2001: A Space Odyssey (film), 231, 242 Two-Lane Blacktop (film), 203 “Two Tramps in Mud Time” (Frost), 247–48 typewriters, writing skills and, 234–35, 237 Uber, 148 Ubisoft, 261 Understanding Media (McLuhan), 102–3, 106 underwearables, 168–69 unemployment: job displacement in, 164–65, 174, 310 in traditional media, 8 universal online library, 267–78 legal, commercial, and political obstacles to, 268–71, 274–78 universe, as memory, 326 Urban Dictionary, 145 utopia, predictions of, xvii–xviii, xx, 4, 108–9, 172–73 Uzanne, Octave, 286–87, 290 Vaidhyanathan, Siva, 277 vampires, internet giants compared to, 50–51 Vampires (game), 50 Vanguardia, La, 190–91 Van Kekerix, Marvin, 134 vice, virtual, 39–40 video games, 223, 245, 303 as addictive, 260–61 cognitive effects of, 93–97 crafting of, 261–62 violent, 260–62 videos, viewing of, 80–81 virtual child, tips for raising a, 73–75 virtual world, xviii commercial aspects of, 26–27 conflict enacted in, 25–27 language of, 201–2 “playlaborers” of, 113–14 psychological and physical health affected by, 304 real world vs., xx–xxi, 36, 62, 127–30 as restrictive, 303–4 vice in, 39–40 von Furstenberg, Diane, 131 Wales, Jimmy, 192 Wallerstein, Edward, 43–44 Wall Street, automation of, 187–88 Wall Street Journal, 8, 16, 86, 122, 163, 333 Walpole, Horace, 12 Walters, Barbara, 16 Ward, Adrian, 200 Warhol, Andy, 72 Warren, Earl, 255, 257 “Waste Land, The” (Eliot), 86, 87 Watson (IBM computer), 147 Wealth of Networks, The (Benkler), xviii “We Are the Web” (Kelly), xxi, 4, 8–9 Web 1.0, 3, 5, 9 Web 2.0, xvi, xvii, xxi, 33, 58 amorality of, 3–9, 10 culturally transformative power of, 28–29 Twitter and, 34–35 “web log,” 21 Wegner, Daniel, 98, 200 Weinberger, David, 41–45, 277 Weizenbaum, Joseph, 236 Wells, H.

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From The Atlantic 2008 SCREAMING FOR QUIET IN 1906, JULIA BARNETT RICE, a wealthy New York physician and philanthropist, founded the Society for the Suppression of Unnecessary Noise. Rice, who lived with her husband and six children in a Manhattan mansion overlooking the Hudson River, had become enraged at the way tugboats would blow their horns incessantly while steaming up and down the busy waterway. During a typical night, the tugs would emit two or three thousand toots, most of which served merely as sonic greetings between friendly captains. Armed with research documenting the health problems caused by the sleep-shattering racket, Rice launched a one-woman lobbying campaign that took her to police stations, health departments, the offices of shipping regulators, and ultimately the halls of Congress.

QI: The Second Book of General Ignorance
by Lloyd, John and Mitchinson, John
Published 7 Oct 2010

Despite such unnerving obstacles, there have been at least half a dozen successful emergency landings by airliners on water, including one off the coast of Sicily in 2005. The most recent and spectacular example occurred in January 2009 when an Airbus A380, US Airways Flight 1549, ditched in the Hudson River in New York. Shortly after take off, the plane hit a flock of geese and Captain Chesley ‘Sully’ Sullenberger III had to make a forced landing on the water. He did this perfectly, saving the lives of all 155 people on board. Airline statisticians like to say that you are ten times more likely to be hit by a comet than to die in a plane crash. This is because, once every million years or so, an extraterrestrial body collides with Earth.

