Genealogy

52 AI Ancestors in 52 Weeks: Week 9: Family Secrets

/ jannetjeb / Leave a comment

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 9: Family Secrets

Introduction

This week’s discussion is on Family Secrets. My paternal grandmother told me many family history stories – all of them wrong. I loved Grandma, but boy, did she spin them.

Discussion

One of the stories I got was about her maternal grandfather, James HART. When I was a baby genealogist and new to the hunt, I did manage to do the “family interviews” part. Grandma told me that James was killed “in a hunting accident” when she (born 1916) was “a girl.”

To say that I searched for years for his death is an understatement. When my boys were small and I was a Cub Scout den leader, we visited a state park where I asked a Park Ranger about researching hunting deaths from the 1920s. They gave me a phone number but it didn’t get me anywhere.

I didn’t find his death in the vitals indexes during the time period I thought it would have happened.

When newspapers started coming online, I spent many late nights getting bleary-eyed.

Finally one day, after my grandmother and father died in quick succession, I was going through family photos and found one labeled “Bob [my dad] with Joseph and Joe <redacted>.” That surname had cousins on this line so I did an internet search to get the photo back to the family. I connected with a cousin and we spent time discussing family history.

“James?” he said. “Oh, he shot himself.”

Wait, what?

Must have been a hunting accident, right?

Nope.

The newspaper headline is “Despondent Man Ends Life With Shotgun.” He was not in the woods and he very deliberately exited this world.  

Grandma, your family secret is no more.

Depression runs through our family, but until recently no one would discuss it.

How AI is Helping My Research

I asked AI how it can help me identify patterns of depression running in a family. It offered several options:

  1. Analyzing Obituaries and Newspaper Reports

AI-powered tools like Newspapers.com and Chronicling America use Optical Character Recognition (OCR) to search for terms like “despondent,” “melancholy,” or “troubled” in historical newspapers, which might indicate depression or suicide.

AI sentiment analysis can review obituaries or death reports to detect language patterns related to mental health struggles.

2. Detecting Mental Health Clues in Family Records

AI-assisted genealogy platforms (like Ancestry and MyHeritage) can analyze cause-of-death records across generations, looking for recurring trends such as “self-inflicted wound,” “nervous breakdown,” or “institutionalized.”

AI handwriting recognition tools can decode personal letters, diaries, and census records to find mentions of mental health conditions.

3. Cross-Referencing Medical and Historical Data

AI can help analyze old medical records and census documents to identify patterns of institutionalization or hospitalization in a family tree.

Tools like Google’s BERT AI model or ChatGPT can scan large volumes of historical text and extract relevant information related to mental health.

4. Family Tree Pattern Recognition

AI tools can analyze relationships and life events to identify stressors that may have led to depression or suicide, such as economic downturns, family deaths, or war experiences.

Predictive modeling could compare your family’s history to broader social trends, revealing external factors that contributed to mental health struggles.

5. Speech-to-Text for Oral Histories

AI transcription tools (like Otter.ai or Whisper) can convert old family interviews into searchable text, helping you detect recurring themes of depression or emotional distress in family stories.

6. Photo Analysis for Hidden Clues

AI-powered facial recognition tools might help analyze historical photos for physical signs of illness or distress.

Some AI models can even compare expressions across multiple generations to spot potential inherited traits related to emotional well-being.

Challenge for Readers

Mental health research may not be as thrilling as chasing an elusive ancestor, but it’s just as important. It’s crucial to have the knowledge in order to combat it.

My recommendation: give your GEDcom to an AI model such as Claude or ChatGPT and ask it to look for words indicating mental health struggles, identify the people, and identify clusters or potential inheritance of such. Add in other factors such as military service and other situational and environmental factors. With that information, we may be able to identify those who are more at risk, and take early steps for treatment.

Summary and Next Steps

I’m so grateful that my father, a young adult in the 1960s, thought it important to be open and honest with me, and impressed on me the value of keeping the lines of communication open, even as we had our own mighty struggles. He worked so hard to fight the secrecy he’d been raised in so that we could do better.

Grandma, the truth is finally known—and it’s for the better.

A man with two boys posing for a photo, in black and white

The photo that broke the brick wall

Disclosure

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

52 AI Ancestors in 52 Weeks: Week 8: Migration

/ jannetjeb / 1 Comment

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 8: Migration

Introduction

Migration is a theme that touches every genealogist because all of us descend from migrants. My own maternal haplogroup, I4, traces a journey from eastern Africa through the Middle East to Europe. But rather than focusing on just my distant ancestors, I’m turning the lens inward—to my own migration story.

Migrations

I take great pride in my American ancestors, from the religiously persecuted Huguenots who arrived in 1624 to the post-famine Irish who faced hardship head-on. For generations, my family remained rooted on the East Coast of the United States, particularly Staten Island, New York, where they settled in 1665. I was born and raised there, had my children there, and expected that our roots would remain firmly planted.

Then came the attacks of September 11, 2001.

I was in Manhattan when the towers fell. My husband managed to reach our small children, but I was trapped in the city, desperate to get home and hold them close. Like many others, I left New York in the time that followed. My father remained, the last of my direct line on Staten Island. When he passed in 2009, the link to my ancestral home of nearly 350 years was severed. What was once my family’s anchor became a memory.

