Framing as a Fire or as a Fight

One way to change an experience, and all experience is subjective, is to change the framing of it. Our food takes longer because we make it fresh. Via a16z:

“There has been some interesting work in the linguistics community asking if we should be using war as a metaphor for the virus. There’s a lot of discussion about ‘front line workers’, which is a war metaphor, but unlike people in the military, they didn’t volunteer for this degree of risk.”

Gretchen McCulloch

McCulloch goes on to consider how things would be different if the pandemic were described as a fire or natural disaster. What if outbreaks were flareups, people sheltered temporarily, and we extinguished the threat?

Some added stress of this pandemic is from our ambiguity aversion: we don’t like the feeling of not knowing.

So we use metaphors. Fights are: Us vs them, victory is this mark, loss is this, collateral damage is undesired but expected.

This post isn’t to say that Fire or Fight is better for the pandemic, but to think about using framing in interesting ways. Here’s one we’ve featured before:

This ad frames opportunity cost. It says, you’ve got 1,200 dollars. Do you want a new iPhone or a nearly-new iPhone and tickets to the ballet?

Framing works not because people can’t do the thinking by themselves, but that they don’t because thinking about all this is hard. We’ve evolved to process information where available equals important. That’s often good enough, so we stop thinking.

This is all good news. It’s why Alchemy is possible. Using the right words changes the focus which changes the understanding which changes the actions.

Would the pandemic be different if we viewed it more as a natural disaster? Maybe. Would our understanding, focus, and concept be different? Certainly.

The Vaccine Friendship Paradox

One non-intuitive concept, at least in scale, is the network. Like average numbers, it takes some work to construct the correct conclusions. Graph, chart, and count the way that people interact, decide, and connect and there will be patterns. It’s network effects which fuel companies like Instagram and create the increasing returns economy.

Networks, as Nicholas Christakis notes, are agnostic. They spread whatever they are seeded with, whether real viruses like Ebola or WOW viruses like corrupted blood. The question then is; How and what to seed a network with?

Eric Bradlow wondered about Covid vaccines on Wharton Moneyball:

“We study diffusion of products all the time. In theory, you want to observe the social graph. In marketing the question is: Who do you give the free product to? This is standard network analysis and with that data you could do a smarter initial seeding (of a vaccine).”

Is there more bang for the buck if one person gets the vaccine rather than another?

Yes, though it’s not intuitive.

As the Friendship Paradox video shows, we aren’t all connected to the same number of friends. Some people have more, some have fewer friends and to wisely allocate a scare resource (like with marathon slots) it takes some small adjustments.

Christakis has spent a lot of time mapping networks and noted that across cultures, space, and time most human networks look the same. Some people are more connected than others. A few have hundred of connections and hundreds have a few.

It’s important for Christakis because like Bradlow, he works with a diffusion problem. Rather than marketing products though, it’s about sharing vaccines and vitamins. The thinking for both goes like this, if you can share something that works with the right person then they will share the benefits of that with the rest of their network.

But how do you pick the right person? Christakis shared this tip: “Go into a village and pick people at random. Have them suggest their friends and vaccinate their friends rather than the originals.”

Most networks are like the Curb Your Enthusiasm network (via Funkhauser).

curb_your_enthusiasm_-_season_9_-_network_graph

Randomly enter that network and you could get anyone but then ask for that person’s friend and more often than not you’ll get Larry. He’s the hub. He’s the super spreader. He’s who to vaccinate or market to.

It’s a neat bit of math. Rather than random choice, ask one question to improve the odds of an idea, movement, or effect catching on.

While there’s nothing on networks, my latests pay-what-you-want is on Tyler Cowen’s ideas about decision making. One idea is ‘meta-rationality’ or knowing when you don’t know AND knowing where or who to go to to find out. 

Jobs with Rules

Education has been top of mind lately around our house (thanks Covid). We’ve considered college admissions, advantages of online learning, and whether reading is different than listening to a book (spoiler: both are good).

There’s some big picture ideas too: curriculums, college, and careers. My daughters (12, 10) aren’t near that yet, but it’s hard not to think about as we see careers adapt to remote work. My wife can work online, somewhat. Teachers can teach online, somewhat. Aside from some manual labor, for the last decade all my income has been earned online.

