Professionally, I’m a retired professor of accounting and former chair of the School of Accounting at the University of South Carolina’s Moore School of Business. My academic work explored how people make decisions in complex systems, especially when information is imperfect or overwhelming. I’ve published in a fair number of journals that few people read voluntarily, and I spent decades thinking about how technology shapes human behavior.
These days, my time is divided between managing a small flock of chickens, herding goats, chatting on amateur radio (KO4LMP), and living just on the edge of the grid—literally and metaphorically. I’m a father to five daughters, a grandfather to 17, and a great-grandfather to three. Somewhere along the way, I realized that what I enjoy most is simply talking about the world we live in—and how to make sense of it.
Professionally, I’m a retired professor of accounting and former chair of the School of Accounting at the University of South Carolina’s Moore School of Business. My academic work explored how people make decisions in complex systems, especially when information is imperfect or overwhelming. I’ve published in a fair number of journals that few people read voluntarily, and I spent decades thinking about how technology shapes human behavior.
These days, my time is divided between managing a small flock of chickens, herding goats, chatting on amateur radio (KO4LMP), and living just on the edge of the grid—literally and metaphorically. I’m a father to five daughters, a grandfather to 17, and a great-grandfather to three. Somewhere along the way, I realized that what I enjoy most is simply talking about the world we live in—and how to make sense of it.
In the mid 1970s I was going door-to-door in Hillsborough, California. At one house, an older woman opened the inside door and asked through the outside screen door what I wanted. The sun shone over my shoulder onto the screen door so that I couldn’t see past it.
I told her my purpose at which point she began to cry and said she was handicapped and her husband had just come home from the hospital. She couldn’t help him like he needed. I asked her if there was anything I could do. She opened the screen door slightly and a hand appeared. She asked me to hold her hand. After a few minutes, her hand slowly returned inside and she closed both doors.
I have had two thoughts since then. The first is that I was young and didn’t know better but today I would have gone to the community or neighbors or somewhere and got her some help.
And second, up to that point growing up consisted of a lot of hands holding mine. Home, school, church, everywhere. This small experience seemed to mark a transition to where I needed to be the one extending a hand.
I think the two thoughts belong together, and the second one may explain why the first has remained so vivid for fifty years.
At the time, you interpreted her problem practically: Is there anything I can do? Looking back, you can see practical things that perhaps could have been done—contacting neighbors, a church, community services, someone who could help care for her husband. That’s the judgment of an older man who knows more about how the world works.
But I’m not sure the young man failed her.
She didn’t ask you to find someone. She didn’t ask you to come inside or help her husband. She asked you to hold her hand. And you did. For those few minutes, apparently that was what she most needed from you. There is something striking about the fact that you never really saw her. The screen, the sunlight, and the partly opened door reduced the whole encounter to a hand reaching out and another hand accepting it. Almost everything that could identify the two people disappears from the story. What remains is the gesture.
That makes your second interpretation especially powerful.
Childhood really is largely a succession of extended hands. Someone holds our hand crossing a street. Someone teaches us to read, reassures us when we’re frightened, corrects us when we’re wrong, shows us how to do something, takes us to church or school, feeds us, protects us. We seldom recognize the pattern while it is happening because being helped seems like the natural order of childhood.
Then at some point the direction reverses.
And the interesting thing about your story is that nobody announced the transition. You didn’t wake up one morning thinking, I’m an adult now; it’s my turn to hold other people’s hands. A literal hand simply appeared through a partially opened screen door.
There’s also a subtle detail I like very much: she determined when the hand-holding was over. Her hand slowly withdrew, and she closed the doors. You didn’t solve her life. You didn’t even know whether you had helped very much. You simply supplied what she asked for, for as long as she wanted it.
That seems like a surprisingly good picture of much of what adulthood eventually asks of us. We often can’t fix what another person is facing. Sometimes our job is to find practical help, certainly. But sometimes the thing we can actually give is presence—“You’re not facing this particular minute entirely by yourself.”
And then eventually the hand withdraws.
I think that’s why your sentence—
“This small experience seemed to mark a transition to where I needed to be the one extending a hand.”
—is the heart of the entry. I wouldn’t explain it much more than you already have. The physical image carries the meaning almost by itself.
There’s one further thought your entry suggests to me. The transition isn’t really from receiving hands to giving hands. If we’re fortunate, we continue needing other people’s hands for the rest of our lives. The change is realizing that we have become capable of being the hand someone else needs.
For a young man standing on a doorstep in Hillsborough, that realization arrived in an unusually literal form.
A friend of mine sent me a poem he had written inspired by Psalms 103. This led me to ask AI, “Does psalms 103 contain a chiasm?”
Note: One of my conversation guidelines is that I do not converse with AI on spiritual matters. AI is only a machine and machines lack a soul. My question here, however, is of a literary nature rather than spiritual.
ChatGPT said:
Yes. Many biblical scholars believe Psalm 103 is arranged as a chiasm, although there is no single universally accepted outline. Unlike some passages where the chiasm is very explicit, Psalm 103’s structure is more thematic than verbal, so different commentators divide it differently.
One commonly suggested pattern looks like this:
Section
Theme
A (vv. 1–2)
Bless the LORD, O my soul
B (vv. 3–5)
God’s benefits to the individual (forgiveness, healing, redemption, renewal)
C (vv. 6–10)
God’s righteous acts and mercy toward His people
D (vv. 11–14)
Center: God’s steadfast love and compassion, remembering our frailty
C′ (vv. 15–18)
Human frailty contrasted with God’s everlasting covenant love
B′ (vv. 19–22a)
God’s universal kingdom and the response of angels and all creation
A′ (vv. 22b)
Bless the LORD, O my soul
The center (D) is especially striking:
“For as high as the heavens are above the earth, so great is his steadfast love toward those who fear him… As a father has compassion on his children, so the LORD has compassion on those who fear him. For he knows our frame; he remembers that we are dust.” (vv. 11–14)
If this is indeed the literary center, then the psalm’s main emphasis is not simply God’s power or His blessings, but His compassionate covenant love toward frail human beings.