Figure 1 By Niels Jørgensen (1859-1943) – bruun-rasmussen.dk, Public Domain, https://commons.wikimedia.org/w/index.php?curid=80153432

How AI is Helping My Research

AI is transforming how we understand migration, both in the broader historical sense and in personal genealogy. Here are some ways AI is assisting my research:

  1. DNA Analysis & Migration Patterns: AI-driven tools like MyHeritage’s “Theory of Family Relativity” and 23andMe’s haplogroup mapping provide insights into ancestral migration routes. AI helps compare my DNA with ancient population data, identifying possible pathways my ancestors took.
  2. Historical Record Analysis: AI-powered platforms like Ancestry’s StoryScout and FamilySearch’s record hinting system analyze documents, connecting names, locations, and migration events. AI can surface records I might have overlooked, revealing new details about how and why my ancestors moved.
  3. Newspaper & Obituary Searching: AI-driven newspaper archives can identify migration clues hidden in articles, obituaries, and legal notices. By scanning old papers for names, locations, and key terms, AI has helped me uncover mentions of family moves, ship arrivals, and land purchases.
  4. Census & Ship Passenger List Analysis: AI makes searching census records more intuitive, predicting potential matches and migrations by analyzing occupation changes, neighbors, and household structures. Passenger lists and naturalization papers also benefit from AI’s ability to extract and organize details quickly.
  5. Geographical Data Visualization: Tools like Google Earth’s AI-powered historical overlays allow me to visualize ancestral locations. AI-driven mapping software reconstructs old neighborhoods, providing a clearer sense of the landscapes my ancestors knew.

Challenge for Readers

Have you traced your ancestors’ migration patterns? Try using an AI-powered genealogy tool to uncover a migration story in your family tree. Look at census records, passenger lists, or even DNA migration maps. You might be surprised at what you find! Share your discoveries in the comments or with fellow researchers.

Summary and Next Steps

Migration is not just an event—it’s a story of movement, struggle, and change. Whether fleeing persecution, seeking better opportunities, or adapting to life-altering events like 9/11, migration shapes our family narratives.

AI offers new ways to uncover these stories, making research faster and more insightful. By harnessing AI, we can connect with our ancestors in ways never before possible.

Disclosure

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

52 AI Ancestors in 52 Weeks: Week 7: Letters and Diaries

/ jannetjeb / 6 Comments

UPDATED 16Aug2025 with the letter!

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 7: Letters and Diaries

Introduction

Every family has a story passed down through generations, and sometimes, a single letter can open a window into the past. In my family, that letter is known as “The Patience Letter.”

Patience P. SPIEGLE (1833-1889), my great-great-grandmother, was born in New Jersey and married John T. WEST (1830-1924) in 1852. They started a family in Philadelphia before moving to Liberty Center, Henry County, Ohio, in 1858. Among their children was my great-grandfather, Adam Grant WEST (1866-1939), a traveling salesman.

Decades ago, I saw a letter that Patience wrote to her son Adam, presumably while he was on the road. Though I haven’t seen it in years, its content and significance have stuck with me.

A handsome man in a suit

Figure 1 Adam West, the letter’s recipient

The Letter: A Glimpse Into the Past

While I can’t quote the letter verbatim, I remember key details that made an impression:

  • Remarkably Literate – Patience’s handwriting, spelling, and grammar were far better than one might expect for a woman born in the early 19th century. This suggests she had a solid education, likely from American-born parents of German and English descent.
  • A Family in Motion – The letter mentions that her husband, John, was considering another move—perhaps to Michigan. Given that I’ve traced at least six moves in John’s lifetime, this letter confirms his “wandering spirit.”
  • A Piece of History Lost – Unfortunately, my grandmother, the last known owner of the letter, passed away 28 years ago. I have asked my uncle if he has a copy or remembers more details, but the fate of the letter remains unknown at the moment. UPDATE: he sent me a copy!

How AI is Helping My Research

Losing a treasured family letter is frustrating, but modern technology—especially AI—offers new ways to recover lost history. Here’s how AI can assist:

  • Handwriting Recognition & Analysis – If I find even a fragment of the letter, AI-driven Optical Character Recognition (OCR) tools can help transcribe difficult-to-read handwriting and reconstruct missing words.
  • Historical Context & Language Analysis – AI can analyze old letters and compare them with similar writings from the same period, offering insights into common expressions and historical references.
  • Predictive Text Generation – While AI can’t fully recreate Patience’s words, it can generate plausible reconstructions based on similar letters and known details of her life.

By applying these tools, I hope to get closer to understanding what Patience might have written—and what insights she left behind.

Challenge for Readers

Have you ever discovered an old family letter or diary entry? What did it reveal about your ancestors? If you have a historical document but struggle to read it, try using an AI-powered transcription tool to bring it to life.

If a cherished letter is missing, consider reconstructing its contents with family memories and historical research. AI might just help you fill in the gaps!

Summary and Next Steps

Even when original documents disappear, modern genealogy tools—including AI—can help us reconstruct and preserve family history. Whether through transcription, historical context analysis, or predictive modeling, AI is a powerful ally in uncovering the past.

Next week, I’ll explore another AI-enhanced discovery in my family history. Stay tuned!

Disclosure

This post was created with AI assistance and refined with my insights. While AI helps organize research, the storytelling and discoveries are my own.

52 AI Ancestors in 52 Weeks: Week 6: Surprise!

/ jannetjeb / 1 Comment

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!

A woman in an old fashioned hat

Figure 1 Alice Britton Makey, my great grandmother and product of Cornelius’ second marriage

Surprise! My Ancestor Had a Secret First Family
52 AI Ancestors in 52 Weeks: Week 6: Surprise!

Introduction

Have you ever thought you knew everything about an ancestor, only to find out there was an entire family you never knew existed? That’s exactly what happened when I stumbled upon Cornelius Britton’s hidden past. I believed I had his life well-documented—until one record changed everything.

Background

Cornelius Britton (1852-1910) and his wife, Alice Matilda Smith (1850-1913), were the proud parents of three daughters, including my great-grandmother. Oral history in my family confirmed I had everything squared away about this branch of my tree. But, as genealogy often teaches us, our ancestors have their own ways of keeping secrets!

