Shackleton's Flawed Ship

 

Ernest Shackleton (1874-1922) almost reached the South Pole in 1909, although he lost the title of being first to get there to Roald Amundsen, who achieved that record in 1911.  Shackleton then set his sights on being the first to traverse Antarctica from one side to the other, and for that project purchased the wooden excursion ship Endurance.  He embarked on his grandly-named "Imperial Trans-Antarctic Expedition" on Dec. 5, 1914 from the small island near the tip of South America called South Georgia, intending to land at Vahsel Vay in the Weddell Sea, reach the South Pole, and cross to the other side with the aid of a second provisions-laying party.

 

It was a complicated and ambitious undertaking.  Endurance got stuck in the ice in mid-January after nearly reaching Vahsel Bay, and Shackleton decided to wait on board the ship until the following spring, nine months later.  Meanwhile, over the Antarctic winter, the drifting ice slowly moved the ship several hundred miles northwest until the following October, when the spring thaws began to exert extreme pressure on the hull.

 

On October 24, the hull broke, water rushed in, and Shackleton ordered the ship abandoned.  The crew transferred to camps on the ice, and the ship finally sank on Nov. 21, 1915.  This began a series of adventures for Shackleton and his men which would be too long to recite here, but eventually they made it back to something like civilization in August of 1916.

 

Now we fast-forward to 2022, when an equally daring expedition called Endurance22 found Endurance below 3000 meters of water (9900 feet) and did extensive photographic documentation of the wreck, which by international agreement will remain undisturbed. 

The details of what they found about why the Endurance sank are described in a recent UPI report by Stephen Feller.

 

After the wreck was found, researcher Jukka Tuhkuri and his colleagues of Aalto University in Finland conducted an investigation into why Endurance sank.  Even as long ago as the 1910s, shipwrights knew how to construct ships that would withstand the extreme pressures exerted by ice in the Antarctic.  But as their analysis of documents such as ship's plans, diaries, and other sources indicated, Endurance wasn't built that way.

 

On the lowest deck, which contained the boilers and steam engine, there was only one beam that crossed the entire ship from one side to the other.  Ships designed to withstand the compressive forces of ice normally had several such beams spaced along the length of the ship to resist the ice, which otherwise will crack a hull like someone squeezing an eggshell too hard.  But that is apparently what happened to Endurance.  Although it lasted nearly a year stuck in the ice, the stresses caused by the following spring's thaw exceeded its capacity to resist them, and it cracked and sank.

 

According to Tukhuri, Shackleton was aware that the ship he bought was built only for polar excursions and not what amounted to ice-breaking duty.  The researchers even found a letter written by Shackleton, mentioning that he had recommended adding additional internal hull-bracing beams for another polar exploration ship that had got stuck in ice but didn't get crushed.  Tukhuri speculates that Shackleton was in a hurry and bought the ship knowing it wasn't sufficiently braced, but hoping that he could avoid putting it in a situation where the missing beams wouldn't be needed.  Unfortunately, that's not what happened.

 

Although he wasn't an engineer, Shackleton was making engineering decisions as he prepared for his grand expedition.  Engineering is the application of limited resources to a technical problem, and that's exactly what Shackleton was doing.  Sometimes the time and expense required to prevent a somewhat unlikely event from happening simply isn't available.  Rather than abort the whole project, Shackleton decided to go ahead, trusting in his navigation skills and previous Antarctic experience to avoid disaster.  But his gamble with the missing beams didn't pay off, and he had to rely even more than he expected to on his survival skills to get him and his crew off the ice and back to civilization.

 

Shackleton's ill-fated expedition reminds me of the Apollo 13 near-disaster, in which three astronauts were stranded in space on their way to the moon in 1970 by an oxygen tank that exploded when some damaged insulation resulted in an internal fire.  The resulting damage led to a long series of improvised solutions to unexpected problems, which the astronauts carried out in coordination with the extensive NASA support staff on the ground.  Like Shackleton, the Apollo 13 team never reached their goal, but simply getting back to civilization after the accident was a bigger triumph than even landing on the moon again. 

