PhD Chemical Engineer Finds New Career Booty Hooping

I read Straw Dogs, a critique of modern society by English political philosopher John Gray, shortly after it was published in 2002. (No relation to the movie with the same name). Wikipedia summarizes the author’s view as, “Gray blames humanism, and its central view of humanity, for much of the destruction of the natural world, and sees technology as just a tool by which humans will continue destroying the planet and each other.”  I cannot recommend the book as a whole – the reader is left in a state of despairing passivity. My AI justly notes, “Critiques of John Gray’s Straw Dogs: Thoughts on Humans and Other Animals generally center on its extreme pessimismlogical inconsistencies, and rhetorical excesses.”  

All that said, the book did contain many interesting observations. One line of thought that struck me at the time was that, with increasing efficiencies in the production of basic goods and services, more and more human effort will go into simply entertaining or “distracting” each other:

The days when the economy was dominated by agriculture are long gone. Those of industry are nearly over. Economic life is no longer geared chiefly to production. To what then is it geared? To distraction. Contemporary capitalism is prodigiously productive, but the imperative that drives is not productivity. It is to keep boredom at bay. With wants so quickly sated, the economy soon comes to depend on the manufacture of ever more exotic needs.

I was reminded of that line of thought when, at a recent gathering of PhD chemical engineers, I heard that one of our number has become somewhat well-known for a late-career shift. She goes by the name Andrea Hulamyhoop these days. (I happen to know her real last name and approximate age, but she wishes to keep those private).

Her father was a chemical engineering professor, and she earned a PhD in the discipline at Princeton University. She was just going along living a fairly normal sort of life, with a regular job, when without warning, it happened:

Then one day, she saw a girl hula hooping. “She looked really free and happy, and I thought, interesting, maybe I’ll try it.” A few minutes at a time quickly became an obsession. Turns out, there are whole online communities of hula hoopers who share tips and support. Conferences. And many shows and events looking for a pro to dazzle and inspire audiences.

“The hula hoop has changed everything in my life,” she says. “I didn’t know I could become a fit, sporty person. I didn’t know I was one. I love performing, and I love people, and I love parties.

“I always thought my life was a bit OK. My kids were grown up. I was enjoying my job,” she says. “But you know, we kind of think, is this all there is? And then to realize there’s this whole world — it’s been incredible. I’m happier than I’ve ever been in my life.”

Andrea Hulamyhoop doesn’t just swirl a hoop around her waist. She can twirl multiple hoops around multiple body parts, with style. She is perhaps best known for her appearance on America’s Got Talent in 2025, where she smashed previous records by bending over and twirling a hoop around her rear end for just over an hour and fifteen minutes. The crowd went wild.

The physics of this feat seem almost impossible, but seeing is believing. Andrea gives a gracious tutorial here.

When I asked who is the most famous holder of a Princeton chemical engineering PhD, both ChatGPT and Claude insisted that former GE president Jack Welch is more well-known than Andrea the butt-hooper, but I doubt that is true below a certain audience age bracket. She has some 17,000 Instagram followers. I’d be willing to bet that in a crowd of under-40’s today, if you asked “Have you heard about the guy who was president of GE in the 1980’s and 90’s?” or “Have you heard about the gal who can twirl a hula hoop on her butt?”, Andrea Hulamyhoop would win.

All this brought back to my mind the notion that as a society we are able to afford to devote a great deal of time to sheer entertainment, rather than growing potatoes.   A comment by a certain @petesounds9321 on Andrea’s epic 2025 AGT YouTube showed he had evidently not read Straw Dogs:

“I’d say we need more scientists than hula hoopers but hey…maybe I’m way off.”

The Day the Cloud Evaporated: Life After the Data Center Collapse (A Guest Post by AI)

This is a “guest” blog post that I asked Google Gemini Pro to write. Data centers are increasingly becoming a political issue in communities across America. People are asking questions like: “Why do we need these things? How much water will this use?” Because these are sometimes referred to as “AI Data Centers,” people might assume that data centers are primarily about creating cat memes and fake videos. And it’s true that’s a part of AI, and it’s true that much of the new data center construction is for AI.