The Discovery

As I refined my genealogy skills, I became determined to fill in every missing piece. Cornelius had always been a well-documented figure in my family’s history—until I uncovered a record that rewrote his story.

I was reviewing census records, expecting to confirm what I already knew, when I found something that made me freeze. Before marrying Alice, Cornelius had a first wife, Frances Housman, and together they had three sons. I stared at the screen. Three boys? I had never heard a single mention of them.

In the 1880 census, Cornelius and Alice were listed as “married within the year,” but the boys weren’t with them. Instead, they were living with their maternal grandparents. My heart sank as I followed their trail. One son died young, another disappeared from the records, but the third? He had descendants—relatives I never knew existed.

I tried to imagine Cornelius’s reality. A widower in the 1870s, left to raise three young boys alone—it must have been overwhelming. But why didn’t he reclaim them after remarrying? Did Alice refuse? Did circumstances make it impossible? His granddaughter, my great-grandmother, never spoke of them. Did she even know?

This discovery left me with more questions than answers. And that’s when I turned to AI for help.

How AI Helped My Research

Realizing I had missing branches in my tree, I wondered—could AI help me track them down? I started with ChatGPT, asking how I could investigate Cornelius’s first marriage. The responses were generic at first, so I refined my prompt, a key step when working with AI.

I also brought in Claude, which is known for its web searching capabilities. I asked both tools to create an AI-assisted locality guide for Cornelius’s time in New York City, focusing on records I might have missed.

Here’s what AI suggested:

🗂 Census & Vital Records
✔ Federal Census (1850-1880): Track household changes over time.
✔ New York State Census (1855, 1865, 1875): Available at the NY Public Library.
✔ Birth, Marriage, Death Records: NYC Municipal Archives has key documents.

📚 Local Directories & Newspapers
✔ Trow’s NYC Directory (Manhattan) & Lain’s Brooklyn Directory: Track Cornelius’s addresses and occupations.
✔ Newspaper Archives: Obituaries, announcements, and news mentions in the Brooklyn Public Library and online databases.

🏛 Legal & Church Records
✔ Probate & Land Records: Wills and deeds at county clerk offices could show connections.
✔ Church Records: Baptisms, marriages, and burials often provide missing details.

🔎 What Surprised Me?
I expected Claude to be stronger at web searches, since it’s known for research, but ChatGPT provided direct links to resources, while Claude gave broader summaries. I also revisited Judy Russell’s “Reasonably Exhaustive Research Checklist” (free download here), which helped me double-check my sources.

Challenge for Readers

Have you ever uncovered a surprise in your family tree? Maybe a secret sibling, a hidden marriage, or an ancestor who vanished? I’d love to hear your stories! Share in the comments.

Summary and Next Steps

This discovery has left me with more questions than answers, and I’m eager to keep searching. My next steps? Exploring Cornelius’s families with the tools that AI suggested, particularly city directories and newly digitized newspapers, to see if I can track down more information about his missing son and his descendants.

Disclosure

This post was created with AI assistance and refined with my insights. While AI helps organize research, the storytelling and discoveries are my own.

52 AI Ancestors in 52 Weeks: Week 5: Challenge

/ jannetjeb / 3 Comments

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 5: Challenge

Introduction

Week 5 of the 52 Ancestors challenge invites us to reflect on challenges—those faced by our ancestors or ones we’ve encountered in uncovering their stories. For me, the word “challenge” instantly conjures up my second great-grandmother, Theresa Kilkenny Anderson. Her story is one of resilience, quiet strength, and perseverance in the face of obstacles.

Meet Theresa Kilkenny Anderson

Theresa was born around December 1851 in Ireland, a time marked by the devastation of an Gorta Mór (the Great Hunger). Imagine the courage it took to survive, let alone emigrate to a new country under those circumstances. By the time she arrived in the United States—probably in New York—she was likely young, perhaps alone, and determined to build a new life.

Theresa married Michael Anderson by about 1872, and the couple welcomed children at a steady two-year rhythm. But their firstborn’s apparent early death foreshadowed the difficulties to come. The most crushing blow arrived in 1883, when Michael passed away suddenly at just 31 years old, leaving Theresa widowed with five small children and one on the way. Their daughter, Mary Frances, born later that year, also died young.

By 1900, Theresa was listed as a laundress in the U.S. Census, a widow, supporting her three children remaining at home. Her story is one of survival against the odds—a testament to fortitude and self-reliance in a time of few social safety nets.

The FAN Club: A New Research Angle

Researching Theresa’s life has not been easy. Despite her bravery, records of her early years remain elusive. I’ve struggled to find her FAN Club (Friends, Associates, and Neighbors)—a genealogist’s go-to method for piecing together an ancestor’s story.

That’s where AI entered the picture. Inspired by Theresa’s perseverance, I decided to give her story a boost by asking AI for help. Could technology uncover what traditional methods have not?

AI to the Rescue: Building Theresa’s FAN Club

When I shared Theresa’s story with ChatGPT, it suggested a methodical approach to reconstruct her network. The AI offered me a plan for identifying potential connections to her origins or her life after immigration. Here’s a taste of what it suggested:

  1. Passenger Lists and Ship Manifests
    • Objective: Identify fellow passengers who might have traveled with Theresa to the United States.
    • AI Support: Use name variation searches, contextual filters (e.g., age, gender, and nationality), and clustering tools to pinpoint people with similar migration paths.
    • Next Step: Search for Irish immigrants on the same ships arriving around the presumed timeframe of her immigration.
  2. Community and Church Records
    • Objective: Locate Theresa in New York parish records, which may reveal connections to other Kilkennys or Andersons.
    • AI Support: Analyze patterns in names and locations in digitized parish records to identify clusters of families or potential sponsors.
    • Next Step: Narrow down parishes near her residence in the census years.
  3. City Directories and Neighbors
    • Objective: Investigate Theresa’s neighborhoods for familiar surnames.
    • AI Support: Cross-reference census and city directory entries with Theresa’s address to identify potential friends or family nearby.
    • Next Step: Build a map of her social and geographic proximity to other Irish immigrants.
  4. DNA and Genetic Genealogy
    • Objective: Use DNA matches to piece together Theresa’s family tree.
    • AI Support: Generate hypotheses about familial relationships using shared matches and clustering tools.
    • Next Step: Collaborate with DNA cousins to uncover connections to Kilkenny or Anderson relatives.