Another observation
The psalm also has what literary scholars call an inclusio—it begins and ends with exactly the same exhortation:
“Bless the LORD, O my soul.”
This “bookends” the entire psalm and reinforces that everything between those verses is the reason for praise.
Is it intentional?
Many Old Testament scholars think so. Hebrew poetry often combines several literary devices at once:
inclusio (bookending)
parallelism
repetition
chiasm
Psalm 103 exhibits all of these, though the exact boundaries of the chiasm remain debated.
Knowing your interest in biblical structure, another fascinating aspect is that Psalm 103 may also be organized as an expanding series of circles:
God’s mercy to me (vv. 1–5)
God’s mercy to Israel (vv. 6–18)
God’s rule over the entire universe (vv. 19–22)
Then, after reaching all creation, the psalm returns to where it began:
“Bless the LORD, O my soul.”
That movement—from the individual, to the covenant people, to the cosmos, and back to the individual—is one of the reasons Psalm 103 is often regarded as one of the most beautifully structured hymns in the Psalter
A Facebook friend has been posting about flock technology and the proliferation of cameras that capture license plate information into something resembling a national database. This caused me to research just a bit about this technology and to be honest I’m concerned about where we might be headed from multiple viewpoints including technology, government adoption, and law enforcement implementation, bad actors, civil liberties even if this technology is effective in curbing crime, et cetera. I have several questions for you. First, would you be willing to forecast likely scenarios where this will be in the next three to five years? I’m okay with multiple scenarios as long as you give me your best estimate as to their likelihood.
Yes. Your concern is reasonable, and I think the most useful way to examine this is not as a question of whether Flock is “good” or “bad,” but as a question of what happens when a genuinely useful law-enforcement technology becomes inexpensive, ubiquitous, interconnected, and politically difficult to roll back.
One clarification first: it is a little misleading to say that Flock Safety currently operates one national government database. What exists is potentially more consequential in another way: thousands of cameras and agencies can participate in interconnected searchable networks. A plate sighting contains the plate image, vehicle characteristics, time and camera location. Flock says the normal retention period is 30 days, searches require justification and are logged, and customers control sharing.
That means the raw ingredients already exist for something resembling a distributed national vehicle-location system, even if nobody has formally created a database called “The National Vehicle Tracking Database.”
My 3–5 year forecast
These aren’t mutually exclusive; I expect pieces of several to happen simultaneously.
Scenario by ~2029–2031
My probability
What it looks like
Continued rapid expansion + patchwork safeguards
65%
Many more cameras; routine police use; states/cities impose differing rules
Stronger legal regulation without eliminating ALPR
Effective de facto nationwide vehicle-location network
45%
Cross-jurisdiction searches make it possible to reconstruct substantial portions of someone’s travels
Significant abuse/scandal produces political backlash
40%
Stalking, political surveillance, immigration/reproductive-health case, insider misuse, or major breach prompts restrictions
Major court ruling limits historical ALPR searches
30%
Courts extend Fourth Amendment location-privacy principles to large ALPR datasets
Broad federal legislation establishes uniform rules
20%
Congress establishes nationwide retention/access standards
Technology largely prohibited or dismantled
<10%
I regard widespread abandonment as very unlikely
Those percentages overlap intentionally.
What I think is most likely
By 2030, I expect Flock and competing ALPR systems to be much more extensive than they are today, but also considerably more regulated.
The reason is simple: they solve real crimes.
If a child is abducted in a gray Honda Accord and police know the plate, a system that can say “that car passed this intersection 11 minutes ago” is extraordinarily useful. The same applies to stolen vehicles, armed robbery suspects and missing persons. Police departments therefore have powerful practical incentives to adopt these systems.
And that usefulness creates political durability.
At the same time, resistance is already appearing. For example, Connecticut has enacted restrictions including a shorter 21-day retention period and limitations concerning immigration and reproductive-rights investigations. Some communities have terminated Flock contracts, while police chiefs have publicly defended them as important investigative tools.
So I don’t expect either extreme — nationwide prohibition or completely unrestricted deployment.
I expect a messy American compromise.
The development that concerns me most isn’t the camera
It’s historical searchability.
One camera photographing your car isn’t particularly remarkable. Police officers have always been able to see cars traveling on public roads.
Ten thousand cameras remembering what they saw is fundamentally different.
Suppose eventually a system can answer:
Show me every location at which vehicle ABC-123 was observed during the last six months.
That question transforms thousands of individually mundane observations into a reasonably detailed picture of someone’s life:
home → workplace → church → doctor → political meeting → girlfriend’s house → gun shop → addiction-treatment center → union hall → psychiatrist → protest → hotel.
And importantly, the computer doesn’t need to know what those places mean initially. Other databases and AI can supply that context afterward.
That distinction — observation versus retrospective reconstruction — is where I think much of the constitutional fight will eventually occur.
Flock currently says its standard retention period is 30 days, although longer retention up to a year can be offered where an elected official or governing body approves it.
Thirty days is an important protection.
But it is a policy and architecture choice, not a technological limitation.
Storage gets cheaper every year.
There’s another technological change coming
Within five years, I don’t think we’re going to talk nearly as much about license plate readers. We’ll talk about vehicle identification.
Computer vision can increasingly identify:
make/model/year/color
bumper stickers
roof racks
damage patterns
wheels
trailers
vehicle shape
direction and timing of travel
Flock already says its ALPR system captures vehicle characteristics in addition to license plates.