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Charles 1 Kittenger, Joseph 1 Kleitman, Dr Nathaniel 1, 2 Knox, Father Ronald 1, 2 knuckle cracking 1 Kodak 1 König, Peter 1 Krakatoa, eruption of 1 Kraken Mare lake (Titan) 1 Kwok, Dr Robert Ho Man 1 Lack, David 1 lactose tolerance 1 Ladbrokes 1 lake, largest 1 Lanfray, Jean 1 Lang, Gerhard 1 language official 1 spoken in ancient Rome 1 Latin 1, 2 as official language in Vatican 1 latitudinal libration 1 laurel wreath 1 lavatories 1 on aeroplanes 1 and hygiene 1 injuries while on 1 lead, hardness of 1 Leaning Tower of Pisa 1 Lebensprüfer (’Life-prover’) 1 Lebistina beetle 1 Leeuwenhoek, Anton van 1 Lent 1 Leo XIII, Pope 1 lepers, carrying bells 1, 2 leprosy 1 letterboxes 1 lexical-gustatory synaesthesia 1 libration 1, 2 lichens 1 Lilienthal, Otto 1 lingua franca 1, 2 Linnaean Society 1 liver 1 Llanfair PG 1 London 1 London Fire Brigade 1 longitudinal libration 1 ‘loo’ 1 see also lavatories Lorenzini, Stefano 1 lorikeet 1 lost, going round in circles when 1 lottery 1 Louis XIII, King 1 Lovelace, Ada 1 Lusitania, sinking of (1915) 1 Luxembourg 1 lying 1 give-aways 1 McCay, Professor Clive 1 McClelland Royal Commission 1 Macedonia/Macedonians 1, 2 Macfarlane, Charles 1 MacMahan, Dr Jamie 1 Mafia 1 Magna Carta (1215) 1, 2 magnetoception 1 Mahavira 1 mammals and heartbeats 1 most aggressive 1 smallest 1 mangoes, speeding up ripening process 1 Mansfield, Lord 1 Manx Shearwater 1, 2 Mao Zedong 1, 2 Maralinga nuclear tests (Australia) 1 Mariani, Angelo 1 Marie Byrd Land 1, 2 Marmite 1 marngrook (‘game ball’) 1 Marryat, Captain Frederick 1 Mars 1, 2, 3, 4 marula tree 1 Marx, Karl 1 Mary I, Queen 1 Mary, Queen of Scots 1 Mather, Graham 1 Matilda, Queen 1, 2 mating mayflies 1 octopus 1, 2 snakes 1 Max Planck Institute for Biological Cybernetics (Tübingen) 1 mayflies 1 Mediterranean 1 size 1 tides 1 Melton Mowbray 1 Melville, Herman Moby Dick 1 Omoo 1 menstruation, vicarious 1 Merian, Maria Sibylla 1 Mertz, Xavier 1 mesophere 1 Messalina, Empress 1 Messinian Salinity Crisis 1 meteorites 1 Metronidazole 1 Meyers-Briggs Type Indicator 1 mice, species of British 1 Michelin man 1 Michelin stars 1 Michelin Tyre Company 1 Mickey Mouse 1 micro-frog 1 microwave ovens 1 microwaves 1 military success, and France 1 Milk Marketing Board 1 Milton, John 1, 2 Milton Keynes 1, 2 minerals, creation of 1 mink 1 mints 1 mirages 1 mockingbirds 1 Mohs, Friedrich 1 Mohs Hardness scale 1 Molotov (Vyacheslav Mikhailovich Skriabin) 1 Molotov cocktails 1 Molotov-Ribbentrop pact (1939) 1 Mongolians 1, 2 monkey-pump 1 monosodium glutamate see MSG Montgomerie, Lieutenant Thomas 1 Moon 1 view from Earth 1 More, Sir Thomas 1 Morris, Reverend Marcus 1 Morris, Sir Parker 1 Morris, Steve 1 Morton, Charles 1 mosses 1 Motion Picture Association of America (MPAA) 1 Moulin Rouge 1 mountains estimating height of 1 ‘in a high place’ notices 1 world’s second highest peak 1 Mpemba, Erasto 1 MSG (monosodium glutamate) 1, 2, 3 Munsters, The 1 Murray, Dr Stewart 1 mushrooms 1 Musk ox 1 Muslims, in India 1 Mussolini, Benito 1 mycology 1 naming, of new species 1 Naples 1 Napoleon 1, 2 height of 1 ‘Napoleon complex’ 1 narcotics 1 Natural History Museum 1 Nautilus pompilius 1 Nazis 1 Neanderthals 1, 2 Nelson, Horatio, height of 1, 2 Netherlands 1 see also Dutch New Labour laws 1 new towns 1 New Zealand 1 Newcastle Brown Ale 1 Newton, Humphrey 1 Newton, Sir Isaac 1, 2 Newton, Wayne 1 Nichols I, Tsar 1 nightmares, and eating cheese 1 Nile, River 1 nitrous oxide (laughing gas) 1 Nixon, Richard 1 no-man’s-land 1 noctilucent clouds 1 Normans 1, 2, 3 north, finding of in a forest 1 North Korea 1 North Sea 1 North Star (Polaris) 1 nosebleeds causes 1, 2 and death of Attila the Hun 1 treatment of 1 ‘not enough room to swing a cat’ phrase 1 Nubian people 1 Obama, Barack 1 oceans, temperature of 1 octopus 1, 2 Odo, Bishop of Bayeux 1 oil 1 Olympic Games 1 perfect 1 score 2 sports no longer included 1 opiods 1 opium 1 oranges, colour of 1 Orbison, Ray 1 organ transplants 1 Oswald the Lucky Rabbit 1 Ouroboros 1 ovum 1 Owen, Jennifer 1, 2 Oxford English Dictionary 1 oxygen 1 oxytocin 1 ozone layer 1 Pacioli, Luca 1 Paget, Stephen 1 pandas 1 pandemics 1 panspermia 1 papal infallibility 1 paper money 1 Papua New Guinea 1 parachute, opening of 1 paraesthesia 1 Paris, Michelin stars 1 Parker Morris standards 1 Parliament Acts (1911/1949) 1 Parthenon 1 Pascal, Blaise 1 Pasteur, Louis 1 peanuts, avoiding of in bars 1 Peary, Admiral Robert E. 1, 2 Peary Land 1 Pemberton, John Stith 1 Pen-tailed tree shrew 1 penguins 1 penicillin 1 penises Argentinian Lake Duck 1 snake’s two 1 Penny Black stamp 1 Penny Red stamp 1 Peterlee 1 Petition of Right Act (1628) 1 Pharnaces II, King 1, 2 phi 1 Phidias 1 Philip II, King of Spain 1 Phoenicians 1 phosphoric acid 1 photic sneeze reflex 1 pilchards 1 Pinker, Stephen 1 pins and needles 1 Pins and Needles (musical) 1 pirates 1, 2 Pius XII, Pope 1 place names, longest 1 plague 1, 2, 3 Plane Crazy 1 Plantagenet, House of 1 Plato, Timaeus 1 Pliny the Elder 1, 2 Plough (Big Dipper) 1 ploughman’s lunch 1 Ploughman’s Lunch, The (film) 1 Pocohontas 1 poisoning, by Vitamin A 1 ‘polar bear effect’ 1 Polyphemus 1 Pompey 1, 2 Pope 1 Poppaea (wife of Nero) 1 Post Office 1 postcards 1 postcodes 1 Potter, Beatrix 1 Powhatans 1, 2 praetors 1 preformationism 1 premature burial 1 prison uniforms, striped 1 progesterone 1 Progressive Muscle Relaxation 1 prostitutes 1 Protected Designation of Origin (PDO) status 1, 2 Protected Geographical Indication (PGI) status 1 Ptolemy I 1 Ptolemy XII 1 Ptolemy XIII 1 public speaking, fear of 1 puffins 