 

Apollo 13's accident was caused by a manufacturing flaw, not a design flaw.  Still, the improvisation and backup systems used to rescue the mission were similar to what Shackleton used in getting his crew back safely. 

 

Most of us will never go on expeditions to unexplored lands or planets.  But the civilizational urge is still there, which is why several countries continue to plan both manned and unmanned expeditions to the Moon, Mars, and even farther. 

 

If and when these plans come to fruition, we can count on several things.  One is that not everything will go according to plan.  When engineers encounter a novel situation, despite all the advance information they can gather about it in advance, there is always something unexpected.  Sometimes it's just a matter for curiosity, but other times it can be a matter of life and death. 

 

Another thing is that good engineering practice and planning can provide enough backup resources to allow clever individuals to create a survival plan even in the face of a major disaster.  Losing the Endurance was a big setback, but Shackleton had packed enough auxiliary supplies in the form of food, shelter, and other necessaries, so that he and his crew could perform the extraordinary feat of extracting themselves from what must have looked like certain death at times.  And the ingenuity of NASA engineers combined with the intrepid actions of the Apollo 13 crew to get them safely home, despite major damage to the Service Module that contained the oxygen tank which blew up.

 

Companies such as SpaceX are now leading the way into space, and it remains to be seen how well they balance the goals of achieving a mission first at any cost, including death, versus proceeding more slowly with more backup systems and more thoughtful engineering.  So far, none of the commercial space enterprises has ever lost a life in space.  Let's hope it stays that way as long as possible.

 

Sources:  The article "Shackleton's sunken polar ship may have been weaker than thought" by Stephen Feller was published on the UPI website on Oct. 6, 2025 at https://www.upi.com/Science_News/2025/10/06/shackleton-endurance-ship-crushed-in-ice/9321759774913/.  The Endurance22 website is at https://endurance22.org/.  I also referred to the Wikipedia articles on Apollo 13,  Ernest Shackleton, and Endurance. 

What Managers Think About Replacing Workers With AI

 

It's hard to look at a website, talk to anybody in business, or read a magazine for very long these days without encountering something about artificial intelligence (AI).  One of the biggest concerns for the average symbolic-manipulator employee, in George Gilder's phrase, is whether AI will replace you in your job.  Examples of symbolic manipulators are software developers, accountants, writers, and to some degree sales people and counselors.  Hospital nurses and construction workers, on the other hand, are not symbolic manipulators, at least not most of the time. 

 

A company called Trio realized that even if AI was available to replace a lot of these folks, somebody would have to decide to do it.  And that somebody would be middle-level managers, for the most part.  So last month, they performed an online survey of about 3000 U. S. managers in all 50 states to find out their attitudes toward replacing their employees with AI.  And the results are illuminating.

 

First of all, when broken down by state, there are wide variations in how enthusiastic managers are in replacing flesh-and-blood workers with AI software.  Openness to doing this varies from a high of 67% in Maine to a low of 8% in Idaho.  Both being fairly rural states, the difference is hard to account for except by cultural factors.  If I had to guess, I'd say finding good, reliable workers is more of a challenge in Maine, and so that may be one reason why managers in our most northeastern state would rather skip the hassle of hiring people and go straight to an AI program.

 

When all states were lumped together, the top reason that managers would replace workers with AI turns out to be pressure from upper management or shareholders, at 36%.  Presumably this was one of a list of "choose-one" options handed to the survey respondents.  The next most favored reason was for productivity gains (31%) and then cost savings (27%).  This pressure from above makes me think that a sheep-like mentality which now and then manifests itself in the boardroom may be why we are hearing so much about AI replacing workers.  No CEO wants to be left behind in a stampede to the next great thing, even if the thing turns out to be not so great.

 

What is perhaps most disturbing to engineers about the survey results is the kinds of jobs that managers see most ripe for replacement by AI.  "Technical roles like coding and design" (sounds like engineering to me) were perceived as most replaceable at 33%, while the least replaceable jobs were seen to be sales (11%) and "creative work" at 15%.  There are a lot of sales jobs that could pretty easily be replaced by good AI software, but evidently managers still believe in that personal touch that good salespeople can bring to the task.  Whereas, engineers and programmers, who are always carried as overhead on budgets, don't have as direct a connection between sales and their salaries as salespeople do. 

