bystander effect

The Choice Factory: 25 Behavioural Biases That Influence What We Buy
by Richard Shotton
Published 12 Feb 2018

They termed this diffusion of responsibility the bystander effect, although it’s sometimes referred to as the Genovese syndrome. A practical application It struck me that these findings related to a problem I was grappling with. At the time, I was working as a media planner and one of my clients was the NHS and their Give Blood campaign. They regularly ran appeals warning of low blood stocks across the country. But these campaigns weren’t generating as many donations as hoped. If the psychologists were right, then the NHS’s broad appeals were suffering from the bystander effect. Perhaps it would be more effective to run specific appeals?

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They ignore ads about generic, average savings as they suspect that vague claims may hide misleading statistics. A localised message assuages these worries as specific claims leave less room for deceit. 3. Charitable campaigns particularly benefit from localisation Localisation may be of particular benefit to the charity sector, which suffers from the bystander effect – the idea that mass appeals for help suffer from a diffusion of responsibility. The effect was first studied in the late 1960s by two psychologists, Bibb Latané and John Darley, from Columbia and Princeton University, respectively. They were inspired by one of the most infamous murders in New York’s history, the brutal stabbing in 1964 of Kitty Genovese, which I mentioned earlier in the book.

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Conclusion Do you remember the story of Kitty Genovese I mentioned in the Introduction and Bias 24? She was the 28-year-old who was murdered while none of the 37 (or 38) witnesses intervened. It was a brutal incident – but some good came from it. It inspired Latané and Darley to begin their research into the bystander effect and it even kick-started the establishment of a single number, 911, for calling the police. But you may be surprised to learn that these important consequences were in fact based on a lie. Yes, Winston Moseley murdered Genovese in 1964, but the apathy that so enraged the New York Times was grossly exaggerated.

Don't Even Think About It: Why Our Brains Are Wired to Ignore Climate Change
by George Marshall
Published 18 Aug 2014

The tragic Genovese incident launched a rich and still expanding body of research into the importance of social cues in defining what issues people respond to and what ones they ignore. It is a fascinating feature of this bystander effect—as it was subsequently named—that the more people we assume know about a problem, the more likely we are to ignore our own judgment and watch the behavior of others to identify an appropriate response. A string of experiments confirmed the power of the bystander effect. In one particularly entertaining experiment, an actor faked having a seizure over the laboratory intercom. The last words heard from him were “I could really—er—use some help, so if somebody would—er—give me a little h-help uh er er . . .

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Years later, when a subject in a psychology experiment had a real epileptic fit, the other participants were convinced that it was being faked for the experiment and refused to get off their chairs. Climate change is a global problem that requires a collective response and so is especially prone to this bystander effect. When we become aware of the issue, we scan the people around us for social cues to guide our own response: looking for evidence of what they do, what they say, and, conversely, what they do not do and do not say. These cues can also be codified into rules that define the behaviors that are expected or are inappropriate—the social norm.

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The psychologist Stephan Lewandowsky received enough aggressive responses to his first research paper on climate denial conspiracy theories to provide the basis for yet another study. It bears the enticing title “Conspiracist Ideation in the Blogosphere in Response to Research on Conspiracist Ideation.” While the bystander effect emerges from a sense of shared powerlessness, and a sense of shared power enables a range of abuses and violence, the anonymity of the new electronic norm enables outright bullying—abusive and violent e-mails received by high-profile scientists and activists calling them “Nazi climate murderers” and telling them to “go gargle razor blades.”

You Are Not So Smart
by David McRaney
Published 20 Sep 2011

Have you ever seen someone broken down on the side of the road and thought, “I could help them, but I’m sure someone will be along.” Everyone thinks that. And no one stops. This is called the bystander effect. In 1968, Eleanor Bradley fell and broke her leg in a busy department store. For forty minutes, people just stepped over and around her until one man finally stopped to see what was wrong. In 2000, a group of young men attacked sixty women at a Central Park parade in New York City. Thousands of people looked on. No one used a cell phone to call police. The culprit in both cases was the bystander effect. In a crowd, your inclination to rush to someone’s aid fades, as if diluted by the potential of the group.

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Table of Contents Title Page Copyright Page Dedication Introduction Chapter 1 - Priming Chapter 2 - Confabulation Chapter 3 - Confirmation Bias Chapter 4 - Hindsight Bias Chapter 5 - The Texas Sharpshooter Fallacy Chapter 6 - Procrastination Chapter 7 - Normalcy Bias Chapter 8 - Introspection Chapter 9 - The Availability Heuristic Chapter 10 - The Bystander Effect Chapter 11 - The Dunning-Kruger Effect Chapter 12 - Apophenia Chapter 13 - Brand Loyalty Chapter 14 - The Argument from Authority Chapter 15 - The Argument from Ignorance Chapter 16 - The Straw Man Fallacy Chapter 17 - The Ad Hominem Fallacy Chapter 18 - The Just-World Fallacy Chapter 19 - The Public Goods Game Chapter 20 - The Ultimatum Game Chapter 21 - Subjective Validation Chapter 22 - Cult Indoctrination Chapter 23 - Groupthink Chapter 24 - Supernormal Releasers Chapter 25 - The Affect Heuristic Chapter 26 - Dunbar’s Number Chapter 27 - Selling Out Chapter 28 - Self-Serving Bias Chapter 29 - The Spotlight Effect Chapter 30 - The Third Person Effect Chapter 31 - Catharsis Chapter 32 - The Misinformation Effect Chapter 33 - Conformity Chapter 34 - Extinction Burst Chapter 35 - Social Loafing Chapter 36 - The Illusion of Transparency Chapter 37 - Learned Helplessness Chapter 38 - Embodied Cognition Chapter 39 - The Anchoring Effect Chapter 40 - Attention Chapter 41 - Self-Handicapping Chapter 42 - Self-Fulfilling Prophecies Chapter 43 - The Moment Chapter 44 - Consistency Bias Chapter 45 - The Representativeness Heuristic Chapter 46 - Expectation Chapter 47 - The Illusion of Control Chapter 48 - The Fundamental Attribution Error Acknowledgements BIBLIOGRAPHY DUTTON Published by Penguin Group (USA) Inc. 375 Hudson Street, New York, New York 10014, U.S.A.

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When it comes to buying lottery tickets, fearing the West Nile virus, looking for child molesters, and so on, you use the availability heuristic first and the facts second. You decide the likelihood of a future event on how easily you can imagine it, and if you’ve been bombarded by reports or have filled your head with fears, those images will overshadow new information that might contradict your beliefs. 10 The Bystander Effect THE MISCONCEPTION: When someone is hurt, people rush to their aid. THE TRUTH: The more people who witness a person in distress, the less likely it is that any one person will help. If your car were to break down and your cell phone had no service, where do you think you would have a better chance of getting help—a country road or a busy street?

Humankind: A Hopeful History
by Rutger Bregman
Published 1 Jun 2020

Or maybe there’s something special about the Dutch culture, or this neighbourhood in Amsterdam, or even these four men, that accounts for the anomaly? On the contrary. Though the bystander effect may still be taught in many textbooks, a meta-analysis published in 2011 has shed new light on what bystanders do in emergencies. Meta-analysis is research about research, meaning it analyses a large group of other studies. This meta-analysis reviewed the 105 most important studies on the bystander effect from the past fifty years, including that first experiment by Latané and Darley (with students in a room).18 Two insights came out of this study-of-studies. One: the bystander effect exists. Sometimes we think we don’t need to intervene in emergencies because it makes more sense to let somebody else take charge.

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‘I could really-er-use some help,’ moaned a voice at some point, ‘so if somebody would-er-give me a little h-help-uh-er-er-er-er-er c-could somebody-er-er-help-er-uh-uh-uh [choking sounds] … I’m gonna die …’10 What happened next? When a trial subject thought that they alone heard the cries for help, they rushed out into the corridor. All of them, without exception, ran to intervene. But among those who were led to believe five other students were sitting in rooms nearby, only 62 per cent took action.11 Voila: the bystander effect. Latané and Darley’s findings would be among the most pivotal contributions made to social psychology. Over the next twenty years, more than a thousand articles and books were published on how bystanders behave in emergencies.12 Their results also explained the inaction of those thirty-eight witnesses in Kew Gardens: Kitty Genovese was dead not in spite of waking up the whole neighbourhood with her screams, but because of it.

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When her husband went to call the police, she held him back: ‘I told him there must have been thirty calls already.’13 Had Kitty been attacked in a deserted alleyway, with only one witness, she might have survived. All this only fuelled Kitty’s fame. Her story found its way into the top ten psychology textbooks and continues to be invoked by journalists and pundits to this day.14 It’s become nothing less than a modern parable on the perilous anonymity of big-city life. 3 For years I assumed the bystander effect was just an inevitable part of life in a metropolis. But then something happened in the very city where I work – something that forced me to reassess my assumptions. It’s 9 February 2016. At a quarter to four in the afternoon Sanne parks her white Alfa Romeo on Sloterkade, a canal-side street in Amsterdam.15 She gets out and heads to the passenger side to take her toddler out of the car seat when, suddenly, she becomes aware the car is still rolling.

Think Complexity
by Allen B. Downey
Published 23 Feb 2012

We could instead be more fair and distribute the burden of volunteering among the players by asking each of them to volunteer some percentage of the time, but the high-damage situation will occur more frequently as the number of players who share the burden increases. Example 14-1. Read about the bystander effect at http://en.wikipedia.org/wiki/Bystander_effect. What explanation, if any, does the Volunteer’s Dilemma provide for the bystander effect? Example 14-2. Some colleges have an honor code that requires students to report instances of cheating. If a student cheats on an exam, other students who witness the infraction face a version of the Volunteer’s Dilemma.

Rationality: From AI to Zombies
by Eliezer Yudkowsky
Published 11 Mar 2015

Something like this may well be a contributor, but two observations that mitigate against it are (a) the experimental subjects did not report smoke coming in from under the door, even though it could well have represented a strictly selfish threat and (b) telling people about the bystander effect reduces the bystander effect, even though they’re no more likely to be held publicly responsible thereby. In fact, the bystander effect is one of the main cases I recall offhand where telling people about a bias actually seems able to strongly reduce it—maybe because the appropriate way to compensate is so obvious, and it’s not easy to overcompensate (as when you’re trying to e.g. adjust your calibration). So we should be careful not to be too cynical about the implications of the bystander effect and diffusion of responsibility, if we interpret individual action in terms of a cold, calculated attempt to avoid public censure.

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People seem at least to sometimes hold themselves responsible, once they realize they’re the only ones who know enough about the bystander effect to be likely to act. Though I wonder what happens if you know that you’re part of a crowd where everyone has been told about the bystander effect . . . * 1. Bibb Latané and John M. Darley, “Bystander ‘Apathy,’” American Scientist 57, no. 2 (1969): 244–268, http://www.jstor.org/stable/27828530. 2. Cialdini, Influence. 327 Collective Apathy and the Internet In the last essay I covered the bystander effect, a.k.a. bystander apathy: given a fixed problem situation, a group of bystanders is actually less likely to act than a single bystander.

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Nervousness about public action may also play a role. If Robin Hanson is right about the evolutionary role of “choking,” then being first to act in an emergency might also be taken as a dangerous bid for high status. (Come to think, I can’t actually recall seeing shyness discussed in analyses of the bystander effect, but that’s probably just my poor memory.) Can the bystander effect be explained primarily by diffusion of moral responsibility? We could be cynical and suggest that people are mostly interested in not being blamed for not helping, rather than having any positive desire to help—that they mainly wish to escape antiheroism and possible retribution.

