CHAPTER 17 On the Limits of Quantification Flashcards
What do data and quantitative evidence not tell us?
Everything we need to know to make decisions.
What should decisions consider besides quantitative evidence?
The effects of our actions and our values.
What can happen if we mistake correlation for causation?
Quantification can lead you astray.
What is the danger of relying solely on evidence in decision-making?
There is no purely evidence-based decision.
What does the absence of evidence not mean?
The question is unimportant or safely ignored.
What is a common bias created by the demand for evidence?
Status quo bias.
What is required for many new regulatory actions by the U.S. government?
Quantitative cost-benefit analysis.
What is a consequence of regulations requiring quantification?
Narrowing the field of vision to quantifiable areas.
What example illustrates the risks of focusing only on quantifiable data?
The drunk man searching for keys under the lamppost.
What did the EPA report on arsenic regulation highlight?
Quantified benefits only included bladder and lung cancers.
What conclusion can be drawn from the meta-analysis regarding flossing?
There is ‘very unreliable’ evidence that flossing reduces plaque.
Why does Anthony continue to floss despite the lack of evidence?
Absence of evidence is not proof of absence.
What theoretical reasons support wearing masks during the COVID-19 pandemic?
Masks mitigate the flow of respiratory particles.
What do good decision makers acknowledge about quantitative evidence?
It only tells them so much.
What can happen if our goals and values are shaped by the mandate to quantify?
We might embrace values we would otherwise reject.
What is a risk of machine learning in decision-making?
Objectionable values can creep into decisions unnoticed.
How can algorithms exhibit racial or gender bias without relevant data?
Through correlations with other biased variables.
What is a common application of predictive machine learning algorithms?
Job placement, credit evaluation, and content recommendations.
What issue arises in health care algorithms predicting care needs?
They may unintentionally discriminate based on correlated variables.
Fill in the blank: Evidence is meant to be a tool used in service of our _______.
[goals and values]
True or False: Quantitative evidence can tell us how to act.
False.
What do large health care providers in the U.S. use to predict patients with complex health needs?
Machine learning algorithms
These algorithms aim to identify patients likely to have the greatest care needs.
What is the correlation between health care costs and health care needs?
Strong positive correlation
Sicker patients tend to receive more and more expensive treatment.
What type of data does the algorithm use to predict health care costs?
Data on patients’ past insurance claims, medical diagnoses, and medications
The algorithm does not receive information about race.
What is a comorbidity score?
A measure of active chronic health conditions
Used to assess true health care needs.
How did the algorithm’s predictions differ between Black and White patients?
Systematically under-estimated how sick Black patients were relative to White patients
Black patients were less likely to be enrolled in special programs despite similar health.
What is a potential reason for the algorithm’s racial bias?
Using cost as a proxy for health care needs
Less money is spent on Black patients on average than similarly sick White patients.
What is welfarism?
The view that policies should be evaluated based on their implications for human well-being
It often prioritizes utilitarianism.
What is utilitarianism?
The view that policies should be evaluated based on their implications for the sum total of human well-being
It often focuses on material costs and benefits.
What is crass utilitarianism?
A form of utilitarianism that defines well-being primarily in terms of material costs and benefits
It simplifies complex ethical considerations.
What did the presenter at the academic presentation conclude about removing children from abusive homes?
Children from abusive homes are, on average, better off in foster care
The benefits appear to exceed the costs of providing foster care.
What critique was raised regarding the policy recommendation to remove children from abusive homes?
The researcher had not estimated all relevant costs and benefits
Benefits to abusive parents were not considered.
What problematic suggestion did Larry Summers make regarding pollution?
Encouraging the migration of dirty industries to less developed countries
This was based on the economic logic of cost-effectiveness.
What is the issue with valuing outcomes based on willingness to pay?
It can imply that the well-being of the rich is more important than that of the poor
This raises ethical concerns about equity.
What is the role of cost-benefit analysis in policy decision making?
It quantifies costs and benefits to provide bounds on decision making
However, it does not eliminate subjective moral opinions.
What is a potential moral concern with transferring toxic waste from rich to poor countries?
It may violate principles of fairness, justice, and responsibility
Rich countries should take responsibility for their own actions.
What is the relationship between quantification and values in decision making?
Quantification can shape the goals and values we pursue
We often become utilitarians because we quantify.
What is an ethical position consistent with quantifying consequences?
It can be flexible and include considerations like rights and responsibilities
Quantitative analysis can incorporate equity considerations.
What moral arguments should be considered when discussing toxic waste disposal?
The manner in which decisions are made regarding toxic waste disposal should be considered, especially in terms of consent and compensation for poor countries.
What was Summers’s stance on shipping toxic waste to poor countries?
Summers initially supported the idea but later criticized it, stating that the sentiment was obviously wrong and that the expression of the idea was not constructive.
What are the potential consequences of quantification in moral arguments?
Quantification can lead to crass utilitarianism, pushing towards ruthless conclusions, but it can also provide valuable insights into trade-offs.
What is the danger of focusing on quantifiable data in ethical discussions?
Focusing on quantifiable data can obscure rights, dignity, and fairness, which are harder to quantify and may lead to objectionable utilitarianism.
What should be the goal of using quantitative analysis?
The goal should be to estimate important quantities without distorting the underlying values and goals against which choices are evaluated.
True or False: It is acceptable to use data to mislead others if one is skilled in quantitative thinking.
False
What responsibility comes with being a savvy quantitative thinker?
To be transparent about the strengths and weaknesses of evidence and to help others think clearly with data.
What fundamental concepts should a quantitative thinker understand?
- Selecting on the dependent variable
- Statistical vs. substantive significance
- Reversion to the mean
- Publication bias
- Sources of cosmic habituation
- Correlation vs. causation
- Research design
What is a key critique of the economic benefits presented for low-income neighborhood amenities?
Questions regarding the accuracy of the cost and benefit estimates should be asked before proceeding with the plan.
Fill in the blank: The exercise of quantifying costs and benefits can lead to a serious argument for policies involving _______.
consent and compensation
What is the importance of thinking clearly about data?
It is essential for understanding the world and making it a better place.
What does the concept of ‘publication bias’ refer to?
The tendency for journals to publish positive results more than negative or inconclusive ones.
What is the significance of the meta-analysis on flossing?
It found statistically significant evidence that flossing reduces gingivitis.
What does the term ‘crass utilitarianism’ imply in the context of moral reasoning?
A form of reasoning that focuses solely on material costs and benefits, neglecting ethical considerations.
What should individuals consider when making decisions without quantitative evidence?
The factors leading to their decisions and how quantitative studies could provide more compelling evidence.
What is the role of transparency in quantitative analysis?
To clarify the strengths and weaknesses of the evidence used in analysis.
What does ‘reversion to the mean’ refer to in statistics?
The phenomenon where extreme values in a dataset tend to be followed by values closer to the average.
What is a critical takeaway regarding the relationship between correlation and causation?
Correlation does not imply causation.
True or False: All quantitative evidence is free from bias.
False
What does the term ‘cosmic habituation’ refer to?
The tendency of individuals to become desensitized to certain stimuli over time.
