Daily one-pagers about AI, leadership, technology, and being human.

johnmaconline

I'm writing to think, learn, and remember in public. I'll be here everyday.

April 15, 2024 2 minute read

The Cobra Effect

The attempted solution to a problem makes the problem worse through unintended consequences. 

Economic theory states that you usually get what you incentivize properly. This one is closely related to Goodhart’s Law. 

Colonial India had a live cobra problem. So, the government offered a reward for every dead cobra. This worked. Eventually, there are very few live cobras. 

But now, the people making money from the incentive had a dead cobra problem. So, the people started breeding cobras just to kill them. This worked.

But then the government caught wind of the scam and eliminated the reward. So, the breeders just released all the captive snakes back into the wild.

And once again, colonial India had a live cobra problem.

Removing older, more polluting vehicles from the road can increase overall emissions due to the environmental cost of manufacturing new vehicles.

Using antibiotics to promote livestock growth can lead to the proliferation of antibiotic-resistant bacteria.

Pay-as-you-throw schemes to encourage recycling and reduce waste can increase illegal dumping.

Traffic congestion taxes to reduce center city traffic can lead to grid-lock in neighborhoods just outside the fee zone.

Solutions to multi-variable and complex problems require rigorous analysis, experimentation, and assessment of consequences and reactions to incentive schemes. Reassessment of data. Adjustments over time. Willingness to change directions. Admission of false starts. Unbiased rethinking. Empathy and kindness. Forgiveness. 

What doesn’t work is soundbite-worthy, toggle-switch, single-variable, fist-pumping slogans. 

April 14, 2024 2 minute read

Hofstadter’s Law

It always takes longer than you expect, even when you take into account Hofstadter’s Law.

One of my friends and I have a funny little tension around the scheduling of software development work. We call it the 3X fudge factor. I look at the work he’s to do and I come up with my estimate of how long it should take him. I tell him, and then he immediately multiplies by three. If I say it should take a week, he says it’ll be three weeks.

It works in reverse also. If he gives me an estimate of three days, I immediately translate that as one day.

Who’s right? Well, we both are. Kind of.

I’m right if he’s totally focused, nobody gets in his way, and nothing goes wrong—the best-case scenario. But when does that happen? Never. So, his 3X estimate usually turns out to be closer to right and sometimes even aggressive, as the second clause of Hofstadter’s Law kicks in.

But you gotta know the best-case scenario to know how much Hofstadter’s Law will effect the final outcome. The longer the best-case, the more effect. Plus, if we need him to get it done ASAP, I can use my position to create the best possible environment by reassigning responsibilities, swatting flies, and giving him every possibility to remain focused.

One of the key leadership attributes is knowing how and when to apply Hofstadter’s Law.

April 13, 2024 1 minute read

Braess’s Paradox

Adding extra capacity sometimes leads to worse overall performance.

“More is better.”
“If I just had more money.”
“That’s easy for you, you have more money/time/land/etc.”

We often conflate abundance with advantage. It can be. But it isn’t automatically.

a) Don’t let them tell you why you can’t, what you can’t, or how amazing you can’t be with what you have.
b) Don’t tell yourself why you can’t, what you can’t, or how amazing you can’t be with what you have.

April 12, 2024 3 minute read

The Principle of Least Astonishment

Last weekend, I drove to NYC to deposit my oldest son and his girlfriend back in Brooklyn after they had spent a nice weekend with us. Up and back through three of the five boroughs: Staten Island, Brooklyn, and Manhattan. I’ve driven through NYC dozens, maybe 100’s of times, and even before they lived there, I was already a hardened veteran of NYC driving. As soon as I cross the Goethals Bridge or emerge from the Holland Tunnel into the canyons of lower Manhattan, I’m in NYC driver mode. Like flicking a switch.

I’m a freakin pro. And truth be told, I love it.

