The Declining Value of Personal Advice

27 Jun

There used to be a time when before buying something, you asked your friends and peers about advice, and it was the optimal thing to do. These days, it is often not a great use of time. It is generally better to go online. Today, the Internet abounds with comprehensive, detailed, and trustworthy information, and picking the best product, judging by its quality, price, appearance, or what have you, in a slew of categories is easy to do.

As goes for advice about products, so goes for much other advice. For instance, if a coding error stumps you, your first move should be to search StackOverflow than Slack a peer. If you don’t understand a technical concept, look for a YouTube video or a helpful blog or a book than “leverage” a peer.

The fundamental point is that it is easier to get high-quality data and expert advice today than it has ever been. If your network includes the expert, bless you! But if it doesn’t, your network no longer damns you to sub-optimal information and advice. And that likely has welcome consequences for equality.

The only cases where advice from people near you may edge ahead of readily available help online is where the advisor has access to private information about your case or where the advisor is willing to expend greater elbow grease to get to the facts and think of advice that aptly takes account of your special circumstances. For instance, you may be able to get good advice on how to deal with alcoholic parents from an expert online but probably not about alcoholic parents with the specific set of deficiencies that your parents have. Short of such cases, the value of advice from people around is lower today than before, and probably lower than what you can get online.

The declining value of interpersonal advice has one significant negative externality. It takes out a big way we have provided value to our loved ones. We need to think harder about how we can fill that gap.

Why do We Fail? And What to do About It?

28 May

I recently read Gawande’s The Checklist Manifesto. (You can read my review of the book here and my notes on the book here.) The book made me think harder about failure and how to prevent it. Here’s a result of that thinking.

We fail because we don’t know or because we don’t execute on what we know (Gorovitz and MacIntyre). Of the things that we don’t know are things that no else knows either—they are beyond humanity’s reach for now. Ignore those for now. This leaves us with things that “we” know but the practitioner doesn’t.

Practitioners do not know because the education system has failed them, because they don’t care to learn, or because the production of new knowledge outpaces their capacity to learn. Given that, you can reduce ignorance by 1) increase the length of training, b) improving the quality of training, c) setting up continued education, d) incentivizing knowledge acquisition, e) reducing the burden of how much to know by creating specializations, etc. On creating specialties, Gawande has a great example: “there are pediatric anesthesiologists, cardiac anesthesiologists, obstetric anesthesiologists, neurosurgical anesthesiologists, …”

Ignorance, however, ought not to damn the practitioner to error. If you know that you don’t know, you can learn. Ignorance, thus, is not a sufficient condition for failure. But ignorance of ignorance is. To fix overconfidence, leading people through provocative, personalized examples may prove useful.

Ignorance and ignorance about ignorance are but two of the three reasons for why we fail. We also fail because we don’t execute on what we know. Practitioners fail to apply what they know because they are distracted, lazy, have limited attention and memory, etc. To solve these issues, we can a) reduce distractions, b) provide memory aids, c) automate tasks, d) train people on the importance of thoroughness, e) incentivize thoroughness, etc.

Checklists are one way to work toward two inter-related aims: educating people about the necessary steps needed to make a decision and aiding memory. But awareness of steps is not enough. To incentivize people to follow the steps, you need to develop processes to hold people accountable. Audits are one way to do that. Meetings set up at appropriate times during which people go through the list is another way.

Wanted: Effects That Support My Hypothesis

8 May

Do survey respondents account for the hypothesis that they think people fielding the survey have when they respond? The answer, according to Mummolo and Peterson, is not much.

Their paper also very likely provides the reason why—people don’t pay much attention. Figure 3 provides data on manipulation checks—the proportion guessing the hypothesis being tested correctly. The change in proportion between control and treatment ranges from -.05 to .25, with a bulk of changes in Qualtrics between 0 and .1. (In one condition, authors even offer an additional 25 cents to give a result consistent with the hypothesis. And presumably, people need to know the hypothesis before they can answer in line with it.) The faint increase is especially noteworthy given that on average, the proportion of people in the control group who guess the hypothesis correctly—without the guessing correction—is between .25–.35 (see Appendix B; pdf).

So, the big thing we may have learned from the data is how little attention survey respondents pay. The numbers obtained here are similar to those in Appendix D of Jonathan Woon’s paper (pdf). The point is humbling and suggests that we need to: a) invest more in measurement, and b) have yet larger samples, which is an expensive way to overcome measurement error—a point Gelman has made before.