In Shop Class as Soulcraft Mathew Crawford notes that you can’t hammer a nail over the internet. Or, are things rule based or not? Rules mean code, code means computers and as Feynman explains, computers are fast at following rules.

TikTok’s design is simple rules. On, off. Yes, no. Open, closed. Watched, not. Shared, not.

Circa 2013 self-driving trucks were the topic du jour. However, driving a truck isn’t that binary, it’s not that rules based.

Our truck driver, Finny Murphy writes more about the problems solving involved. Keep the truck between the lines. Pick up this cargo, take it there. Then go here. Unload, schedule workers, back down this long driveway. Get stuck. Negotiate with owner to use his chainsaw, trim a limb. Murphy’s job would have been better with more computer help as he’d spend less time ‘bob-catting’ (driving without a trailer) if there were a network that listed jobs.

Contrast truck driver with financial planner, the latter has years of college. They’re licensed. They’re a charter holder or a master of business. Even more likely is that they have a podcast. The financial planner helps people with money, a very important thing. They wear suits! They have offices!

Which is more rule based?

One sign to spot rule based conditions is when we stop calling something the ‘internet something’. Internet banking, internet dating, and ‘I read it online’ are all things of the past. It’s just banking, dating, and reading now. Did you know, that internet bill pay used to be an add-on, banks *charged* for that service.

Which is more like TikTok, financial planning or truck driving? Finances is already rule based with target date and index funds.

Okay, so what direction should education head?

In Average is Over, Tyler Cowen writes that three things are scarce: quality land and natural resources, intellectual property or good ideas that should be produced, and quality labor with unique skills. I’ll read ‘good ideas’, ‘quality labor’, and ‘unique skills’ as antonyms for ‘rules based’.

Note: About 7% of truck drivers have bachelor degrees compared to 35% of the population. Both figures lower than I’d guessed. Also, rules can be especially helpful when they make you ‘color blind‘ to unhelpful information.

The pool of tears

A lesson from distance learning.

To keep up with my kids I’ve been taking Khan Academy classes and in one, founder Sal Khan noted that when Abraham Lincoln was in law school he used Euclid’s geometric proofs as a test for understanding. Recounted:

“In the course of my law-reading I constantly came upon the word demonstrate,” Lincoln said. “I thought, at first, that I understood its meaning, but soon became satisfied that I did not.” Resolving to understand it better, he went to his father’s house and “staid there till I could give any propositions in the six books of Euclid at sight.”

That’s ambitious, and demonstrates how much of learning is not linear.

In this way online learning excels. If we need time we take time. If we’re done early we make things. We act like Lincoln. Like Naval.

This is hard to do in school, scheduled to the year, week, day, hour, and even minute. Compounding and confounding is that we are relative creatures. I don’t get it compared to the kids that do. In the same way we are spending by neighbors but not saving, we see those who excel and calculateaccordingtothat.

Online learning isn’t great but it’s not all bad either and we’ve shed a few fewertears.

Gambling with Votes

Thirty days of September and October PredictIt markets.

Like Gambling with Covid19, betting markets can demonstrate probabilistic thinking. In that post we considered an idea from Matt (+EV) about Tom Brady’s potential passing yards.

In April Brady’s over-under yardage was 4,256, nicely inline with previous years of 4057, 4355, 4577, and 3554. However, Matt noted, there’s a lot more room under 4,256 than over it. Brady could get injured, retire mid-year, have a worse system, lose teammates and so on.

On Wharton Moneyball Cade Massey noted that the same idea can apply to modeling voting and prediction markets. In the FiveThirtyEight simulation (40,000 runs), Joe Biden wins eighty-seven times out of one hundred.

What’s the gap between 87 and 66?

  • Potential polling errors. 538 is an aggregation. Put another way, the level of awareness while driving one hour twelve times is not the same as driving twelve hours one time.
  • The Brady effect. There’s just more room for ‘something to happen‘ in one direction instead of another.
  • Matt’s Twitter handle +EV gives an idea too. It could be that Donald Trump’s odds to wins are less than a coin flip just not as bad as a single number on a roll of the dice. That middle area is the market.
  • People like betting favorites, public teams, and for the safety.

A neighbor invited me to a watch party on November third. Another challenges himself to go as long as possible without finding out the news (in 2016 he made it three days). I follow things loosely but thinking about it this way does feel sharp.