1, 2 Puffinus puffinus 1 Pythian Games 1 Quinion, Michael 1 radar 1 radiation 1 radio plays, world coming to an end broadcasts 1 radioactivity 1 radium 1 railways, Italian 1 rainfall 1 Ransome, Arthur 1 Rapid Eye Movement (REM) sleep 1 rats 1 magnetic 1 rattlesnakes, on television 1 Rawlinson, Thomas 1 Raytheon 1 razor blade, as compass 1 Reagan, Nancy 1 recessions, and suicide 1 Red Sea 1 Rehn, Ludwig 1 Reith, Lord 1 Renaissance Bug see Halobacteria Rentokil 1 Representation of the People Act (1969) 1 reproduction 1 and budding 1 see also mating Rescue Annie 1 restaurants, and Michelin stars 1 resuscitation 1 Richard III, King 1, 2 Roberts, Andy 1 Roe, Donald 1 Rolfe, John 1 Roma 1 Romani 1 Romans/Roman Empire 1, 2 army/legions 1 conquering of Rome by Goths (410 AD) 1 eating of dormice 1 fighting of Huns 1 and glass 1 and hair 1 invasion of Britain 1 language spoken in Rome 1 sacking of Rome by Vandals (455) 1 treatment for insomnia 1 Roosevelt, President Theodore 1, 2 rope-climbing Olympians 1 Rothschild, Lord 1 rubber balls 1 Russian Revolution (1917) 1 rust 1 Rutzen, Michael 1 St Andrew’s Day 1 salt 1 Samaritans 1 sardines 1 satellite navigation 1 Saturn 1, 2, 3 sauna 1 Scarfe, Gerald 1 Schatz, Albert 1 Schimper, Anna 1 Schuetz, George and Edward 1 Scotland, wearing of kilts 1 Scott, Sir Walter 1, 2, 3 Scythians 1 seawater, freezing of 1 Second World War 1, 2, 3 Sellmer, Richard 1 semen 1 sensory substitution 1 Sequin, Albert 1 serfdom 1 Settlement Act (1701) 1 sewage, polluting of beaches 1 sex sneezing during 1 see also mating Shakespeare, William 1, 2 Henry VI Part (1) 1 sharks and tonic immobility 1 tracking by 1 Shaw, George Bernard 1, 2 shearwater 1 sheep-counting 1, 2 Sheffield 1 Sheffield FC 1 Shelley, Mary, Frankenstein 1 Shima Marineland Aquarium (Japan) 1 shivering 1 Sikhs, in India 1 silkworms 1 Sino-Japanese War (1937–45) 1 skin 1 breathing through 1 effect of drinking water on 1 shedding of dead 1 Skipsea (Yorkshire), planned atomic bomb explosion 1 slavery, in England 1 sleep 1 and dreaming 1 and eating cheese 1 REM (rapid eye movement) 1 slim appearance and black clothes 1 and stripes 1 smell 1 smiling 1 Smith, John 1 Smyrna 1 Smyth, Admiral W.H. 1 snakes beating heart of cobra 1 rattlesnakes on television 1 swallow big objects 1 tail 1 sneezing during sex 1 in response to bright light 1 snow 1 sound in space 1 speed of 1 South African pilchards 1 South Pacific 1 Southern Pole star 1 sovereigns 1 Soviet Union, and Second World War 1 space, sound in 1 Spanish Armada 1 Spanish Civil War 1 Spanish national anthem 1 species discovering new 1 naming of 1 Specific Anthropomorphic Mannequin (SAM) 1 spectacles 1 speed cameras 1 destruction of 1 Spelling Reform Bill 1 Spencer, Percy 1 sperm human 1 octopus 1 Spiderman 1 spiders 1 sportsmen, and huddles 1 Spratly Islands 1 staircases, helical 1 Stalin, Joseph 1 stamps 1 stars, finding north through observing 1 Steamboat Willie 1, 2 steel balls 1 Stevenson, Robert Louis, Treasure Island 1 ‘stiff upper lip’ 1 stiffness, measuring 1 Stilton cheese 1 Stilton (town) 1 stings, treatment of jellyfish 1 Stone Age 1 Stowe, Harriet Beecher 1 Straits of Gibraltar 1, 2 stratosphere 1 streptomycin 1, 2 stripes and appearance 1 substances hardest known 1 strangest 1 Sudan 1, 2 sugary drinks/food 1 suicide (s) and handwriting 1 and recessions 1 and Wall Street Crash (1929) 1 Sullenberger III, Captain Chesley ‘Sully’ 1 Sun rising of 1 setting of 1, 2 water vapour traces 1 supercooling 1 Superman 1 swallowing 1 sweat/sweating 1, 2 swordtail fish 1 Table Alphabeticall 1 tapestries 1 tartan 1 taste fifth (umami) 1, 2 and tongue 1 TATT (‘tired all the time’) syndrome 1 Tattersall, Ian 1 tautonyms 1 tea 1 tectonic plates 1 teeth, effect of fizzy drinks on 1 Telford 1 Telford, Thomas 1 temperature coldest recorded in England 1 country with widest range of 1 in oceans 1 on Titan 1 of water 1 Temple, Frederick 1 testosterone 1, 2, 3 Thames helmet 1 Thatcher, Margaret 1 Thing, The (film) 1 Thirty Years War 1 Thompson, Dr Peter 1 Thomsen, Christian Jürgensen 1 Three-Age System 1 3-D 1, 2 Thrombosis Institute 1 thujone 1 Tibet 1 tidal locking 1 tides, Mediterranean 1 Titan 1 titan (bank note) 1 Titanic 1 toe cleavage 1 toilet 1 see also lavatories Tokyo, Michelin stars 1 tongue swallowing of 1 and taste 1 tongue map 1 Tours, Battle of (732) 1 Towton, Battle of (1461) 1 trains 1 transient paraesthesia 1 Tre Skillin Yellow stamp 1 treasure maps 1 trees 1 Trehane, Sir Richard 1 Trollope, Anthony 1 troposphere 1, 2 Troy weight 1 tuberculosis 1, 2 Tuf Tuf Club 1 Tunisia 1 Turpin, Dick 1 Turritopsis nutricula 1 Twain, Mark 1, 2, 3 umami 1, 2 Unger, Donald L. 1 United States burning of American flags 1 constitution 1 electoral system 1 and English language 1 and First World War 1 Flag Code 1, 2 orange producer 1 Pins and Needles Day 1 plane crashes 1 Presidents of 1 and sinking of Lusitania 1 and ‘stiff upper lip’ term 1 toilet hygiene 1 use of gavel 1 weight of average citizen 1 Uranus 1 urine frozen 1 and treatment of jellyfish stings 1 US Embassy (Grosvenor Square) 1 Uys, Jamie 1 vampire bats 1 Varah, Chad 1 Vasari, Georgio 1, 2 Vatican 1, 2, 3 lowest age of consent 1 Venetian glass 1 Venezuela 1 ‘veni, vidi, vici’ phrase 1 Venus 1 Vermouth 1 Versailles, Treaty of 1 vertebrae 1 vertigo 1 Vertigo (film) 1 Viking helmet 1 Vin Mariani 1 vinegar, and jellyfish stings 1 Virgil, Aeneid 1 viruses 1 vision 1, 2 Vitamin A poisoning 1 Vitruvius 1 voles 1 von Baer, Karl Ernst 1 von Helmholtz, Hermann 1 von Hipper, Admiral Franz von 1 von Rosenhof, Johann Rösel 1 Vulgar Latin 1 Waksman, Selman 1 Wales 1 Walk, R.