But… data centers have been around for a while. People are only now taking notice of them, for the most part. To better understand this issue, I asked — what else? — AI to explain how much data centers are used in our daily lives. AI in this case means Google Gemini Pro.

I’ll paste the full guest post below, but I want to point something out first: this blog post makes no mention of AI. Instead, it talks about: GPS and mapping apps; almost everything you do if you work in an office; credit cards and digital banking; news and social media. All of these things rely on data centers and would cease to function without data centers. That’s not because I asked Gemini to leave out AI from the guest post — when I followed up on this omission, Gemini said “It was a calculated omission—partly to keep the focus on the immediate ‘analog’ shock to daily life.” Most people probably wouldn’t care of they lost the ability to create funny images with AI. They would care if they lost all of their photos, access to their Dropbox account, and the ability to send email.

You could interpret all of this as saying we are “too dependent” on data centers and the modern Internet. You could also say we are “too dependent” on electricity. Or modern plumbing. Or modern supply chains. Or agriculture. Modern life is based on modern technology. I don’t know if it really makes sense to say we are “dependent” on these things, other than that we use them and they are beneficial.

Anyway, on to the guest post from Google Gemini Pro:


The Day the Cloud Evaporated: Life After the Data Center Collapse

Imagine waking up tomorrow morning in your suburban home in Ohio, or your apartment in Seattle. You reach for your smartphone to silence the alarm, but the screen is a stubborn, glowing rectangle of error messages. You try to check the weather, but the app’s spinning wheel never stops. You try to text your partner, but the message stays “Sending…” until it eventually fails.

This isn’t just a bad Wi-Fi connection. Every data center on Earth—those massive, humming warehouses filled with silicon and cooling fans—has vanished. In an instant, the “brain” of the modern world has been lobotomized. For the average person in the United States, life wouldn’t just slow down; it would fundamentally reset to 1950, but without the physical infrastructure of 1950 to catch the fall.

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100,000 Glyphosate Lawsuits: Why Roundup Does Not Kill Your Weeds Like It Used To

I don’t like wasting time bending over and pulling out weeds, one by one. Much more efficient to go squirt squirt and eliminate lots of weeds at a time. But I realized in the past year that the Roundup I spritzed on the weeds in my mulch beds and sidewalk cracks just wasn’t killing them like it used to. The weeds would shrivel a bit, but then many would bounce right back. So, when I went to Home Depot to buy some more this week, I looked at the ingredients on the label. What?? Where is the glyphosate? For decades, “Roundup” was synonymous with glyphosate.

Glyphosate has several desirable properties as an herbicide. You spray it on the leaves, and it kills the plants right down to the roots. However, it has minimal residual toxicity in the soil, so it is unlikely to kill any plants you did not spray, and you can replant quickly in a soil patch that you had cleared with glyphosate. Farmers love it, because you can buy genetically engineered strains of crops like corn that are immune to glyphosate, so you can spray your fields to kill weeds without harming standing crops.

The glyphosate story is much bigger than homeowners bending over to pull weeds. The chemical has become indispensable for current agriculture. Global glyphosate sales are about $10 billion per year, and its impact on crop productivity is enormous. A 2017 study (apparently not paid for by Monsanto) predicted dire effects of discontinuance:

World prices of all grains, oilseeds and sugar are expected to rise, especially soybeans (+5.4%) and rapeseed (+2%). The welfare impacts are mostly negative, with global welfare falling by $7,408 million per year. Land use changes will arise, with an additional cropping area of 762,000 ha, of which 53% derives from new land brought into cropping agriculture, including 167,000 of deforestation. These land use changes are likely to induce the generation of an additional 234,000 million kg of carbon dioxide emissions.

What’s not to like about glyphosate? Well, maybe it causes cancers in humans. This is a contested claim, and I don’t have the expertise to penetrate the arguments. Because glyphosate makers like Monsanto and its successors Bayer have deep pockets, lawyers on contingency have swarmed like killer bees to file lawsuits, over 100,000 of them, of which about 60,000 remain active globally.