As Howard Marks says, it’s not so much what you buy as what you pay. Brady, for those interested, is on pace to go over.

Baseline data

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One of the coronavirus problems, one of any system’s problems, is lack of good data. When data is precise and simple it’s just a math problem. This is why we have to gamble with coronavirus.

In mid-March I started to feel kinda ill. Did I have it? Everything pointed to yes.

I’d traveled through airports. I felt congested and achy. The news talked more about coronavirus than allergies. Wait. What? The noise of the news made me overlook the color of my car, which was a nicely tinged yellow thanks to an above average pollen count in central Florida. 

My problem was that the ‘fifth vital sign’ had overtaken all the others. Or put differently, the only data I was using was highly subjective. Instead of continuing my confoundedness I started counting. 

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Regularly tracking my temperature showed nothing to worry about.

The other potential problem at the the time was toilet paper. 

Well before we were storming stores and short sheets I had stocked up. But watching the paper pandemonium I had no idea how long our stockpiles would last. So, I counted. Our  conservative count is two rolls per person per month. Prior to counting, I’d never have known.

Now do emergency funds

Good data is an objective tool to use alongside the subjective. If we kinda feel ill, we can take temperatures. If we see toilet paper rolling out of stores, we can use a rule of thumb. If we’re worried about finances, we can compare spending to savings. Good data is the base rate, our adjustments are the subjective. 

In any quantitative field three things matter: counts, computations, and communications.

Without accurate counts, we know nothing. 

Without accurate counts and computations, we infer nothing. 

Without accurate counts, computations, and communications, we do nothing. 

Sometimes we jump the gun. We build a model and share it to the world. #dataisbeautiful. Sometimes though we just need to start at the beginning and count. 

Thanks for reading. 

Hand Washing Update

bathroom bottle clean container
Photo by Pixabay on Pexels.com

We looked at hand washing design research because conditions matter. People are influenced by their environment, often more than they realize. In that first post we highlighted to:

  • Turn off the water, to feel less rushed.
  • Make bosses (attending physicians) clean their hands.
  • Use incentives to reward (or penalize).
  • Put the hand-cleaning area adjacent to the need-hands-clean area.
  • Create a social expectation.

That research maps well to the EAST framework. To change behavior make things Easy, Attractive, Social, and Timely.

There are two updates since then.

First, The Behavioral Insights team researched which infographics communicated the best. Comparing seven ‘how to’ posters from around the world on 2,500 UK adults they found that “bright infographics with the step-by-step procedure prominently displayed without too much accompanying text” worked best to communicate good hand washing steps.

However, this was a ‘what I say’ question on a ‘what I do topic.’ Instead of hand washing it could have been a personal savings infographic about spending too much on a car. Sure, people will confirm they know the information but what would they do? It’s an encouraging start but more needs done.

Second, Google Search Trends for ‘hand wash’ negatively correlates with coronavirus cases. A few years ago, Google Trends predicted the flu rates ahead of the CDC but in following years erred enormously. Researchers suggested it was because people aren’t great at diagnosing the flu. How many times have you gone to WebMD AND had the thing. This bodes well for  the hand washing research, which stepped over that obstacle of unfamiliarity.

This focus on hand washing is timely but it’s also generalizable. It’s any verb. Investing. Driving. Loving. Parenting. All of these things are affected by the conditions they exist in.

Thank you for reading and supporting.

Parlay Maths

A gambling parlay is a bet where two or more things have to happen. Will you have coffee and eggs for breakfast is less likely—thus longer odds and higher payout–than just betting on one or the other.

And people love betting parlays. The most popular Super Bowl bet is the coin toss, and Americans bet seven billion dollars (legally) on the game. 

And casinos love people betting parlays. According to UNLV, sports books earn five percent on bets, except for parlays. On those bets casinos take 30%.

Why do bettors do so poorly? It’s a little too much psychology and a little too little numeracy. Bettors, said Rufus Peabody, love to bet for things to happen. It’s easier to imagine one outcome than all outcomes. It’s why the ‘no safety’ bet almost always has positive EV. 

Bettors also don’t consider the numbers in the right light. Two independent seventy percent events only both occur half the time. Let’s run with that.

According to smart air filters, a t-shirt-mask will stop 70% of an airborne bacteria which is smaller than the coronavirus. That’s good. But what if we parlay masks?