A Fresh Perspective

As a genealogist, I tend to work in a process-driven way, and I was thrilled when AI offered clear “next steps.” It wasn’t just about data—it was about taking actionable strides in the right direction. AI’s support reminded me that while I may not have all the answers today, each clue brings me closer to understanding Theresa’s story.

Tracking Theresa’s FAN Club with AI and Spreadsheets

To systematically uncover Theresa’s network, I created a spreadsheet to track potential connections across different sources. Each worksheet represents a distinct research category:

  • Census Records: I recorded all indexed individuals from FamilySearch on the same census page as Theresa, plus three pages before and after (this is just a copy/paste from FamilySearch, NOT a transcription of my own).
  • Passenger Lists: I extracted the full list of steerage passengers from Theresa’s likely immigration record to identify potential travel companions (also a copy/paste).
  • Baptismal Sponsors: Once I obtain Theresa’s children’s baptismal records, I will add the sponsors to see if their names appear elsewhere in her life.

Once the data was organized, I turned to AI tools for assistance. First, I asked Copilot:

“Look at the names on the Immigration worksheet. Tell me which of these names occur on other worksheets, and where.”

Unfortunately, it wasn’t able to process the request effectively. However, when I posed the same question to ChatGPT, it successfully identified overlapping names across different sources—giving me valuable clues about possible relationships.

While I didn’t find immediate breakthroughs with those two people, this exercise confirmed that AI can assist in detecting patterns and connections that might be overlooked in manual research. The next logical step is to focus on the baptismal records, where sponsors might provide the missing links to Theresa’s origins.

Summary and Next Steps

Theresa Kilkenny Anderson is more than a name on a page. Her life is a reminder that even in the face of unimaginable adversity, strength and determination can carry us forward. By tapping into AI tools, I’m reinvigorating my research and finding new ways to honor her legacy. My focus now is uncovering her FAN Club and exploring potential connections to Ireland.

Challenge for Readers

Who’s the “challenging ancestor” in your tree? Is it someone who overcame incredible odds, or someone whose story remains an enigma? Use Theresa’s story—and the AI tools I’ve explored—as inspiration to tackle those brick walls. Share your journey in the comments!

Figure 1 Michael Anderson, Theresa’s son and my great grandfather

52 AI Ancestors in 52 Weeks: Week 4: Overlooked

/ jannetjeb / 3 Comments

52 AI Ancestors in 52 Weeks: Week 4: Overlooked

Introduction

Week 4 of the 52 Ancestors challenge dives into the overlooked. “Who is someone in your family tree who you haven’t researched very much?” It didn’t take any time for me to come up with the name: Andrew Driskol.

52 AI Ancestors in 52 Weeks: Week 4 – Overlooked

Introduction

Who in your family tree have you overlooked? For me, it’s Andrew Driskol. Or, rather, Andrew “Does-He-Even-Exist?” Driskol. He’s a puzzle—a man whose shadow falls across family records but refuses to leave a solid footprint. One of my very first finds as a baby genealogist was the marriage record of his daughter, my great grandmother, which listed his name. But as I dug deeper, the trail went cold. This week, I decided to tackle Andrew’s mystery with the help of a modern-day Watson: artificial intelligence.

Andrew Driskol: A Ghost in the Records

Andrew’s story—or lack thereof—begins in the 19th century, when civil and church records were often kept. The absence of documentation for someone like Andrew is unusual because his life spanned eras and locations where detailed records typically existed. This gap raises questions about whether his name was misspelled, misrecorded, or lost in migration. when civil and church records were often kept. He was likely born in Prussia, possibly Hesse-Darmstadt, around the 1830s or 1840s. He presumably married Malvina Hendell in England before emigrating to the United States in the 1870s. But here’s the kicker: there’s no direct record of Andrew. Not a birth certificate, not an immigration record, not a census entry. Yet, his children’s records consistently name him as their father.

The hunt for Andrew is a genealogist’s equivalent of chasing a will-o’-the-wisp. And yet, his legacy lives on in the scattered records of his children, like breadcrumbs leading nowhere. With AI in the picture, though, I wondered if I could piece together these fragments into something more substantial.

Figure 1 Anna Driskol Anderson ca 1914

My Data

I created a table of information I’ve gathered about him, all from records of his children; names:

Parents’ names as per childrens’ vitals

ChildMarriage YearMarriage Parents ListedDeath YearDeath Parents Listed
EdwardNot foundNot applicableNot foundNot applicable
Mary1891Andrew Driskoll M. Hendell1938Andrew Driskol (Ger) Malvina Helda (Ger)
1926Andrew Driscol Malvina Henall
Josephine1899Andrew Driscoll Melvina Hendel1925Andrew Driscoll (Ger) Malvina _endels (Ger)
Anna1906Andrew Driskol Malvina1922Andrew Driscoll (Ger) Malvina Driscoll (Eng)
JosephNot foundNot applicable1925Andrew Driscoll (Ger) Malvina Hendell (Eng)

I also created a table of places of birth, since there is a little variation:

Census parents’ places of birth (child/father/mother)