Super Thinking: The Big Book of Mental Models
by Gabriel Weinberg and Lauren McCann
Published 17 Jun 2019

DuckDuckGo similarly assigns a DRI to every company activity—from the smallest task to the largest company objective. The DRI concept helps avoid diffusion of responsibility, also known as the bystander effect, where people fail to take responsibility for something when they are in a group, because they think someone else will take on that responsibility. In effect, they act like bystanders, and the responsibility diffuses across all the members of the group instead of being concentrated in one person who is held accountable. You can see the bystander effect in many situations, including when people need help in an emergency. In a famous 1968 study, “Bystander Intervention in Emergencies: Diffusion of Responsibility,” John Darley and Bibb Latané had a group of subjects participate in a group discussion about their lives, communicating with one another electronically from separate rooms.

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A&P, 70 absence of evidence is not the evidence of absence, 167 A/B testing, 136 Accidental Empires (Cringley), 253 accountability, 275 acne, 169–71 activation energy, 112–13 actor-observer bias (self-serving bias), 21, 272 Adams, John, 222 adaptability, 121, 129 ad hominem, 226 adverse selection, 46–47 advertising, 103–4, 120, 262 advisers, 44, 45, 296 Affordable Care Act (ACA), 46, 47 Afghanistan, 54, 243 agent, 44–45 aggregation, 205 aggression, obnoxious, 264 agreeableness, 250 AIDS, 233 Airbnb, 276, 288, 292 air pollution, 41 air travel, 53–54 Aldi, 70 Alexander, Christopher, 92 algorithms, 94, 97 Allen, David, 76 all-nighter, 83 alpha, 161, 182 al-Qaeda, 52, 54 alternative hypothesis, 163, 164, 166, 167 altruism, effective, 80 alumni, 119 Amazon, 61, 70, 95–96, 283, 290, 300 American Revolution, 221–22, 239, 240 American Statistical Association, 168 Amway, 217 analysis paralysis, 60–62, 93 anchoring, 14–15, 30, 199 anecdotal evidence, 133, 139, 146 antibiotics, 37, 47–49 Antifragile (Taleb), 2, 105 antifragility, 2–3, 31–33 anti-patterns, 93 AOL, 106 Apollo 13, 4 appeasement, 237 Apple, 103, 104, 231, 241, 258, 289–91, 305, 309 iPad, 290 iPod, 296–97 Newton, 290 approval ratings, 152–54, 158 arbitrage, 282–83 Archilochus, 254 Archimedes, 78 arguing from first principles, 4–7, 31, 207 Ariely, Dan, 14, 222–23 arithmetic, ix–x, 23–24, 30, 178 arms races, 209–12, 214 Ashley Madison, 229 Associated Press (AP), 306 asymmetric information, 45–47 atomic bomb, see nuclear weapons Atwood, Jeff, 253 authority, 219–20, 226 automation, 95, 310 availability bias, 15–18, 30, 33, 300 average, 146, 187 Avon, 217 Aztecs, 243–44 babies, 198, 279 sleep and, 131–32 babysitters, 222 backfire effect, 26 back-of-the-envelope calculation, 299 bacteria, 47–49, 295 bait and switch, 228, 229 bandwagon effect, 202 barriers to entry and barriers to exit, 305 baseball, 83, 145–46, 289 base rate, 157, 159, 160 base rate fallacy, 157, 158, 170 BATNA (best alternative to a negotiated agreement), 77 Battle of Heraclea, 239 Battle of Tsushima, 241 Bayes’ theorem and Bayesian statistics, 157–60 beachhead, 300–301 Beatles, 105 Beautiful Mind, A, 213 beliefs, 103, 107 bell curve (normal distribution), 150–52, 153, 163–66, 191 Bell Labs, 89 benefit of the doubt, 20 benefits: cost-benefit analysis, 177–86, 189, 194 eliminating, 224 net, 181–82, 184 Berlin, Isaiah, 254 Bernoulli distribution, 152 best practices, 92 beta, 162, 182 Better Angels of Our Nature, The (Pinker), 144 Bezos, Jeff, 61–62, 286–87 bias, 3, 139 availability, 15–18, 30, 33, 300 confirmation, 26–28, 33, 103, 159 disconfirmation, 27 groupthink, 201–3 hidden, 139–43 hindsight, 271–72 nonresponse, 140, 142, 143 observer-expectancy, 136, 139 optimistic probability, 33 present, 85, 87, 93, 113 publication, 170, 173 response, 142, 143 selection, 139–40, 143, 170 self-serving, 21, 272 survivorship, 140–43, 170, 272 Big Short, The (Lewis), 289 bike-shedding, 75, 93 Bird, Larry, 246 birth lottery, 21–22, 69 black-and-white thinking, 126–28, 168, 272 black boxes, 94–95 Black Flags rebellion, 276 blackouts, electric, 120 black swan events, 190–91, 193 Blank, Steve, 294 bleeding them dry, 239 blinded experiments, 136 Blockbuster, 106 blowback, 54 Boaty McBoatface, RSS, 35 body mass index (BMI), 137 body temperature, 146–50 boiling frog, 55, 56, 58, 60 bonds, 180, 184 Bonne, Rose, 58 Boot, Max, 239 boots on the ground, 279 Boston Common, 36–38, 42 Boyd, John, 294 Bradley, Bill, 248 brainstorming, 201–3 Brandeis, Louis, 307 breast cancer, 156–57, 160–61 Breathalyzer tests, 157–58, 160 Brexit, 206, 305 bright spots, 300 bring in reinforcements, 279 British Medical Journal (BMJ), 136–37 broken windows theory, 235–36 Broderick, Matthew, 230 Brody, William, 290–91 Brookings Institution, 306 brute force solution, 93, 97 Bryson, Bill, 50 budget, 38, 74–75, 81, 95, 113 national, 75–76 Buffett, Warren, viii, 69, 286, 302, 317, 318 burning bridges, 243 burnout, 82, 83 Burns, Robert, 49 burn the boats, 244 Bush, George H. W., 104 business case, 207 butterfly effect, 121, 122, 125, 201 Butterfly Effect, The, 121 Butterworth, Brian, x buyout, leveraged, 79 bystander effect, 259 cable television, 69, 100, 106 Caesar, Julius, 244 calculus, 291 call your bluff, 238 cameras, 302–3, 308–10 campaign finance reform, 110 Campbell, Donald T., 49–50 Campbell’s law, 49–50 cancer: breast, 156–57, 160–61 clusters of, 145 lung, 133–34, 137 cap-and-trade systems, 42–43 capital, cost of, 76, 77, 179, 182 careers, 300–301 decisions about, 5–6, 57, 175–77, 201, 207, 296 design patterns and, 93 entry barriers and, 305 licensing and, 306–7 Carfax, 46 Cargill, Tom, 89 cargo cults, 315–16 caring personally, 263–64 car market, 46–47 Carrey, Jim, 229 carrot-and-stick model, 232 cascading failures, 120, 192 casinos, 220, 226 cast a wide net, 122 catalyst, 112–13, 115, 119 Catherine II, Empress, 228 causal loop diagrams, 192–93 causation, correlation and, 134, 135 cellphones, 116–17 center of gravity, 112 central limit theorem, 152–53, 163 central tendency, 147 chain reaction, viii, 114, 120 Challenger, 31–33 challenging directly, 263–64 change, 100–101, 112–13, 129 resistance to, 110–11 chaos, 124 balance between order and, 128 chaos theory, 121 chaotic systems, 120–21, 124, 125 Chatelier’s principle, 193–94 cheating, 50 Chekhov, Anton, 124 chess, 242 chilling effect, 52–54 China, 231, 276 choice, 62 paradox of, 62–63 Christensen, Clayton, 296, 297, 310 Cialdini, Robert, 215–17, 219–21 circle of competence, 317–18 climate change, 42, 55, 56, 104, 105, 183, 192 Clinton, Hillary, 70, 97 clustering illusion, 144–45 CNN, 220 Coase, Ronald, 42 Coase theorem, 42–43 cobra effect, 50–52 Coca-Cola, 305 cognitive dissonance, 27–29, 216 coin flips, 143–44, 154–55, 158–59 Cold War, 209, 235 collateral damage, 53–54, 231 collective intelligence, 205 collectivist versus individualist, in organizational culture, 274 college, 209–10 choice of, 58–60 rankings of, 50, 137 Collins, Jim, 109, 254 commandos, in organizations and projects, 253–54 commitment, 87–88 escalation of, 91 influence model of, 216, 220 commodities, 283 commons, 36–38, 43 Common Sense (Paine), 221–22 communication, high-context and low-context, 273–74 competence, circle of, 317–18 competition: and crossing the chasm, 312 moats and, 302–5 perfect, 283 regulatory capture and, 305 sustainable competitive advantage, 283, 285 complexity, complex systems, 185–86, 192, 194 diagrams and, 192–93 simulations and, 192–94 compound interest, 69, 85 Concorde fallacy, 91 conditional probability, 156 Confederate leaders, 113 confidence intervals, 154–56, 159 confidence level, 154, 155, 161 confirmation bias, 26–28, 33, 103, 159 conflict, 209, 226 arms races, 209–12, 214 game theory and, see game theory confounding factor, 134–35, 139 conjunction fallacy, 9–10 conscientiousness, 250 consensus, 202 consensus-contrarian matrix, 285–86, 290 consequence-conviction matrix, 265–66 consequences, 35 unintended, 35–36, 53–55, 57, 64–65, 192, 232 containment, 233, 237 contests, 35–36 context-switching, 71, 74 continental drift, 24–25, 289 contrarian-consensus matrix, 285–86, 290 Contrarian’s Guide to Leadership, The (Sample), 28 control group, 136 conventional wisdom, 5 convergent thinking, 203 conviction-consequence matrix, 265–66 cooperation, 215, 226 tit-for-tat, 214–15 correlations, 134, 135, 139 corruption, 307 Cortés, Hernán, 243–44 cost-benefit analysis, 177–86, 189, 194 Costco, 70 cost of capital, 76, 77, 179, 182 cost of doing business, 232 counterfactual thinking, 201, 272, 309–10 cramming, 83, 262 credible intervals, 159 crime, 16, 161, 231, 232 broken windows theory and, 235–36 Cringley, Robert X., 253 critical mass, viii–x, 114–15, 117, 119, 120, 129, 194, 308 critical thinking, 201 crossing the chasm, 311–12 crossing the Rubicon, 244 crowdsourcing, 203–6, 286 culture, 113, 273 organizational, 107–8, 113, 273–80, 293 customers, 300 development of, 294 personas for, 300 types of, 298–300 winner-take-most markets and, 308 Cutco, 217 Danziger, Shai, 63 dark patterns, 226–29 Potemkin villages, 228–29 Darley, John, 259 Darwin, Charles, 100, 101, 291 data, 130–31, 143, 146, 301 binary, 152 dredging of, 169–70 in graphs, see graphs mean in, 146, 149, 151 meta-analysis of, 172–73 outliers in, 148 streaks and clusters in, 144 variance in, 149 see also experiments; statistics dating, 8–10, 95 daycare center, 222–23 deadlines, 89 death, causes of, 17 death by a thousand cuts, 38 debate, 225 decisions, 1–2, 11, 31, 127, 129, 131–33, 175, 209 business case and, 207 choices and, 62–63 cost-benefit analysis in, 177–86, 189, 194 decision fatigue and, 63–64 decision tree in, 186–90, 194, 215 Eisenhower Decision Matrix, 72–74, 89, 124, 125 irreversible, 61–62, 223–24 opportunity cost and, 76–77, 80, 83, 179, 182, 188, 305 past, analyzing, 201, 271–72 pro-con list in, 175–78, 185, 189 reversible, 61–62 sequences of, 144 small, tyranny of, 38, 55 utilitarianism and, 189–90 Declaration of Independence, 222 deep work, 72, 76, 88, 278 default effect, 87–88 Defense, U.S.