…

Though studying medicine and divinity to please his father, he dismissed lectures as ‘cold, breakfastless hours, listening to discourses on the properties of rhubarb’. But he was also an enthusiastic amateur biologist and fossil-hunter and was keen to see the tropics, so he signed on as a ‘gentleman naturalist’ for HMS Beagle’s second survey expedition (1831–6). He almost didn’t get the job: the captain was keen on physiognomy and thought that Darwin’s nose indicated laziness. Charles later noted that ‘I think he was afterwards well satisfied that my nose had spoken falsely’. The story goes that, during the voyage, Darwin noticed that finches on different islands in the Galapagos had distinctive beaks, which led him to guess that each type had adapted for a specific habitat and evolved from a common ancestor.

Decisive: How to Make Better Choices in Life and Work
by Chip Heath and Dan Heath
Published 26 Mar 2013

Suppose, as a far-fetched example, that a commercial airplane pilot plowed through a flock of Canadian geese, disabling his two engines and necessitating an emergency landing on a river. That impact would put huge, unexpected strain on the airplane wings. (This “far-fetched” example really happened, of course. In 2009, pilot Chesley “Sully” Sullenberger landed the plane safely in the Hudson River. Amazingly, no lives were lost, thanks to his skill and, also, the engineers’ safety factors!) In a more everyday example, engineers might compute, in designing a ladder, that it needed to be able to support 400 pounds, but then they’d multiply that number by a safety factor of, say, six.

