I’ve combined Amy Johnson Crow’s 52 ancestors in 52 weeks challenge, and Steve Little’s The 2025 AI Genealogy Do-Over, to create a unique 52 AI ancestors in 52 weeks party!

52 AI Ancestors in 52 Weeks: Week 43: Urban

Introduction

What brings a country boy to the city?

At the recent 22nd Annual Genealogy Lock-in co-sponsored by the Ridgewood Public Library and the Genealogical Society of Bergen County (both New Jersey, USA), I told another attendee that I had three separate SMITH lines (oh joy). But Jason M. Smith (1807 – 1890) of New York City is easier than he might have been, because he (and his children) very consistently recorded his place of birth as Vermont.

What prompted this move?

I found an article mentioning that move at NYS Historic Newspapers, a free online newspapers site focused on New York State where you can filter by county.

“His 80th Anniversary,” Richmond County Advance (Staten Island, NY), 17 Dec 1887, page 4, column 2, As found on nyshistoricnewspapers.org

Discussion

Jason Smith moved when he was just 7, so it wasn’t likely to have been his decision. The early move combined with the mention of an apprenticeship makes me wonder if he didn’t lose a parent at a young age. Another possibility is the War of 1812, since he would have turned 7 in 1814. Or perhaps it was economic conditions.

Nonetheless, Jason clearly “made it” in New York. He married twice and raised several children, all of whom seemed to live reasonably comfortable lives.

At 80, he was called “remarkably well preserved for a man of his advanced age.” Whatever the reason for his move, it was apparently a good thing for him.

Figure 1 ChatGPT’s imagining of Vermont to New York City

How AI can help

I can run my theories past AI as a sounding board:

Me to Google: economic conditions in 1814

Google AI’s response: In 1814, the United States experienced severe economic hardship, characterized by high inflation, a trade – crippling British blockade, and a government drowning in debt from the War of 1812.

Or, which theory makes sense? I ran this blog post through Copilot Researcher and asked it.

Me to Copilot Researcher: Using the attached blog post, what do you think of the three options I mentioned for why he moved? Are there reasonable alternatives I didn’t consider?

Copilot Researcher’s response:

Most plausible: Jason’s move at age 7 was likely due to the loss of a parent. In early 1800s New York, fatherless children were often placed in apprenticeships or sent to live with guardians, especially if the family lacked resources. The mention of an apprenticeship strongly supports this scenario. If his father died around 1814, it would explain both the relocation and Jason’s early entry into city life.

Also plausible: Economic hardship during the War of 1812 – especially the trade blockade and inflation – could have pushed the family to seek better opportunities in New York. The timing aligns with widespread financial strain in Vermont, and urban centers offered more support and work options.

Less likely but possible: If Jason’s father served in the War of 1812 and died or was disabled, that could have triggered the move. However, without direct evidence of military service, this remains speculative.

Other ideas: Family migration, remarriage, or urban job prospects may have played a role, but they’re harder to confirm without more records.

I don’t think Jason’s parents had died, but I am not GPS – level confident (I’m not sure I could meet the Genealogical Proof Standard on that supposition). But, AI can be a great sounding board for my theories, and can provide valuable historical context.

Challenge for Readers

Try this two-part “urban exploration” challenge:

1. Map It Out – Pick one ancestor who lived in a city or town. Use an online historical map (such as the David Rumsey Map Collection or Sanborn Fire Insurance Maps) to locate their neighborhood. What was nearby – factories, churches, schools, or parks?
2. Ask AI – Upload a short description of that ancestor’s life to an AI chat tool and ask:

“What might daily life have been like for someone living here around [year]?”
Compare the AI’s answer to what you find in city directories, newspapers, or censuses. How close is it?

(And for extra credit: see if AI can find connections between your ancestor’s city job and migration patterns of the time!)

AI can suggest possible scenarios, but remember it doesn’t replace checking probate or church records.

Want to Learn More?

• Copilot Researcher: https://www.microsoft.com/en-us/microsoft-365/copilot – overview of Microsoft Copilot features for research and writing

Here are some free, trustworthy resources to look into your city – dwelling ancestors:

• NYS Historic Newspapers: nyshistoricnewspapers.org – already helped in this post!
• Chronicling America: chroniclingamerica.loc.gov – U.S. historic newspapers searchable by city and date.
• City Directories on FamilySearch: familysearch.org/search/catalog – find local residents, occupations, and addresses.
• David Rumsey Map Collection: davidrumsey.com – high – resolution maps for historical city research.