Warnings
by Richard A. Clarke
Published 10 Apr 2017

The President of the United States or the CEO of a corporation might be the person who could order action, but there may not be a general understanding of who should take the issue to them. Who owns it? Frequently, no one wants to own an issue that’s about to become a disaster. This reluctance creates a “bystander effect,” wherein observers of the problem feel no responsibility to act.7 Increasingly, complex issues are multidisciplinary, making it unclear where the responsibility lies. New complex problems or “issues on the seams” are more likely to produce ambiguity about who is in charge of dealing with them.

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It also illustrates the “Pet Rock problem,” not wanting to defund an organization’s chosen projects, or Pet Rocks, in order to deal with some unpleasant, unplanned, and unwelcome obligation. Organizations faced with this kind of intrusion into their priorities usually think that somebody else should fund efforts at risk reduction, that it should come from some “national budget,” not theirs. It’s a classic example of the bystander effect, or a diffusion of responsibility. Second, Morrison said, we are talking about “a hypothetical danger.” There has never been an asteroid impact with any significant number of casualties in human history. This is a clear example of what we in this book are calling Initial Occurrence Syndrome, the failure to value a risk sufficiently even in the face of convincing data, because “it has never happened before.”

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Madoff Investment Securities, 101, 104, 107–8 Betrayal of Trust (Garrett), 232 Bettencourt, Liliane, 101 Bezos, Jeff, 202 Big data, 16, 184 Big Short, The (Lewis), 145–46, 162–63 Bikini Atoll, 373n Bikini Boot Camp, 158 Bilton, Nick, 294 Bin Laden, Osama, 69, 269 Biological Weapons Convention (BWC), 218 Birth control, 192, 193 BitSight, 295 BlackEnergy, 285, 288 Black Monday (1987), 146 Blankenship, Don, 139–40 Bloomberg, 145, 155–59 Boeing KC-135 Stratotankers, 28 Boisjoly, Roger, 11–13 Borlaug, Norman, 193 Boston, sea-level-rise in, 256–57 Bostrom, Nick, 203, 380n, 381n Botnets, 296, 297 Bove, Dick, 163 Bowen, Mark, 258–59 Bowen, Richard M., III, 155, 157, 162, 163 Brain, 13, 14–15, 34–35 Brimstone missiles, 214 Brooks, Mel, 186 Brown, George, 312, 313, 315 Brown, Michael, 54 Brown University, 151, 152, 153 Bubiyan, 27–30 Buffett, Warren, 147 Burry, Michael, 149 Bush, George H. W., 24, 28–29, 30, 242 Bush, George W., 8, 262, 315 energy policy, 243–44 FEMA and Hurricane Katrina, 47, 54 Iraq war, 37, 357–58 Butner Federal Correctional Complex, 114 “Bystander effect,” 176–77, 321 Caldeira, Ken, 254 Capital One, 152 Caribou Biosciences, 333 Carnegie Institution for Science, 254 Casey, Frank, 102–3, 105, 106, 110 Cassandra, 1–5 Allen as, 31–32, 36 Doudna as, 336–37, 347–48, 349 false, 191–98 financial term usage, 150 Ford as, 64–65, 72 Garrett and Webster as, 224–25, 233, 236 Hansen as, 259–60, 260 Markopolos as, 105–9 Morrison as, 318–20, 324 Robock as, 280–81, 282 Sagan and Turco and, 276–77 van Heerden as, 50–51 Weiss as, 288, 300, 300 Whitney as, 149, 150 Yudkowsky as, 215–16, 216 Cassandra Coefficient, 6–7, 167–98, 351, 357 AI and, 214–16 the audience or decision makers, 168, 170, 176–82 components of, 169–88 CRISPR and genetic engineering, 347–48 the critics, 168, 170, 186–88 making the same mistakes, 189–91 Morrison and asteroid threat, 318–19 the predictor or possible Cassandra, 168, 170, 182–86 Robock and nuclear winter, 281 the warning, 168, 170, 170–76 Weiss and IoT, 299 Cassandra Events, 4–7, 6, 9, 168 ackowiak and UBB, 133, 141 Ford and Syria, 70, 71 Fukushima nuclear disaster, 94–95 van Heerden and levee failures, 51–52 Castro, Fidel, 279 Category 2 storms, 53 Category 3 hurricanes, 46 Censoring Science (Bowen), 258 Center for Disease Control, 195 Centralia mine disaster of 1947, 126–27 Chabris, Christopher, 175 Challenger disaster, 11–13 Chamberlin, Neville, 10 Chamorro-Premuzic, Tomas, 183 Chanos, Jim, 163 Chapman, Clark, 302, 303, 304–5, 308–9, 312, 314–15, 319 Charpentier, Emmanuelle, 329–30, 333 Chelo, Neil, 102, 105–7, 110 Chelyabinsk meteor, 309–10, 316 Chenault, Ken, 152 Cheney, Dick, 243 Chernobyl disaster, 87 Chertoff, Michael, 51 Cheung, Meaghan, 110–11, 117–18 Chicken Little, 2, 150, 162, 164, 180 Chicxulub crater, 307–9 Chinese Academy of Science, 345 Chodas, Paul, 310–11 Chūetsu offshore earthquake of 2007, 76 Church, George, 341–42S Churchill, Winston, 365 Churchill, Winston S., 9–11 CIA (Central Intelligence Agency) Counterterrorism Center, 8 Gulf War and, 20, 24, 27, 31–32, 33, 37–38 September 11 attacks and, 8 Syria and, 64, 72 CIT Group, 152 Citigroup, 148–50, 153–65, 154 Whitney’s downgrade of, 143–46, 154, 156–60, 164–65 Clarke, Arthur C., 313 Clarke, Richard al Qaeda and 9/11, 7–9 Ebola virus and, 220 Gulf War and, 21–22, 28, 29–30 LNOs and, 271–72 at State Department, 21–22, 28, 33–34 Ukraine power grid cyber attack of 2015, 283–84 Weiss and, 283, 286–87 Climate change, 237–60, 278 Hansen and, 237–42, 238 melting polar ice and, 239, 245–52, 258–60 Paris Agreement and, 247–50 rise in temperature, 239–40, 244–47, 249 sea-level rise, 238, 244–60 Climate change feedback, 246, 248 Clinton, Bill, 53–54, 71, 124, 220, 228, 243, 354 Clinton, Hillary, 64 CNBC, 150, 154, 161, 162–63 CO2 emissions, 239, 244–46, 252–53 Coal dust, 123, 124, 125, 128–29, 130 UBB Mine disaster, 135–36 Coal Mine Inspection and Investigation Act of 1941, 126 Coal Mine Safety Act of 1952, 127 Coal Mine Safety and Health Act of 1969, 128, 141–42 Coal mining, 121–42.

The Sellout: A Novel
by Paul Beatty
Published 2 Mar 2016

Family lore has it that from ages one to four, he’d tied my right hand behind my back so I’d grow up to be left-handed, right-brained, and well-centered. I was eight when my father wanted to test the “bystander effect” as it applies to the “black community.” He replicated the infamous Kitty Genovese case with a prepubescent me standing in for the ill-fated Ms. Genovese, who, in 1964, was robbed, raped, and stabbed to death in the apathetic streets of New York, her plaintive Psychology 101 textbook cries for help ignored by dozens of onlookers and neighborhood residents. Hence, the “bystander effect”: the more people around to provide help, the less likely one is to receive help. Dad hypothesized that this didn’t apply to black people, a loving race whose very survival has been dependent on helping one another in times of need.

SuperFreakonomics
by Steven D. Levitt and Stephen J. Dubner
Published 19 Oct 2009

To mark the thirtieth anniversary, President Bill Clinton visited New York City and spoke about the crime: “It sent a chilling message about what had happened at that time in a society, suggesting that we were each of us not simply in danger but fundamentally alone.” More than thirty-five years later, the horror lived on in The Tipping Point, Malcolm Gladwell’s groundbreaking book about social behavior, as an example of the “bystander effect,” whereby the presence of multiple witnesses at a tragedy can actually inhibit intervention. Today, more than forty years later, the Kitty Genovese saga appears in all ten of the top-selling undergraduate textbooks for social psychology. One text describes the witnesses remaining “at their windows in fascination for the 30 minutes it took her assailant to complete his grisly deed, during which he returned for three separate attacks.”

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See also specific researcher or experiment Bernheim, Douglas, 105 Berrebi, Claude, 62–63 Bertrand, Marianne, 45–46 BigDoggie.net, 51 birth effects, 57–62 Bishop, John, 44 blood-pressure cuffs, disposable, 207 boats, wind-powered fiberglass, 202 Bolívar, Simón, 63 border security, 66 Budyko, Mikhail, 191 Budyko’s Blanket, 193–99, 200 Buffett, Warren, 195 “butterfly girls,” 24–25, 34 bystander effect, 99 Caldeira, Ken, 183–84, 185, 186, 191–92, 196, 200 Canada, Athabasca Oil Sands in, 195 cancer, 84–87, 92 cap-and-trade agreement, 187 capitalism, as “creative destruction,” 11 carbon emissions, 11, 166, 171, 173, 182–83, 184–85, 187–88, 192, 199, 203 cardiovascular disease, 86 careers/professions and feminist revolution, 43–44 and prostitution, 54–55 Carnegie Institution, 183 “casual sex,” 30–31 Cedars-Sinai Medical Center, 205–6 Chamberlen, Peter, 141 change behavioral, 148–49,173, 203–9 charitable giving, 106–7, 124 Chavez, Hugo, 198 cheap and simple fixes and Agricultural Revolution, 141–42 and automobiles, 146–58 and childbirth, 133–38 and drugs, 145–46 and hurricanes, 158–63,178 and law of unintended consequences, 138–41 and oil, 142–43 and polio, 143–45 and population, 141–42 and puerperal fever, 133–38 and technological innovation, 11 and whaling, 142–43 See also Myhrvold, Nathan cheating, 116–17, 121 chemotherapy, 84–86 Chen, Keith, 211–16 Chevrolet, 158 Chicago, Illinois, prostitution in, 23–25, 26–38, 40–42, 50–55, 70–71 chief executive officers (CEOs), women as, 44–45 childbirth and cheap and simple fixes, 133–38,177 forceps in, 140–41 children and MBA wage study, 45–46 seat belts for, 150–58 “chimney to the sky,” 200–201 circumcision, 208–9 civil rights, 100 Civil Rights Act (1964), 43 climate change and Budyko’s Blanket, 193–99, 200 and carbon emissions, 166, 171, 173, 182–83, 184–85, 187–88, 192 control of, 198 cost-benefit analysis about, 168–69 and hurricanes, 158–63 incentives concerning, 203 lack of experiments about, 168 manipulation of, 190–91 prediction models about, 181–86 scary scenarios about, 169, 202–3 and volcanoes, 188–90 See also global warming/cooling Clinton, Bill, 99 clouds, puffy white, 201–2 Club (anti-theft device), 173–74 coal, 187, 189, 200–201 competition, for prostitutes, 30–31 condoms in India, 5, 6 and prostitution, 36, 53 Congress, U.S.