There is also the point about the worthiness of including ‘manipulation checks.’ Experiments tell us ATE of what we manipulate. The role of manipulation checks is to shed light on ‘compliance.’ If conveying experimenter demand clearly and loudly is a goal, then the experiments included probably failed. If the purpose was to know whether clear but not very loud cues about ‘demand’ matter—and for what it’s worth, I think it is a very reasonable goal; pushing further, in my mind, would have reduced the experiment to a tautology—the paper provides the answer.

Advice that works

31 Mar

Writing habits of some writers:

“Early in the morning. A good writing day starts at 4 AM. By 11 AM the rest of the world is fully awake and so the day goes downhill from there.”

Daniel Gilbert

“Usually, by the time my kids get off to school and I get the dogs walked, I finally sit down at my desk around 9:00. I try to check my email, take care of business-related things, and then turn it off by 10:30—I have to turn off my email to get any writing done.”

Juli Berwald

“When it comes to writing, my production function is to write every day. Sundays, absolutely. Christmas, too. Whatever. A few days a year I am tied up in meetings all day and that is a kind of torture. Write even when you have nothing to say, because that is every day.”

Tyler Cowen

“I don’t write everyday. Probably 1-2 times per week.”

Benjamin Hardy

“I’ve taught myself to write anywhere. Sometimes I find myself juggling two things at a time and I can’t be too precious with a routine. I wrote Name of the Devil sitting on a bed in a rented out room in Hollywood while I was working on a television series for A&E. My latest book, Murder Theory, was written while I was in production for a shark documentary and doing rebreather training in Catalina. I’ve written in casinos, waiting in line at Disneyland, basically wherever I have to.”

Andrew Mayne

Should we wake up at 4 am and be done by 11 am as Dan Gilbert does or should we get started at 10:30 am like Juli, near the time Dan is getting done for the day? Should we write every day like Tyler or should we do it once or twice a week like Benjamin? Or like Andrew, should we just work on teaching ourselves to “write anywhere”?

There is a certain tautological aspect to good advice. It is advice that works for you. Do what works for you. But don’t assume that you have been given advice that is right for you or that it is the only piece of advice on that topic. Advice givers rarely point out that the complete set of reasonable things that could work for you is often pretty large and contradictory and that the evidence behind the advice they are giving you is no more than anecdotal evidence with a dash of motivated reasoning.

None of this to say that you should not try hard to follow advice that you think is good. But once you see the larger point, you won’t fret as much when you can’t follow a piece of advice or when the advice doesn’t work for you. As long as you keep trying to get to where you want to be (and of course, even the merit of some wished for end states is debatable), it is ok to abandon some paths, safe in the knowledge that there are generally more paths to get there.

The Risk of Misunderstanding Risk

20 Mar

Women who participate in breast cancer screening from 50 to 69 live on average 12 more days. This is the best case scenario. Gerd has more such compelling numbers in his book, Calculated Risks. Gerd shares such numbers to launch a front on assault on the misunderstanding of risk. His key point is:

“Overcoming innumeracy is like completing a three-step program to statistical literacy. The first step is to defeat the illusion of certainty. The second step is to learn about the actual risks of relevant eventsand actions. The third step is to communicate the risks in an understandable way and to draw inferences without falling prey to clouded thinking.”

Gerd’s key contributions are on the third point. Gerd identifies three problems with risk communication:

  1. using relative risk than Numbers Needed to Treat (NNT) or absolute risk,
  2. Using single-event probabilities, and
  3. Using conditional probabilities than ‘natural frequencies.’

Gerd doesn’t explain what he means by natural frequencies in the book but some of his other work does. Here’s a clarifying example that illustrates how the same information can be given in two different ways, the second of which is in the form of natural frequencies:

“The probability that a woman of age 40 has breast cancer is about 1 percent. If she has breast cancer, the probability that she tests positive on a screening mammogram is 90 percent. If she does not have breast cancer, the probability that she nevertheless tests positive is 9 percent. What are the chances that a woman who tests positive actually has breast cancer?”

vs.

“Think of 100 women. One has breast cancer, and she will probably test positive. Of the 99 who do not have breast cancer, 9 will also test positive. Thus, a total of 10 women will test positive. How many of those who test positive actually have breast cancer?”

For those in a hurry, here are my notes on the book.

Disgusting

7 Feb

Vegetarians turn at the thought of eating the meat of a cow that has died from a heart attack. The disgust that vegetarians experience is not principled. Nor is the greater opposition to homosexuality that people espouse when they are exposed to foul smell. Haidt uses similar such provocative examples to expose chinks in how we think about what is moral and what is not.

Knowing that what we find disgusting may not always be “disgusting,” that our moral reasoning can be flawed, is a superpower. Because thinking that you are in the right makes you self-righteous. It makes you think that you know all the facts, that you are somehow better. Often, we are not. If we stop conflating disgust with being in the right or indeed, with being right, we shall all get along a lot better.