Jason’s story reminds us that even a childhood move two centuries ago can echo through generations – and with a little AI help, we can listen more closely.

Next Week’s Topic: “Rural”

AI Disclosure

This post was created by me with the help of AI tools. While AI helps sort out research, the storytelling and discoveries are my own.

I’ve combined Amy Johnson Crow’s 52 ancestors in 52 weeks challenge, and Steve Little’s The 2025 AI Genealogy Do-Over, to create a unique 52 AI ancestors in 52 weeks party!

52 AI Ancestors in 52 Weeks: Week 42: Fire

Introduction

Most of us hope to find old photos, love letters, or maybe a land deed in our genealogy research. I found a fire.

It came by way of a newsletter from the now-defunct Henry County Genealogical Society. Inside was a reprinted clipping from the Democratic Northwest and Henry County News, and there, under the quiet clatter of the surname “West,” was a fiery surprise. A few page flips later, I had the full story. And sure enough, there was my ancestor, J[ohn] T. West, listed in the aftermath of a town-wide disaster.

Discussion

On Sunday morning, May 26, 1889, a fire broke out at 2 a.m. in the oil room of Viers’ hardware store in Liberty Center, Ohio. It spread fast. In the words of the article:

“Seven buildings with most of their contents were licked up by the fierce flames.”

John T. West owned the stable across the alley from the hardware store, and it didn’t stand a chance. The flames jumped to his property almost immediately. By the end, the fire had consumed:

• Two stables (including West’s)
• A residence
• A barber shop
• A saloon
• A meat market
• A large ice house

The community fought the blaze valiantly, but with no functional fire engine – locked away due to a legal dispute with the town council – there was only so much they could do.

John T. West’s stable was insured for just $100. In today’s dollars? Still not enough.

How AI Can Help

Once I had the article, I was curious about the broader picture. Could AI help me:

• Understand the historical value of $100 in 1889?
• Reconstruct what a livery stable might have looked like?
• Locate other fires in Liberty Center’s past?

It turns out, yes.

I asked ChatGPT to help me estimate the 1889-to-modern equivalent. It also described the typical use of a stable in a rural Ohio town at the time: transportation hub, business asset, sometimes even housing for boarders or deliveries.

The most helpful prompt I used:

“In 1889, if a livery stable was insured for $100, what would that cover, and what might the true loss have been?”

The answer wasn’t exact (and shouldn’t be taken as legal advice), but it painted a richer picture than I could’ve imagined. A stable wasn’t just a building; it was a livelihood. Which means the West family didn’t just lose lumber and nails. They lost income.

Challenge for Readers

Have you ever found your ancestor in a newspaper article – burning barn, flood, blizzard, or scandal?

Try this:

• Search local newspaper indexes or newsletters for your ancestor’s surname + town.
• Ask an AI tool: “What disasters happened in [town] between [year] and [year]?”
• Use AI to recreate a scene: “Describe what a town fire in 1889 would have looked like.”

And if your ancestor lived through a town-wide disaster, try mapping their recovery. Did they move? Rebuild? Disappear from the record?

Sometimes, it’s the smoke that shows us where to dig.

🧭 Summary

Thanks to one local newspaper and a dedicated genealogical newsletter, I discovered my ancestor wasn’t just living in Liberty Center: he was living through literal fire. AI helped me understand the scale of the loss and place the event in context. The past doesn’t always come quietly. Sometimes, it burns.

---

📚 Want to Learn More?

• Liberty Center Conflagration
• Inflation Calculator: 1889 to Today
• Ohio Memory – Historic Newspapers
• Prompt idea: “Explain what a livery stable was like in rural Ohio in the 1880s.”

Next Week’s Topic: “Urban”

AI Disclosure

This post was created by me with the help of AI tools. While AI helps organize research, the storytelling and discoveries are my own.

I’ve combined Amy Johnson Crow’s 52 ancestors in 52 weeks challenge, and Steve Little’s The 2025 AI Genealogy Do-Over, to create a unique 52 AI ancestors in 52 weeks party!

52 AI Ancestors in 52 Weeks: Week 40: Cemetery

Introduction

Even experienced genealogists get it wrong sometimes. Here’s a quick story and a simple tip for cemetery lookups.

Discussion

Some years ago, I wanted to request a photo on Find A Grave of my husband’s great grandparents’ grave.