Learning to Think: A Memoir
by Tracy King
Published 12 Mar 2025

Interestingly to me, it is the differences in their statements that make them more believable. I would be suspicious of identical testimony, simply because eyewitness testimony is controversial in its reliability, so the chance of five children all having identical versions of events is implausible. There’s a theory called the Bystander Effect, which re-emerges whenever there’s a crime in which witnesses are alleged to have insufficiently intervened. The idea is that if other people are around, individuals are less likely to help, perhaps assuming someone else will, or perhaps because the sense of responsibility is diffused. While there is safety in numbers, there is also apathy and denial.

…

Kitty was attacked at 2.30 a.m. by a man with a hunting knife who had followed her home. A few weeks later, the New York Times claimed that thirty-eight people had witnessed the attack, and they all did nothing. This claim is not true, and is unfair to those witnesses who did indeed try to help. The Bystander Effect has since been disputed in a number of academic studies. And yet in DCI Burns’s report the paramedic states there were perhaps a dozen people standing around watching at a little distance, and he has to ask why none had helped the man lying there. I’m not sure the reasons for that are easily captured in a psychology study.

Global Catastrophic Risks
by Nick Bostrom and Milan M. Cirkovic
Published 2 Jul 2008

A college student apparently having an epileptic seizure was helped 85% of the time by a single bystander and 31% of the time by five bystanders. The bystander effect is usually explained as resulting from diffusion of responsibility and pluralistic ignorance. Being part of a group reduces individual responsibility. Everyone hopes that someone else will handle the problem instead, and this reduces the individual pressure to the point that no one does anything. Support for this hypothesis is adduced from manipulations in which subjects believe that the victim is especially dependent on them; this reduces the bystander effect or negates it entirely. Cialdini (2001) recommends that if you are ever in an emergency, you single out one bystander, and ask that person to help - thereby overcoming the diffusion.

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But if combinatorics could not correctly predict that a lottery ticket has a w - 8 chance of winning, ticket sellers would go broke. 5 . 1 1 Bystander apathy My last bias comes, not from the field of heuristics and biases, but from the field of social psychology. A now-famous series of experiments by Latane and Darley (1969) uncovered the bystander effect, also known as bystander apathy, in which larger numbers of people are less likely to act in emergencies - not 110 Global catastrophic risks only individually, but also collectively. Among subjects alone in a room, on noticing smoke entering from under a door, 75% of them left the room to report it.

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What is easy to forget, though, is that everybody else observing the event is likely to be looking for social evidence, too. Because we all prefer to appear poised and unfl.ustered among others, we are likely to search for that evidence placidly, with brief, camouflaged glances at those around us. Therefore everyone is likely to see everyone else looking unruffled and failing to act. The bystander effect is not about individual selfishness or insensitivity to the suffering of others. Alone subjects do usually act. Pluralistic ignorance can explain, and individual selfishness cannot explain, subjects failing to react to a room filling up with smoke. In experiments involving apparent dangers to either others or the self, subjects placed with non-reactive confederates frequently glance at the non-reactive confederates.

The Secret of Our Success: How Culture Is Driving Human Evolution, Domesticating Our Species, and Making Us Smarter
by Joseph Henrich
Published 27 Oct 2015

That is, if the primary father dies or is injured, and there is only one father left, the responsibility clearly falls to him. However, if two or more fathers remain, it’s not clear who should do what, or who should step up. Among Westerners, psychologists have documented this diffusion of responsibility phenomenon and call it the “bystander effect” (Fischer et al. 2011). 19. See Lieberman, Fessler, and Smith 2011, Chapais 2008, Sepher 1983, Wolf 1995, and Hill et al. 2011. 20. See Fessler and Navarrete 2004 and Lieberman, Tooby, and Cosmides 2003. 21. See Henrich 2014, Henrich, Boyd, and Richerson 2012, and Talhelm et al. 2014. 22.

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Finniss, D. G., T. J. Kaptchuk, F. Miller, and F. Benedetti. 2010. “Biological, clinical, and ethical advances of placebo effects.” Lancet 375 (9715):686–695. Fischer, P., J. I. Krueger, T. Greitemeyer, C. Vogrincic, A. Kastenmüller, D. Frey, M. Heene, M. Wicher, and M. Kainbacher. 2011. “The bystander-effect: A meta-analytic review on bystander intervention in dangerous and non-dangerous emergencies.” Psychological Bulletin 137(4): 517–537. http://dx.doi.org/10.1037/a0023304. Fischer, R., D. Xygalatas, P. Mitkidis, P. Reddish, P. Tok, I. Konvalinka, and J. Bulbulia. 2014. “The fire-walker’s high: Affect and physiological responses in an extreme collective ritual.”

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See also aboriginal Australian societies Australopiths: brain size of, 281–82; cultural accumulation of, 295; cultural nature of, 281–82; tool use of, 282–86 authentic price, 127–28 autocatalytic process, 57–58, 64 Baffin Islanders, 211–12 Baltic peoples, genetic adaptations of, 83–85 “band of brothers” phenomenon, 161–62 Barí society, multiple fathers in, 151 Barrett, Clark, 341–42n.33 Bauer, Michal, 208–9 Berlin, Brent, 364n.13 Biesele, Megan, 159–60 big-headed baby problem, 62 big man societies, 130, 137–38 Billing, Jennifer, 110–11 biological transitions, major, 314–15, 318 Birch, Sue, 43 bird augury, 105–6 bodily development, slow, 64–65 bodily displays: dominance versus prestige, 126–27; high status, 126–28; submissive, 128 body language, 234 bonobos, nonviolence of, 354n.9 bows and arrows, development of, 107, 183, 228 Boyd, David, 173–74 Boyd, Rob, 35 brain: cortical interconnections and folding in, 61–62; cultural adaptations of, 267–69; development of, 62–63; evolution and expansion of, 62; extended childhood in development of, 63–64; internalized norm effects on, 196–97; in learning complex sequences, 254–56; literacy in evolution of, 327–28; multispecies evolutionary expansion of, 296–97; size of in Australopiths, 281–82; taxi drivers’ adaptations of, 266–67; wired for reading, 260–64. See also collective brains brain letterbox, 260–61, 367n.2 breast-feeding taboos, 100–102 Broesch, James, 338n.23, 341–42n.33 Broesch, Tanya, 366n.37 Buffett, Warren, generosity of, 128 Burke, Robert, 27–30 Burke and Wills expedition, 27–30 bystander effect, 352n.18 cannibalism, 23, 27, 31, 183 capsicum-containing food, learning to like, 110–12, 345–46n.30 Cassar, Alessandra, 208–9 category-based induction, 78–79 causal models, 14; ability to build, 322–23 celebrities: admiration and prestige of, 43, 125–26; copycat suicides of, 49; endorsements by, 120 ceremonial gatherings, linguistic expansion and, 178 Chaldean language speakers, 202 Chameleon effect, 125 Chapais, Bernard, 305 cheese making technology, 90, 92 childhood, extended, 63–64 children: cultural learning in, 41–42, 224–25; effects of war on, 208–10; imitating models, 189–90; intellectual ability of versus chimpanzees, 13–15; language-learning ability of, 233–34, 249–50; mentalizing abilities in, 51; responses of to norm violations, 185–87 chili peppers, learning to like, 111–12, 345–46n.30 chimpanzees: aggression of toward strangers, 199; brain myelination in, 62–63; cumulative cultural learning in, 224–25; dexterity of versus humans, 70–71; fission-fusion social organization of, 313; fluid-dipping practice in, 229; intergroup competition among, 166–67; intergroup violence among, 354n.9; memory in, 15–17; Ngogo group of, 304; pair-bonding in, 304–5; performance of in artificial fruit experiment, 108–9; social learning in, 14–15; strength of versus humans, 69–70 Chinese astrology, 277 Chinookan-speakers, ethnic markers of, 202–3 Chudek, Maciej, 43 Chytilová, Julie, 208–9 ciguatera toxin, 100–101 climatic variation, social learning and, 368–69n.1 cognitive abilities: of apes versus humans, 13–17; versus collective brains, 11–12; cultural evolution of, 6–7, 316; mentalizing and, 50–52 cognitive tools, 229–30 Cohen, Dov, 271 collective brains, 5–6; group size and interconnectedness in, 213–15; human intelligence and, 6–7, 11–12, 320–23; Internet in, 326; learnability and, 214–15; power of, 212; process of, 212–13; tools and norms in, 228–40 color terms, inventory of, 240–43, 364n.13, 364n.14 Comanches, 356n.30 communication: genetic evolutionary selection pressures for, 250–53; social interconnectedness and, 259 communication systems: adaptations of, 233–50; cooperation and, 256–58; cultural evolution of, 365n.31; development of, 231–33, 250–56, 259; skills and norms in, 250–56 communicative economy, 364–65n.24 community influence, 347n.10 competence cues, 37, 38, 41, 42, 65; age and, 46–48, 338n.22; in cultural learning, 233 complex adaptations, 60, 99–100, 113–14 complex sequences, brains for learning, 254–56 complex societies, war in cultural evolution of, 356n.33 compositionality, 365n.31 Concorde fallacy, 20 conditioning, 273–74, 276 conformist transmission, 48–49, 338n.24 conjunctions, subordinating, 247–48 Cook, Captain James, 139, 222 cooking, in digestive system evolution, 66–69 cooperation: creating, 130–31; evolutionary theories of, 142–43; group norms promoting, 167–68; in human cultural evolution, 319–20; in hunter-gatherer societies, 155–64, 353n.37; intergroup competition and, 356–57n.34, 360n.38; reciprocity-based, 371n.22; social norms and, 143–45, 153–54 cooperative dilemma, 193–95; language evolution and, 255–58 cooperative hunting, 156–59 cooperative instincts, 10–11 copying, 20; loss of skills with, 219–20; of models, 189–90; of prestigious individuals, 123–25; seemingly irrelevant steps, 108–10; of selected models, 120, 125–26.

Engineering Security
by Peter Gutmann

On the Internet the bystander effect is particularly pernicious. Recall that the effect increases with the number of bystanders present. In the Genovese murder the presence of a relatively small group people was enough to trigger the bystander effect. On the Internet, the entire world is potentially a bystander. This is the worst possible situation into which you can deploy a mechanism that can fall prey to the bystander effect, and although phishers probably aren’t psychology graduates they do know how to take advantage of this. (If you’re ever caught in a situation where the bystander effect is causing problems then you can counteract the diffusion of responsibility by singling out an individual and making it their direct responsibility.

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For example when phishers spammed (possible) customers of the Mountain America credit union in Salt Lake City they were able to display the first five digits of the card as “proof” of legitimacy because all cards issued by the bank have the same prefix (in addition they used a legitimate CA-issued certificate to authenticate their phishing site) [641].  Providing an independent verification channel for information such as a phone number to call. This exploits the “not-my-problem” fallacy (more formally the bystander effect, see below), no-one actually calls the number since they assume that someone else will. As a one study put it, “subjects stated that they would not call the number to verify the authenticity, but someone else would” [621]27. In addition phishers have already set up their own interactive voice response (IVR) systems using VoIP technology that mimic those of target banks, so having a phone number to call is no guarantee of authenticity [642][643][644]

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As with the phone verification channel for web pages and auditing of OSS security software, people who heard her cries for help during separate attacks spread over about thirty minutes assumed that someone else had called the police and so didn’t call themselves (although some of the details, and in particular the number and apparent apathy of some of the bystanders, was exaggerated by journalists). This event was later investigated in depth by psychologists, who termed the phenomenon the “bystander effect”. They found that the more bystanders there are, the less likely it is that any one of them will come to a victim’s aid because the assumption is that someone else must have already done so [652]. This effect, which arises due to diffusion of responsibility, is so noticeable that it’s been quantified by experimental psychologists.