If I wear a mask a t-shirt-mask and you wear a t-shirt mask we’ve reduced the viral load ten-fold. Thirty-percent of thirty-percent is .09. 

The same math that makes parlays good for Vegas and bad for gamblers is what makes masks good for all of us.

I wore mine to the store for the first time. It felt kinda foolish. But then I did the math.

UNLV explains the casino win percentage as “Win percentage, or win as a percentage of drop, AKA hold percentage, the percentage of money wagered that the casino kept.”

Peabody also tweeted about this: 

Framing Employment

Framing is so important because it’s a way to get ‘free value’. Things well framed are perceived as well done—and perceived value is all there is.

I ran this one question poll on Mechanical Turk, Amazon’s data collection service, and Twitter to see how people perceive the same news. Each option describes the US labor market from mid-March to mid-April.

The question was, which one of these is the best (or least bad) way to describe what’s happened.

Over the last month..

The most important data isn’t that one section of the pie is larger than another but that there are sections of the pie. If  “135 million people remained employed” took the king’s share there would be nothing to figure out. In the many slices though we get many ideas.

Jason Zweig demonstrated this magnificently in a recent WSJ column. Imagine you’re of a certain age with a certain income and a certain promise of social security. It’s likely more than you realize. Zweig wrote:

The $2,000 a month that you and your spouse will each receive in the future has a present value of $772,235, according to OpenSocialSecurity.com.

That’s roughly what it would cost an insurance company to provide each of you with a guaranteed, inflation-adjusted $2,000 monthly payment for the rest of your lives (assuming you file for retirement benefits at age 70 and your spouse at 62).

So your expected Social Security payments are like a giant phantom annuity—a bundle of inflation-adjusted bonds you don’t own but whose income you have the right to receive. The same is true—usually without the ability to keep pace with inflation—if you are fortunate enough to have a defined-benefit pension plan.

Much of poker is played by the number. Professionals fold many more hands than they play because the numbers tell them that. But people don’t like to feel like automatons. They want action. When Annie Duke started teaching clients how to play poker she had to reframe how they saw the game.

Duke’s insight was to get her clients to choose to play by the numbers. She appealed to their meta side. They had to see the analytical next to the emotional and make a choice from those two options.

People are relative thinkers and many many decisions come down to framing one thing against another. It works for news, marketing, home purchases, dinner options, and dates. It works for everything.

 

Colossal Comprehension

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This is the earth.

Part of our quarantine education was to get outside and make some scale drawings of our solar system.

We made our earth one roadway wide, about twenty feet in diameter and paced off two hundred yards and drew the moon. It was five feet wide. The ISS was seven inches from the earth’s surface.

It’s always challenging to consider the scale of the universe. It’s huge. It’s so huge that Mars was sixty miles away in our little universe.

Part-of-the-reason Einstein marveled about compound interest is because scale is really hard to understand. Once things scale up or down past the human perspective we just don’t quite get it. This came up on two recent podcasts.

First, Peter Attia spoke with his daughter about the coronavirus. It was an excellent, simple, good-for-kids episode. So how big (or little) is the virus?

“If were to cut one of your hairs, and you can barely see the edge when it’s cut, how many coronaviruses do you think we could line up on the tip of your hair when it’s cut?” Attia asked

A thousand viruses. That’s beyond the human scale of understanding.

One the other end of the spectrum, and closer to the solar system situation was Cade Massey’s longhorn lament.

“One of the things that frustrated me most when I to talk with people was them saying ‘Well, you’re not going to get this if you’re young.’ We knew the probabilities are steeply related to age but there’s still a probability for every age group. Throw millions of people at a small probability and you’ve got some sick people. We just aren’t good psychologically with these kinds of probabilities.” Cade Massey

The percentage for infection, hospitalization, and ventilation are remarkably small.

New York City houses eight million people and the metro area is home to twenty-one million. Projections note that only .27% will need beds, and only .063% will need ventilators.

Right now my sixth grade daughter is learning percentages as parts of the whole. She answers questions like; “If sixty percent of a class of twenty-four are boys, how many children are in the class?”

That’s good sixth grade math but it gets hard with large numbers. One-fourth of a percent is really small but eight million is really large. How does someone make sense of that? We probably just need to think slow, not fast.