I was quite pleased to have located death records for them with the cemetery identified, and created memorials so I could ask for photos. I created a Joseph Frank memorial and one for his wife Jennie Felder or Feldeloss in 2011. They were buried in the same cemetery in different sections.

Joseph’s photo was added the following year, but Jennie’s just languished. I couldn’t figure out why, but went on with other things.

Perhaps you’ve already spotted my error. In 2020, a kind genealogist located Jennie Frank, and uploaded the photo. Oops. As a genealogist, I only thought of her under her maiden name, but she was buried under her married name. That must have been one dogged photographer, and I am so grateful to that volunteer.

How AI can help

My mistake with Jennie sat for years because I didn’t circle back to unfinished requests. Today, AI tools can nudge us when something looks unfinished. For example:

• Name Variations: AI can spot common errors like using a maiden name instead of a married name. Upload your records, and an AI assistant can suggest alternative searches you might have overlooked.
• Research Reminders: Instead of forgetting a stalled request, you could ask AI to keep a “research to-do” list. It can summarize what’s pending, flag what hasn’t been wrapped up, and even generate reminders to check back on memorial sites or archives. (Side note: AI even reminds me weekly to report on my foster cats!)

The goal isn’t to let AI “do the genealogy” for us, but to use it as a second set of eyes: a patient research buddy who notices what we miss when our attention drifts elsewhere.

Challenge for Readers

Try one (or both) of these experiments with free AI tools:

1. Name Variations Test: Take a record from your own research where you’ve been stuck. Ask an AI tool (like ChatGPT or Claude) this:
   “Suggest possible alternative names or spellings for [insert ancestor’s name], including nicknames, misspellings, or married names, that might appear in records.”
   See if it sparks a new search idea.
2. Research To-Do List: Paste in a short list of your current “incomplete tasks” (like pending Find A Grave photo requests, document orders, or unanswered emails). Ask:
   “Turn this list into a simple research reminder I can check weekly.”
   Bonus: Have it format the list as a timeline or checklist to keep things moving.

Next Week’s Topic: “Water”

AI Disclosure

This post was created by me with the help of AI tools. While AI helps organize research, the storytelling and discoveries are my own.

I’ve combined Amy Johnson Crow’s 52 ancestors in 52 weeks challenge, and Steve Little’s The 2025 AI Genealogy Do-Over, to create a unique 52 AI ancestors in 52 weeks party!

52 AI Ancestors in 52 Weeks: Week 39: Disappeared

Introduction

My ancestor Andrew DRISKOL never existed.

At least, not on paper.

Several people, born England and New York from the 1860s to the 1880s, claim their father was Andrew DRISKOL born Germany.

I’ve written about him before, 35 weeks ago, in Overlooked. But he truly is a disappeared also.

Discussion

I wish I could say that since I wrote about him early this year, I have uncovered some miracle findings. Unfortunately, though I have re-examined records, I have no new revelations.

A son was born in 1883.

Andrew’s wife was a widow in 1900.

His eldest son seems to have bought property in 1890, so one can speculate that he had died by then, as son Edward seemed to be acting as head of the house.

So the first step in any research question is, “What do you know?” Here’s my writeup on him:

Andrew Driskol was born ca. 1835-1840 in Prussia. He married Malvina Hendell probably between 1860 and 1865, possibly in England. Andrew immigrated to the United States about 1868-1869, followed by his wife and eldest children about 1875. He died between 1883 and probably 1890. Documentation for Andrew’s life derives primarily from his children’s vital records, as direct records for him have not been located in standard repositories.

Immigration and Settlement:

Andrew’s initial settlement in New York City, evidenced by his daughter Mary’s birth there about 1876, was followed by the family’s relocation to Staten Island, where subsequent children were born between 1878 and 1883. The family’s absence from both the 1870 and 1880 federal censuses suggests either enumeration under variant names or temporary residence outside standard enumeration areas.

Death and Family Survival:

Andrew’s death occurred by 1890, as evidenced by his son Edward’s property purchase on Van Pelt Avenue at age 25, suggesting assumption of family financial responsibility. By 1900, Malvina was enumerated as a widow. Edward Driskol survived as the family’s last known member, residing in Kew Gardens, Queens, as of 1938.

Possible timeline:

He was married to Malvina Hendell.

Ultimately, Andrew disappeared – on both ends of his life – to me.

How AI can help

Let’s not use any fancy tools this time, but some good old-fashioned LLM prompting.