…

This approach became a specialty of Captain D. Michael Abrashoff when he took over command of the USS Benfold, a guided-missile destroyer commissioned in 1996 for duty in the United States’ Pacific Fleet. As recounted in his book It’s Your Ship, one of Captain Abrashoff’s first moves was to interview every one of the 310 crew members on the ship. He learned their personal histories and their motivations for joining the navy, and he sought their opinions about the Benfold: What do you like most? Least? What would you change if you could? Drawing from those conversations, Captain Abrashoff sorted all the jobs performed on the Benfold into two lists: List A contained the mission-critical tasks, and List B contained the things that were important but not core, “the dreary, repetitive stuff, such as chipping and painting.”

…

Drawing from those conversations, Captain Abrashoff sorted all the jobs performed on the Benfold into two lists: List A contained the mission-critical tasks, and List B contained the things that were important but not core, “the dreary, repetitive stuff, such as chipping and painting.” After compiling the two lists, Captain Abrashoff declared war on List B. Perhaps the most dreaded task on List B was painting the ship, so Captain Abrashoff and his sailors hunted for ways to minimize the need for repainting. One sailor suggested replacing the ship’s ferrous-metal bolts—which streaked rust down the side of the ship, ruining the paint job—with stainless-steel bolts and nuts. Captain Abrashoff loved the idea, but his crew quickly hit a roadblock: The navy supply system didn’t stock stainless-steel bolts.

WTF?: What's the Future and Why It's Up to Us
by Tim O'Reilly
Published 9 Oct 2017

The app had already begun showing “trending topics” (using algorithms to detect common events even if they do not have the same hashtag), but hashtags added fuel to the fire. When photos were added to Twitter (again by an outside developer providing features that the platform developer itself hadn’t imagined), Twitter’s power to reveal the real-time pulse of the world increased even further. On January 15, 2009, four minutes after Captain “Sully” Sullenberger ditched US Airways Flight 1549 in the Hudson after multiple bird strikes had disabled the engines, Jim Hanrahan posted the first tweet. Janis Krums snapped an iPhone photo of passengers standing on the wing of the downed plane a few minutes later and shared it on Twitter via a third-party app called TwitPic, and it went worldwide long before the story appeared on the television news.

…

See also individual platforms “Social Responsibility of Business Is to Increase Its Profits” (Friedman), 240 software, 15, 35 continuous improvement process, 30, 119–21, 122 and DevOps, 121–23 generative design, 327–28 MapReduce, 325 as organizational structure, 113–19 Perl, 10–11, 15, 16–17, 120–21 programmers as managers of, 153–54 RegTech, 175 for scheduling employees or ICs, 193 See also Microsoft; open source software “Software Above the Level of a Single Device” (O’Reilly), 31 solar energy, 326–27 Solomon, Jake, 141–43 Sony, 351 Soros, George, 210, 236 South by Southwest conference, 148–49 Southwest Airlines, 48–49 Spafford, George, 122 Spence, Michael, 67 sports and rewriting rules, 266–67 Spotify, 116 “Spy Who Fired Me, The” (Kaplan), 193 SRE (Site Reliability Engineer), 123, 146–47 Stallman, Richard, 6, 71, 72 stand-up meetings, 118 Stanton, Brandon, 370–71, 372 startups, 41, 186, 247, 275, 279, 282–85, 316 Steinberg, Tom, 146 Stern, Andy, 305 Sternberg, Seth, 332–33 “Stevey’s Platform Rent” (Yegge), 111–13 Stiglitz, Joseph, 255, 261, 266, 272–73 stock buybacks, 242–44, 245, 256 stock options, 247, 279–80 Stoppard, Tom, xii Stout, Lynn, 292 Strickler, Yancey, 292 Strine, Leo, 292 structural literacy, 343–44 success as a by-product, 353. See also achievement Sullenberger, “Sully,” 43 Sullivan, Danny, 157–58, 214 Summers, Larry, 271 Summit on Technology and Opportunity, 269–70 Sun Microsystems, 125, 126 sun-tracking system for solar farms, 326–27 supermoney, 276–79, 280–84, 289 Supplemental Nutrition Assistance Program (SNAP), 140–42, 266 Surely You’re Joking, Mr.