National security issues have muddied the waters here. For instance, Robert F. Kennedy, Jr. led a landmark legal case against Monsanto in 2018, securing a $289 million jury verdict (later reduced on appeal to $20.4 million) for a school groundskeeper who developed non-Hodgkin’s lymphoma after prolonged exposure to Roundup. That case energized a bazillion further lawsuits. But now Kennedy is going along with the current administration’s position that it is strategically necessary to maintain production and responsible access to glyphosate: farmers demand it, and Bayer operates the only plant in the U.S. producing significant amounts of elemental phosphorus, which is a vital material for defense and, increasingly, for lithium batteries.

Naturally, Bayer denies that glyphosate is particularly harmful. The firm continues to sell the product to farmers and landscape professionals, but it has removed it from retail bottles of Roundup you see on Home Depot shelves, in an effort to reduce exposure for further litigation.

What have they substituted for good old glyphosate? I found a brew of three other chemicals. I can report reliably that this mixture is much less effective, especially on grasses and on well-established weeds. The Internet backs up my observations. The Iowa State garden extension has a great table of the real-world effects of all common herbicides.

So, what to do? For grasses in my backyard gravel patch, I am spraying multiple times. If that doesn’t work, I may try covering that area with a black tarp for a month to kill the grass. I have considered buying a propane flamethrower weeder, but that seems only effective on the same things the current wimpy Roundup kills (small/young broadleaf weeds).

For mulched areas, I am incentivized to keep up with fresh mulch to keep weeds from growing in the first place. For larger weeds, I have now found myself bending down low, grasping them close to the ground, and actually pulling them out by hand.

A Rant about Long Run Problems and Passe Solutions

If you listen to or read major economists discussing what they think are big-picture problems, then their list usually includes three topics: Fertility, Culture, & the Fiscal Health.  On the wonkier side, you’ll also hear that housing scarcity and affordability is a problem, but let’s stick with the first three.

Fertility

People are deciding to have fewer children for a variety of reasons. In no particular order, the reasons include greater access to financial institutions, more popular female education, higher female wages, lower infant mortality, and falling religiosity. Some also speculate that housing affordability, safety regulations, and social safety nets contribute too.

What’s wrong with lower fertility? In an objective sense, there is nothing wrong. But, in the sense that people value similar things, we are in somewhat uncharted territory. Realized fertility is dropping across the globe. We know that economies of scale increase productivity and real wages. We also know that technological innovation comes from having more minds engaged with economic problems. It’s possible that labor productivity rises faster than the productivity that we lose with smaller scale, but it’s an open question. What happens to the liberal societies and polities when the liberals fail to persist? These are big geopolitical concerns.

Culture

People seem to be more fragmented religiously and culturally. Social scientists used to discuss Judeo-Christian norms more often. Sometimes you’d hear about English or Roman legal tradition or enlightenment values. But now, there seems to be very little in terms of common social cohesion. In the USA, the general common culture seems to be ‘smile and be nice’. That’s not the worst common rule, but it’s not enough to hang our hat on for a capable liberal state.

The lack of cultural cohesion isn’t my own particular concern – public intellectuals in economics and elsewhere feel like there is a problem. There is a mix of reasoning behind the concern. Some people are worried about transmitting values to the next generation, some are worried about how people behave when no one’s watching, and still others are worried about simply lacking a Schelling  point that coordinates large scale economic cooperation.

Fiscal Health

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How to Install Drywall

Nearly every interior wall and ceiling in every home in America is covered with sheetrock = drywall = gypsum board. Sheetrock (a brand name for drywall) consists of an interior layer of rigid gypsum (a mineral composed of calcium sulfate dihydrate) plus some additives, with outside layers of strong paper or fiberglass. It normally comes in 4 ft x 8 ft sheets.

Normal houses have a framework of mainly 2×4 or larger wood lumber. Each wall has vertical 2×4 studs, spaced every 16”. Sheetrock is trimmed to size, and nailed or (these days) screwed into the studs.

That is the theory, anyway.

I have never done this stuff at large scale before, other than clumsily patching occasional small dings in a wall. A little while ago, I got to experience the process, hands-on. I was part of a team that helped someone whose basement had flooded. We cut out the lower ~4 ft of drywall, and replaced it with fresh drywall.