U-turn in the middle of the street? Yup. Turn left from the right lane? Of course. Just stop in the middle and double park? You betcha.

I’ve not (yet) had an accident, and I know why. Because when I’m driving around there, I expect any and all things all the time. Just as I don’t think twice about disregarding all traffic decorum, I expect all of those around me to do the same.

Of course you can cut me off. Oh, you want to stick your bumper into the 8-inch space separating me and the guy in front of me? Sure, go ahead. Going around me on the sidewalk to the right? Be my guest.

It’s all good because none of it is astonishing to me in this context. I expect it, I’m ready for it, I adjust, and it’s no big deal. And yeah, I do it also.

But what happens on the roads in the small rural community in eastern Pennsylvania in which I live? Nothing like that. It’s all slower, orderly, and calm. I don’t expect any of that.

But then someone gets cut off, and what happens? Boom. Accident. Or, at the very least, “You idiot! Where’d you learn to drive!” It might bother me for the rest of the day.

This is the Principle of Least Astonishment — minimizing confusion and unexpected behaviors while maximizing intuitive understanding.

We in the software development world use the Priniciple of Least Astonishment (also called the Law of Least Surprise) all the time.

If we’re doing our job and using this principle, you (the user) can figure out how to do things on your phone or computer that nobody has taught you explicitly. For example, nobody taught you how to find the settings on your phone. You know they’re in the “Settings” app. We use this principle under the covers as well, even in the nitty-gritty interworkings of the technology. We argue vehemently about how this API should work or what should data it requires.

Least astonishment changes with the intuition of the culture and its people. Which means it changes over time and with context. If you handed an iPhone to George Washington, he wouldn’t be able to find the settings, nor even understand how to turn it on because he doesn’t have any context or intuitive build-up for the technology.

He would be very astonished.

Next time you’re organizing your closet, developing a set of guidelines for your Church committee, or driving around your town, make sure you’re applying the Principle of Least Astonishment. It will serve you well.

April 11, 2024 2 minute read

Parkinson’s Law

Work expands to fill the time available for completion.

I hate meetings at work. And you do, too. I know you do. 

Long ago, bleary-eyed in the middle of the night, I learned a couple of valuable lessons about meetings. The first is we have way too many. Therefore, the first step in taking back ownership of your time is to decline useless meetings. But the second was just as important — meetings will last as long as the calendar says they will.

If you invite people to a one-hour meeting, someone, or sometimes several someones, will yammer on for 60 minutes until the bell dings. Then, the herd will just move on to the next meeting, where someone else will yammer on for the full 60 minutes.

It’s stupid. It’s a productivity killer (personally and organizationally). It sucks your energy and willingness to live. 

But it’s also not really someone’s fault. It’s just a trait of human beings. It’s kinda just in us. Hence, the naming of the phenomena. 

So how do you combat it? By also applying a little human psychology of your own.

  1. Change your default meeting time to 15 minutes. Only selectively and intentionally schedule a discussion for longer than 15 minutes. 
  2. Why have a meeting if you can work it out with a few exchanges on Slack? Do it.
  3. Announce that you have hard stop at 15/30/60 minutes. Then leave/drop at that time. 

You can do this. Break the grip of Parkinson’s Law. 

April 10, 2024 1 minute read

Goodhart’s Law

When a measure becomes a target, it ceases to be a good measure.

“Is this going to be on the test?”
“What code do I use to ensure this is covered by insurance?”
“How do you rank me against my peers?”

We game the system. It’s what we do.

Great leaders look outside the system, procedures, and policies to recognize great performance and impact.

April 9, 2024 1 minute read

Two-Way and One-Way Door Decisions

Two-way door decisions are the kind where you can always change your mind, back up, and make the other decision. Ordering a burger is a two-way door decision.

One-way door decisions are the kind where you can’t go back once you make it. Jumping out of the airplane is a one-way door decision.

Two-way door decisions allow testing, trying new things, and changing one’s mind. One-way door decisions require commitment, careful consideration, and learning as much as possible before making it.

