Author Archives: kevin

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How to give to homeless people

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From someone who has been homeless, a good discussion of the pros and cons of different ways of responding to beggars.
The problem with giving panhandlers money is severalfold. First, you provide economic incentive for panhandling. While I have long since gotten over my hatred of the homeless, I still hate people coming up to me every few minutes, interrupting my conversation to ask for money. It also enables an alcohol or drug habit that keeps that person complacent in their situation. I could go on about how our individual guilt adds up to an unacceptable, unofficial, welfare state, but let’s keep this to you and me. Second, giving money to the homeless is expensive. A dollar here, a dollar there—you’ll be out a hundred bucks by the time the week is over. Maybe you don’t mind the money, but you will mind the frustration, as the same person asks you for money night after night and you realize you’re not accomplishing anything worthwhile. Ignoring the homeless, or begging off, carries its own problems. For one thing, from the perspective of the panhandler, being ignored only confirms their hatred of humanity. Eventually a person who is ignored starts to escalate their behavior, just to get a reaction. Talking to them, learning their names, and explaining why you don’t have money for them just infuriates them more. It also takes a lot of time, worsening the interruption.
He recommends not giving food. The author has a good solution:
Here’s what you do: pick up a pack of the cheapest cigarettes you can find. You should be able to get a pack for less than $5—That’s 20 homeless encounters at less than 25¢ each. Make sure it’s a brand neither you nor anyone you know would smoke. This sets up a separate budget so you can give without worrying about your own needs. When someone asks you for money, say you don’t have any, then offer them a cigarette. In my experience, no homeless person has every not taken a cigarette, nor asked for money in addition to the cigarette. Most of the time they don’t even light it—saving it either to savor later, or as a kind of currency. Instead, they walk away and leave me alone, barely interrupting the conversation at all.
One of the toughest parts of living in India was finding a way to interact with beggars that didn't leave you feeling like shit for the rest of the day. I made donations instead.

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The data-driven approach is changing the world

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I was reading this profile of Esther Duflo in the New Yorker last night when I realized that rural development and the tech sector aren't too different in their approach to problems. In each one you're trying to convince the customer that what you're selling - immunizations, software - will make their lives better. Sometimes you're not reaching out to the customer that well, in which case you try experiments to make things better. In tech, this is pretty low cost - you segment the customer base, show the treatment group a revised page and then measure the differences. In development this is more expensive - you have to create a randomized controlled trial, divide your population in two and then measure the results later. The basic principles are the same, though. Most successful web designers and aid workers/economists believe the following: 1. We can be doing a better job selling our product 2. Our assumptions could be right or could be wrong, but we have no way to tell without testing them 3. Good data is essential 4. Opinions without data are meaningless 5. Experiment constantly to collect more data and find things that work The success of this approach has become so clear, and such a part of my approach to problems, over the past few years that it's hard to imagine doing things differently, or having a discussion with people that rely on their gut. Even having discussions with people is pointless, when you can go look up some papers or evidence that proves or disproves your point, but most people aren't willing to trust the data over their intuitions. There are two types of people who have opinions about social promotion in schools: people who have looked at the data and people who haven't. Overwhelmingly the people who look at the data are in favor of social promotion (as are school administrators). Institutions push back against the data-driven approach, however, because of its implications. Underlying the hierarchical system at most companies is a belief that the people at the top are better at making decisions, or their assumptions are somehow better than the people just starting. If we're trusting the data, then your guess as the CEO is just as good as mine, as the intern; the people at the top must be comfortable ceding power. Plus we have all these biases, like the ability to discern patterns out of random data and anchoring, and if you're not familiar with cognitive bias by this point go read this. In both the tech sector and in development, there are companies that - for the moment - aren't randomizing, and are still doing okay and collecting money. That's going to change, though, and soon, because relying on the data gives you such a clear advantage. Google's made billions with it. J-PAL's gaining on everyone else in development, only because their experiments are demonstrating results. If you've got nothing else to go on, evaluate the future success of an organization by how it makes decisions, and how open it is to change.

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One failure of globalization

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Earlier I wrote a post on the benefits of globalization and free trade. Here's a story about globalization gone wrong in Ladakh:
Most important of all, I have been able to witness first-hand the evolution of tensions between the Buddhist majority and Muslim minority in Ladakh, or `Little Tibet', in the western Himalayas. For more than 600 years these two groups lived side by side with no recorded instance of conflict. They helped each other at harvest time, attended one another's religious festivals, even intermarried. But within a decade of the imposition of western-style `development', Buddhists and Muslims were engaged in pitched battles — including the bombing of each other's homes — that took many lives. Even mild-mannered grandmothers — who a decade earlier would have been drinking chang, eating tsampa and laughing with their Muslim neighbours — told me, “we have to kill all the Muslims or they will finish us off.”
Hat tip Jenny B.