…

Note that Joshua Schachter had earlier used # as a symbol for tags in his link-saving site del.icio.us. 42 during the San Diego wildfires: Chris Messina, “Twitter Hashtags for Emergency Coordination and Disaster Relief,” retrieved March 29, 2017, https://factoryjoe.com/2007/10/22/twitter-hashtags-for-emergency-coordination-and-disaster-relief/. 42 The app had already begun showing “trending topics”: “To Trend or Not to Trend,” Twitter Blog, retrieved March 29, 2017, https://blog.twitter.com/2010/to-trend-or-not-to-trend. 43 features that the platform developer itself hadn’t imagined: “Twitpic,” retrieved March 29, 2017, https://en.wikipedia. org/wiki/TwitPic. 43 Jim Hanrahan posted the first tweet: Jim Hanrahan, Twitter update, retrieved March 29, 2017, https://twitter.com/highfours/status/1121908186. 43 passengers standing on the wing of the downed plane: “There’s a plane in the Hudson. I’m on the ferry going to pick up the people. Crazy.” Twitter update, retrieved March 29, 2017, https://twitter.com/jkrums/status/1121915133. 43 “We Are All Khaled Said”: Facebook page, retrieved March 29, 2017, https://www.facebook.com/ElShaheeed. 43 “an internal life of its own”: Michael Nielsen, Reinventing Discovery (Princeton, NJ: Princeton University Press, 2011), 53. 44 “A theory is a species of thinking”: Thomas Henry Huxley, “The Coming of Age of ‘The Origin of Species,’” Collected Essays, vol. 2, as reprinted at http://aleph0.clarku.edu/huxley/CE2/CaOS.html. 45 “the way a genome runs on a multitude of cells”: George Dyson, Turing’s Cathedral (New York: Pantheon, 2012), 238–39. 46 income that it can’t deliver: Sami Jarbawi, “Uber to Pay $20 Million to Settle FTC Case,” Berkeley Center for Law, Business and the Economy, January 31, 2017, http://sites.law.berkeley. edu/thenetwork/wp-content/uploads/sites/2/2017/01/Uber-to-Pay-20-Million-to-Settle-FTC-Case.pdf. 46 technology to deflect their investigations: Mike Isaac, “How Uber Deceives the Authorities Worldwide,” New York Times, March 3, 2017, https://www.nytimes.com/2017/03/03/technology/uber-greyball-program-evade-authorities.html. 47 Rivals sue over claims of stolen technology: Alex Davies, “Google’s Lawsuit Against Uber Revolves Around Frickin’ Lasers,” Wired, February 5, 2017, https://www.wired.com/2017/02/googles-lawsuit-uber-revolves-around-frickin-lasers/. 47 tolerates sexual harassment: Susan J.

Late Bloomers: The Power of Patience in a World Obsessed With Early Achievement
by Rich Karlgaard
Published 15 Apr 2019

The Southwest jet, its pressurization compromised by the shattered window, dived from 31,000 feet to 10,000 feet in less than five minutes; passengers were screaming and throwing up. When Captain Shults safely landed the plane, the world’s press hailed her for her calm demeanor and “nerves of steel” throughout the midair emergency. She was compared to Chesley “Sully” Sullenberger, the US Airways pilot who landed a packed commercial jet on the Hudson River after hitting a flock of birds, disabling both engines. Captain Shults was fifty-six when she managed her feat of calm bravado. Sully was fifty-eight. Their stories illustrate another late bloomer strength.

…

I would argue that quitting was the best possible option for young Dan Brown. By saying no to the expectations of others, including his parents, he set his life on a much healthier track. Later in life, Brown performed another defiant act of quitting. In doing so, he had to abandon his father’s expectations: My brother had been a captain in the Air Force. Then he went to law school, became a law professor. I was teaching part-time composition classes at San Jose State—barely able to pay my rent. That’s when my father died. He must have gone to his death wondering, Is Dan ever going to amount to anything? Not that my father was a person who really measured people that way.

…

tend to be self-centered: Henry Bodkin, “Teenagers Are Hard Wired to Be Selfish, Say Scientists,” Telegraph, October 6, 2016, http://bit.ly/​2CQVh08. “brittle”: Carol Dweck, interview by author, August 2016. This Tammie Jo grew up on a ranch: The amazing story of Southwest Airlines pilot Captain Tammie Jo Shults was widely reported following the catastrophic engine failure and depressurization of Flight 1380, en route to Philadelphia, on April 17, 2018. As starting points, I recommend Eli Rosenberg, “She Landed a Southwest Plane After an Engine Exploded. She Wasn’t Supposed to Be Flying That Day,” Washington Post, May 10, 2018.

Adaptive Markets: Financial Evolution at the Speed of Thought
by Andrew W. Lo
Published 3 Apr 2017

Despite the extraordinary complexity of determining the causes of a plane crash, the NTSB manages to communicate a definitive narrative that satisfies all stakeholders, not just those with specialized knowledge. A case in point is the water landing of USAir Flight 1549, piloted by Captain Chesley Sullenberger, in the Hudson River on January 15, 2009. Given the history of terrorist acts in New York over the years, you can imagine how New Yorkers might have reacted to an airplane crash landing within walking (or swimming) distance of the financial district. But that very afternoon, the NTSB issued a statement that, pending more detailed investigation, the initial best guess as to what happened was a bird strike that shut down both engines of Flight 1549.