First, how to you cut drywall? A long, straight cut is accomplished by drawing a straight line and cutting along it, all the way through one layer of the facing paper. Then you hang the drywall sheet on the edge of a table, and crack the interior gypsum layer. Then you cut the other side of the paper. The end result of such a cut is like this:

Typically, you install drywall on the ceiling first. Then the top 4 ft of the walls, then the bottom 4 ft of the walls. You butt the pieces close to each other. For the lowest piece of drywall, you insert a curved metal wedge under it, and step on the wedge with your foot to lift that drywall piece to butt its top edge up against the upper piece. If you look carefully near the middle of the following photo, you can see the red wedge I used to jack up that small lower piece of drywall. It’s OK to leave a gap between the floor and the lower edge of the bottom drywall, since that gap will be covered by baseboard.

This was in a bathroom. I cut the lower green pieces with a little hand power saw, and screwed them into the studs, using the green and black driver visible on the stand in the left foreground.

The next two photos are before and after of a bedroom wall, again showing the bottom course of sheetrock we installed.

Filling in Cracks and Holes

As you can see, at this stage, there are like ¼” cracks between the installed sheets of sheetrock, and the mounting screw holes are visible. These imperfections are filled in with goo called joint compound, or “mud.” The mud is applied with a “knife” like this:

Cracks are covered with paper or fiberglass tape, with mud smeared over the tape. Typically, three layers of mud are needed to achieve perfect, smooth coverage. Each layer must dry hard before applying the next layer. Each layer may be sanded lightly as needed.

 A key technique is to tilt the knife so the mud is maybe 1/16” thick over the tape or over a screw, but taper the mud to zero thickness on the wall away from the tape or screw. This feathering is essential; if your mud layer ends with appreciable thickness instead of feathering, you have to do a lot of sanding to get a smooth blending into the plain drywall at that edge. Pro tip: carefully stir more water into the joint compound as needed to keep it wet and flowing, especially for overnight storage. This video from Vancouver Carpenter displays mudding technique.

That is mainly it. For perspective and confidence building, it is helpful to work with an expert, as I was able to do.

What is an AI Skill?

If you’ve been on LinkedIn recently, then you may have seen the chatter about teaching your artificial intelligence to have various skills. I saw one post by a guy who claimed to have created several skills, each representing a tech billionaire.

At first, I thought “I am behind the 8-ball. What is this new thing?”. Obviously I know what the word “skill” is and how people use it, but I had not encountered its use in the context of AI having it. What does it mean for an AI to have a skill? I somewhat dreaded the the work of learning the new skill of teaching my AI skills.

Then I had lunch with a computer scientist and I learned that skills are nothing new.

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Regulatory Burden By Presidential Administration

During president Trump’s first term in office, he made a bunch of waves (as he’s wont to do). His more educated supporters said that he engaged in substantial deregulation of telecommunications, which got a lot of press. There was a quiet contingent of educated voters who were relatively silently supportive on Trump’s regulatory policy, even if his character was indefensible or his other policy was less desirable.

But was Trump a great deregulator? Or was it one of those cases when we say that he regulated *less* than his fellow executives? The George Washington University Regulatory Studies Center can help shed some light with their data. Specifically, they have calculated the number of ‘economically significant’ regulations passed during each month of each president going back through Ronald Reagan’s term. What counts as ‘economically significant’? The definition has changed over time. But, generally, ‘economically significant’ regulations:

  1. “Have an annual [adverse] effect on the economy of $100 million or more
  2. Or, adversely affect in a material way the economy, a sector of the economy, productivity, competition, jobs, the environment, public health or safety, or State, local, or tribal governments or communities.”

The only exception to this is between April 6, 2023 and January 20, 2025 when the threshold was raised to $200 million.

The Data

The graph below-left shows the number of economically significant regulations for each president since the start of his term, through July of 2025. It’s reproduced from the link above except that I appended Trump’s second term onto his first term. What does the graph tell us? There doesn’t seem to be much of a difference between republicans and democrats. Rather, it seems that, generally, the number of economically significant regulations increases over time. Importantly, the below lines are cumulative by president. So each year’s regulations each cost $100m annually and that’s on top of the existing ones already in place. So, regulatory costs generally rise, with the caveat that we don’t see the relief provided by small or rescinded regulations (for that matter, we don’t see small regulatory burdens here either). Something else that the below graph tells us is that presidents tend to accelerate their economically significant regulations prior to leaving office. Reagan was the only exception to this pattern and he *slowed* the number of regulations as the end of his term approached.