Using ChatGPT 5, ask:

Using the Genealogical Proof Standard (GPS) as a basis, create a research question for Andrew Driskol. His biography so far is: <paste it here>

Its research question (RQ) was far too long; it responded:

What are the origins, immigration circumstances, and death details of Andrew Driskol, born ca. 1835–1840 in Prussia, who married Malvina Hendell about 1860–1865 (possibly in England), immigrated to the United States ca. 1868–1869, settled in New York City and Staten Island, and died between 1883 and 1890?

I encouraged:

What are the standards around generality vs granularity of a research question? Is that a good RQ, or is it too broad?

ChatGPT justified itself using the GPS, so I looked up Standard 10, Effective research questions, which covers how to frame a clear, testable research question. And while I would not ever draft such a research question, it does seem that the LLM’s is supported by Board for Certification of Genealogists. However, my brain would get overwhelmed, so I forced a narrower question:

OK, Let’s focus on the death so that I can understand. Create a research question for that, and a research plan to answer that question.

I got the updated RQ:

Research Question (Granular)

When and where did Andrew Driskol, born ca. 1835–1840 in Prussia and husband of Malvina Hendell, die between 1883 and 1890, likely on Staten Island, New York, and what records document that event?

And the research plan:

Research Plan

1. Define Context

• Known facts:
  • Last known child born Staten Island, 1883.
  • Absent by 1890 (Edward assumed financial role).
  • Malvina a widow by 1900.
• Death window: ca. 1883–1890.
• Likely place: Staten Island (Richmond County, NY), but consider broader NYC.

---

2. Identify Possible Record Types

Civil Records

• NYC Death Certificates (1866–1897): Check NYC Municipal Archives index (also on FamilySearch/Ancestry).
• NYC Department of Health death registers: May list cause of death, burial place, occupation.

Church & Cemetery Records

• Search Catholic, Lutheran, Jewish, Episcopal churches near Staten Island residences.
• Identify burial grounds: Silver Mount Cemetery, Moravian Cemetery, St. Peter’s Cemetery, Lutheran Cemetery (Middle Village, Queens), etc.

Newspapers & Obituaries

• Staten Island Advance (began 1886), New York Herald, New York Times.
• Local German-language newspapers (if Driskol/variant targeted immigrant community).

Probate & Court Records

• Richmond County Surrogate’s Court: estate files, guardianship if minor children.
• Deeds in Edward’s name may reference inheritance or widow’s release of dower rights.

Directories & Tax Records

• NYC and Staten Island directories (late 1870s–1890s).
• Absence after certain year may suggest timing of death.

Census & Substitutes

• 1880 Census: already noted missing.
• 1890 NYC Police Census (1890–1891): Surviving substitute for parts of NYC (check Staten Island).

---

3. Search Strategy

1. Start with death indexes (FamilySearch, Ancestry, ItalianGen, NYC Historical Vital Records site).
   1. Try variant spellings: Driskol, Driscoll, Driskoll, Driscol, Drisckel, etc.
   1. Search both Andrew and possible Anglicized/Germanic versions.
2. Check cemeteries
   1. Query burial registers (FindaGrave, BillionGraves, local cemetery offices).
   1. Look for Hendell family burials; Malvina may be buried near Andrew.
3. Newspapers
   1. Search 1883–1895 in local & regional papers for death notices.
   1. Broaden to German-language press (e.g., Staats-Zeitung).
4. Probate
   1. Search Richmond County Surrogate’s Court (on-site, microfilm, or via index).
   1. Look for estate of Andrew or guardianship for children.
5. Property Records
   1. Review 1890 Van Pelt Avenue purchase by Edward.
   1. Check grantor/grantee indexes ca. 1883–1890 for Driskol/variant.

---

4. Correlation & Resolution

• Compare death certificate data, if found, with known facts (age, occupation, spouse).
• If absent, correlate indirect evidence:
  • Last mention (1883 child’s baptism/birth).
  • First absence (Edward’s property purchase, widow status in 1900).
  • Directories/obituaries/probate to tighten timeframe.
• Write a conclusion using the GPS elements: reasonably exhaustive research, correlation of sources, resolution of conflicts (e.g., multiple men with similar names), and soundly reasoned conclusion.

---

✅ This plan moves you from the umbrella RQ → a specific, testable sub-question → a roadmap of sources, with contingency steps if the death certificate itself isn’t found.