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Do you kill good ideas?

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Via Bob Sutton, here’s an old post about the importance of killing good ideas.

The thing I remember best was that Jobs advised them that killing bad ideas isn’t that hard — lots of companies, even bad companies, are good at that. Jobs’ argument went something like this: What is really hard – and a hallmark of great companies – is that they kill a lot of good ideas. Sure, this is tough on people who have come-up with the good ideas as they love them and don’t want to see them die. But that for any single good idea to succeed, it needs a lot of resources, time, and attention, and so only a few ideas can be developed fully. Successful companies are tough enough to kill a lot of good ideas so those few that survive have a chance of reaching their full potential and being implemented properly.

[..]

His argument also resonates with our experience teaching in the d.school — the groups that often do the worst work have too many pet ideas and can’t bring themselves to kill enough of them, so they don’t do a decent job on any of them.

This applies at the personal level, as well. In an interview with Colin Marshall a few months ago, Robin Hanson noted that he’s similarly interested in many areas, but he forces himself to focus and become a specialist in particular areas. This is probably my biggest failing so far – being interested in many different things but not doing enough work to get extraordinary at any of them. The consulting blog was an attempt to get around this.

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Thoughts on CMC’s Graduation, May 15

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  • The primary purpose of the graduation speaker is to reassure the parents in the audience that the 200K+ that they spent on their college education was worth it. The speaker's impressiveness helps with this but they also should stick to one of a few topics: discuss the impressiveness of the students, the value of their education, the challenges of the broad world and how their sparkling degree helps them to meet these challenges head on, or how their education prepares them for a life of success, just like the speaker. Henry Kravis was the speaker today, and I have all the respect in the world for his ability to turn around companies and improve their management, but his speech didn't fit the above criteria. Instead he decided to give lots of advice, in short bursts. He also mixed in current events terms like "iPad" and "Obama" to keep people on their toes. I thought it was pretty bad but the bar and expectations for graduation speeches are pretty low. He got a standing ovation.
  • Pretty much everyone from Kravis to Pam Gann to William Robelo-Lara either downplayed the amount of work that goes into getting a degree or played up the amount of drinking they or the students did at college. Andy says it's because it's impressive that you can drink and still get good grades. I think that it's an attempt to reframe the relevant status game from "who gets the best grades" to "who can party hardest." Because we can delude ourselves about partying hard but it's difficult to delude ourselves about GPA, especially when the Summa Cum Laude students are wearing special tassels. It's partly self defense. And, in the big picture, Kravis did just fine after school even though he did pretty terribly while he was here.
  • Airhorns! People blow airhorns because they want to show everyone else that they care about the student that's graduating. Unfortunate. I'd prefer something more subtle, or more awesome, like releasing doves into the air, co-ordinating an Air Force flyover with my name being read. Surely there are better ways to show that you care about someone.
  • Another common graduation failure is that speakers don't coordinate. Everyone starts their speech like they're the first person to get to the podium. If you're not the first speaker you don't need as much of a hook, because everyone's on the same team. Just say your bit and leave the stage before you think you should.

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The downside and upside of our ability to rationalize

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We had another discussion last night about how happy the people in the villages seem to be, in spite of hunger, unstable water supply, long days of labor for low wages, etc. This time someone brought up how shallow it seems that rich people get upset over things that, to the poor people, sound ridiculous, like the wireless being down or not having enough money to purchase some new toy. Anyone who's read Daniel Gilbert's book "Stumbling on Happiness" would know the amazing power of the human brain to rationalize and adjust to new circumstances. The band of possible human conditions is much wider than the band of human emotion; people near the top are only a little bit happier than people near the bottom. Paraplegics report higher levels of happiness than normal people, despite not having the use of their legs. If we couldn't adjust, then people who've scaled the heights of income and status would just walk around in a halo of golden, happy feelings, and people who are desperately poor would be despondent and depressed all of the time. That world state is definitely worse than our current one. People who live in conditions absolutely and materially much worse than those in the West have a chance to be happy. On the flipside, though, people in the West who live in historic material and absolute comfort have a chance to experience sadness, and because their lives aren't filled with drama such as "will I be able to get a gallon of water today, or three?" this sadness always seems shallow, even though the feeling is surely real. The ability of poor people to be extremely happy and the ability of rich people to be extremely sad are flip sides of the same token, I believe. I'm not sure you could have one without having the other. This tradeoff has been positive on net for the human condition.