Behave: The Biology of Humans at Our Best and Worst
by Robert M. Sapolsky
Published 1 May 2017

Consider a famous study of Asian American women who took a math test.35 Everyone knows that women are worse at math than men (we’ll see in chapter 9 how that’s not really so) and Asian Americans are better at it than other Americans. Subjects primed beforehand to think about their racial identity performed better than did those primed to think about their gender. Another realm of rapid group influences on behavior is usually known incorrectly. This is the “bystander effect” (aka the “Genovese syndrome”).36 This refers to the notorious 1964 case of Kitty Genovese, the New Yorker who was raped and stabbed to death over the course of an hour outside an apartment building, while thirty-eight people heard her shrieks for help and didn’t bother calling the police. Despite that being reported by the New York Times, and the collective indifference becoming emblematic of all that’s wrong with people, the facts differed: the number was less than thirty-eight, no one witnessed the entire event, apartment windows were closed on that winter’s night, and most assumed they were hearing the muffled sounds of a lover’s quarrel.* The mythic elements of the Genovese case prompt the quasi myth that in an emergency requiring brave intervention, the more people present, the less likely anyone is to help—“There’s lots of people here; someone else will step forward.”

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Despite that being reported by the New York Times, and the collective indifference becoming emblematic of all that’s wrong with people, the facts differed: the number was less than thirty-eight, no one witnessed the entire event, apartment windows were closed on that winter’s night, and most assumed they were hearing the muffled sounds of a lover’s quarrel.* The mythic elements of the Genovese case prompt the quasi myth that in an emergency requiring brave intervention, the more people present, the less likely anyone is to help—“There’s lots of people here; someone else will step forward.” The bystander effect does occur in nondangerous situations, where the price of stepping forward is inconvenience. However, in dangerous situations, the more people present, the more likely individuals are to step forward. Why? Perhaps elements of reputation, where a larger crowd equals more witnesses to one’s heroics.

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Levine et al., “Identity and Emergency Intervention: How Social Group Membership and Inclusiveness of Group Boundaries Shape Helping Behavior,” PSPB 31 (2005): 443; R. Enos, “Causal Effect of Intergroup Contact on Exclusionary Attitudes,” PNAS 111 (2014): 3699. 35. M. Shih et al., “Stereotype Susceptibility: Identity Salience and Shifts in Quantitative Performance,” Psych Sci 10 (1999): 80. 36. P. Fischer et al., “The Bystander-Effect: A Meta-analytic Review on Bystander Intervention in Dangerous and Non-dangerous Emergencies,” Psych Bull 137 (2011): 517. 37. B. Pawlowski et al., “Sex Differences in Everyday Risk-Taking Behavior in Humans,” Evolutionary Psych 6 (2008): 29; B. Knutson et al., “Nucleus Accumbens Activation Mediates the Influence of Reward Cues on Financial Risk Taking,” Neuroreport 26 (2008): 509; V.

And Finally
by Henry Marsh

This process generates those notorious ‘free radicals’ beloved of quack medical treatments, in particular hydroxyl ions. These are pairs of single hydrogen and oxygen atoms, with a negative charge. They react with many other atoms and molecules, causing extensive damage to both cancerous and healthy cells. Recent research has shown that there are also ‘bystander’ effects, where cells outside the main radiation field also show changes. As with so much of science, the more you look, the more you find, and the more complicated it gets. From a practical point of view, what all this means for me is that if my tumour dies, it will take months. The malignant cells with damaged DNA will – I hope!

Life You Can Save: Acting Now to End World Poverty
by Peter Singer
Published 3 Mar 2009

When another person who appeared to be a student completing the survey—but was in fact a stooge—was also present, and that person did not respond to the calls for help, only 7 percent offered to help. Even when two genuine students were together in the room, the proportion offering to help was much lower than when there was only one student. The diffusion of responsibility had a marked inhibiting effect—the “bystander effect.” Other experiments have yielded similar results.20 The Sense of Fairness Nobody likes being the only one cleaning up while everyone else stands around. In the same way our willingness to help the poor can be reduced if we think that we would be doing more than our fair share. The person considering giving a substantial portion of his or her disposable income can’t help but be aware that others, including those with a lot more disposable income, are not.

The Joys of Compounding: The Passionate Pursuit of Lifelong Learning, Revised and Updated
by Gautam Baid
Published 1 Jun 2020

Compared with larger companies, the accounts are simpler, the management is more accessible, and the business segments are few. The market often misprices small-cap companies, as they are relatively illiquid and often ignored by the bigger participants. When it comes to blue-chip stocks, many investors have a common bias that reminds me of the “bystander effect” seen in the Kitty Genovese murder. (No one who witnessed the crime called the police because they all thought someone else would.) Many investors avoid looking at the widely followed large-cap stocks because they assume that everyone else does. These investors assume that such stocks must be fully priced and that they lack the possibility of having an edge.

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Market, 229; Munger and, 4–6, 167, 289; on opportunity cost, 302; on owner earnings, 162; on passion, 36; on pattern recognition, 307; philanthropy of, 64; on portfolio concentration, 245, 365; on reading, 2, 19, 359; on reported earnings, 162–163; on reputations, 266; on restricted earnings, 165; on risk, 58, 262–263; on role models, 45; on savings accounts, 214; on sector tailwind, 315; on shareholders, 229; on simplicity, 72; on staying power, 266; on stocks, 121; on success, 209, 327; on time, 216; on turnarounds, 294; on wealth, 258–259, 363; on Wells Fargo, 317–318 Buffett indicator, 218 Buffett Partnership Ltd., 88–95 bull markets, 61, 173–174; end of, 237; Marks on, 233; Neill on, 250; stages of, 233; Templeton on, 233 Bullock, Sandra, 322 Burger, Edward B., 31 Business Adventures (Brooks), 264 business models: Buffett on, 219; earnings in, 211; evaluation of, 211; gruesome, 213; intrinsic value in, 216; longevity of growth in, 212; Munger on, 214–215; switching costs in, 211 business ownership: exiting in, 120–121; flexibility and, 120–121; managers in, 119; partial, 118; rare opportunities in, 120; terms of, 119–120 business-to-business (B2B), 213 business-to-consumer (B2C), 213 buybacks, share, 226 bystander effect, 230 Cadila Healthcare, 197–198 CAGR. See compound annual growth rate Calcutta Electric Supply Corporation (CESC), 311 calmness, 353 candor, 125–127 CAP. See competitive advantage period CAPE ratio, 236 capital allocation, 170, 302; ROIC and, 226–227 Capital Cities Communications, 117 capital cycle: illustrating, 194; red flags, 182–184 capital discipline, 124 capital expenditure, 131, 164 capitalism, 278, 316; brutality of, 222; correcting forces of, 250; Greenblatt on, 202 Capital Returns (Chancellor), 182, 189, 369 capital stewardship, 124–125 Capital Trust, 340 capital work in progress, 132 cap-to-sales ratio, 191 Carlson, Ben, 73; on diversification, 243 Carnegie, Andrew, 64–65, 286 Caro, Robert, 12 Carr, Nicholas, 14 cash, 254; value of, 299 cash balances, 131 cash flow, 124, 177–178; analysis, 131; discounted, 290; free, 131 cash flow from operating activity (CFO), 131 Cassel, Ian, 371, 372 categorical imperative, 93–94 CBOE VIX, 264 Central Intelligence Agency, 293–294 CEOs, 123, 126 certainty: in bear markets, 212–213; stocks and, 212; uncertainty and, 54–55 CESC.

Explaining Humans: What Science Can Teach Us About Life, Love and Relationships
by Camilla Pang
Published 12 Mar 2020

The same is true in our bodies, where cancer cells rely on their mutational outliers to accelerate progress: it’s the side branches – subclones – that make cancer so hard to treat, because they allow it to adapt to different scenarios and respond dynamically to attacks. Cancer’s diversity of structure is what gives it options – and the same is ultimately true of humanity. We rely on the outliers to evolve and avoid the stasis of the bystander effect, where everyone simply copies each other and no one goes to help the person in need. Ergodicity is something that has been hugely important to me. As someone who grew up feeling like an island, it took me a long time to even glimpse the other coastlines, let alone build bridges to them. I have had to model the dynamics of the crowds in my life from the ground up – blind to the social nuances and ‘isms’ that instinctively inform most people’s chosen paths.

Working in Public: The Making and Maintenance of Open Source Software
by Nadia Eghbal
Published 3 Aug 2020

Older projects with messy codebases can, strangely, engender a small but very dedicated group of contributors. The same goes for tooling: I’ve heard more than one Go developer confess they like that Go uses Gerrit instead of GitHub because this cuts down on the noise. On the other end, projects with widespread user adoption can create a sort of bystander effect: nobody contributes because they assume someone else is probably doing it. How these factors affect contributor growth depends on the project in question, but it’s important to acknowledge that they do affect projects in some way. Focusing on the relationship between contributors and users, we can think of projects in terms of their contributor growth and user growth.

Transport for Humans: Are We Nearly There Yet?
by Pete Dyson and Rory Sutherland
Published 15 Jan 2021

Contributing effects Combine to produce Resulting in Presenteeism Pressure and desire to conform Mission creep Need to keep a job Defensive decision making Repeated errors Marginalization Narrow solutions Optimism bias Homogeneous management teams Narrow range of problem-solving methods Bystander effects Blame culture Groupthink Organizations are not monolithic Organizations are a hotchpotch of teams, departments, specialists and operations governed by competing targets and metrics that are always proxies for their real goals. Total simplicity and stability are an illusion; complexity and change are inevitable for organizations.

The Twittering Machine
by Richard Seymour
Published 20 Aug 2019

And it wasn’t just one, two or three people. There were dozens of people following us. I was in an excited state.’ This claim is astonishing on its own terms, but the mere existence of these ‘likes’ is also arresting. Most viewers presumably had no reason to expect to see a rape, let alone egg it on. The ‘bystander effect’ is notoriously worse in the case of witnessed sexual assault than for other crimes, but these were no bystanders. The ‘like’ button seems to have facilitated a form of detached involvement in spectacular cruelty. And it’s plausible that the feedback made a difference. By her own account, for Lonina the approval of a watching public was decisive: she was abruptly making a hit, a box-office success, and it was thrilling enough to override any concern she could have had for her friend.

The Uninhabitable Earth: Life After Warming
by David Wallace-Wells
Published 19 Feb 2019

In the case of climate, this has meant trusting that economic systems unencumbered by regulation or restriction would solve the problem of global warming as naturally, as surely as they had solved the problems of pollution, inequality, justice, and conflict. These biases are drawn only from the A volume of the literature—and are just a sampling of that volume. Among the most destructive effects that appear later in the behavioral economics library are these: the bystander effect, or our tendency to wait for others to act rather than acting ourselves; confirmation bias, by which we seek evidence for what we already understand to be true, such as the promise that human life will endure, rather than endure the cognitive pain of reconceptualizing our world; the default effect, or tendency to choose the present option over alternatives, which is related to the status quo bias, or preference for things as they are, however bad that is, and to the endowment effect, or instinct to demand more to give up something we have than we actually value it (or had paid to acquire or establish it).

