It's perniciously easy to accept societal defaults without questioning whether something non-standard would be better for you.

Noticed this heavily during spouse's pregnancy and in parenting. We benefited hugely from doing the opposite of many people in our family+network. Felt this sharply as we were looking at options for the Abrahamic ritual for son, and it struck both of us—what even the fuck are we doing this utterly stupid thing for? Similarly our daycare choices, homeschool choices, etc.

This'd be better with more examples but I'd like to leave it general for privacy.

An area where I notice this hugely is career progression. I thought programmers picked up through cultural osmosis that

- managers frequently undermine their projects and
- clients frequently give you fake requirements (level12.io/who-wins/)

but so many devs in my circle default to "I will grow up to be a manager" till I explain they sound like a child saying "I'm gonna be astronaut" or "I'm gonna have kids".

I'm fine with people becoming parents, doing grad school, or becoming a manager if they have evidence that they'd be good at these incredibly difficult and alien tasks—

- your performance in regular school is not indicative of your preparedness to do research

- unless you grew up around people having kids (very rare in our society), you're woefully unprepared to raise kids

- being a good dev is orthogonal to being a good manager—managing is a brand new skill you'll suck at for years.

Obligatory reference to Peter Principle that I'm glad they teach kids in college these days—people are rewarded for skill in one area by being moved to another they're woefully unskilled in (I had to read it in Gall's hilarious ).

I'm trying to unindoctrinate devs in my circle to not assume management is some default next life step—if your company lacks a technical non-management route (which may or may not be a big red flag), you could always leave for the many companies that do.

Sidebar.

I'm rereading my copy of the first edition of Gall's (which I first picked up more than fifteen years ago) and it's so ! At least in its statement of the problem:

> Things (Things Generally/All Things/The Whole Works) Are Indeed Not Working Very Well. In Fact, They Never Did.

and its call to resign yourself to that problem

> Large Complex Systems Are Beyond Human Capacity To Evaluate.

but Gall didn't quite reach Buddha's level in suggesting a meta-solution!

Follow

As I was thinking about the costs of conventional wisdom and unexamined societal defaults, "The new dot com bubble is here: it’s called online advertising" landed:

thecorrespondent.com/100/the-n

This explains the insane, expensive, poisonous unexamined beliefs about 's (non-)efficacy.

“all the traffic that had previously come from paid links was now coming in through ordinary links. … Annually, eBay was burning a good $20m on ads targeting the keyword ‘eBay’.”

“What was the effect of pulling the ads? Almost none. For every dollar eBay spent on search advertising, they lost roughly 63 cents… [in sidebar] The 95% confidence interval is between negative $0.03 and negative $1.24.”

And bravo for citing confidence intervals in a lay piece!

"I kind of had the belief that most economists have: businesses are advertising, so it must be good. Because otherwise why would they do it? … But after my experience at eBay that’s all out of the window."

'Picture this. Luigi’s Pizzeria hires three teenagers to hand out coupons to passersby. After a few weeks of flyering, one of the three turns out to be a marketing genius. Customers keep showing up with coupons distributed by this particular kid. … "I stand in the waiting area of the pizzeria."'

Lovely image to understand selection effect vs advertising effect.

"the brightest minds of this generation are creating algorithms which only increase the effects of selection"—aka 'targeted ads'.

'Algorithmic targeting may be technologically ingenious, but if you’re targeting the wrong thing then it’s of no use to advertisers. Most advertising platforms can’t tell clients whether their algorithms are just putting fully-automated teenagers in the waiting area (increasing the selection effect) or whether they’re bringing in people who wouldn’t have come in otherwise (increasing the advertising effect).'

I love the teenagers handing out flyers in the restaurant lobby visual.

"Economists at conducted 15 experiments… A large retailer launched a Facebook campaign. Initially it was assumed that the retailer’s ad would only have to be shown 1,490 times before one person actually bought something. But the experiment revealed that many of those people would have shopped there anyway; only one in 14,300 found the webshop because of the ad. … selection effects were almost 10 times stronger than the advertising effect"

The willful blindness to waste—jawdropping.

'Advertising rationally, the way it’s described in economic textbooks, is unattainable. Then how do advertisers know what they ought to pay for ads? "Yeah, basically they don’t know," Lewis said in one of those throw-away clauses that kept running through my head for days after.'

😖

"Following the news about the millions of dollars eBay had wasted, brand keyword advertising only declined by 10%. The vast majority of businesses proved hell-bent on throwing away their money."

😒

This article is fire. I have to pay someone for this: their inline footnotes are amazing and constantly link to published papers, e.g.

'When these experiments showed that ads were utterly pointless, advertisers were not bothered in the slightest. They charged gaily ahead, buying ad after ad.

> See Rao, Justin M., and Andrey Simonov. "Firms’ reactions to public information on business practices: The case of search advertising." Quantitative Marketing and Economics 17.2 (2019)'

and charts too!

"It might sound crazy, but companies are not equipped to assess whether their ad spending actually makes money. It is in the best interest of a firm like eBay to know whether its campaigns are profitable, but not so for eBay’s marketing department. … The fact that management often has no idea how to interpret the numbers is not helpful either."

"Marketers are often most successful at marketing their own marketing."

Or, in :

> The System Itself Does Not Do What It Says It Is Doing

In the end, of course the value of something is what people pay for it (ads, bonds, and boat shoes). But this thread shows a couple of big areas where people pay for stupid things, because doing something stupid as a group can help belonging.

So one takeaway I think is, as you build your toolkit to detect and measure things (statistics, code, ETLs, etc.), make it bullshit-proof. Aggressively science your findings—be costantly open to the possibility you've completely fooled yourself.

Here's the "appendices" section of the toot thread.

"Decisions have to be made, somebody has to lay out a strategy, doubt must stop at some point. For that reason, companies hire overconfident people who act like they know what they cannot possibly know."

I love this statement of fact: likely we all know of that one guy (or several guys—invariably guys) whose overconfidence got them power. Of course they see that power as meritocratic reward for talent.

Appendix 2—from the linked causaleffect.io/ghost-ads-a-re:

"In-campaign optimization breaks PSA experiments: to maximize performance of the focal ad and PSA, the ad platform will assign different types of consumers to be exposed to the PSA or the focal ad."

Translation—they can measure ad effectiveness by using ads for charities as a control group. But most campaigns first optimize WHO GETS SHOWN THE CHARITY AD AND WHO GETS SHOWN THE REAL AD.

What kind of unethical scum dev would sell this??

Appendix 3: for those who want to study , see

- this 1990s-style page is a good summary, you have to click the various sub-links: draftymanor.com/bart/systems1.

- laetusinpraesens.org/docs/syst for a review of John Gall's book.

Appendix 4: "5 hours to assess an employee's performance will have lots of false positives / false negatives… companies drive all of their business decisions with data; recruiting shouldn't be any different."

(news.ycombinator.com/item?id=2 if you're lucky enough to not know, FAANG=FaceAppAmazNetflGoog, darling tech stocks/employers)

This thread has hopefully prepared you to evaluate this steaming pile of poo—if big tech firm blow (& accept) cash for ads, recruiting likely too.

@22 this entire thread is a trip. Really good information to know

@22
This entire thread is brilliant, and I want to boost all of it, but a choice teaser will have to do.

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