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More on the difference between millions and billions

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I wrote earlier on the ease with which people confuse millions and billions, even though one is 1,000 times larger than the other. The million/billion problem struck again today: a trader accidentally sold $15 billion worth of Procter & Gamble shares, even though he meant to sell only $15 million. Procter & Gamble soon recovered but the market didn't; it lost 10% of its value. As I said before, if we start referring to billions as "thousand millions" we'd have much smarter thinking about the issue. And "T" is pretty far away from "M" on a keyboard so people wouldn't make this kind of mistake.

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Let’s reframe “What do you want to be when you grow up?”

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Asking kids what they want to be when they grow up is a silly question. Because the answer has pretty much zero bearing on where they're going to end up. What job you take when you grow up isn't really a question of what you want to do so much as it is a question of how hard you're willing to work to get there. Almost always the kid will answer with some high-status profession that's designed to impress the person asking the question, like NBA player, singer, firefighter, and everyone nods sagely. I'm not one for bursting a kid's bubble, but I am against lying through statements about beliefs that you have no intention of following through on, no matter how old you are. Sure, these kids are young, but it's a bad habit to develop; look at how many adults profess to care about the environment, or animals, and then do nothing about it, or only act in ways that signal their care, without actually helping the problem. If a kid tells me what he wants to be when he grows up, I want to know right now what that kid's doing to make that dream a reality. Better questions are, "How hard are you working right now? Are you in the top 1% of your class in terms of work rate?" "How much do you read?" (if he/she wants to be an athlete, musician, programmer) "How much time are you devoting to practicing your game?" Bill Bradley, one of my heroes, once said that anyone could be an All-American, all it takes is three hours a day. It helps to be 6'6, but the point is well taken - the best athletes/musicians are those who work the hardest and practice consistently. (if he/she wants to be an entrepreneur) "How many businesses have you started?" "Do you have an addictive personality? How hard do your friends work?" - evaluate risk of backsliding Taking a kid's answer at face value when he tells you he wants to play in the NBA is hurting the kid. It prolongs the belief that just wanting something to be true will make it so, and the cheap approval lets the kid know his current work rate is okay. I wish that people would start designating the kids that are working on their game for three hours a day as the kids who want to play in the NBA, not the ones who tell you they want to be an NBA player.

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Cognitive Bias of the Week: The Availability Bias

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The availability bias is the human tendency to judge the natural frequency of an event by how many examples of the event come to mind. For example, people can readily think of examples of plane crashes or murders, because these events are well publicized, but not so easily think of examples of death from heart disease, so they tend to believe rare deaths happen more frequently than they actually do. One fact that may shock you is that children are about eighty times as likely to drown in a swimming pool than they are to kill themselves or another with a parent's firearm. When judging the chance of landing in one of two future world states (flood or no flood, banking crisis or no banking crisis), we tend to over-weight the one that we have examples for. We should expect that people who have never lived through an earthquake, like me, would underestimate the probablility and necessity of earthquake preparation, while people should over-prepare for an earthquake in the years following a large one. Availability bias is what leads sports fans to view a team's win streak and compute that there's no way that team could lose; there just aren't examples of it happening. This is relevant for consultants because consultants often need to estimate the risk that various events occur, and if they underestimate the probability that a bad event occurs, then they can damage themselves or their company. For example, in 2006 everyone underestimated the probability of a nationwide downturn in the housing market, because it had never happened before. To give good advice, consultants need to have a good grasp on the various risks and probability that each one occurs. Furthermore, consultants may be swayed by advice they've recommended in the past, because it's available to them. As Bob Sutton and Jeffrey Pfeffer write in Hard Facts,
[VC Steve] Dow has been a general partner at Silicon Valley's Sevin Rosen since 1983 and served on dozens of boards over the years. He tells us that many board members, especially young venture capitalists who lack operational experience, are quick to talk about replacing the CEO at the first hint of trouble. Dow asks them, "Now, suppose you were CEO, what would you do differently than the one we have right now? Dow says that most of the time they can't think of much, if anything, they would change.
For many of those young VC's, the CEO is the available face of the company, and swapping the CEO's been what they have done in the past. These cognitive shortcuts lead people to believe that replacing the CEO will do good things for the company. One good way to overcome this bias is to force people to bet on their beliefs, or establish a market for predictions. When people can profit from mistaken beliefs, the odds are high that the price of an event occurring will be a good guess of the probability that it actually occurs. The bias may still be there, but if only one person in your organization is unbiased, they could bet enough money to correct the market. A second measure is to fight a heuristic with a heuristic. If you're giving the odds that an event will occur, and the event's never happened before, give it two or three times as much weight as you think it deserves. It's not perfect but it's probably better than the original estimate.

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