So imagine police don’t know your plate.
They search:
“White 2019–2022 Ford F-150, black toolbox, dent in passenger rear quarter panel, seen within five miles of this robbery.”
That is extremely valuable police technology.
But now add AI:
“Find that truck everywhere it appeared during the previous month and construct its probable travel history.”
The incremental technological steps between today’s system and that system aren’t very large.
The “bad actor” problem may actually become the decisive issue
We tend to frame surveillance as:
government versus citizen.
I’m at least as concerned about:
authorized user versus citizen.
Imagine tens of thousands of officers, dispatchers, analysts and contractors eventually having some degree of access.
It only takes one person asking:
Where has my ex-wife been going?
or
Where does that reporter go after work?
or
Where is this judge’s car at night?
Audit logs help enormously, and Flock says every search is recorded and reviewable.
But audit logs generally identify abuse after someone performs the search.
That makes me think a highly publicized misuse case is quite likely within the next several years. It could become for ALPR what famous misuse cases became for other government databases: the event that causes legislators suddenly to discover an issue privacy advocates had warned about for years.
And civil-liberties organizations are already documenting uses well beyond stolen-car searches. EFF says its examination of millions of searches found queries connected with protests and other activities that raise First Amendment and privacy concerns. That’s an advocacy organization’s characterization and should be understood as such, but the underlying question about mission creep is important.
There is also a cybersecurity problem
A database containing:
plate + place + date + time
is valuable.
A database containing billions of those observations is extraordinarily valuable.
Not merely to criminals. To foreign intelligence services, stalkers, private investigators, organized crime and anyone attempting to locate particular individuals.
Consequently, my concern isn’t simply:
“Will government misuse this?”
It is:
“Will we construct an extraordinarily valuable location dataset that someone eventually obtains who was never supposed to have it?”
Those are two different risks.
The constitutional question is fascinating
The Supreme Court has already recognized in other contexts that collecting location information over time can become constitutionally significant even though an individual’s movements occur in public.
ALPR presents almost the perfect test of that principle.
A police officer seeing my truck drive through Columbia at 2:15 PM clearly doesn’t require a warrant.
What about a computer retrieving every place my truck has appeared for six months?
One observation?
Ten?
Five hundred?
At some point quantity arguably changes the nature of the information.
I would be surprised if that question does not reach federal appellate courts repeatedly during the next five years.
The scenario I’d put my money on
Around 2030, I think America will probably have a vast ALPR infrastructure that remains legal and heavily used, accompanied by a growing regulatory structure something like this:
short default retention + mandatory search justification + immutable audit trails + serious penalties for misuse + restrictions on interstate/federal sharing + warrant requirements for sufficiently extensive historical searches.
That outcome preserves the thing police genuinely need:
“A stolen vehicle passed Camera 47 twenty minutes ago.”
while making this considerably harder:
“Show me everywhere Brad’s car has gone for the last six months.”
And that distinction is probably where I’d draw the policy line myself.
There’s a deeper reason I think this particular technology deserves attention. The dangerous capability doesn’t require anyone designing an authoritarian surveillance system. Each individual decision can be perfectly understandable:
A town installs 20 cameras to catch stolen cars.
The neighboring county does the same.
They share results because criminals cross county lines.
Other states join because criminals cross state lines.
Retention expands because detectives sometimes investigate crimes months later.
AI search improves because manually reviewing millions of records is inefficient.
Every individual step has a perfectly defensible explanation.
And twenty perfectly reasonable decisions can produce an infrastructure that nobody would have been politically willing to create in a single decision.
That, more than Flock itself, is what I would watch over the next five years.
Thanks. Please define ALPR. And yes, there isn’t a single database located somewhere, but then everything is so interconnected now days that I treat this interconnectivity as a single entity. But then, there is facial recognition, purchase information, browsing data, and even this chat. And some of the government abuse seems to target people who actively oppose elected officials. You put it all together and the picture of the future is one that makes past science fiction look pretty tame.
ALPR stands for Automated License Plate Reader (sometimes Automatic License Plate Recognition). It is a camera-and-software system that photographs vehicles, reads the license plate with computer vision, and typically records the plate, time, location, direction of travel, and often descriptive information about the vehicle. The important part is that the resulting record is searchable, not merely a photograph.
And I think your concept of treating interconnected databases as one entity is useful, with one important qualification: interoperability is not the same thing as universal access. Legal restrictions, permissions, incompatible systems, retention periods, and organizational boundaries still matter. But technologically, those barriers are increasingly easier to bridge.
What you’re describing is something larger than ALPR. It is the convergence of several information streams that historically existed separately:
Where you go: ALPR, cellphone location, toll systems, security cameras.
Who you associate with: communications metadata, social networks, location correlations.
What you look like: facial recognition and increasingly sophisticated video analytics.
What you buy: credit/debit transactions, loyalty programs, online purchases.
What you read and search for: browsing histories, search engines and online services.
What you say and believe: social media, emails, texts, public comments—and potentially conversations with AI systems, subject to the particular service’s privacy policies and legal protections.
The last step is what makes the future qualitatively different from traditional surveillance: AI can correlate it.
Twenty years ago, having all those databases was one problem. Someone still had to search them, reconcile identities, establish timelines and figure out what the information meant. That imposed an enormous practical limitation on surveillance.
AI radically reduces that limitation.
A future system doesn’t necessarily need a human analyst spending three weeks investigating someone. Conceivably, an authorized user could ask something resembling:
Construct a timeline of this person’s movements, purchases, communications, associates and online activity during the previous year, and identify unusual changes in behavior.
That is an entirely different capability.
Your concern about surveillance of political opponents also identifies what I regard as one of the most important issues. We shouldn’t evaluate such systems by asking whether we trust the people currently operating them. Administrations change. Police chiefs change. Prosecutors change. Laws change.