Child1900 census1910 census1920 census1930 census
EdwardGer/Ger/Ger   
MaryNY/Ger/EngNY/NY/NYNY/Ger/EngNY/Ger/Eng
JosephineNY/Ger/GerNY/Ger/EngNY/PRUS-Ger/PRUS-Ger 
AnnaNY/Ger/GerNY/IRE/GerNY/Ger/Ger 
JosephNY/Ger/GerNY/Ger/Eng  

I’ve created a timeline for him:

Timeline for Andrew Driskol

  • ca. 1830s – Andrew Driskol is born, perhaps in Prussia and/or Hesse-Darmstadt, Germany.
  • by 1864 – He migrates to England and (presumably) marries Malvina Hendell.
  • ca. 1864 – His son, Edward, is born in England.
  • ca. 1866 – His daughter, Edith, is born in England.
  • by 1875 – Andrew immigrates to the United States.
  • 1875 – His wife Malvina and their children arrive in the United States, probably joining him.
  • 1873 – A child is born in New York [sic].
  • 1878 – Another child is born in New York.
  • 1880 – Another child is born in New York. Andrew and family are not located in the 1880 census.
  • 1883 – Last known child is born in New York.
  • 1890 – Had Andrew died by now, as his son purchased land?
  • by 1900 – Andrew Driskol dies, as Malvina is listed as a widow in the census.

I’ve not been able to locate him and every so often, I track him for a while, encounter the same nonanswers, and give up again for a time.

My AI-Assisted Research Plan

Using AI tools to analyze my data, I created a structured research plan.

Using the three tables in the attached (parents names as per childrens’ vitals, census parents places of birth, and timeline, create a research plan for Andrew Driskol.             

<I attached a document with the three tables above>

It replied with a research plan, containing a research objective, timeline hypothesis, research goals, specific research steps, analysis and documentation, and further considerations:

Research Plan for Andrew Driskol

Research Objective

To confirm the life events of Andrew Driskol, including his birth, marriage, immigration, and death, and to verify family relationships and origins through vital records, census data, and immigration documents.

Timeline Hypothesis

  • <not reproduced here; it was really the timeline above>

Research Goals

  1. Locate Vital Records:
    1. Birth record (Prussia, ca. 1835–1840).
    1. Marriage record (possibly England, ca. 1860–1865).
    1. Death record (United States, ca. 1890).
    1. Children’s vital records to confirm parentage.
  2. Investigate Immigration:
    1. Ship manifests for Andrew, Malvina, and children.
    1. Naturalization records for Andrew.
  3. Census Records:
    1. Locate Andrew and family in the 1870 and 1880 U.S. censuses.
    1. Review 1900 and later censuses for children to verify reported parent birthplaces and relationships.
  4. Confirm Parentage and Origins:
    1. Cross-reference children’s marriage and death certificates for consistency.
    1. Explore German and Prussian records for potential leads.
  5. Community and Local Records:
    1. Staten Island and NYC directories or church records.
    1. Burial records or cemetery listings.

Specific Research Steps

Step 1: Census Research

  • Goal: Locate Andrew in 1870 and 1880 censuses and confirm family details.
  • Strategy:
    • Search for “Andrew Driskol” with variations (e.g., Driscoll, Driscol) in New York City and Staten Island.
    • Explore neighboring areas for missed or misindexed records.

Step 2: Immigration Records

  • Goal: Confirm immigration details for Andrew, Malvina, and children (1868–1875).
  • Strategy:
    • Search passenger lists on major databases (e.g., Ancestry, FamilySearch) for ships arriving in New York.
    • Check manifests for individuals born in Prussia, traveling with family.

Step 3: Vital Records

  • Goal: Obtain key documents to confirm relationships and dates.
  • Strategy:
    • Search NYC vital records for Andrew’s death record (ca. 1890).
    • Obtain marriage certificates for Mary (1891, 1926), Josephine (1899), and Anna (1906).
    • Acquire death certificates for Josephine (1925), Anna (1922), Joseph (1925), and Mary (1938).

Step 4: European Records

  • Goal: Identify Andrew’s origins in Prussia and confirm marriage details in England.
  • Strategy:
    • Search Prussian birth records (1835–1840) using German archives or online resources.
    • Investigate English marriage records (1860–1865) for Andrew and Malvina.

Step 5: Community and Church Records

  • Goal: Supplement missing information with local data.
  • Strategy:
    • Explore Staten Island directories, church baptismal records, and cemetery logs.
    • Check for obituaries or probate records in local archives.

Analysis and Documentation

  • Focus Areas:
    • Reconcile discrepancies in children’s vital records (e.g., variation in mother’s maiden name: Hendell, Helda, Henall).
    • Note inconsistencies in census parentage (e.g., Germany vs. Ireland vs. England origins).
    • Track potential family movement between census years.
  • Tools:
    • Timeline to track findings against the hypothesis.
    • Research log to document sources and results.

Further Considerations

  • If records are inconclusive, pursue DNA testing with known descendants to confirm connections.
  • Collaborate with online genealogy communities for fresh insights or rare record access.

AI’s Role in Clarity

AI didn’t magically find Andrew hiding in a forgotten archive (though I wished for that). Instead, it helped me organize my research into actionable steps and avoid the dreaded rabbit holes. By using tools like ChatGPT for brainstorming and database-specific AI search assistants, I was able to identify patterns, generate alternative search strategies, and refine my focus on critical records. ChatGPT didn’t help much with creating a timeline, but Dana Leeds encouraged me to try it with Claude. This structured approach keeps me grounded as I continue the search.

Summary and Next Steps

Artificial Intelligence is actually a really good way to ground the genealogist who tends to dive down rabbit holes (not that I do that, wink wink).