…

Gary, 262 short selling, 26, 223, 229–230, 233, 326 Siegel, Jeremy, 253, 255 Siegel, Stephan, 161 sigma (measure), 232 SIMON (risk management process), 388–389, 392 Simon, Herbert, 172; academic background of, 177; artificial intelligence research by, 101, 181, 182; bounded rationality notion of, 34, 36, 185, 188, 209, 213, 215, 217; environmental complexity viewed by, 198; heuristics notion of, 66, 179, 217; optimization viewed skeptically by, 178–180, 183; satisficing conceived by, 180–182 Simons, James, 6, 224, 225, 244, 277, 350 Sinclair, Upton, 319 Singapore, 411 single-photon emission computed tomography (SPECT), 102 Siri, 132, 396 Sirri, Erik, 308, 311 60/40s rule, 252, 255 skin conductance, 93–94 slot machines, 91–92 Slovic, Paul, 84 “SM” (patient incapable of fear), 83, 104, 106, 107, 144, 158, 323 small-cap stocks, 250, 259 smallpox, 344 smiling, 105 Smith, Adam, 28, 211 Smith, David V., 100 Sobel, Russell, 206 social Darwinism, 215 social exclusion, 85–86 social media, 55, 270, 405 Société Générale, 60–61 Society of Mind, The (Minsky), 132–133 sociobiology, 170–174, 216–217 Sociobiology (Wilson), 170–171 Solow, Herbert, 395 Soros, George, 6, 219, 222–223, 224, 227, 234, 244, 277 sovereign wealth funds, 230, 299, 409–410 Soviet Union, 411 Space Shuttle Challenger, 12–16, 24, 38 specialization, 217 speech synthesis, 132 Sperry, Roger, 113–114 “spoofing,” 360 Springer, James, 159 SR-52 programmable calculator, 357 stagflation, 37 Standard Portfolio Analysis of Risk (SPAN), 369–370 Stanton, Angela, 338 starfish, 192, 242 Star Trek, 395–397, 411, 414 stationarity, 253–255, 279, 282 statistical arbitrage (“statarb”), 284, 286, 288–291, 292–293, 362 statistical tests, 47 Steenbarger, Brett, 94 Stein, Carolyn, 69 sterilization, 171, 174 Stiglitz, Joseph, 224, 278, 310 Stocks for the Long Run (Siegel), 253 stock splits, 24, 47 Stone, Oliver, 346 Stone Age, 150, 163, 165 stone tools, 150–151, 153 stop-loss orders, 359 Strasberg, Lee, 105 stress, 3, 75, 93, 101, 122, 160–161, 346, 413–415 strong connectedness, 374 Strong Story Hypothesis, 133 Strumpf, Koleman, 39 “stub quotes,” 360 subjective value, 100 sublenticular extended amygdala, 89 subprime mortgages, 290, 292, 293, 297, 321, 327, 376, 377, 410 Sugihara, George, 366 suicide, 160 Sullenberger, Chesley, 381 Summers, Lawrence (Larry), 50, 315–316, 319–320, 379 sunlight, 108 SuperDot (trading system), 236 supply and demand curves, 29, 30, 31–33, 34 Surowiecki, James, 5, 16 survey research, 40 Sussman, Donald, 237–238 swaps, 243, 298, 300 Swedish Twin Registry, 161 systematic bias, 56 systematic risk, 194, 199–203, 204, 205, 250–251, 348, 389 systemic risk, 319; Bank of England’s measurement of, 366–367; government as source of, 361; in hedge fund industry, 291, 317; of large vs. small shocks, 315; managing, 370–371, 376–378, 387; transparency of, 384–385; trust linked to, 344 Takahashi, Hidehiko, 86 Tanner, Carmen, 353 Tanzania, 150 Tartaglia, Nunzio, 236 Tattersall, Ian, 150, 154 Tech Bubble, 40 telegraphy, 356 Tennyson, Alfred, Baron, 144 testosterone, 108, 337–338 Texas hold ’em, 59–60 Texas Instruments, 357, 384 Thackray, John, 234 Thales, 16 Théorie de la Spéculation (Bachelier), 19 theory of mind, 109–111 thermal homeostasis, 367–368, 370 This Time Is Different (Reinhart and Rogoff), 310 Thompson, Robert, 1, 81–82, 83, 103–104 three-body problem, 214 ticker tape machine, 356 tight coupling, 321, 322, 361, 372Tiger Fund, 234 Tinker, Grant, 395 Tobin tax, 245 Tokugawa era, 17 Tooby, John, 173, 174 tool use, 150–151, 153, 162, 165 “toxic assets,” 299 trade execution, 257, 356 trade secrets, 284–285, 384 trading volume, 257, 359 transactions tax, 245 Treynor, Jack, 263 trial and error, 133, 141, 142, 182, 183, 188, 198, 265 Triangle Shirtwaist Fire, 378–379 tribbles, 190–205, 216 Trivers, Robert, 172 trolley dilemma, 339 Trusty, Jessica, 120 Tversky, Amos, 55, 58, 66–67, 68–69, 70–71, 90, 106, 113, 388 TWA Flight 800, 84–85 twins, 159, 161, 348 “two-legged goat effect,” 155 UBS, 61 Ultimatum Game, 336–338 uncertainty, 212, 218; risk vs., 53–55, 415 unemployment, 36–37 unintended consequences, 7, 248, 269, 330, 358, 375 United Kingdom, 222–223, 242, 377 University of Chicago, 22 uptick rule, 233 Urbach-Wiethe disease, 82–83 U.S.