The Best We Can Do is Responsibly Answer the Questions that Life Asks of Us

5 Feb

Faced with mass murder, it is hard to escape the conclusion that life has no meaning. For how could it be that life has meaning when lives matter so little? As a German Jew in a concentration camp, Victor Frankl had to confront that question.

In Man’s Search for Meaning, Frankl gives two answers to the question. His first answer is a reflexive rejection of the meaninglessness of life. Frankl claims that life is “unconditional[ly] meaningful.” There is something to that, but not enough to hang on to for too long. It is also not his big point.

Instead, Frankl has a more nuanced point: “If there is … meaning in life …, then there must be … meaning in suffering.” (Because suffering is an inescapable part of life.) The meaning of suffering, according to him, lies in how we respond to it. Do we suffer with dignity? Or do we let suffering degrade us? The broader, deeper point that underpins the claim is that we cannot always choose our conditions, but we can choose the “stand [we take] toward the conditions.” And life’s meaning is stored in the stand we take, in how we respond to the questions that “life asks of us.”

Not only that, the extent of human achievement is: responsibly answering the questions that life asks of us. This means two things. First, that questions about human achievement can only be answered within the context of one’s life. And second, in responsibly answering questions that life asks of us, we attain what humans can ever attain. In a limited life, circumscribed by unavoidable suffering, for instance, the peak of human achievement is keeping dignity. If your life offers you more, then, by all means, do more—derive meaning from action, from beauty, and from love. But also take solace in the fact that we can achieve the greatest heights a human can achieve in how we respond to unavoidable suffering.

Ruined by Google

13 Jan

Information on tap is a boon. But if it means that the only thing we will end up knowing—have in your heads—is where to go to find the information, it may also be a bane.

Accessible stored cognitions are vital. They allow us to verify and contextualize new information. If we need to look things up, because of laziness or forgetfulness, we will end up accepting some false statements, which we would have easily refuted had we had the relevant information in our memory, or we will fail to contextualize some statements appropriately.

Information on tap also produces another malaise. It changes the topography of what we know. As search costs go down, people move from learning about a topic systematically to narrowly searching for whatever they need to know, now. And knowledge built on narrow searches looks like Swiss cheese.

Worse, many a time when people find the narrow thing they are looking for, they think that that is all there to know. For instance, in Computer Science and Machine Learning, people can increasingly execute sophisticated things without knowing much. (And that is a mostly a good thing.) But getting something to work—by copying the code from StackOverflow—gives people the sense that they “know.” And when we think we know, we also know that there is not much more to know. Thus, information on tap reduces the horizons of our knowledge about our ignorance.

In becoming better at fulfilling our narrower needs, lower search costs may be killing expertise. And that is mostly a bad thing.

The Other Side

23 Oct

Samantha Laine Perfas of the Christian Science Monitor interviewed me about the gap between perceptions and reality for her podcast ‘perception gaps’ over a month ago. You can listen to the episode here (Episode 2).

The Monitor has also made the transcript of the podcast available here. Some excerpts:

“Differences need not be, and we don’t expect them to be, reasons why people dislike each other. We are all different from each other, right. …. Each person is unique, but we somehow seem to make a big fuss about certain differences and make less of a fuss about certain other differences.”

One way to fix it:

If you know so little and assume so much, … the answer is [to] simply stop doing that. Learn a little bit, assume a little less, and see where the conversation goes.

The interview is based on the following research:

  1. Partisan Composition (pdf) and Measuring Shares of Partisan Composition (pdf)
  2. Affect Not Ideology (pdf)
  3. Coming to Dislike (pdf)
  4. All in the Eye of the Beholder (pdf)

Related blog posts and think pieces:

  1. Party Time
  2. Pride and Prejudice
  3. Loss of Confidence
  4. How to read Ahler and Sood

Loss of Confidence

21 Oct

We all overestimate how much we know. If the aphorism, “the more you know, the more you know that you don’t know” is true, then how else could it be? But knowing more is not the only path to learning about our ignorance. Mistakes are another. When we make mistakes, we get to adjust our parameters (understanding) about how much we know. Overconfident people, however, incur smaller losses when they make mistakes. They don’t learn as much from mistakes because they externalize the source of errors or don’t acknowledge the mistakes, believing it is you who is wrong, not them. So, the most ignorant (the most confident) very likely make the least progress in learning about their ignorance when they make mistakes. (Ignorance is just one source of why people overestimate how much they know. There are many other factors, including personality.) But if you know this, you can fix it.