Risk: A User's Guide
by Stanley McChrystal and Anna Butrico
Published 4 Oct 2021

While firms did name CROs and gave them important responsibilities, they failed to account for a psychological concept known as moral licensing. To put it simply, if you were a trader or an executive at a firm with a CRO and a risk management structure, you could assume that someone else was responsible for monitoring risk and so you didn’t need to worry about it individually. It’s similar to the bystander effect: when someone, for example, falls ill and a first responder asks a group of bystanders to dial 9-1-1, nobody calls—assuming someone else has. What this meant in practice at banks was that if a risky investment was under evaluation, traders could assume that an authority figure charged with risk management would intervene if the proposal put the firm at risk.

The Equality Machine: Harnessing Digital Technology for a Brighter, More Inclusive Future
by Orly Lobel
Published 17 Oct 2022

Bazarova, “Upstanding by Design: Bystander Intervention in Cyberbullying,” in CHI ’18: Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems (New York: Association for Computing Machinery, 2018), 1. 16. Marco van Bommel, Jan-Willem van Prooijen, Henk Elffers, and Paul A. M. Van Lange, “Be Aware to Care: Public Self-Awareness Leads to a Reversal of the Bystander Effect,” Journal of Experimental Social Psychology 48, no. 4 (July 2012): 926. 17. Lara Maister, Mel Slater, Maria v. Sanchez-Vives, and Manos Tsakiris, “Changing Bodies Changes Minds: Owning Another Body Affects Social Cognition,” Trends in Cognitive Sciences 19, no. 1 (January 2015): 6. 18. Anne C.

Emotional Ignorance: Lost and Found in the Science of Emotion
by Dean Burnett
Published 10 Jan 2023