So I guess I’m off and running. Again. Andrew, your elusiveness is only temporary!

Challenge for Readers

Have someone on your tree who “disappeared”? This week, try this:

1. Write a brief timeline for your ancestor, just like the Andrew Driskol example. Keep it simple: birth, marriage, immigration, kids, last known date.
2. Craft a research question using Standard 10 from the Genealogical Proof Standard. Don’t overthink it—aim for something testable, not perfect.
3. Use ChatGPT (or a free LLM) to check your research question. See how it responds. What would you keep or tweak?

Bonus: Post your research question in the comments or your favorite genealogy group to crowdsource ideas. You’re probably definitely not the only one chasing a ghost.

Want to Learn More?

• Explore the Genealogical Proof Standard: Start with this article from BCG and focus on Standard 10 about research questions.
• Prompting Tips for Genealogists: Try different phrasing in ChatGPT. Compare broad vs. narrow questions and ask, “What records would help answer this?”
• Free LLMs you can use:
  • Perplexity.ai
  • Claude.ai
  • Microsoft Copilot (built into Edge)

Even if you’re not an AI expert, you can still use these tools to test ideas, brainstorm new paths, or just help spot what’s missing.

Next Week’s Topic: “Cemetery”

AI Disclosure

This post was created by me with the help of AI tools. While AI helps organize research, the storytelling and discoveries are my own.

---

[1] Census ages varied but ultimately since Malvina likely immigrated April of 1875, I feel Mary was born 1876.

I’ve combined Amy Johnson Crow’s 52 ancestors in 52 weeks challenge, and Steve Little’s The 2025 AI Genealogy Do-Over, to create a unique 52 AI ancestors in 52 weeks party!

52 AI Ancestors in 52 Weeks: Week 38: Animals

Introduction

If not for a horse, I might not be here.

Figure 1 Henry

Discussion

My grandmother said her father, Henry MACKEY / MAKEY (1881 Buffalo, New York –1958 NYC) was short of stature (“Medium” height in his WWI Draft card, but probably much less in his WWII Draft card – it’s somewhat illegible), worked as a “horse jockey until a fall.”

WWI:

WWII:

Sure enough, the 1900 census has him in Chicago as an “asst Horse trainer.”

1900:

However, by his 1903 marriage he had moved to Staten Island New York, likely following his brother William, who had married a Buffalo-born girl in Staten Island in 1902. He ended up working as an engineer, helping to pave the streets of Queens, New York with a steamroller.

If not for that fall from a horse, he might not have followed his brother to NY and might not have met my great grandmother and had my grandmother. So while my great grandfather might have disagreed at the time, I am grateful to that horse!

How AI can help

If you have an ancestor like Henry, whose occupation shifted because of an animal-related incident, here are some ways AI tools can help you explore more:

1. Simulate Historical Jobs

You can ask ChatGPT to recreate a “day in the life” of a horse trainer or steamroller operator in 1900s Chicago or New York. These simulations help you understand the physical demands and risks your ancestor might have faced.

Try this prompt:

“Describe a typical day for a horse trainer in Chicago in 1900.”

Or if you want more detail:

“What kind of injuries were common for jockeys or horse trainers around 1900?”

2. Contextualize Job Changes

Henry’s shift from “asst horse trainer” to steamroller engineer was big. [That change might sound dramatic, but it may have felt familiar—his father worked on ship steam engines.] AI can help make sense of that pivot by explaining industrial changes in transportation, paving, and labor trends in early 20th-century urban areas. That gives more context than census records alone.

3. Read Hard-to-Read Documents

Your WWII draft card might be as hard to decipher as mine. AI-powered OCR (Optical Character Recognition) tools can help extract and interpret text from poor-quality scans. Upload the image to a free OCR tool and then ask ChatGPT:

“Help me interpret this draft card. What does the height field say?”

ChatGPT told me 5′ 7 ¼”. But I know that’s wrong because it’s clearly ¾”. So the takeaway here is that if it’s tough for me, it’s tough for AI as well.

4. Visualize the Journey

Use AI to map Henry’s path—from Buffalo to Chicago to Staten Island—by creating a timeline or travel route. Ask:

“Create a travel timeline from Buffalo to Chicago to Staten Island around 1895–1905 for a working-class man.”

Challenge for Readers

• Do you have a relative whose life was changed by an animal—whether through farming, injury, or friendship?
• Can you identify a job title in the census that involved animals? Try asking AI to explain what that job involved, or generate a short description of a typical workday.

