Computers Reduce Efficiency: Case Studies of the Solow Paradox (2023)

Complexity is the outcome of misunderstanding. The misunderstanding can come from lots of areas.

It could be from a requirements perspective: “I understand what I can build easily, but not what you want.”

It could be from an engineering perspective: “I understand what you want, but I don’t understand how to build that cohesively.”

It could be from a scientific perspective: “No one knows what tools we need to investigate this.”

I saw mentioned in other comments that CAD software doesn’t allow for sketching. As someone who was originally trained in drafting the old way, and who has used modern CAD systems to produce models for fantastically large physical simulations, I largely agree that sketching is lost. But the sketching that I can do on paper is just not at the same level of complexity as I can kinda do on my computer.

But the complexity of using the new tool obscures the fact that my model is much more complicated than I could otherwise manage using old tools. And that’s because I’m still learning. In fact, I have to “deploy” while I’m still in learning mode about a problem, unlike before, where I had to understand the problem in order to use the tools to draft the thing.

Being able to do something with a half-formed idea sounds like sketching, but when non-experts rely upon it, it’s pretty fragile. Because it wasn’t done.

Building a memex (something the author disparages multiple times) is super hard because we still don’t understand how to represent ideas separately from language, our original mental sketching tool. But people built Altavista and Google and LLMs anyway. And yeah, they’re super complex.

How does TCP/IP work over wireless connections? Poorly and with a lot of complexity. Why? Because the concept of a connection is ill-defined when communication relies on ephemeral signaling.

But despite the complexity, it is useful and fun to use only half-baked ideas. Just like it’s fun to use language to describe stuff I don’t understand, but merely experience. Graduation. Being a parent to a sick child. Losing a loved one.

Under appreciated: Automation creates, or dramatically enhances, the need to fully understand problems and solutions at the most detailed and practical levels. Because automation removes the valuable manual ad hoc flexibility to adapt to most wonkiness.

1. When a job requires a mix of human and computer work, productivity changes are very dependent on interface details. Even one slightly confusing GUI, slowness of feedback, a tool that isn't quite as flexible as a job needs, or an inability to see/edit/use related information at the same time, can greatly harm productivity.

2. When a job is completely automated, productivity can go way up. But this productivity doesn't get attributed to human workers, it is corporate productivity. And then only if this highly optimized task really provides value. There is a lot of performative information processing, with conjectured long term payoffs, serving the needs of management and tech workers to look busy, and believe they are valuable.

For both human and corporate productivity, automation makes it extremely easy to decrease productivity due to the most subtle mismatches between problems and solutions.

When work is done by hand, these mismatches tend to be glaringly obvious, less tolerated, and more easily mitigated or eliminated.

>By the 1960s, the systematic selection for competence came into direct conflict with the political imperatives of the civil rights movement. During the period from 1961 to 1972, a series of Supreme Court rulings, executive orders, and laws—most critically, the Civil Rights Act of 1964—put meritocracy and the new political imperative of protected-group diversity on a collision course.

Lot of this kind of stuff. Thesis summarized is that America is going to hell in a handbasket because the Feds are demanding that black people get hired once in a blue moon, a practice which dilutes meritocracy, according to the author.

Heh.

>When this was not enough, MIT increased its gender diversity by simply offering jobs to previously rejected female candidates. While no university will admit to letting standards slip for the sake of diversity, no one has offered a serious argument why the new processes produce higher or even equivalent quality faculty as opposed to simply more diverse faculty.

Ah, MIT now pumping out dumb blondes, are they? Having encountered such people as the author of this piece several times before,I have to wonder about the "meritocracy" process in place prior. So "merit" correlates positively with sunscreen purchases, and inversely to tampon expenditure, does it?

>This effect was likely seen in a recent paper by McDonald, Keeves, and Westphal. The paper points out that white male senior leaders reduce their engagement following the appointment of a minority CEO. While it is possible that author Ijeoma Oluo is correct, and that white men have so much unconscious bias raging inside of them that the appointment of a diverse CEO sends them into a tailspin of resentment, there is another more plausible explanation. When boards choose diverse CEOs to make a political statement, high performers who see an organization shifting away from valuing honest performance respond by disengaging.

I mean... is there an actual difference here? First, I'm not convinced it's unconscious bias. Second, this "disengagement" certainly seems like the kind of "meritocracy" we have sadly grown quite familiar with.

>The problem is that complex systems have not made us more knowledgeable and capable, but instead they have become a crutch.

This article kind of sounds like some people want the old crutch back. There is a non trivial question of your fitness for this, however. In the 50's the rise of psychotherapy made it quite clear that people were cracking under the strain of delivering "merit."

I'm quite delighted that this is such a concern to you people. Excellent.

Sounds like an argument for C, honestly. After all, that complexity is either in the language, or solved on a case by case basis. Every patch adds complexity, because it reflects changes in the business environment that presents the problem the code is solving.

Not even close.

That can break and isn’t perfectly 100% available like my analog method and has much less transportability