absence of emotions: DB’s imagined scenario 1, 2, 3; negative consequences of 1; in science fiction 1, 2, 3, 4 acting work: actor/character relationship 1; emotional labour 1 action representation network (brain) 1 adolescence and early adulthood: brain development 1; crushes 1, 2; intense emotions 1; nightmare frequency 1, 2; safe exposure to negative emotions 1, 2; social media use 1 see also infancy and childhood affect: definition and components 1; versus basic emotions 1 airport security, facial recognition technology 1 altruism 1, 2 amygdala (brain region): and dreaming 1; and emotional regulation 1, 2; and emotions processing 1, 2, 3, 4, 5, 6, 7, 8, 9; gender differences 1; influence of testosterone 1; and memory formation 1; as part of olfactory system 1 AND model of nightmare production 1 anger: as ‘basic’ emotion 1, 2; and colour red 1, 2; DB’s anger during grief 1, 2, 3; facial expression of 1, 2; as ‘masculine’ 1(fn); and motivation 1, 2 see also negative emotions angular gyrus (brain region) 1, 2 anosmia (inability to smell) 1 anterior cingulate cortex (brain region) 1, 2, 3, 4 anterior olfactory nucleus (brain region) 1 anxiety: caused by work 1; performance anxiety 1; social anxiety 1, 2, 3; and status 1; vagus nerve stimulation treatment 1 see also negative emotions; stress apatheia (ultimate goal of Stoicism) 1 appraisal theory 1, 2 approach-attachment behaviour 1 approach versus avoid motivation 1, 2 arguments with romantic partner 1 arousal (component of affect) 1, 2, 3 asexuality 1 @AstroKatie (Katherine Mack) 1 attachment during early childhood 1, 2 see also parent emotional bond attention restoration, and colour green 1 auditory cortex (brain region) 1, 2(fn) auditory processing 1, 2, 3, 4, 5(fn) autism 1, 2 automated voices and announcements, annoyance caused by 1 avatar therapy 1 avoid versus approach motivation 1, 2 babies in the womb, playing music to 1, 2 baby-parent emotional bond 1, 2, 3 see also attachment during early childhood Bain, Alexander 1 Baron-Cohen, Simon 1 Barrett, Lisa Feldman 1, 2 basal ganglia (brain region) 1 basic emotions theory 1, 2, 3, 4 BDSM (sexual practice) 1, 2 belief perseverance 1 Bell, Charles 1, 2 bias: confirmation bias 1, 2, 3; fading affect bias 1, 2, 3; ingroup versus outgroup bias 1; negativity bias 1, 2 Blackmore, Chris 1, 2, 3 blinking, by cartoon characters 1 blood sugar, effect on emotions 1 blue colour, associations and effects 1, 2, 3 body, emotions experienced in see physiology-emotion connection body language: communicating emotion 1, 2, 3, 4; mimicry 1; missing from communication technologies 1 brain: body’s influence on 1; competing resource demands 1, 2, 3; development 1; distinguishing what is real/not real 1, 2; emotions as conscious or subconscious processes 1; gender differences (beliefs and experimental studies) 1; influence of oestrogen and testosterone 1; left brain/right brain facts and myths 1, 2, 3(fn), 4(fn); lobotomies 1; mirror neurons 1, 2, 3, 4; nervous and endocrine system regulation 1; neurotransmitters 1, 2, 3, 4, 5, 6; reward pathway and system 1, 2, 3, 4; somatic marker hypothesis 1; spindle cells 1; synapses 1, 2; triune model 1, 2 see also cognition (thinking); learning (of information); memory(ies) brain, functional regions: action representation 1; auditory processing 1, 2, 3, 4, 5(fn); cognition 1, 2, 3, 4; disgust 1; emotional regulation 1, 2; emotions (overview) 1, 2, 3; fear 1; imagination 1; intention processing 1; language processing 1; love 1, 2; lust 1, 2; memories 1, 2, 3, 4, 5; motivation 1, 2; olfactory processing 1, 2; visual processing 1, 2, 3 see also specific brain regions brain scans, limitations for studying emotions 1 brainstem 1, 2, 3, 4, 5 breastfeeding 1, 2 Broca’s area (brain) 1 Brown, Thomas 1, 2 Buddhism 1 bullying online 1 burnout 1, 2 Bushman, B.J. 1 bystander effect 1 cancer awareness, role of news and media 1 canned laughter, annoyance caused by 1, 2 categories and types of emotion: basic emotions (theory) 1, 2, 3, 4; identified by James McCosh 1 see also identifying and defining ‘emotions’ cats and other pets, emotional attachment to 1 caudate nucleus (brain region) 1 celebrity endorsements 1, 2, 3, 4 cerebellum (brain region) 1, 2, 3 childbirth, role of oxytocin 1 childhood see infancy and childhood chilli, enjoyment of pain caused by 1 cigarette smoke, DB’s memories and associations 1, 2 cognition-emotion relationship see emotion-cognition relationship cognition (thinking): brain regions associated with 1, 2, 3, 4; effect of love on 1; executive control 1, 2, 3; ‘flow’ state 1; and intrusive thoughts 1; and motivation 1, 2, 3, 4, 5; and social relationships 1, 2 see also learning (of information) cognitive dissonance 1 colours: cultural associations 1; in DB’s friend’s home 1, 2; emotional response to 1; and visual processing 1, 2, 3 communicating and sharing emotions: machine detection of emotions 1, 2; nonverbal information 1, 2, 3; online versus in-person 1, 2; at work 1, 2, 3, 4, 5 see also emotional contagion; empathy; facial expressions and emotions communication technologies see phone calls; social media and online communication; therapeutic applications of technologies; video calls confirmation bias 1, 2, 3 conformity 1, 2, 3, 4 consciousness, evolution of 1 consolidation of memories 1, 2, 3, 4 conspiracy theories 1, 2, 3, 4, 5 see also deception; misinformation and ‘fake news’ constructed emotions theory 1, 2 corpus callosum (brain region) 1 cortex/neocortex (brain region) (in general) 1 see also specific regions of the cortex cortisol 1 cross-race effect 1 crushes, in adolescence 1, 2 crying: DB’s (in)ability to cry 1, 2, 3, 4, 5, 6; gender differences 1; induced by TV and films 1; types and functions of tears 1 cuteness and cute aggression 1 cyberbullying 1 dancing 1 Darwin, Charles 1, 2 deception: automated voices and announcements 1; response to 1, 2; self-deception 1 see also manipulation of emotions; misinformation and ‘fake news’ defining ‘emotions’ 1, 2, 3, 4 deindividuation and ‘mob mentality’ 1 depression: caused by work 1, 2; gender differences 1; and gut microbiome 1; and memory 1; post-natal depression 1, 2; vagus nerve stimulation treatment 1 Diana, Princess of Wales, impact of death 1 digestive system, influence of 1, 2 disgust: as ‘basic’ emotion 1, 2; brain region associated with 1; and colour green 1; facial expression of 1, 2; and horror 1; and memory 1; and suppressed motivation 1 see also negative emotions doctors, emotional aspects of work 1 dopamine 1 drama therapy 1 dreams and nightmares: AND model 1; bizarre nature of 1, 2; DB’s bad dreams 1, 2, 3; due to COVID-19 pandemic 1, 2; and emotion processing 1; Freud’s interpretations 1; and memory consolidation 1; and mental health 1; post-traumatic 1; prevalence of nightmares 1; recurring 1; threat simulation theory 1 Dunbar’s number (of social relationships) 1 dysgranular field (brain region) 1 dysphoria 1 see also depression e-learning, motivation in 1 earworms 1 Ekman, Paul 1, 2, 3, 4 Eleri, Carys 1 embarrassment 1, 2, 3, 4, 5, 6, 7 see also negative emotions emojis and emoticons 1 emotion-cognition relationship: appraisal theory 1, 2; in attention and focus 1, 2, 3, 4; belief perseverance 1; cognitive dissonance 1; competition for brain’s resources 1, 2; confirmation bias 1, 2, 3; distinction recognised by Stoics 1; in effect of emotions experienced 1; in empathy 1; in ‘flow’ state 1; interrelatedness (in general) 1, 2, 3, 4; in learning and information processing 1, 2, 3; in love 1; motivated reasoning 1; in motivation 1, 2, 3; negativity bias 1, 2; role of imagination 1; shared evolutionary origin 1; in stage fright 1 emotion-memory relationship: appraisal theory 1, 2; emotions triggered by memories 1, 2, 3, 4; fading affect bias 1, 2, 3; happy memories being more detailed 1; for implicit memories 1; later emotions changing memories 1, 2, 3; longevity and potency of emotional memories 1, 2, 3, 4, 5, 6; in memory consolidation 1, 2; in PTSD 1, 2, 3, 4, 5; role of nightmares 1; suppressing emotional memories 1 emotional contagion: dangers of ‘mob mentality’ 1; versus empathy 1; evolutionary importance 1; from groups of people 1, 2, 3; from music 1, 2, 3; neurological mechanism for 1; from social media 1 emotional detachment/suppression at work 1, 2, 3, 4 emotional manipulation see manipulation of emotions emotional processing 1, 2 emotional regulation, brain regions responsible for 1, 2 emotional relationships: attachment during early childhood 1, 2; friendships 1, 2; one-sided see parasocial (one-sided) relationships; parent-baby emotional bond 1, 2, 3; role of neurotransmitters 1, 2; romantic see romantic relationships; see also social relationships emotions: causing change 1; as conscious/subconscious processes 1; historical study of 1; identifying and defining 1, 2, 3, 4; language of 1, 2 see also categories and types of emotion; communicating and sharing emotions; emotion relationship; emotion relationship; negative emotions; physiology connection; positive emotions; specific emotions empathy: and autism 1, 2; in babies 1; and body language mimicry 1; versus emotional contagion 1; evolutionary importance 1, 2, 3; influence of own emotions on 1; as ingrained 1, 2; ingroup versus outgroup bias 1; versus mentalising (theory of mind) 1; neurological mechanism for 1, 2, 3, 4; and physical pain 1; in romantic relationships 1; as selfish/unselfish 1 endocannabinoids 1 endocrine system 1 endorphins 1, 2 envy 1, 2 see also negative emotions episodic memories 1, 2, 3 evaluative conditioning 1 excitation transfer theory 1 executive control 1, 2, 3 see also cognition (thinking) existential dread, as a motivator 1 explicit memories 1 extrinsic versus intrinsic motivation 1 Facebook: DB’s use of 1, 2; research into emotional manipulation 1, 2, 3 see also social media and online communication faces, seeing in inanimate objects 1 facial colour changes 1 facial expressions and emotions: in artificial/CGI faces (uncanny valley) 1; automated emotion recognition 1; in cartoon characters (blinking) 1; cross-cultural similarities and differences 1, 2; difficulties distinguishing between emotions without context 1, 2, 3; early writings on 1; Ekman’s work 1, 2, 3, 4; ‘invisible’ emotions 1; involuntary nature of expressions 1, 2, 3, 4; online curation of emotions portrayed 1 facial paralysis, and empathy 1 facial recognition, cross-race effect 1 facial recognition technology 1 fading affect bias 1, 2, 3 ‘fake news’ see misinformation and ‘fake news’ fandom 1, 2 see also parasocial (one relationships fear: as ‘basic’ emotion 1, 2; brain region associated with 1; enjoyment of 1, 2; facial expression and colour 1, 2; as first emotion 1; of flying 1; and horror 1; and imagination 1; and motivation 1, 2, 3; in PTSD 1; smell of (in sweat) 1 see also negative emotions films and TV causing negative emotions 1, 2, 3, 4 Firth-Godbehere, Richard 1, 2, 3, 4, 5 flat Earth conspiracy theory 1, 2 ‘flow’ state 1 flying, fear of 1 football shirts, red colour’s competitive advantage 1 Freud, Sigmund 1, 2 friendships 1, 2 see also emotional relationships; social relationships frosty atmospheres, emotional contagion 1, 2 funerals: crying at 1; of DB’s father 1, 2, 3, 4, 5; emotional contagion at 1, 2; live streaming 1, 2 gender differences: adolescent crushes 1(fn); attitudes towards infidelity 1; in brains (beliefs and experimental studies) 1; in brains (DB’s impossible experiment) 1; in emotional regulation and expression 1, 2, 3, 4, 5, 6; ‘maternal instinct’ 1; mental health problems 1; other physiological differences 1; societal influences 1 gender discrimination 1, 2, 3 goal distraction 1 green colour, associations and effects 1, 2, 3 grief: DB’s acceptance of emotions 1; DB’s anger 1, 2, 3; DB’s attempts to disguise grief 1; DB’s emotional confusion 1, 2, 3; DB’s (in)ability to cry 1, 2, 3, 4, 5, 6; DB’s motivation and productivity 1, 2; DB’s need to talk after funeral 1; at death of Princess Diana 1; emotional processing 1, 2; shared grieving 1; stages of 1 see also negative emotions guilt 1 see also negative emotions habituation 1, 2 ‘hangry’ behaviour 1 happiness 1 hippocampus (brain region): and dreaming 1; and emotional regulation 1; and emotions processing 1, 2, 3; and imagination 1; and memory 1, 2, 3, 4, 5; and navigation 1 Holmes and Rahe stress scale 1, 2 Holmes, Sherlock (analogy for action representation) 1 hormones: cortisol 1; digestive 1, 2; effect of tears on 1; influence on the brain (and emotions) 1; oestrogen 1, 2; oxytocin 1, 2, 3, 4, 5, 6; testosterone 1, 2, 3; vasopressin 1, 2, 3 see also endocrine system horror (emotion) 1 horror movies 1, 2, 3 hypothalamus (brain region) 1, 2, 3 hysteria 1 Icke, David 1 identification, in parasocial relationships 1 identifying and defining ‘emotions’ 1, 2, 3, 4 imaginary friends 1 imagination and mental imagery 1, 2 imitation of observed actions 1 implicit memories 1 impression management 1, 2, 3, 4, 5 infancy and childhood: attachment with primary caregiver 1, 2; breastfeeding 1, 2; DB’s memories of 1, 2; emotional experiences 1; empathy in babies 1; imaginary friends 1; importance of sense of smell 1; learning from media characters 1; nightmare frequency 1, 2; oxytocin in newborns 1; parent-baby emotional bond 1, 2, 3 see also adolescence and early adulthood inferior frontal cortex (brain region) 1, 2 inferior parietal cortex (brain region) 1 infidelity, emotional versus sexual 1 insular cortex (insula) (brain region) 1, 2, 3, 4 intelligence, and brain anatomy 1 intention processing 1 intrinsic versus extrinsic motivation 1 intrusive thoughts 1 Izard, Carroll E. 1 jealousy 1 Kübler-Ross, Elizabeth 1 language of emotions 1, 2 language processing 1 learning (of information): from media characters 1; motivation 1, 2; from other people 1, 2; processing demands and information prioritisation 1, 2; from senses 1 LeDoux, Joseph 1 left brain/right brain facts and myths 1, 2, 3(fn), 4(fn) limbic system (brain region) 1, 2, 3, 4 lobotomies 1 Lomas, Tim 1 London taxi drivers, brain study 1 losing oneself in a book/film 1 love: brain regions associated with 1, 2; demands on the brain 1; effect on cognition 1; for family and friends 1, 2(fn); role of dopamine 1; romantic love 1, 2, 3 see also romantic relationships lust and sexual attraction: asexuality 1; brain regions associated with 1, 2; and romantic relationships 1, 2; Stoics’ rejection of 1, 2; suppression of 1 Mack, Katherine (@AstroKatie) 1 mammal brain (region) 1, 2, 3, 4 manipulation of emotions: by authorities 1; for marketing 1, 2, 3, 4, 5; response to 1; by social media 1; by traditional news and media 1, 2, 3, 4 marketing 1, 2, 3, 4, 5 McCosh, James 1 medical work, emotional aspects 1 memory(ies): brain regions associated with 1, 2, 3, 4, 5; changeable nature of 1, 2, 3, 4, 5, 6, 7; connections with objects 1, 2, 3, 4; consolidation 1, 2, 3, 4; DB’s memories of early childhood 1, 2; DB’s memories of his father 1, 2, 3, 4, 5, 6; episodic memories 1, 2, 3; explicit memories 1; fading affect bias 1, 2, 3; forgetting memories 1; and imagination 1; implicit memories 1; and music 1; procedural memories 1; reminiscence bump 1; retroactive memory enhancement 1; semantic memories 1; and sleep 1; and smell(s) 1, 2, 3, 4; suppression of 1; as synapses 1, 2; working memory 1; Zeigarnik effect 1 see also emotion relationship mental health/illness: and social media 1; and status 1; therapeutic applications of technologies 1 see also anxiety; depression; PTSD; schizophrenia mental imagery and imagination 1, 2 mentalising (theory of mind) 1, 2 mirror neurons 1, 2, 3, 4 mirroring body language 1 misinformation and ‘fake news’: about COVID-19 pandemic 1, 2; David Icke’s space lizards 1; flat Earth theory 1, 2; and social media/internet 1, 2, 3, 4; susceptibility to 1 see also deception ‘mob mentality’ (deindividuation) 1 Moebius syndrome (facial paralysis) 1 monkey experiments, mirror neurons 1 Morgan, Matt 1 motivated reasoning 1 motivation: approach-attachment behaviour 1; approach versus avoid motivation 1, 2; brain regions associated with 1, 2; and cognition 1, 2, 3, 4, 5; DB’s experiences during grief 1, 2; and emotions 1, 2, 3, 4, 5, 6; intrinsic versus extrinsic motivation 1; and novelty 1, 2, 3, 4 motivational salience 1 music: dancing 1; DB’s emotional response to 1, 2, 3, 4; differentiating between voice and instruments 1; earworms 1; emotional contagion from 1, 2, 3; emotional response to 1, 2; evolutionary significance 1, 2; and memory 1 musical expectancy 1, 2 navigation, role of hippocampus 1 negative emotions: and attention/focus 1, 2, 3, 4, 5; and creativity 1; emotion processing 1, 2; feeling good whilst experiencing 1, 2, 3; induced by TV and films 1, 2, 3, 4; and intrusive thoughts 1; and memory 1, 2, 3; as more impactful than positive emotions 1; negativity bias 1, 2; and novelty 1; and performance 1 see also specific emotions negativity bias 1, 2 nervous systems: enteric (‘second brain’) 1; parasympathetic 1, 2, 3; regulation by brain 1; somatic and autonomic 1; sympathetic 1, 2, 3 neurotransmitters 1, 2, 3, 4, 5, 6 news and media (traditional): credibility 1, 2, 3, 4; emotional content 1, 2, 3, 4; precursors to 1 see also conspiracy theories; misinformation and ‘fake news’; social media and online communication nightmares see dreams and nightmares noises, emotional response to 1, 2, 3 see also music novelty 1, 2, 3, 4, 5 objects, and memories 1, 2, 3, 4 oestrogen 1, 2 olfactory bulb and cortex (brain region) 1, 2, 3 olfactory system 1, 2, 3, 4 one-sided relationships see parasocial (one-sided) relationships online communication see social media and online communication online learning, motivation in 1 orbitofrontal cortex (brain region) 1, 2 oxytocin 1, 2, 3, 4, 5, 6 pain (physical): and empathy 1; enjoyment of 1, 2 paracingulate sulcus (brain region) 1 parasocial (one-sided) relationships: adolescent crushes 1, 2; benefits 1, 2; ending the relationship 1; with fictional characters 1, 2, 3, 4; identification with the object 1; with imaginary friends 1; losing oneself in a narrative 1; meeting the object 1; negative aspects 1; neurological mechanisms 1; with people you haven’t met 1, 2, 3, 4, 5 parasympathetic nervous system 1, 2, 3 Parch (TV drama), actor’s experiences 1 pareidolia 1 parent-baby emotional bond 1, 2, 3 see also attachment during early childhood ‘passions’ 1, 2, 3 pathos 1 performance anxiety (stage fright) 1 personality, influence of early experiences 1, 2 phone calls: DB’s last call to father 1; lack of nonverbal emotional cues 1; walking around during 1 physiology-emotion connection: body influencing emotion 1; emotion influencing the body 1; somatic marker hypothesis 1 see also crying Pickle (DB’s cat) 1 Pixar movies 1, 2(fn), 3 positive emotions: and attention/focus 1, 2; and memory 1, 2 see also specific emotions ‘Positive Lexicography’ project 1 post-natal depression 1, 2 posterior parietal cortex (brain region) 1, 2 prefrontal cortex (brain region): cognitive functions 1, 2, 3; and emotional regulation 1, 2; and emotions processing 1, 2; and imagination 1; influence of testosterone 1; and memory 1; and mentalising (theory of mind) 1; and motivation 1, 2 pride 1 procedural memories 1 processing (negative) emotions 1, 2 Proust, Marcel, In Search of Lost Time 1 psycho-emotional tears 1, 2 PTSD (post-traumatic stress disorder) 1, 2, 3, 4, 5 racism: cross-race effect 1; and oxytocin 1 rage see anger red colour, associations and effects 1, 2, 3 relationships see emotional relationships religious perspectives on emotions 1 reminiscence bump 1 reptile brain (region) 1 ‘resting bitch face’ 1 retroactive memory enhancement 1 reward, and motivation 1 reward pathways of brain 1, 2, 3, 4 Ridley, Rosalind 1 Rippon, Gina 1, 2, 3 romantic relationships: adolescent crushes as preparation for 1; attitudes towards infidelity 1; disagreements and disputes 1; emotional connection between partners 1, 2; empathy versus problem ‘fixing’ in 1; long-term relationships 1, 2; love in 1, 2, 3; negative emotions in 1; online versus in-person 1; and own identity 1, 2; physical attraction in 1, 2; role of oxytocin 1; stress associated with losing partner 1, 2; trumpeting on social media 1 see also emotional relationships sadness: as ‘basic’ emotion 1; and colour blue 1, 2; enjoyment of 1, 2, 3; facial expression of 1 schadenfreude 1, 2 schizophrenia 1 scientific method 1, 2 scientists: motivations 1, 2, 3; popular portrayal as lacking emotion 1 self-deception 1 semantic memories 1 Sesame Street (TV) show, learning from 1 sex differences see gender differences sexism see gender discrimination sexual activity, BDSM 1, 2 sexual attraction see lust and sexual attraction sharing emotions see communicating and sharing emotions Simpsons, The (TV show), blinking in 1(fn) Singer, Tania 1 sleep 1, 2, 3 see also dreams and nightmares smell(s): anosmia (inability to smell) 1; DB’s memories of cigarette smoke 1, 2; and emotions 1, 2; evolutionary importance 1, 2, 3; and memory 1, 2, 3, 4; olfactory system 1, 2, 3, 4 social anxiety 1, 2, 3 social media and online communication: adolescents 1; adults/older people 1; emojis and emoticons 1; and emotional contagion 1; impression management 1, 2, 3, 4, 5; lack of nonverbal emotional cues 1, 2; live streaming funerals 1, 2; machine detection of emotions 1; negative aspects 1, 2, 3, 4, 5; online versus in-person emotions and personae 1; positive aspects 1, 2; versus real-world interactions, cognitive demands 1; and reward 1, 2, 3; and self-deception 1; and self-validation 1, 2, 3; and status 1, 2 see also conspiracy theories; Facebook; misinformation and ‘fake news’; news and media (traditional); video calls social relationships: cognitive load associated with 1, 2; Dunbar’s number 1; friendships 1, 2; one-sided see parasocial (one-sided) relationships; see also emotional relationships somatic marker hypothesis 1 spicy food, enjoyment of pain caused by 1 spindle cells 1 Spiner, Brent 1 sports kit, competitive advantage of wearing red 1 SPOT (Screening of Passengers by Observation Techniques) programme 1 stage fright 1 stalkers 1 Star Trek: The Next Generation (TV series): Data actor’s experience of fans 1; Data’s inability to choose ice-cream flavour 1 Star Trek (TV series): Stoicism of Vulcans 1, 2; universal use of English language 1 Starbucks (branding) 1 status: and emotions 1; and social media 1, 2; subjective status and mental health 1 Stoics and Stoicism 1, 2 stress: benefits of green environments for 1; caused by uncertainty 1; caused by work 1, 2; coping mechanisms 1; cortisol 1; Holmes and Rahe stress scale 1, 2; PTSD 1, 2, 3, 4, 5; and status 1; Yerkes-Dodson curve 1 see also anxiety; negative emotions striatum (brain region) 1 study of emotions (historical) 1 suicide 1, 2 superior temporal cortex (brain region) 1, 2, 3, 4 suppression of emotions: during disagreements with romantic partner 1; in learning and decision making (as impossible) 1; at work 1, 2, 3, 4 supramarginal gyrus (brain region) 1 surprise 1, 2 sympathetic nervous system 1, 2, 3 synapses (neuron connections) 1, 2 taxi drivers, brain study 1 tears, types and functions of 1 teenage years see adolescence and early adulthood temporal lobe (brain region) 1, 2 testosterone 1, 2, 3 thalamus (brain region) 1, 2, 3 theories of emotions see basic emotions theory; constructed emotions theory theory of mind (mentalising) 1, 2 thinking see cognition (thinking) threat simulation theory 1 transportation phenomenon 1 triune brain model 1, 2 TV and films causing negative emotions 1, 2, 3, 4 types of emotion see categories and types of emotion uncanny valley 1 uncertainty, unpleasant nature of 1 vagus nerve 1 valence (component of affect) 1, 2 vasopressin 1, 2, 3 video calls: DB’s call with friends after father’s funeral 1; lack of nonverbal emotional cues 1 virtual reality (VR) 1 visual cortex (brain region) 1, 2 visual processing 1, 2, 3, 4, 5, 6 see also colours voice characteristics, and communicating emotion 1 volcano/cupcake scenario (competing motivations) 1 wine tasting and appreciation 1 work and workplaces: communicating the wrong emotions at work 1; DB’s job embalming cadavers 1, 2, 3(fn); emotional aspects of medical work 1; emotional detachment/suppression 1, 2, 3, 4; emotional labour of acting work 1; mental health problems caused by 1, 2, 3, 4, 5, 6; performance appraisals 1, 2; wellbeing initiatives 1, 2 working memory 1 yawning, as contagious 1 Yerkes-Dodson curve 1 Zeigarnik effect (tendency to forget completed tasks) 1 ‘zone,’ state of being in 1 Zoom calls see video calls About the Author Dean Burnett is a neuroscientist, blogger, sometimes-comedian and author.