Next Week’s Topic: “Disappeared”

AI Disclosure

This post was created by me with the help of AI tools. While AI helps organize research, the storytelling and discoveries are my own.

Prompt: “The theme for Week 37 is “In the News.” Have you made a family history discovery in a newspaper? What about a reporter, editor, or newsie in the family?”

I’ve combined Amy Johnson Crow’s 52 ancestors in 52 weeks challenge, and Steve Little’s The 2025 AI Genealogy Do-Over, to create a unique 52 AI ancestors in 52 weeks party!

52 AI Ancestors in 52 Weeks: Week 37: In the News

Introduction

What newsworthy discoveries have you found in your family history? You might have found a family link, or an ancestral accomplishment. Perhaps a scoundrel was exposed, or a migration uncovered.

For me, it’s finding good people. I just love reading my ancestors’ obituaries and finding that they were well-respected among their peers, and learning that I have good in my blood.

Discussion

Of course, it’s not all good. My grandfather, who worked for a newspaper, took a jab when his daughter married a man he disapproved of: “Elise West, Dongan Hills Man Wed” read the headline. [1]

But it’s mostly good news. Adam West was “a good citizen, a dependable merchant, honest and upright in dealing with everybody.”

William Carey’s obituary discussed his “faithfulness to duty” and stated that he “was a man highly respected by his acquaintances, and a good citizen.” [2]

Adam’s father, John T. West, “was a faithful worker and supporter of the church.” [3]

Jason M Smith got to see his celebration while he was still alive, in an article lauding his 80^th birthday, calling him “remarkably well preserved.” [4]

Michael Dobbins’s 1886 obituary called him “an old and respected citizen.” Sadly, I don’t have a clipping in my e-files, and don’t have the energy for my paper files.

His wife Mary Malone “is much respected and will be sadly missed.” [5]

I do know that I have more of these which have not yet been organized. “Don’t take me, Lord, my genealogy isn’t done yet!”

But think how much fun you can have looking for your ancestors in old newspapers, more and more of which are coming online!

How AI can help

AI is OCR’ing and indexing newspapers all the time!

Crawling AIs like Microsoft Researcher can find newspapers for you too.

When I asked Copilot for Kansas City newspapers in 1886, it listed seven of them:

It offered help locating digital copies of these newspapers online, and provided more information:

AI is a big help for projects like newspaper research!

Challenge for Readers

Newspapers are coming online all the time. Don’t let a lack of past success stop you from trying now. Go to your favorite LLM and ask a question like I did:

What newspapers were in <location> in <year>? Help me find them online.

Then go follow the trail!

Want to Learn More?

• For researching:
  • Microsoft Researcher is found within Copilot
• • Perplexity
  • Google Gemini
• For newspapers:
  • Free
    • Chronicling America
• • • List of links: Wikipedia
• • • Google News
• (goodness, this WordPress formatting is a bear. Go easy on me, please.)
  • Paid
    • Newspapers.com
    • Newspaper Archive

These are just a sampling of the many, many links out there!

Next Week’s Topic: “Animals”

AI Disclosure

This post was created by me with the help of AI tools. While AI helps organize research, the storytelling and discoveries are my own.

---

[1] “Elise West, Dongan Hills Man Wed,” Staten Island Advance (Staten Island, N.Y.), 22 May 1965, page 5, column 3.

[2] “William Carey,” Madison Eagle (Madison, NJ), 20 Mar 1903, page 5.

[3] Source unknown, but would have been a Liberty Center or Toledo-area newspaper in Ohio in 1924.

[4] “His 80th Anniversary,” Richmond County Advance (Staten Island, NY), 17 Dec 1887, page 4, column 2, As found on nyshistoricnewspapers.org

[5] “Argentine,” Kansas City Times (Kansas City, Missouri), 02 Feb 1886.

I’ve combined Amy Johnson Crow’s 52 ancestors in 52 weeks challenge, and Steve Little’s The 2025 AI Genealogy Do-Over, to create a unique 52 AI ancestors in 52 weeks party!

52 AI Ancestors in 52 Weeks: Week 35: Off to Work

Introduction

Introduction: The Family Commute

I used to watch my dad board the bus to “the city” (Manhattan) every morning. Same time. Same bus. Same briefcase. There was something both comforting and mysterious about it. I didn’t really know what he did all day. I just knew he went to work. That ritual – coat on, door shut, bus gone – was the first time I realized adults had lives beyond the kitchen table.