Often, we trick ourselves into thinking that two-way door decisions are actually one-way door decisions. That’s not surprising because restricting the number of variables is a hack we use to solve problems. If we tell ourselves, “OK, I have to commit,” and believe it, we’re more likely to make that outcome successful. Let’s not consider the other side.

But most decisions we make are two-way door decisions. There’s usually a path to back out, chang your mind, and do the other thing.

Sometimes you gotta bite the bullet and start again. That’s just being a human.

April 8, 2024 1 minute read

Not My Job

Customer: Can you help me with this problem?
Clerk: Not my job.

Manager: Will you help Jane figure this out?
Employee: Not my job.

Test Engineer: Can you help me understand how this works?
Software Engineer: Not my job.

“Not my job” may seem like the opposite, or at least orthogonal to “just doing my job.” But at their core, they’re both about responsibility — specifically, a deflection of responsibility (if even in a faux manner).

Not my job is an attitude.

I’ve banned the phrase “not my job” from my teams. That doesn’t mean that we always take on everything, no matter the request. It just means we don’t have the “not my job” attitude. If the request or task isn’t something we can or should handle, then we set the requestor on the right path as best we can.

We help. We don’t deflect responsibility.

Is it your job?

April 7, 2024 1 minute read

Just Doing My Job

Reporter: What were you thinking when you ran into the burning building to save that child?
Firefighter: Just doing my job.

Tenant: How could you evict us?
Sheriff: Just doing my job.

Parent: Why did you help our son and tutor him after school and on weekends?
Teacher: Just doing my job.

Regulator: How could you continue after knowing your company was dumping illegally?
Employee: Just doing my job.

Just doing my job is a utility answer. It provides both a cover and a deflection for real or faux humbleness. Equal parts “not my responsibility” and “oh, thank you for noticing that I took responsibility.” 

Doing your job in either case is about responsibility. 

Your company and customers need someone who takes responsibility. Your team needs someone who takes responsibility. Your community, Church, and book group need someone who takes responsibility. This world need people who take responsibility. 

Are you just doing your job?

April 6, 2024 2 minute read

AI and Music

The music artists have stood up.

Much like the authors did over the summer, songwriters and musicians have penned an open letter to the tech industry — let’s pump the brakes on music generation with AI.

And like the authors, the musicians are afraid of two things:

  1. Losing revenue
  2. AI will generate music that sounds like them or is as good as or better than they are (which, for many, but not all, is just a form of the first thing)

“When used irresponsibly, AI poses enormous threats to our ability to protect our privacy, our identities, our music and our livelihoods. Some of the biggest and most powerful companies are, without permission, using our work to train AI models. … For many working musicians, artists and songwriters who are just trying to make ends meet, this would be catastrophic.”

“This assault on human creativity must be stopped. We must protect against the predatory use of AI to steal professional artists’ voices and likenesses, violate creators’ rights, and destroy the music ecosystem.”

As with the authors and anybody whose job sits in AI’s crosshairs, I agree with part of their argument. 

The copyright and “likeness” argument is very interesting. Let’s face it: Humans do this all the time, not just with the arts but also with science. We always use those who came before us as inspiration and sometimes quite directly to move the state of the art forward. Art and science are additive. 

Why is AI different than humans in this regard? Is it scale? Is it that AI has illegally ingested the content?

I’m interested to see how it turns out. I agree that protection for the creators must exist. Basically, I trust the legal process.

The fear of “AI might do our job better than us” is, in my opinion, a non-argument.

Drum machines and GarageBand didn’t put drummers out of business. Synthesizers haven’t put orchestras and horn sections out of business. Pre-recorded loops haven’t put touring musicians out of business.

AI is a brand new toolbox full of new toys. The true creators will find innovative and interesting ways to incorporate the new AI toolbox into their art. 

They always have. They always will. 

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