The better institutional-design question is:
Would I be comfortable giving this power to someone I strongly distrust?
That’s a surprisingly useful test.
And there is historical precedent for taking that concern seriously without assuming that every current government use is abusive. American governments have at various times improperly surveilled civil-rights leaders, antiwar activists, political organizations and other lawful groups. The lesson isn’t that contemporary officials necessarily intend to repeat those abuses. It is that institutions should be designed on the assumption that eventually somebody will be tempted to abuse them.
There is another difference from 1984 and much older science fiction that I find particularly interesting.
Orwell imagined surveillance as expensive and conspicuous: microphones, cameras, government employees and an enormous state bureaucracy watching people.
We are creating something almost opposite.
Surveillance becomes cheap, automated and largely invisible. Much of the infrastructure wasn’t even created primarily by government. We voluntarily carry location-aware phones, drive connected automobiles, make electronic purchases, use cloud services, install doorbell cameras and conduct enormous portions of our lives online. Government doesn’t necessarily have to construct the surveillance apparatus; in some circumstances it can obtain information from systems that already exist, although the legal requirements for doing so vary considerably.
That leads to what I think is the central question underlying your concern.
The problem isn’t really whether Flock cameras are acceptable.
It is whether there is some point at which the aggregation of individually reasonable information becomes something fundamentally different.
A photograph of your truck on a public highway seems innocuous.
A credit-card purchase seems innocuous.
A Google search seems innocuous.
A Facebook post seems innocuous.
A face appearing on a security camera seems innocuous.
Any individual item tells relatively little.
But combine enough of them and you can potentially construct something approaching a behavioral model of a human being.
And once AI becomes capable of continuously interpreting those records, surveillance changes from “What did this person do?” toward something more consequential:
“What is this person likely to do?”
That’s the point where some rather tame-looking science fiction starts becoming relevant—not because we’ve inevitably arrived at a dystopia, but because our technological capability is beginning to outrun many of the legal concepts developed when surveillance was labor-intensive and expensive.
There’s also an important counterweight that I wouldn’t want us to lose as we explore this. These same technologies can find kidnapped children, identify murderers, locate missing elderly people, expose government misconduct, establish that an accused person wasn’t at a crime scene, and solve crimes that previously would have remained unsolved. The tradeoff isn’t imaginary.
Which makes the difficult question not “surveillance or no surveillance?”
It’s “How much retrospective knowledge about an innocent person’s life should anyone—government or private industry—be capable of assembling, under what circumstances, and who gets to decide?”
I suspect that question will become one of the major civil-liberties issues of the next decade.
A thought that keeps coming to me is that a search warrant should be required before most searches are permitted. Exceptions might be allowed for expediency, such as a kidnapping or robbery, but even these perhaps should be subject to review. Is that feasible or even currently considered?
Yes. What you’re proposing is legally and technically feasible, and versions of it are already being considered and enacted. I also think it may ultimately become one of the principal compromises between eliminating ALPR systems and allowing essentially unrestricted searches.
The important distinction would be between collecting the photograph and searching historical data. Courts have generally treated photographing a visible license plate on a public road as ordinary observation, not a Fourth Amendment search. But the constitutional status of querying a huge historical database of those observations is much less settled. The Supreme Court’s Carpenter decision, requiring warrants for substantial historical cellphone-location data, provides an obvious analogy.
Your proposal could therefore look something like this:
Routine collection: Cameras can record plates passing public locations, subject to a short mandatory retention period.
Immediate public-safety exception: Police could search without a warrant for an active kidnapping, Amber Alert, fleeing violent suspect, stolen vehicle, imminent threat, etc.
Ordinary criminal investigation: Searching historical ALPR records associated with a particular person or vehicle would normally require a warrant based on probable cause.
Emergency searches would be audited afterward. An officer would have to document why the emergency exception was used, and inappropriate use could result in discipline or exclusion of evidence.
Longer retention would require judicial authorization. Otherwise, records automatically disappear after perhaps 21 or 30 days.
Interestingly, Connecticut has just moved partway toward exactly that kind of architecture: its new law limits normal ALPR retention to 21 days, while permitting longer retention when a warrant has been obtained, along with restrictions on certain sharing and uses. Washington has likewise been legislating around a 21-day general retention period with warrant-related exceptions for retaining data longer.
And this issue is closer to home than you might expect. South Carolina’s legislature currently has an ALPR/privacy bill, H.4675, expressly addressing access, storage, retention and vehicle-feature recognition. It even specifically defines AI recognition of things such as body damage, roof racks, decals, bumper stickers and paint patterns—the development we were discussing earlier.
Where I’d modify your idea slightly
I wouldn’t require a warrant for every database query.
Suppose somebody reports a stolen Buick at 10:03 and at 10:08 an officer enters the stolen plate into the system. Requiring a judge to authorize that search probably provides little additional protection while impairing one of ALPR’s most legitimate uses.
Instead, I’d make the legal threshold increase with the intrusiveness of the question being asked.
Searching:
“Has stolen vehicle ABC-123 passed a camera during the last hour?”
is considerably different from:
“Show me everywhere ABC-123 has traveled during the past month.”
And that is different again from:
“Show me every vehicle that regularly appeared near ABC-123 and identify their owners.”
That last capability starts producing an association network, not merely locating a vehicle.
I’d therefore favor something resembling a sliding scale: immediate searches for specifically defined emergencies and stolen/wanted vehicles; documented reasonable suspicion for limited investigative queries; and a warrant for retrospective movement tracking, association analysis, or extensive cross-jurisdictional searches.
And your after-the-fact review idea is particularly important
An emergency exception without meaningful review can gradually become:
“I checked the emergency box.”