Rationality: What It Is, Why It Seems Scarce, Why It Matters
by Steven Pinker
Published 14 Oct 2021

Journal of Personality and Social Psychology, 78, 853–70. https://doi.org/10.1037/0022-3514.78.5.853. Thaler, R. H., & Sunstein, C. R. 2008. Nudge: Improving decisions about health, wealth, and happiness. New Haven, CT: Yale University Press. Thomas, K. A., De Freitas, J., DeScioli, P., & Pinker, S. 2016. Recursive mentalizing and common knowledge in the bystander effect. Journal of Experimental Psychology: General, 145, 621–29. https://doi.org/10.1037/xge0000153. Thomas, K. A., DeScioli, P., Haque, O. S., & Pinker, S. 2014. The psychology of coordination and common knowledge. Journal of Personality and Social Psychology, 107, 657–76. https://doi.org/10.1037/a0037037.

The Net Delusion: The Dark Side of Internet Freedom
by Evgeny Morozov
Published 16 Nov 2010

“Undersecretary Glassman and Jared Cohen Hold a News Briefing on the Alliance for Youth Movements Summit at Columbia University at the Foreign Press Center, as Released by the State Department.” Political Transcript Wire, November 24, 2008. van Dick, R., P. A. Tissington, and G. Hertel. “Do Many Hands Make Light Work?” European Business Review 21, no. 3 (2009): 233-245. Voelpel, S. C., R. A. Eckhoff, and J. Forster. “David Against Goliath? Group Size and Bystander Effects in Virtual Knowledge Sharing.” Human Relations 61, no. 2 (2008): 271. Wagner, J. A., III. “Studies of Individualism-Collectivism: Effects on Cooperation in Groups.” Academy of Management Journal 38, no. 1 (1995): 152- 172. Williams, K. D. “Social Loafing on Difficult Tasks: Working Collectively Can Improve Performance.”

The Lonely Century: How Isolation Imperils Our Future
by Noreena Hertz
Published 13 May 2020

Paulo and Ellen Lokajaya, ‘3 in 4 youngsters say they have been bullied online’, CNA Insider, 1 March 2018, https://www.channelnewsasia.com/news/cnainsider/3-in-4-teens-singapore-cyberbullying-bullied-online-survey-10001480. 85 Christo Petrov, ‘Cyberbullying Statistics 2020’, Tech Jury, 2 June 2020, https://techjury.net/stats-about/cyberbullying/#Cyberbullying_around_the_world. 86 ‘The Annual Bullying Survey 2017’ (Ditch the Label, 2017), 28, https://www.ditchthelabel.org/wp-content/uploads/2017/07/The-Annual-Bullying-Survey-2017-2.pdf. 87 Simon Murphy, ‘Girl killed herself after intense social media activity, inquest finds’, Guardian, 17 April 2019, https://www.theguardian.com/uk-news/2019/apr/17/girl-killed-herself-social-media-inquest-jessica-scatterson. 88 Clyde Haberman, ‘What the Kitty Genovese Killing Can Teach Today’s Digital Bystanders’, New York Times, 4 June 2017, https://www.nytimes.com/2017/06/04/us/retro-report-bystander-effect.html; Carrie Rentschler, ‘Online abuse: we need Good Samaritans on the web’, Guardian, 19 April 2016, https://www.theguardian.com/commentisfree/2016/apr/19/online-abuse-bystanders-violence-web. 89 Gordon Harold and Daniel Aquah, ‘What works to enhance interparental relationships and improve outcomes for children?’

Energy: A Human History
by Richard Rhodes
Published 28 May 2018

Journal of Industrial and Engineering Chemistry 13 (1921): 841–43. Hickam, Homer H., Jr. Torpedo Junction: U-Boat War Off America’s East Coast, 1942. Annapolis: Naval Institute Press, 1989. Hidalgo, César. Why Information Grows: The Evolution of Order, from Atoms to Economies. New York: Basic Books, 2015. Hill, Colin K. “The Low-Dose Phenomenon: How Bystander Effects, Genomic Instability, and Adaptive Responses Could Transform Cancer-Risk Models.” Bulletin of the Atomic Scientists 68, no. 3 (2012): 51–58. Hills, Richard L. “The Origins of James Watt’s Perfect Engine.” Transactions of the Newcomen Society 68 (1997): 85–107. ———. Power from Steam: A History of the Stationary Steam Engine.

Site Reliability Engineering: How Google Runs Production Systems
by Betsy Beyer , Chris Jones , Jennifer Petoff and Niall Richard Murphy
Published 15 Apr 2016

This is a single person who responds to pages and manages the resulting incidents or outages. The primary on-call engineer might also manage user support communications, escalation to product developers, and so on. In order to both minimize the interruption a page causes to a team and avoid the bystander effect, Google on-call shifts are manned by a single engineer. The on-call engineer might escalate pages to another team member if a problem isn’t well understood. Typically, a secondary on-call engineer acts as a backup for the primary. The secondary engineer’s duties vary. In some rotations, the secondary’s only duty is to contact the primary if pages fall through.

Atomic Accidents: A History of Nuclear Meltdowns and Disasters: From the Ozark Mountains to Fukushima
by James Mahaffey
Published 15 Feb 2015

The Man Who Wrecked 146 Locomotives: The Story of “Head-On Joe” Connolly. David City, NE: South Platte Press, 2009. Chapter 1: We Discover Fire Harve, David I. Deadly Sunshine: The History and Fatal Legacy of Radium. Gloucestershire, UK: Tempus Publishing Limited, 2005. Hill, Colin K. The Low-Dose Phenomenon: How Bystander Effects, Genomic Instability, and Adaptive Responses Could Transform Cancer-Risk Models. Thousand Oaks, CA: SAGE Publications, 2012. Kaperson, Roger E. The Social Amplification of Risk and Low-Level Radiation. Thousand Oaks, CA: SAGE Publications, 2012. Mahaffey, J. A. The History of Nuclear Power.