For Andrew, the search continues. My next steps are to delve into European records, seek out local church and burial data, and perhaps even explore DNA testing with descendants. Andrew may be a ghost in the records, but with persistence and a little AI assistance, I’m determined to uncover his story—or at least understand why it’s missing.

Challenge for Readers

Who’s the most elusive ancestor in your tree? Apply these research strategies to uncover their story. For example, try creating a timeline of what you already know about your ancestor. Highlight gaps where records are missing and focus your searches on those areas. This simple step can make your research more efficient and targeted. Start by organizing what you know, then create a clear plan using actionable steps like those above. AI tools can help you stay on track and think critically.

52 AI Ancestors in 52 Weeks: Week 3: Nickname

/ jannetjeb / 1 Comment

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 3: Nickname

Introduction

Week 3 of the 52 Ancestors challenge dives into nicknames. “Which of your ancestors had a nickname? Do you know how they got it?”

This week, I’ll step away from my maternal grandmother’s line to focus on my paternal grandmother’s mother, my great-grandmother Mary Agnes HART CAREY (1892-1978) —known to us as “Nanny.”

Background

Great Grandma, “Nanny” we called her, was named Mary Agnes HART CAREY. She was born, you might have guessed, into an Irish Catholic family.

The nickname

Her formal name, Mary Agnes, seemed typical for her heritage and era, but it also carried a hidden twist: she was universally called “Aggie.”

My grandmother shared how, after Nanny passed, she was shocked to learn her mother’s first name wasn’t actually “Agnes.” Nanny named one of her children “Agnes,” but not “Mary,” indicating how she wanted to leave the name behind.

Nicknames like “Aggie” often reflect personal preferences, family traditions, or even community influences. But what’s fascinating is how these seemingly small details offer insights into how ancestors presented themselves to the world or were seen by others.

Figure 1 Mary Agnes HART CAREY, date perhaps 1940s to early 1950s

The AI Connection: How AI Can Help Decode Nicknames

Nicknames can be tricky in genealogy, especially when records use formal names instead of the name your ancestor was commonly called. AI tools can be a game-changer here by offering innovative ways to trace and decode these hidden connections:

  1. Name Matching in Records
    AI-powered genealogy platforms can identify patterns in historical records, connecting nicknames to formal names. For example, searching for “Aggie” might yield records for Mary Agnes, even if “Aggie” isn’t explicitly listed. AI algorithms that analyze phonetic similarities (like the Soundex system) make this possible.
  2. Document Analysis
    Some AI tools can scan personal letters, diaries, or even old newspapers to detect nicknames alongside formal names. This can help clarify how nicknames were used and even uncover clues about their origins.
  3. Family Tree Suggestions
    Platforms like Ancestry.com and MyHeritage use AI to suggest connections. If an ancestor was known by different names in various documents, AI can consolidate the data, revealing hidden patterns or relationships you might otherwise miss.
  4. Cultural Context Insights
    AI can also analyze naming trends by era and region. For instance, “Aggie” as a nickname for Agnes was more popular in Irish communities during certain periods. Understanding these trends can make your ancestor’s story richer and more relatable.

Going Forward

What about you? Who in your family had a nickname that stood out? Did it reveal a personality quirk, a fond memory, or a cultural connection?

Take this week’s challenge to the next level by pairing your research with AI tools. You might discover a nickname hiding in plain sight or uncover how a loved one’s identity evolved over time.

52 AI Ancestors in 52 Weeks: Week 2: Favorite Photo

/ jannetjeb / 1 Comment

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 2: Favorite Photo

Introduction

Week 2 of the 52 Ancestors challenge dives into your favorite photo. “Photos capture our family history like few other things can,” right? Picking a favorite is tough—I have a handful that hold deep meaning for me. Let me share one particularly special image with you: a portrait I labeled “Unknown Sailor.”

Background

My maternal grandmother, whom I wrote about last week, lost her mother at the age of three. As the only daughter, she inherited a collection of keepsakes, including a stack of photographs—most of them frustratingly unlabeled. One photo, though, stood out:

A sepia-toned image of a confident sailor, standing tall with an unmistakable pride.

This sailor seemed to radiate pride and confidence, but who was he?

The search

At first, I had no clues to identify him. Then, while researching Grandma’s maternal grandmother, Alice, I learned Alice had three brothers who served in the Civil War, including one in the Navy. That gave me a potential name: Oscar Smith.

For years, Oscar remained an enigma. No evidence could prove his identity. Then one day, while exploring collateral research, I connected with another genealogist studying the surname of Alice’s first husband (I descend from the second), my second cousin once removed. We compared notes and decided to meet, each bringing our family photo collections.

Imagine my surprise when she produced the exact same [unlabeled] sailor photo! Together, we became convinced the sailor was indeed Oscar Smith. Over a century after his naval service, Oscar had unwittingly brought two branches of our family back together.

Kathie and I corresponded and collaborated for quite a while. I assume she is now asking Alice for family information.

The AI connection

Here’s where modern tools entered the picture. Steve’s Photograph Analysis, a custom GPT from Steve Little, became my new research ally. I uploaded the sailor photo, and the AI provided a detailed analysis:

  • Composition: Lighting, subject placement, and atmosphere.
  • Context: Potential date, location, and even identity clues.
  • Insights: Surprising details about the photo’s timeline.

To my amazement, ChatGPT placed the photo in a time frame after Oscar had died. Was my theory wrong? Or was there a misstep in the analysis? This unexpected twist turned the photo into a deeper mystery, one I’m still unraveling.

Summary report including conclusion that the photo is from the early 1900s.

Going forward

I have my theories, but as any genealogist knows, personal beliefs don’t meet the Genealogical Proof Standard. For now, Oscar’s (?) photo remains a tantalizing puzzle. Who knows—maybe future 52 Ancestors prompts will give me the chance to share updates as this story unfolds.