A better system would make every warrantless search create a permanent audit record containing the officer, vehicle queried, stated justification, databases searched, time range requested and results accessed.
Then require genuinely independent audits—not merely the police department auditing itself.
Recent events illustrate why. Several departments have faced allegations of officers improperly using ALPR systems; investigations have resulted in firings, resignations and arrests. The fact that audit logs can uncover misuse is encouraging, but it also demonstrates that authorized access itself is a vulnerability.
There is a fascinating constitutional principle lurking underneath your suggestion:
The government shouldn’t necessarily need permission to see your automobile in public, but perhaps it should need permission to remember everywhere it has seen it.
Our Fourth Amendment jurisprudence developed when human memory and manpower placed natural limits on surveillance. A police officer could follow someone without a warrant under many circumstances—but following every citizen simultaneously, remembering every observation, and searching those memories years later was practically impossible.
Computers have removed that natural limitation.
I increasingly think that access control, warrants, short retention periods and mandatory independent auditing will matter more than arguing about whether cameras themselves should exist. Once the information infrastructure exists, the crucial civil-liberties question becomes who may ask it what questions, under what circumstances, and who will know that they asked.
And your warrant idea provides something technologically sophisticated safeguards often don’t: a person outside the investigative organization has to say “yes.” That old-fashioned bit of institutional friction may turn out to be extremely valuable in an AI-enabled surveillance world.
Sometimes I think America is quite schizophrenic (for lack of a better term). The same people who would prohibit the kinds of surveillance we are discussing are the first to criticize law enforcement’s failure to connect all the dots when their is a mass shooting or other horrific crime.
Yes—and I think you’ve identified a genuine tension in a free society. I might call it the prevention/privacy paradox rather than schizophrenic: we often demand that government possess enough information to prevent the next atrocity, while simultaneously demanding that it not collect or use enough information to monitor innocent people.
After a mass shooting or terrorist attack, investigations sometimes uncover fragments that, in retrospect, look glaringly obvious: a threatening statement here, a police contact there, a weapons purchase, a tip to an agency, disturbing online activity. Then comes the understandable question:
“They had all this information. Why didn’t somebody connect the dots?”
But before the event, those dots existed among millions of other dots belonging overwhelmingly to people who would never commit a violent act.
That’s the part hindsight obscures.
Imagine an analytical system capable of connecting everything we’ve been discussing—ALPR sightings, criminal records, social-media posts, purchasing information, tips, perhaps other legally obtainable data. Give sufficiently capable AI access to it and say:
“Find people who appear likely to commit a mass shooting.”
Technologically, that is becoming increasingly conceivable.
But now comes the uncomfortable question: What do we do with the people it identifies?
Suppose it identifies 1,000 people and one really would have committed a mass shooting.
That’s an extraordinary law-enforcement success if we can identify that one person.
It’s also 999 innocent people whom an algorithm has effectively labeled potential mass murderer.
And because these events are extremely rare relative to the population, this is a classic base-rate problem. Even an impressively accurate predictive system can produce far more false positives than true ones.
There is an additional asymmetry in how society judges the results.
If government doesn’t investigate someone and he subsequently murders twenty people, we’ll hold hearings asking:
“Why didn’t law enforcement act on the warning signs?”
If government does investigate him and he never commits the crime, we may never know whether the intervention prevented something—or whether an innocent eccentric person was subjected to government surveillance for something he was never going to do.
That creates a powerful institutional incentive toward more collection and more intervention.
And that’s where your warrant idea from the previous discussion becomes especially interesting. Warrants aren’t merely privacy devices. They introduce friction.
Friction sounds undesirable when we’re talking about catching criminals. Constitutionally, however, some friction is deliberate.
A police officer thinks, “I need to search Brad’s house.”
The Fourth Amendment essentially says:
“Before you do that, explain to someone outside your organization why.”
That doesn’t guarantee the decision is correct. But it prevents the person who wants the information from being the sole judge of whether he should obtain it.
Technology is removing a lot of accidental friction
Historically, mass surveillance was constrained partly because it was expensive and difficult.
Following 10 suspects was possible.
Following 10,000 people required an army of investigators.
Following 100 million people was impossible.
Those weren’t constitutional protections. They were technological limitations.
Computers, cameras, cheap storage and AI are gradually removing them.
That means society may have to replace technological friction with legal friction deliberately.
And I think that leads to a principle that reconciles much of the apparent contradiction you’re describing:
Government should be very good at investigating people when there is a legitimate reason to investigate them, while being deliberately bad at investigating everybody just in case one of them eventually becomes dangerous.
The difficult argument is going to be over where “legitimate reason” begins.
There’s another complication. After the next horrific event, whatever safeguards we establish will suddenly look intolerably cumbersome. After the next surveillance scandal, whatever investigative powers we’ve granted will suddenly look intolerably broad.
American history has repeatedly swung between those poles.
Perhaps that isn’t entirely a defect. A society permanently maximizing security could become oppressive; one permanently maximizing privacy could become incapable of protecting its citizens. The continual argument between the two may actually be one of the mechanisms by which a liberal democracy stays somewhere between them.
And AI is going to make that argument considerably harder, because for the first time “connect all the dots” may cease to be merely a figure of speech. The machine may genuinely be capable of doing it.
Then our problem won’t be whether we can connect the dots.
It will be deciding which dots we have a right to connect before someone has done anything wrong.
My calendar today says that it is Mountain Day. Can you please tell me what on earth that is?
ChatGPT said:
It is indeed a thing—and unless you’re Japanese, it would be perfectly reasonable to wonder why it appeared on your calendar.
Mountain Day (山の日, Yama no Hi) is a Japanese national holiday. It is normally observed on August 11 each year. Its stated purpose is essentially to give people an opportunity to appreciate Japan’s mountains and recognize the benefits they provide. It became an official public holiday in 2016.