 

Independent of the question about whether a given job can actually be done better by AI than by a human, this survey looks at those who would be making the immediate decision to do so.  Of course, the options presented to those surveyed were simplified ones.  The fact is that rather than making a simple choice between AI and a human in a given job, what seems to be happening is that almost anybody in the symbolic-manipulation business is adopting some form of AI almost by default—some deliberately and enthusiastically, others (like myself) reluctantly and only if it can't be avoided. 

 

These large workplace shifts tend to be hard to discern over the short term, because they happen gradually.  Take the development of computer-aided design (CAD) software as an example.  My late father-in-law never obtained a four-year college degree, yet in the 1950s he got a good job as a civil engineer and worked for the Texas Highway Department.  If you'd visited him shortly after he went to work there, he would have been sitting at a drafting table in a huge room full of guys (all guys) sitting at drafting tables, churning out drawings that were turned into blueprints for the construction crews working on the new interstate-highway system.

 

Visit that same office today (the building is still there), and you'll see fewer engineers than those old drafting rooms held, and they'll be sitting at computers.  The computer can't design anything by itself, and while the engineer is in some sense in charge of the process, the amount of sheer dogwork handled by the computer far exceeds the mental effort put forth by the engineer, who now does the work of ten or fifteen (or more) of the old drafting-room people.  And the field of civil engineering didn't collapse:  my school (Texas State University) started a new civil-engineering program a few years ago, and we have no problem placing our graduates.

 

The advent of AI, which has actually been going on for a decade at least and isn't as sudden as news reports make it sound, will probably be like the advent of CAD, only more so.  It's easy to forget that the computers need us as much as we need the computers.  Take away the largely-human-produced Internet from ChatGPT, and you'd have a lot of useless server farms on your hands. 

 

There are clearly dangers, of course, if we get too lazy and allow AI to make decisions that should remain in human hands, or minds.  And there are sectors where AI has already done serious damage, such as the harm AI-fueled social media has done to the psychological health of children and teenagers.  But we're not letting the pied piper of AI march away with all our kids.  Schools all across the U. S. are starting to ban smartphone use during classes, and parents are wising up to how harmful too-early use of smartphones can be to young people. 

 

Even if all managers were dying to replace their staff with AI as fast as they could, the software simply isn't available yet.  At the present time, AI has the looks of a fad, indicated by the survey's showing that pressure from upper management is the biggest reason bosses are considering it.  So it's no time to panic, but keep your wits about you and be ready to deal with AI in your job, assuming you still have one.

 

Sources:  The summarized results of the Trio survey can be seen at https://trio.dev/managers-are-ready-to-replace-employees-with-ai/.  The San Marcos Daily Record of Oct. 10, 2025 carried a story on the survey on p. 8, which is how I found out about it, from an old-fashioned piece of paper.  But then I went online. 

Waymo 80% Safer than Human Drivers: Why Not Switch?

 

According to Waymo, the Google division that operates self-driving robotaxis in several U. S. cities, their vehicles are involved in 80% fewer injury-causing crashes than human-driven cars.  This was a surprise to me, as it may also have been to Kelsey Piper, who writes in a substack called The Argument that if we want to reduce the number of traffic fatalities in the U. S by 80%, all we have to do is switch to Waymos.

 

At the current rate of nearly 40,000 U. S. traffic fatalities a year, that would be saving 31,000 lives a year.  But she cites a poll conducted by The Argument which found overall that only about 28% of respondents favored allowing self-driving cars in one's town or city, and 41% favored a ban, as Boston and other cities have considered doing.

 

Piper speculates that a general distaste for AI-powered things may be behind what looks like irrational opposition to self-driving cars.  Some Waymos have even been attacked by modern-day Luddites.  As she puts it, ". . . you can't vandalize ChatGPT, so anti-AI sentiment finds its expression in harrassing Waymos."

