Top 40 Cathy O'Neil Quotes (2024 Update)

1. “In a system in which cheating is the norm, following the rules amounts to a handicap.”

— Cathy O'Neil

2. “In the world of WMDs, privacy is increasingly a luxury that only the wealthy can afford.”

— Cathy O'Neil

3. “We can use the scale and efficiency that make WMDs so pernicious in order to help people. It all depends on the objective we choose.”

— Cathy O'Neil

4. “Nevertheless, many of these models encoded human prejudice, misunderstanding, and bias into the software systems that increasingly managed our lives. Like gods, these mathematical models were opaque, their workings invisible to all but the highest priests in their domain: mathematicians and computer scientists. Their verdicts, even when wrong or harmful, were beyond dispute or appeal. And.”

— Cathy O'Neil

5. “I was forced to confront the ugly truth: people had deliberately wielded formulas to impress rather than clarify.”

— Cathy O'Neil

6. “It’s a silent war that hits the poor hardest but also hammers the middle class. Its victims, for the most part, lack economic power, access to lawyers, or well-funded political organizations to fight their battles. The result is widespread damage that all too often passes for inevitability.”

— Cathy O'Neil

7. “Big Data processes codify the past. They do not invent the future.”

— Cathy O'Neil

8. “Welcome to the dark side of Big Data.”

— Cathy O'Neil

9. “Our own values and desires influence our choices, from the data we choose to collect to the questions we ask. Models are opinions embedded in mathematics.”

— Cathy O'Neil

10. “This creates a pernicious feedback loop. The policing itself spawns new data, which justifies more policing. And our prisons fill up with hundreds of thousands of people found guilty of victimless crimes. Most of them come from impoverished neighborhoods, and most are black or Hispanic. So even if a model is color blind, the result of it is anything but. In our largely segregated cities, geography is a highly effective proxy for race.”

— Cathy O'Neil

11. “Why, specifically, were they targeting these folks? Vulnerability is worth gold. It always has been.”

— Cathy O'Neil

12. “Justice cannot just be something that one part of society inflicts on the other.”

— Cathy O'Neil

13. “The algorithms would make sure that those deemed losers would remain that way. A lucky minority would gain ever more control over the data economy, raking in outrageous fortunes and convincing themselves all the while that they deserved it.”

— Cathy O'Neil

14. “Like gods, these mathematical models were opaque, their workings invisible to all but the highest priests in their domain: mathematicians and computer scientists.”

— Cathy O'Neil

15. “My point is that police make choices about where they direct their attention. Today they focus almost exclusively on the poor. That’s their heritage, and their mission, as they understand it.”

— Cathy O'Neil

16. “What’s more, attempting to score a teacher’s effectiveness by analyzing the test results of only twenty-five or thirty students is statistically unsound, even laughable. The numbers are far too small given all the things that could go wrong. Indeed, if we were to analyze teachers with the statistical rigor of a search engine, we’d have to test them on thousands or even millions of randomly selected students.”

— Cathy O'Neil

17. “Our livelihoods increasingly depend on our ability to make our case to machines. The clearest example of this is Google. For businesses, whether it’s a bed-and-breakfast or an auto repair shop, success hinges on showing up on the first page of search results.”

— Cathy O'Neil

18. “I should note that empathy is hardly a cure-all. It tends to embed biases, because by nature we find it easier to empathize with people like us.”

— Cathy O'Neil

19. “We’ve seen time and again that mathematical models can sift through data to locate people who are likely to face great challenges, whether from crime, poverty, or educations. It’s up to society whether to use that intelligence to reject and punish them – or to reach out to them with the resources they need. We can use the scale and efficiency that make WMDs so pernicious in order to help people. It all depends on the objective we choose.”

— Cathy O'Neil

20. “If we’re going to be equal before the law, or be treated equally as voters, we cannot stand for systems that drop us into different castes and treat us differently.”

— Cathy O'Neil

21. “My love for math eventually became a passion. I went to math camp when I was fourteen and came home clutching a Rubik’s Cube to my chest. Math provided a neat refuge from the messiness of the real world. It marched forward, its field of knowledge expanding relentlessly, proof by proof. And.”

— Cathy O'Neil

22. “Here we see that models, despite their reputation for impartiality, reflect goals and ideology. When I removed the possibility of eating Pop-Tarts at every meal, I was imposing my ideology on the meals model. It’s something we do without a second thought. Our own values and desires influence our choices, from the data we choose to collect to the questions we ask. Models are opinions embedded in mathematics.”

— Cathy O'Neil

23. “The human victims of WMDs, we’ll see time and again, are held to a far higher standard of evidence than the algorithms themselves.”

— Cathy O'Neil

24. “Sometimes the job of a data scientist is to know when you don’t know enough.”

— Cathy O'Neil

25. “Once companies amass troves of data on employees’ health, what will stop them from developing health scores and wielding them to sift through job candidates? Much of the proxy data collected, whether step counts or sleeping patterns, is not protected by law, so it would theoretically be perfectly legal. And it would make sense. As we’ve seen, they routinely reject applicants on the basis of credit scores and personality tests. Health scores represent a natural – and frightening – next step.”