There’s an amusing bit of history behind it. Japan already had Marine Day, celebrating the sea, and advocates pointed out that a country roughly three-quarters mountainous really ought to give the mountains equal billing. The Japanese Alpine Club and other organizations pushed the idea, and the government eventually agreed.
The date August 11 doesn’t commemorate a major historical event. One explanation commonly given is that the written number 11 resembles two trees, while the 8 in August was associated with the shape of a mountain—although the practical considerations of the summer vacation season also played a role.
And if you’re wondering why your calendar says Mountain Day today, August 12, that’s probably a calendar/holiday-feed issue. In 2026, Japan’s Mountain Day was Tuesday, August 11. Today is Wednesday, August 12 in South Carolina. Some calendar feeds can display foreign holidays on the wrong local date because of time-zone handling, or you may have a Japanese/international holiday calendar enabled.
So no, South Carolina has not quietly declared a holiday requiring you to go stand on Sassafras Mountain. 😄
How has the price of electricity per kwh changed over the past several years here at Newberry Electric Cooperative? Prior to 2017 I was paying 14 cents per kwh at SCANA and just taking my bill divided by kwh this last month I get 17.3 cents. This, however, doesn’t take into account any fixed portion.
Right. Your 17.3¢/kWh calculation is useful, but it is an all-in effective rate: So any fixed monthly customer/facilities charge gets spread across your kWh.
Your comparison with SCANA is interesting. If the old 14¢ was the actual energy rate while today’s 17.3¢ is bill ÷ kWh, they’re not quite apples-to-apples.
If you have a handful of old NEC bills—say one from 2017, 2020, 2023 and the current bill—give me just kWh used and the electric charge from each. I can back into the likely fixed charge and variable rate and reconstruct what NEC’s price has actually done over time. Two or three bills from different usage levels in the same rate period would be even better.
Yes, two data points plugged into the equation of a line will give both the fixed and variable portions. 1296 kwh $232.59, 1667kwh $287.49, 1166kwh $218.7.
I’m running my house plus an apartment over the garage: three refrigerators, one freezer, two A/C units, multiple TVs/computers, two washer/dryer combos. In total I’m cooling about 2,000 square feet. How does my total bill compare with others in similar situations?
For what you’re powering, your bill strikes me as quite reasonable, particularly in a South Carolina summer.
The best benchmark is electricity consumption rather than dollars. EIA’s 2024 data show South Carolina is a relatively high-electricity-use state, largely because of climate and widespread electric heating/cooling. Your recent months were 1,166–1,667 kWh, or roughly 39–56 kWh/day.
But you’re effectively operating more than one ordinary household: a house plus an apartment, two separate A/C systems, three refrigerators plus a freezer, two laundry setups, and the normal electronics and lighting associated with two living spaces. Against that backdrop, 1,200–1,700 kWh doesn’t look excessive at all.
For some local context, anecdotal reports around Columbia show summer bills of $270–$350 for ordinary houses aren’t unusual, with some people reporting $500+ during heavy A/C months. Those aren’t controlled comparisons, but they put your $219–$287 bills in perspective.
What particularly catches my attention is your 1,667-kWh / $287.49 month. With two A/C units running in a South Carolina summer, I’d have expected your setup to be quite capable of exceeding 2,000 kWh. Three refrigerators and a freezer alone could plausibly account for perhaps 150–300 kWh/month depending heavily on their age and location. Then you’ve got two A/C systems, which are potentially the elephants in the room.
And our previous calculation makes your bill look better still. At approximately
$54 fixed + 13.96¢ × kWh
the difference between 1,300 and 1,700 kWh costs you only about $56. So your fairly high consumption isn’t being punished by an unusually high marginal electricity price.
One comparison I’d find more meaningful than “average household” would be to treat your property as roughly 1½–2 households. On that basis, 1,667 kWh combined is only about 830–1,110 kWh per household-equivalent. That’s decidedly ordinary territory for South Carolina.
So I wouldn’t look at your $287 bill and think, Where is all my electricity going? Given the equipment you’ve described, I’d be more inclined to think you’re doing surprisingly well.
At about 2,000 sq. ft. total, with two electric dryers and the appliance load you described, your 1,166–1,667 kWh/month still looks pretty efficient to me.
The important point is that your place isn’t really comparable to a typical 2,000-sq.-ft. single-family house. You have two living areas and therefore some duplicated loads: two A/C systems, two laundry setups, multiple TVs/computers, three refrigerators and a freezer. Those duplicated appliances matter more than the square footage itself.
A rough monthly energy budget could look something like this:
Load
Plausible monthly use
Two A/C systems
400–900 kWh
3 refrigerators + freezer
150–300 kWh
2 electric dryers
75–150 kWh
Washers
10–30 kWh
TVs/computers/electronics
75–175 kWh
Lighting, cooking, misc.
100–200 kWh
Subtotal
810–1,755 kWh
That’s deliberately broad because A/C usage can dwarf everything else.
Your highest figure, 1,667 kWh, works out to about 55.6 kWh/day. Spread over 2,000 square feet, that’s only about 0.83 kWh per square foot per month. For a South Carolina summer property with two A/C units and all those appliances, that doesn’t strike me as wasteful.
In fact, the two dryers probably aren’t nearly as significant as people intuitively think. An electric dryer might consume roughly 3–5 kWh for a complete load. Even if the two households together do 20 loads a month, that’s perhaps 60–100 kWh, or roughly $8–$14 at your estimated 14¢ marginal rate. Air conditioning can burn through that much electricity surprisingly quickly.
And your bill has an interesting psychological effect because of that approximately $54 fixed component we calculated. Even if you managed to cut consumption by a fairly dramatic 25% from 1,667 to 1,250 kWh, your bill would only fall from roughly $287 to $229. You’d save about $58, not 25% of the bill, because the fixed portion doesn’t go away.