 

She realizes that anything like a wholesale move to self-driving cars would cause massive disruption to our present transportation system.  She also acknowledges the tendency of government to make optional things mandatory.  Right now, Waymo is one private company offering a specific service in a few carefully chosen markets such as Atlanta, Austin, San Francisco, and Phoenix.  With the possible exception of Atlanta, these are all locations with plenty of sunshine and relatively few days of inclement weather.  And the service in Atlanta only commenced last June, so Waymos in that city have not gone through a typical Atlanta winter, which almost always includes an ice storm, as I know from living there a couple of years.  Ice may present serious challenges to Waymo's algorithms.

 

So there are practical limitations to the areas that Waymo can operate.  As one of the commenters on Piper's article mentions, Waymo has somewhat cherry-picked markets in which it can compete while maintaining its very good safety record.  Even if Boston decided to allow Waymos, I expect a long development period would delay its deployment as the company figured out how to deal with snow, ice, and slush on the former cowpaths that are now Boston streets.  At least the Waymo cars probably wouldn't get lost as much as I did whenever I drove to Boston when I lived in New England, which was, well, pretty much every time I went there. 

 

But there's those 31,000 lives.  As Piper points out, that's more lives than are lost every year to homicides.  Wouldn't it be nice if we could eliminate all homicides?  Well, numerically, changing to self-driving cars would do that. 

 

The psychology of why we tolerate such a lot of annual deaths to traffic accidents is interesting.  People don't always act toward various risks in reasonable ways.  The classic example is driving to the airport to fly somewhere.  Unless you live within walking distance of the airport, you're going to drive or ride.  And unless you take a Waymo there, you will ride in a human-operated car.  While lots of people are afraid of flying much more than they are afraid of driving, the chances of dying in a plane crash are much lower than the chances of dying in a car wreck on the way to or from the airport. 

 

I suspect that we have gotten so used to the 40,000 or so traffic deaths every year with some variation on the notion that it always happens to someone else, and if I were in the same situation that somebody else died in, I would have been clever enough to save myself.  These are pure rationalizations, but the alternative is to experience a little squirt of adrenaline every time we buckle the seat belt and pull out of the garage. 

 

Five or ten years ago, there was a lot of hype about how every new car would be self-driving within a few years.  That obviously hasn't happened, for a variety of reasons.  One factor is the expense per vehicle.  Waymo doesn't advertise how much each of their vehicles cost, but various estimates say it's probably on the order of $160,000 to $300,000.  This puts them in the super-luxury class, and explains why they aren't deployed in areas that will not generate pretty good revenue.  Even with the carefully-chosen markets that Waymo has selected, it appears that they are not making a profit yet, which means the whole thing is still an elaborate experiment oriented toward some future situation that hasn't materialized.

 

Still, I will admit that if I could have a self-driving car that was absolutely trustworthy, a Level-5 one according to the SAE autonomous-vehicle rating system, one you could read or sleep in while the machine takes care of all driving tasks, and not pay a whole lot more for it than I'm paying now, I would at least consider it.  But in my relatively small town, which would not provide enough revenue for Waymo under its present operating circumstances, that's not going to happen.

 

Now and then on my trips to Austin, I see a Waymo eerily coasting along with nobody inside, and once I saw two in a row.  I will admit to having a flash of mischief when I saw one the first time, and wondering what would happen if you pulled in front of it and slammed on the brakes suddenly.  Probably nothing bad.  Fortunately, I was a passenger in the car I was in, not the driver, and so the experiment was never performed.

 

Unless something radical happens in the areas of AI, sensors, or legislation regarding the right to drive your own vehicle, it looks like Waymo and similar autonomous vehicle companies may not spread their wares much farther than they've already done.  And that's too bad for the 40,000 or so people who die on roadways each year.  Some ideas look good in theory, but when you start examining everything that would have to change to put them into practice, it just falls apart.  And converting our fleet of vehicles to nearly 100% self-driving looks like another one of those nice ideas that has had an unfortunate encounter with reality.

 

Sources:  A note in the online magazine The Dispatch referred me to Kelsey Piper's article "Please let the robots have this one," at https://www.theargumentmag.com/p/please-let-the-robots-have-this-one.  I also referred to a Reddit item on the estimated cost of Waymo vehicles at https://www.reddit.com/r/SelfDrivingCars/comments/1g8vv7o/where_did_the_whole_talk_about_the_cost_of_waymo/, and the Wikipedia article "Waymo."