Try it yourself

Curious about your own family photos? Give Steve’s photo analyzer a spin, or prompt an AI tool yourself to uncover hidden details in your family’s history. Happy hunting!

52 AI ancestors in 52 weeks: Week 1: In the Beginning

/ jannetjeb / 1 Comment

52 AI ancestors in 52 weeks: Week 1: In the Beginning

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!

History says I won’t do it every week. But we’re talking about progress, not perfection. So, let’s just jump in and have fun.

52 AI Ancestors in 52 Weeks: Week 1: In the Beginning

Genealogy is like solving a family mystery—part detective work, part heartfelt storytelling. Throw AI into the mix, and it’s a whole new level of discovery. This year, I’m taking up a challenge that blends Amy Johnson Crow’s “52 Ancestors in 52 Weeks” with a techy twist inspired by Steve Little’s “The 2025 AI Genealogy Do-Over.” The goal? To explore both my family’s roots and the potential of AI in genealogy. Let’s kick it off with Week 1.

Why I Got Started

My genealogy obsession began in 6th grade when I got an assignment to create a family tree. Lucky for me, my grandmother—my biggest cheerleader—was just a few steps away. She dug out old records, shared stories, and filled in the gaps with amazing details. Thanks to her, I didn’t just complete the assignment; I caught the genealogy bug for life.

Grandma’s love for family history had its own story. She lost her mother at the tender age of three, and I believe her passion for genealogy was her way of reconnecting with that lost connection. She came from a prominent local family but struggled to tie certain pieces together. Those mysteries drove her—and now, they drive me.

The AI Connection

Fast forward to today. I’ve got tools my grandmother couldn’t have dreamed of—AI among them. This week, I gave an AI model a task: review and rewrite a tribute I wrote for my grandmother. Here’s how it went:

  • Step 1: I asked the AI to evaluate my tribute’s emotional resonance and clarity.
    • Please create guidelines for writing a tribute on the Internet, rate my page according to them, make suggestions, rewrite using the suggestions, and regrade. The page:
  • Step 2: I pasted the text (AI and links don’t always get along) and let it suggest edits.
  • Step 3: After trying a few models, Gemini delivered the most heartfelt rewrite. I put it below this post. What do you think? Let me know in the comments!

AI didn’t just polish the words—it helped me reflect on the way I’d captured my grandmother’s story. But, as powerful as AI is, it didn’t replace my voice; it enhanced it.

Grandma holding me at what was probably my first birthday

Your Challenge

Genealogy is personal, but technology can make it interactive. Here’s how you can join the journey:

  1. Pick an Ancestor: Choose someone in your family tree who inspires you. Write a short tribute to them (just 300 words or so).
  2. Add AI to the Mix: Use a free AI tool to refine your writing. ChatGPT, Claude, or Gemini are great options.
  3. Compare and Reflect: Does the AI version improve your story, or does it miss the mark? Adjust it to reflect your voice.

Share your experience in the comments—I’d love to hear how AI shapes your family’s stories.

In the End, It’s All About Connection

Genealogy and AI might seem like an odd pairing, but at their core, both are about uncovering connections. Whether it’s piecing together family lore or fine-tuning a tribute, every little discovery brings us closer to understanding who we are.

Here’s to Week 1—and to Grandma, who started it all. Without her, this journey wouldn’t be possible. And thanks to AI, it’s more exciting than ever.

Final Thoughts: Technology can amplify the past, but it’s the stories we share that keep it alive. So here’s my challenge: embrace both the wisdom of your ancestors and the tools of today to create something truly timeless.

The AI-revised tribute:

A Tribute to Edith Lillian Makey West (1913-1997)

Edith Lillian Makey West, my beloved Grandma, was born on September 12, 1913, in Staten Island, New York. Her life, though marked by early loss – her mother passed away when she was just three years old – was a testament to resilience and love.

Raised by her strong and loving [Janet adds: aunt, her namesake Edith, and] stepmother, Elfrida, Edith grew into a vibrant young woman. She graduated from Bryant High School and embarked on her career, working first as a candy packer and then for The Corporation Trust Company, where she dedicated many years.

Edith and my Grandpa, Gordon, shared a deep and enduring love. Their marriage, celebrated in 1935, was a cornerstone of her life. They traveled extensively, exploring 37 states together, and cherished raising their children, Alan and Elise.

Grandma’s passion for family history ignited my own. Countless hours were spent discussing ancestors, sharing stories, and piecing together our family’s past. Her excitement was contagious, fueling my own genealogical pursuits.

More than anything, Grandma embodied strength and resilience. She faced life’s challenges with grace and determination, inspiring me with her quiet strength.

Though she is gone, her memory lives on. I will always cherish the warmth of her smile, the comforting sound of her laughter, and the enduring lessons she imparted.

Randolph’s House of Truax – Second Generation (Sara, Susanna, Rachel)

/ jannetjeb / 1 Comment

Part I – House of Truax – Etymology
Part II – House of Truax – Historical
Part III – House of Truax – Church records
Part IV – House of Truax – New Amsterdam records
Part V – House of Truax – First Generation
Part VI – House of Truax – Truax Genealogy (Land Records)
Part VI – House of Truax – “First” Generation – Maria
Part VII – House of Truax – Second Generation (Philip, Rachel, Sara)
Part VIII – House of Truax – Second Generation (Susanna, Rebecca, Abraham)
Part IX – Randolph’s House of Truax – Introduction
Part X – Randolph’s House of Truax – First Generation
Part XI – Randolph’s House of Truax – Second Generation (Philippe, Maria)
Part XII – Randolph’s House of Truax – Second Generation (Sara, Susanna, Rachel) – below

Tonight is ladies’ night, as we hit three more of Philippe’s daughters. Next up are Abraham and Rebecca. Then we make some corrections before resuming. In the meantime, please witness Sara, Susanna, and Rachel, as contrasts to Maria. Then, I have not much of the manuscript remaining, but for miscellaneous notes – but interesting ones.