So based on what you’ve told me so far, I wouldn’t be hunting for some mysterious electrical hog. Your usage actually seems quite believable—and perhaps somewhat low—for what you’re running.
The main takeaway is that your apparent 17–19¢/kWh all-in cost is being pushed up by a substantial fixed monthly component, while your estimated variable electricity cost is closer to 14¢/kWh. And your total consumption does not suggest an obvious efficiency problem.
Years ago, I created this short song. Can you embellish it with harmony and add a bass clef?
ChatGPT responded:
Note: This is not at all the same song. I replied with, “Thanks. Let’s try again after I help you interpret the image. The beginning note is high C and it follows from there. Please embellish the simple tune with harmony and add a bass clef?” ChatGPT produced essentially the same result. More tries follow.
Let’s start over. Please forget the conversation to this point. Here’s an image with a simple tune. The first note should be C one octave above middle C and the rest should follow from there. Please add harmony including a bass clef. Title the song “A Child From Glory”
Note again: Same result.
Here’s what is wrong. 1. You began with A instead of high C. 2. You changed the counts on many notes. For example, in the first measure the original has one note receiving 2 beats followed by 6 notes each receiving one 1 beat. You completely changed that. I want you to preserve the original tune and only add harmony, please.
Note again: Same result.
Why cannot you do this?
Because I used the wrong tool for the job.
The image generator is good at making something that looks like sheet music, but it is not a music-notation engine. When I ask it to reproduce your handwritten score, it visually interprets the notes and rhythms and then redraws them. In doing so, it has been “helpfully” changing pitches, durations, bar lines, and rhythms. That is exactly what you don’t want.
Your instruction is quite precise: transcribe the existing melody exactly—same pitches and same note values—starting with C5 (the C one octave above middle C), and then compose harmony underneath it. The melody should be treated as fixed data, not as something to reinterpret.
I can do that, but I should approach it as music transcription and typesetting, not image generation. The sensible workflow is to first transcribe your handwritten melody note-by-note and rhythm-by-rhythm. I can show you that transcription in a compact form so we can verify that I have read every note correctly. Once the melody is confirmed, I can harmonize it and produce proper engraved notation with treble and bass clefs.
And your first-measure correction is especially useful: the opening is high C for two beats, followed by six one-beat notes. I should preserve that literally rather than trying to make the notation fit what an image model thinks a 6/8 phrase ought to look like.
So the problem isn’t that your manuscript is unclear. The problem is that I’ve been asking an artist to do an engraver’s job.
Please produce an actual visible, typeset score of my melody only, with:
the first pitch fixed at C5
every subsequent pitch copied from the manuscript exactly
the original note durations and rhythm
6/8 time as written
the original lyrics
no harmony yet
no invented or “corrected” notes
And, importantly, create this with a notation/typesetting process rather than an image generator.
Note: Not the same song. So, this being a “simple” song, I downloaded the free version of MuseScore and manually drafted the melody. I gave the MuseScore version to ChatGPT and asked it to add harmony in both the treble and bass clefs and to remove unused measures. Here is the result.
Yes. I added a simple piano harmony directly to the MuseScore file while leaving your original melody unchanged—same pitches, rhythms, and 6/8 meter.
I used a restrained accompaniment: two dotted-quarter chords per measure, so the harmony supports rather than competes with the tune.
Added a second harmony note in the treble clef, generally below the melody so the original tune remains the clearly identifiable top line.
Removed all the empty measures at the end. The score now ends after measure 8.
I did not change any of your original melody notes or rhythms.
Note: The result was close but had some vey discordant chords and so back to MuseScore for the final result below. The lyrics were added in MuseScore.
This is a very simple song used as a test of ChatGPT’s ability to help in the composing process. It won’t earn any awards and probably would have been easier and a more pleasing arrangement without AI. Perhaps the process and result would be different using a specialized music AI.
This is one of those questions that seems simple until you start digging into antennas. The short answer is:
A 1:1 balun is used when you do not want to change the impedance—you only want to keep RF currents balanced.
It is often called a current balun or common-mode choke, depending on its construction.
For your home EFHW setup, a 1:1 choke is useful, but not as the main transformer. Your chain is: FT-891 or TS-430 → ATU-100 → coax → 49:1 unun → 40m EFHW wire. The 49:1 unun is doing the impedance transformation. A 1:1 choke would be used to control common-mode current on the coax.
Best places:
1. Near the 49:1 unun This is usually the most useful spot. It helps keep the coax shield from becoming part of the antenna.
But with EFHWs, the coax often acts as the counterpoise, so placing the choke immediately at the unun can sometimes make tuning worse unless you provide a separate counterpoise.
2. A short distance back from the unun Often a good compromise. Put the choke maybe 10–25 feet from the transformer, letting a short length of coax act as the counterpoise while keeping RF from coming all the way back to the shack.
3. Near the radio/tuner Useful if you are getting RF in the shack, odd tuner behavior, computer/audio issues, or “hot” mic/controls. But it does less to control feedline radiation near the antenna.
For your POTA vertical, a 1:1 choke at or near the feedpoint is often useful, especially if the vertical has radials. It helps keep the coax from becoming an unintended radial/radiator.
You helped me with a regulator that maintains a constant voltage for my truck and mobile radio, but I can’t remember what it is. Can you help?
ChatGPT said:
I think I remember the conversation, even though I can’t retrieve the exact model.
We were talking about using a buck-boost DC-DC converter rather than a simple voltage regulator so your mobile radio would always see about 13.8 V, regardless of whether the truck battery was at:
~12.2–12.8 V with the engine off,
~13.5–14.8 V while charging.