— Cathy O'Neil

26. “In fact, the greatest savings from wellness programs come from the penalties assessed on the workers. In other words, like scheduling algorithms, they provide corporations with yet another tool to raid their employees’ paychecks.”

— Cathy O'Neil

27. “Simpson’s Paradox: when a whole body of data displays one trend, yet when broken into subgroups, the opposite trend comes into view for each of those subgroups.”

— Cathy O'Neil

28. “The result is that we criminalize poverty, believing all the while that our tools are not only scientific but fair.”

— Cathy O'Neil

29. “In a federal lawsuit, Baltimore officials charged Wells Fargo with targeting black neighborhoods for so-called ghetto loans. The bank’s “emerging markets” unit, according to a former bank loan officer, Beth Jacobson, focused on black churches.”

— Cathy O'Neil

30. “People with savings, of course, can keep their credit intact during tough times. Those living from paycheck to paycheck are far more vulnerable. Consequently, a sterling credit rating is not just a proxy for responsibility and smart decisions. It is also a proxy for wealth. And wealth is highly correlated with race.”

— Cathy O'Neil

31. “If it was true during the early dot-com days that “nobody knows you’re a dog,” it’s the exact opposite today. We are ranked, categorized, and scored in hundreds of models, on the basis of our revealed preferences and patterns.”

— Cathy O'Neil

32. “Apollo Group, the parent company for the University of Phoenix, spent more than a billion dollars on marketing in 2010, almost all of it focused on recruiting. That came out to $2,225 per student on marketing and only $892 per student on instruction. Compare that to Portland Community College in Oregon, which spends $5,953 per student on instruction and about 1.2 percent of its budget, or $185 per student, on marketing.”

— Cathy O'Neil

33. “This is a point I’ll be returning to in future chapters: we’ve seen time and again that mathematical models can sift through data to locate people who are likely to face great challenges, whether from crime, poverty, or education. It’s up to society whether to use that intelligence to reject and punish them – or to reach out to them with the resources they need.”

— Cathy O'Neil

34. “In short, WMDs are targeting us all. And they’ll continue to multiply, sowing injustice, until we take steps to stop them.”

— Cathy O'Neil

35. “Instead, they face heightened anxiety and sleep deprivation, which causes dramatic mood swings and is responsible for an estimated 13 percent of highway deaths. Worse yet, since the software is designed to save companies money, it often limits workers’ hours to fewer than thirty per week, so that they are not eligible for company health insurance.”

— Cathy O'Neil

36. “However, when you create a model from proxies, it is far simpler for people to game it. This is because proxies are easier to manipulate than the complicated reality they represent.”

— Cathy O'Neil

37. “If language and child care issues posed problems for otherwise solid candidates, the solution was not to reject those candidates but instead to provide them with help – whether English classes or onsite day care – to pull them through. This is a point I’ll be returning to in future chapters: we’ve seen time and again that mathematical models can sift through data to locate people who are likely to face great challenges, whether from crime, poverty, or education.”

— Cathy O'Neil

38. “Big Data processes codify the past. They do not invent the future. Doing that requires moral imagination, and that’s something only humans can provide. We have to explicitly embed better values into our algorithms, creating Big Data models that follow our ethical lead. Sometimes that will mean putting fairness ahead of profit.”

— Cathy O'Neil

39. “Our livelihoods increasingly depend on our ability to make our case to machines.”

— Cathy O'Neil

40. “According to the American Civil Liberties Union, sentences imposed on black men in the federal system are nearly 20 percent longer than those for whites convicted of similar crimes.”

— Cathy O'Neil

41. “Just imagine if police enforced their zero-tolerance strategy in finance. They would arrest people for even the slightest infraction, whether it was chiseling investors on 401ks, providing misleading guidance, or committing petty frauds. Perhaps SWAT teams would descend on Greenwich, Connecticut. They’d go undercover in the taverns around Chicago’s Mercantile Exchange.”

— Cathy O'Neil

42. “And in Florida, adults with clean driving records and poor credit scores paid an average of $1,552 more than the same drivers with excellent credit and a drunk driving conviction.”

— Cathy O'Neil

43. “Someone who takes the trouble to see her file at one of the many brokerages, for example, might see the home mortgage, a Verizon bill, and a $ 459 repair on the garage door. But she won’t see that she’s in a bucket of people designated as “Rural and Barely Making It,”or perhaps “Retiring on Empty.”

— Cathy O'Neil

44. “Opaque and invisible models are the rule, and clear ones very much the exception. We’re modeled as shoppers and couch potatoes, as patients and loan applicants, and very little of this do we see – even in applications we happily sign up for. Even when such models behave themselves, opacity can lead to a feeling of unfairness.”

— Cathy O'Neil

45. “We are judged by what we do, not by who we are.”

— Cathy O'Neil

46. “A 2013 study by the New York Civil Liberties Union found that while black and Latino males between the ages of fourteen and twenty-four made up only 4.7 percent of the city’s population, they accounted for 40.6 percent of the stop-and-frisk checks by police. More than 90 percent of those stopped were innocent.”

— Cathy O'Neil