Mom was a stay at home with three young children, and Daddy’s arrival heralded dinner and a fun evening. Perhaps we’d work with us on his HO trains, or maybe Star Trek was on that night, or maybe there was another project that needed doing.

Discussion

Section 1: The Man with Molten Type

Before my dad commuted and long before I tapped my first line of code, my (maternal) grandfather worked as a linotype operator: a job that’s now as extinct as the machines he used.

If you’ve never seen one, imagine a typewriter and a small smelter had a very noisy, very dangerous baby. Each line of text was literally cast in hot lead. He didn’t just “type” – he composed entire newspaper pages, one line at a time, one letter at a time, backwards and in metal.

I was 4 when Grandpa retired and didn’t get to visit his place of employment. But years later, in middle school, I took a printing class and got to experience typesetting firsthand. I made several memos with headings such as “Memo from Janet.”

Grandpa’s job demanded precision and speed. A missed letter could ruin a whole page. Burned fingers weren’t rare. But he did it every day for 40 years at the same place.

---

Section 2: Then Came the Code

Just as he arranged type into meaning, I would later arrange code into logic.

Fast forward a few decades, and I found myself in front of a screen instead of a metal keyboard as a computer programmer. When I started, we used punch cards! Eight-inch floppy disks! (gasp) COBOL! Now, code lives in the cloud, and debugging means asking an AI model what went wrong.

But really, the job hasn’t changed that much. Like my grandfather, I still sit in front of a machine and try to arrange symbols into meaning. His lines were made of lead; mine are made of logic.

I am awed and amazed when I consider the change that has happened in my industry in the past 40 years. Steve Little said in his AI class, “I’ve spent 40 years preparing for this year and the next.” I feel the same way.  My father’s routine, my grandfather’s grasp of language, and my logic skills all come together in my current job of creating educational materials for technology learners.

Sometimes I wonder what he would think of my job. Would he laugh at the idea of “virtual servers”? Would he nod in approval at a well-written script? Or would he just say, “At least you’re not setting your eyebrows on fire”?

How AI can help

AI can’t cast a line of hot lead, but it can help us work with the printed word in new ways. Tools like OCR (optical character recognition) can turn old newspapers or documents into searchable text. AI can even clean up fuzzy scans, translate foreign-language articles, and suggest connections you might have missed in census or work records. Just as my grandfather worked to set the words straight, I can now ask AI to straighten out a crooked page from 1905.

This isn’t just theory—AI has already changed how we do genealogy research. One great example of AI doing this is indexing the United States Federal Census.

FamilySearch says that it took 17 years to index the 1880 census. With the help of AI and human reviewers, the 1950 census was completely indexed and reviewed in three months. And usually whatever was still an issue, could be located with the help of tools like Steve Morse’s Census ED finder.

Challenge for Readers

Think about the workers in your own family tree.

• Who had a job that no longer exists?
• Can you picture a relative “off to work” each day—maybe with a lunch pail, uniform, or briefcase?
• Write a short memory, or search the census to see how your ancestors described their occupation.

Then, consider how that work has changed—or vanished—over time. Share your story in the comments or with your own #52Ancestors entry.

Want to Learn More?

Curious about linotype machines? Check out these:

• Linotype at Wikimedia Commons – a close-up view of the machine my grandfather worked on.
• Library of Congress Newspaper Navigator – explore historic newspapers that linotype operators helped set.
• FamilySearch Wiki: Occupations – tips for understanding your ancestor’s work.
• AI Genealogy Do-Over with Steve Little – a modern approach to using AI in family history.

Conclusion: Work, Then and Now

Three generations, three very different workdays—but the rhythm is oddly familiar. We leave the house (or open the laptop), focus on our task, and come home changed—sometimes tired, sometimes proud, sometimes wondering what we really accomplished.

I have long impressed upon my children the value of education. I hope as a corollary they see how important hard work is as well.

Today, no one boards a bus in my household, and molten metal is blissfully absent. But the spirit of showing up and shaping something with your brain and hands? That’s alive and well.

Figure 1 Linotype typesetting machine at Wikimedia Commons

https://commons.wikimedia.org/wiki/File%3ALinotype_typesetting_machine.JPG

Next Week’s Topic: “Off to school”

AI Disclosure

This post was created by me with the help of AI tools. While AI helps organize research, the storytelling and discoveries are my own.