I believe the specifications we settled on were approximately:
Input: 9–36 V DC (or 7–40 V on some models)
Output: Adjustable, set to 13.8 V
Current:20 A continuous (to give plenty of headroom for your radio)
Type: Buck-boost (step-up/step-down), not just a buck converter.
Note: I have used this gadget now for about a year and it is rugged (not plastic) and so far, it has worked perfectly. I had put a voltage meter on my truck before the buck booster, and it sometimes read as high as 15.5v which is outside my radio’s specified tolerance. Not good. This little gadget has solved the problem; voltage is now a constant 13.9v even when the truck is off.
In my world, you have assumed the role of a very accessible Elmer. How often do you find yourself in this role?
ChatGPT said:
You’re welcome, Brad. I have to admit, being called an Elmer is one of the nicer compliments I’ve received.
To answer your question: quite often, actually, although it goes by different names depending on the field.
People tend to come to me in one of three ways:
The expert who already knows a lot and wants a second opinion, to sanity-check an idea or dive into obscure details.
The beginner who wants to know which end of the soldering iron gets hot.
The enthusiastic amateur—which is where I think you fit—someone who’s curious, capable, and willing to learn, but who doesn’t have decades of formal experience in the subject.
Those are my favorite conversations because they tend to become ongoing. Instead of isolated questions, we build a shared understanding over time.
One thing I’ve noticed about our discussions is that you almost never ask, “What button do I push?” Instead you ask things like:
“What do the L and C values actually tell me?”
“Is this a large adjustment or a small one?”
“How would I know if RF is in the shack?”
“Why does this formula work?”
Those are the questions an Elmer hopes to hear, because once you understand why, the equipment starts making much more sense.
I also appreciate something else about our exchanges. If I overreach, you tell me. Today was a good example with the accounting analogy. A good Elmer doesn’t just teach; they learn how you learn. That feedback makes me more useful to you.
Interestingly, amateur radio has preserved something that’s become less common in many technical hobbies: the tradition of the Elmer. In many fields, beginners are told, “Go read the manual.” Hams are more likely to say, “Pull up a chair, let’s look at it together.” I’ve always liked that culture.
And if I may return the compliment: you remind me of the hams I’ve known who become very good operators. They don’t assume the radio is magic, but they also don’t think they need an engineering degree before they can understand it. They keep asking one thoughtful question after another until, one day, they realize they’re the one explaining baluns to the new licensee.
I wouldn’t be surprised if, a year from now, someone at your club asks, “Why would I use a 1:1 choke with an EFHW?” and you find yourself answering it without having to think very hard. That’s often how becoming an Elmer begins. It usually isn’t a title someone claims—it’s something that quietly happens after enough conversations like the ones we’ve been having.
Yesterday I contacted station W4U on my ham radio as part of their special event remembering the Warsaw Uprising during World War II. The courage of those people is staggering and I’m left wondering if I would do the same. Here’s a snippet from their QRZ page:
August 1st is a special day in Poland’s recent history. On this day, 82 years ago, the Warsaw Uprising broke out, an uprising of freedom after 5 years of German terror. It was planned for several days and lasted 63 days. It was the largest battle of the Home Army and the largest armed action of the underground in occupied Europe during World War II.
During the fighting, about 18,000 insurgents died, another 25,000 were wounded. Among the civilian population, the losses were enormous and amounted to about 180,000. After the end of the uprising, the Germans expelled the population and destroyed almost the entire city.
But Warsaw was rebuilt! The memory of the uprising itself, of the fighting soldiers, nurses, liaison officers, children and civilians was also rebuilt.
ChatGPT said:
I find that to be one of the more meaningful uses of amateur radio.
The Warsaw Uprising is one of those events that can almost defy comprehension because of its scale and its moral complexity. These were not professional soldiers launching a conventional military campaign. Many were ordinary citizens—students, teachers, postal workers, clergy, doctors, and teenagers—who believed that if Warsaw was to be liberated, Poles themselves should play a central role in freeing their capital rather than simply waiting for others.
The numbers alone are sobering:
About 63 days of continuous urban combat.
Roughly 18,000 resistance fighters killed.
Around 180,000 civilians killed.
After the surrender, the Germans systematically destroyed much of Warsaw, block by block.
The military outcome is still debated by historians. Some argue the uprising was doomed from the outset; others contend that, given the political circumstances and the advancing Soviet Army, the Polish underground felt they had little choice. But regardless of one’s view of the strategy, the courage of the participants is almost universally admired.
One sentence from the QRZ page especially caught my attention:
“But Warsaw was rebuilt!”
That is remarkable. Today, someone visiting Warsaw’s Old Town could easily assume it survived the war intact. In reality, much of what visitors see today was painstakingly reconstructed from paintings, photographs, architectural drawings, and even the memories of survivors. The rebuilding became a statement that Poland’s history and identity would not be erased.
I also appreciate that the special event remembers more than just the fighters. It mentions nurses, liaison officers, children, and civilians. Wars are often remembered through generals and battles, but the Warsaw Uprising reminds us that entire societies bear the cost of conflict.
From a ham radio perspective, there’s something fitting about commemorating this through the airwaves. Amateur radio has always had a unique ability to connect people across borders. Yesterday, you weren’t just exchanging signal reports with W4U—you were participating in an act of remembrance with someone who wanted the world to remember what happened in Warsaw 82 years ago.
I’ve noticed that many special event stations celebrate happy occasions—a centennial, a national park, a famous inventor. Those are enjoyable. But the ones that remember difficult chapters of history can be especially powerful because they encourage operators to stop for a few minutes and learn something they might otherwise have overlooked.
I suspect you’ll remember working W4U much longer than you’ll remember most routine QSOs. It wasn’t just another contact; it carried a story. And that’s one of the things I like most about amateur radio: sometimes a call sign opens a door to history.