Below-right is the same data, but the x-axis is months until leaving office. Every president since Bush-41 has accelerated their burdensome regulations during their final months in office. The timing of the acceleration corresponds to how close the preceding election was and whether the incumbent president lost. Whereas all presidents regulate more in their last 2-3 months in office, the presidents who were less likely to win re-election started regulating more starting around eight months prior to leaving office. Of course, they wouldn’t say that they expected to lose, but they sure regulated like there was no tomorrow.

What about Trump? Trump’s fewer regulations is caused by his single term. He definitely still added to the regulatory burden (among economically significant regulations, anyway). While Trump started with the fewest additional regulations since Reagan, and Biden started with the most ever initial regulations, together they earn the top prizes for most regulations added in their first term.

What if we append these regulations from end-to-end? That’s what the below chart does. We do have to be careful because the series is a measure of gross economically significant regulations and not net economically significant regulations. So, it’s possible that some rescissions dampened the below values, but this is the data that I have for the moment. While each presidential administrations increases regulation more than the prior, the good news is that the rate of change is not exponential. The line of best fit is quadratic. We’re experiencing growing regulations, but at least it’s not compound growth.

The Cost

We can estimate the costs of these economically significant regulations. It’s a rough cut, and definitely a lower bound since rescission is rare and $100 million is itself a lower bound, but we can multiply the number of regulations by $100m to get minimum annual cost. Like I said, the Biden criterion from April 2023 through January 20, 2025 changed, so those regulations get counted as $200 million instead. The change in definition means that the regulation counts underestimate the late-term Biden regulations relative to the other presidencies.

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Sleigh or Sled Shovels: Move Lots of Snow with No Lifting

Now that we have your attention (if you just got buried in a blizzard yesterday), let’s talk about shoveling snow. Everyone knows how a standard snow shovel works. You bend down, with one hand on the end of the handle and the other hand halfway along the handle, you shove forward, load up the shovel blade, then (Ooof!) lift it up and throw the snow where it needs to go. For many of us, this action uses muscles and joints that are not conditioned for it. Fun facts: every year some 100 Americans die from shoveling snow, and another 11,000 or so end up in the emergency room.

Is there a better way? Well, a powered snowblower can work. But that doesn’t fit everyone’s situation. It turns out there is a better way to manually shovel snow, that fits many (not all) situations.

As I was reading about “electric snow shovels” (more on that another time), I ran across mention of “sleigh shovels” or “sled shovels” or “snow scoops.” Apparently, they are very widely used by Canadians and Alaskans, who ought to know something about snow. A genius aspect of these shovels is that you never have to lift them.

Here is a picture of a 24” Garant brand sled shovel:

Source: Ace Hardware   

Here’s how they work: Start with the position shown, shove it forward (you get to use both hands out in front of you, in an ergonomically good position), till the scoop is largely filled with snow. Then, tilt it back a little, and push this load forward, sledding along until you get to the edge of the driveway. Keep pushing it another several feet, out onto the lawn. Then dump the snow off the shovel by a quick shove forward and a sudden jerk back, to pull the shovel out from under the snow. Plan your dumping points so as to get a gradual ridge beside the driveway, not a narrow, high ridge right at the edge.

Here is a 47-second video demo, on a small scale.

Take a quick look at 1:40 – 3:40 (two minutes) of this video to see a more challenging situation (deep snow, big existing ridge on edge). This shows that one scoop shovel-full is equivalent to more than three regular shovel-fulls, and this snow is expelled from the driveway with NO LIFTING. It’s beautiful! Here are two screen shots from this video:

Garant seems to be the most well-established brand here. ACE hardware (see photo above) is selling them for $70. On Amazon, I see a Garand model being sold for an eye-watering $266, maybe scalping prices for the latest blizzard. That is a lot of money for a plastic scoop with a metal handle. You can probably do better by shopping elsewhere or at a different time.