…

Spock could ask the Enterprise questions and be answered by the voice of Majel Barrett, Gene Roddenberry’s wife; today, we have Siri, Cortana, and Alexa to answer everyday questions about enterprises of our own. When we get home, we can sit in our ergonomic chair as we watch the world’s events on our widescreen television while scrolling through a touchpad, just like Captain Kirk. About the only thing missing is the photon torpedoes. The one aspect of modern life that Star Trek spent no time on was finance. This didn’t occur to me until fairly recently since, as a child, I had no inkling of or interest in finance. But after watching one of the recent Star Trek films, I started to wonder what the finance of the future might look like.

Crash of the Titans: Greed, Hubris, the Fall of Merrill Lynch, and the Near-Collapse of Bank of America
by Greg Farrell
Published 2 Nov 2010

A few hours earlier, a Charlotte-bound U.S. Airways flight experienced engine trouble after taking off from LaGuardia Airport in New York. The captain, Chesley “Sully” Sullenberger, made a split-second decision to ditch the airplane, an Airbus A320, in the Hudson River rather than take a chance on being able to get back to an airport. More than a dozen BofA employees were on the flight, heading back to Charlotte after a four-day workweek in New York. Miraculously, the plane landed intact on the Hudson and stayed afloat for hours, allowing rescue teams to get everyone out alive. Lewis assured the board that everyone was safe and out of harm’s way, and then began describing the final details of the government rescue package, which had been firmed up that week.

…

Smith was flattered by the praise, especially since it came from a man who did so much to put O’Neal into the CEO’s chair in the first place. THERE WAS ONE OTHER contrast Thain would draw between himself and O’Neal, and it involved his predecessor’s corner office on the thirty-second floor, with a commanding view of the Statue of Liberty, New York Harbor, and the Hudson River. The first time he saw the décor of O’Neal’s office Thain cringed reflexively, and couldn’t imagine receiving the firm’s most important clients and investors there. He had been particular about his office at Goldman Sachs, to the point of paying for special furnishings out of his own pocket.

…

Kraus, with piercing blue eyes and a neatly trimmed beard, donned pink and lavender shirts as well as ties sporting splashy colors and patterns. He wore plaid suits and a wristwatch that looked like it had come from the Museum of Modern Art. Just as he had transformed his office into a stunning aerie high above New York Harbor and the Hudson River, he also lavished great care and attention on his own presentation and appearance. He looked more like the creative director of a large advertising agency than an investment banker. The women who worked directly for Thain—Margaret Tutwiler and May Lee—admired their boss’s fierce intellect, but were absolutely taken with Kraus’s presence.

Against All Enemies
by Tom Clancy and Peter Telep
Published 13 Jun 2011

If they attempted to turn without sufficient power, they’d very quickly lose altitude. Pilots of single-engine aircraft were instructed to never, ever, attempt to return to the runway, because they would lose too much altitude to effect the turnaround. Case in point: On January 15, 2009, Captain Chesley Sullenberger was in command of US Airways Flight 1549 en route from La Guardia to Charlotte. He had lifted off and flown through a flock of birds, resulting in the loss of both engines. He knew he’d lose precious altitude if he started a turnaround with no engines producing power, and determined that his best course of action was to ditch in the river.

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(Ret.) and Tony Koltz Every Man a Tiger: The Gulf War Air Campaign with General Chuck Horner (Ret.) and Tony Koltz Shadow Warriors: Inside the Special Forces with General Carl Stiner (Ret.) and Tony Koltz AGAINST ALL ENEMIES TOM CLANCY with PETER TELEP G. P. PUTNAM’S SONS NEW YORK G. P. PUTNAM’S SONS PUBLISHERS SINCE 1838 Published by the Penguin Group Penguin Group (USA) Inc., 375 Hudson Street, New York, New York 10014, USA • Penguin Group (Canada), 90 Eglinton Avenue East, Suite 700, Toronto, Ontario M4P 2Y3, Canada (a division of Pearson Penguin Canada Inc.) • Penguin Books Ltd, 80 Strand, London WC2R 0RL, England • Penguin Ireland, 25 St Stephen’s Green, Dublin 2, Ireland (a division of Penguin Books Ltd) • Penguin Group (Australia), 250 Camberwell Road, Camberwell, Victoria 3124, Australia (a division of Pearson Australia Group Pty Ltd) • Penguin Books India Pvt Ltd, 11 Community Centre, Panchsheel Park, New Delhi–110 017, India • Penguin Group (NZ), 67 Apollo Drive, Rosedale, North Shore 0632, New Zealand (a division of Pearson New Zealand Ltd) • Penguin Books (South Africa) (Pty) Ltd, 24 Sturdee Avenue, Rosebank, Johannesburg 2196, South Africa Penguin Books Ltd, Registered Offices: 80 Strand, London WC2R 0RL, England Copyright © 2011 by Rubicon, Inc.

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As the shadow drew closer, the men on the deck shouted to one another and got to work readying the lines. The shadow rose from the water, taking on a mottled pattern of blue, gray, and black, and then, with seawater washing off its sides, it fully broke the surface … A submarine. The vessel glided alongside them, and Ballesteros cried out to the captain, who was rising into the hatch, “This time, I’m coming along for the ride!” The sub was diesel electric-powered, thirty-one meters long, and nearly three meters high from deck plates to ceiling. It was constructed of fiberglass and could cut through the water via twin screws at more than twenty kilometers per hour, even while carrying up to ten tons of cocaine.