I am tempted to get one, but I don’t have a wide driveway with grassy dumping areas on the sides. I have to shovel mainly steps and narrow sidewalks, often with wet, slushy, not super deep snow. Sleigh shovels can work in these situations, but their advantages are muted, compared to the deep powdery snow found in colder regions.

But if I were living in Boston or Providence or New York, a sleigh shovel would be mighty handy right now.

Truth: The Strength and Weakness of AI Coding

There was a seismic shift in the AI world recently. In case you didn’t know, a Claude Code update was released just before the Christmas break. It could code awesomely and had a bigger context window, which is sort of like memory and attention span. Scott Cunningham wrote a series of posts demonstrating the power of Claude Code in ways that made economists take notice. Then, ChatGPT Codex was updated and released in January as if to say ‘we are still on the frontier’. The battle between Claude Code and Codex is active as we speak.

The differentiation is becoming clearer, depending on who you talk to. Claude Code feels architectural. It designs a project or system and thrives when you hand it the blueprint and say “Design this properly.” It’s your amazingly productive partner. Codex feels like it’s for the specialist. You tell it exactly what you want. No fluff. No ornamental abstraction unless you request it.

Codex flourishes with prompts like “Refactor this function to eliminate recursion”, or “ Take this response data and apply the Bayesian Dawid-Skene method. It does exactly that. It assumes competence on your part and does not attempt to decorate the output. It assumes that you know what you’re doing. It’s like your RA that can do amazing things if you tell it what task you want completed. Having said all of this, I’ve heard the inverse evaluations too. It probably matters a lot what the programmer brings to the table.

Both Claude Code and Codex are remarkably adept at catching code and syntax errors. That is not mysterious. Code is valid or invalid. The AI writes something, and the environment immediately reveals whether it conforms to the rules. Truth is embedded in the logical structure. When a single error appears, correction is often trivial.

When multiple errors appear, the problem becomes combinatorial. Fix A? Fix B? Change the type? Modify the loop? There are potentially infinite branching possibilities. Even then, the space is constrained. The code must run, or time out. That constraint disciplines the search. The reason these models code so well is that the code itself is the truth. So long as the logic isn’t violated, the axioms lead to the result. The AI anchors on the code to be internally consistent. The model can triangulate because the target is stable and verifiable.

AI struggles when the anchor disappears

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Against Eugenics, on its Own Terms

Once upon a time, eugenics was all the rage. It was nascent during the reconstruction era and persisted into the 20th century. It grew out of biological evolutionary theory and emphasized reproductive fitness. In brief, the theory asserted that there are differences in individual fitness and that the more fit living things will survive better and reproduce, eventually becoming a greater part of the population. The ability to compile and evaluate statistics about various human measurements made inferences hard to resist. Of course, researchers were plagued by small sample size, omitted variable bias, and social biases of the day (for example, phrenology inferred fitness characteristics from skull shape).

People employing eugenic thinking, overwhelmingly, supported theories that their own type of person was among the more fit. Eugenicists didn’t promote theories of their own un-fitness. In the progressive era of the early 20th century, eugenics met the prevailing attitude that government could be employed to resolve social and economic ills. This era is when the income tax emerged, prohibition was enacted, the Federal Reserve was formed, and various labor regulations were enacted.

The result was that policy sometimes pursued greater ‘fitness’ among its populations. Rather than systematically encouraging the supposedly more fit with economic incentives, most policy was geared toward reducing the reproductive success of supposedly less fit people. These included forced sterilization, institutionalization, and economic exclusion. Besides rejecting basics individual human dignity, the harm was all the more tragic given that fitness was often poorly specified. That is, policy criteria weren’t dependably related to fitness. Fatal conceit, indeed!

One of my favorite ways to argue is to grant premises and then change details on the margin to see whether the conclusion changes. Let’s do that. Let’s grant that there are innate differences between people that are related to biological success. Since survivability is related to resource acquisition, let’s grant also that economic success overlaps at least somewhat.  Taking that as granted, does pursuit of the historical eugenic policy still follow?

It does not.

There are two mistakes that eugenicists and various sorts of racists and xenophobes made. They assert or imply 1) that fitness characteristics are stable and systematically identifiable, and 2) that policy needed to intentionally select for the fitness characteristics.

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