Randolph’s House of Truax – Second Generation – Sara, Susanna, Rachel

Page 14

  1. Sara2 du Trieux, born in New Netherlands, as distinctly stated in her marriage banns. These banns were published on June 9, 1641, to “Isaacq de Foreest, j. m. Van Leyden”. Isaac de Forest was baptized at Leyden, Holland, July 10, 1616, and was a son of Jesse de Forest. The probable friendship of these two families in Holland has already been discussed. Isaac de Forest had immigrated with his brother Hendrick and his sister Rachel in the Rensselaerswyck, which sailed from Amsterdam on Sept. 25, 1636, and arrived at New Amsterdam March 5, 1637, after many delays. This family has been so fully written in “A Walloon Family in America” that it is only necessary to give an outline of it here. It would seem that Isaac de Forest had been a staunch friend of Maria Peeck through all her many vicissitudes. He was one of the witnesses at the baptism of her illegitimate child in 1640, a year before his marriage to her sister. He was the guardian of her minor children on her second marriage, and she constantly went to him for aid. He died in 1674. His widow, Sara du Trieux, or Sara Philips, as she was sometimes called, died on November 9, 1692.

Children: 14 (de Forest), 11 sons and 3 daughters, all baptised at New Amsterdam:-

  1. i. Jessen3, bap. Nov. 9, 1642. Named for his grandfather, Jesse de Forest. Died in infancy.
  2. ii. Susanna3, bap. Jan. 22, 1645; marriage banns to Pieter de Riemer, widower, Jan. 3, 1665.
  3. iii. Gerrit3, bap. May 21, 1646; died in infancy.
  4. iv. Gerrit3, bap. June 10, 1647; no further record.
  5. v. Marie3, bap. Jan. 10, 1649; died young.
  6. vi. Michael3, twin to Marie, bap. Jan. 10, 1649; died young.
  7. vii. Jan3, bap. March 27, 1650; marriage banns to Susannah, daughter of Nicholas Verlet, June 8, 1673.
  8. viii. Philip3, bap. July 28, 1652; married Tryntje, daughter of Hendrick Kip, Jan. 5, 1676.
  9. ix. Isaac3, bap. April 25, 1655; married Sept. 4, 1681 Lysbeth, daughter of Lawrence Van der Spiegel.

Page 15

  1. x. Hendrick3, bap. Sept. 9, 1657; marriage banns July 5, 1682, to Femmetje, daughter of Barent Van Flaesbeek.
  2. xi. David3, bap. Aug. 1, 1660; died in infancy.
  3. xii. David3, bap. Dec. 19, 1663; died in infancy.
  4. xiii. Maria3, bap. July 7, 1666; married first June 15, 1687, Bernard Darby of London; married second, 1706, Isaac, son of Peter de Riemer (her sister’s husband – a son by his first wife).
  5. xiv. David3, bap. Sept. 7. 1669; married about 1696, Martha Blagge.
  1. Susanna2 du Trieux, born in New Netherlands; marriage banns July 31, 1644, to Evert Jansen Wendel. Evert Jansen Wendel was born in Embden, Friesland, in 1615. He came to New Amsterdam in 1640 in the service of the Dutch West India Company. About 1651 he removed to Fort Orange, and became prominent there. He was an elder of the Dutch church there in 1656; was appointed orphan-master in 1657; and was magistrate in 1660 and 1661. His wife died about 1660, and in 1663 he married second Maritje Abrahamse, widow of Thomas Janse Mingael, and daughter of Abraham Pieter Vosburgh, by whom he had four children. He married third Ariantje ___. He died in 1709, aged 94, and was buried under the old church then standing at the corner of Yonker and Handelaer Streets ,the present State Street and Broadway, in Albany. His will, dated June 30, 1663, speaks of his late wife Susanna de Truwe, and mentions his children Elsie, aged 16; Johannes, 14; Diewer, 10; Jeronimus, 8; Philip, 5; and Evert, 3.

Children:- 8 (Wendel), 5 sons and 3 daughters. The first four were baptised at New Amsterdam, and the last four were born at Fort Orange.

  1. i. Thomas3, bap. Sept. 18, 1645. Name not given in baptismal record, but supplied by Talcott. Died young, as he is not mentioned in his father’s will. Witnesnse: Isaac de Foreest, Tryntje Roelofs.
  2. ii. Elsje3, bap. Jan. 27, 1647. Witnesses: de Hr. Willem Kieft, Gouverneur, Isac de Foreest, Tryntie Roelofs. [Abraham Staats?]
  3. iii. Johannes3, bap. Feb. 2, 1649. Witnesses: Philip du Trieux, Mr. Paulus Van der Beeck, Johannes Rodenburg, Marie en Sara du Trieux.
  4. iv. Dievertje3, bap. Nov. 27, 1650. Witnesses: Susanna Philips (No. 7 of this genealogy). Died in infancy.
  5. v. Dievertje3, born about 1653.
  6. vi. Jeronimus, born about 1655.
  7. vii. Philip3, born about 1658.
  8. viii. Evert3, born about 1660.

Page 16

  1. Rachel2 du Trieux, born at New Amsterdam; married first (banns) Sept. 30, 1656, Hendrick Van Bommel; married second, Aug. 8, 1677, Dirck Jansen de Groot. “Dirck Janszen de Groot, Wedr. Van Wybrug Jans, Rachel Detru, Wede. Van Hendr. Van Bommel, beyde woonende tot N. Yorke.”

Dirck Jansen de Groot was probably from Groet in North Holland, according to Bergen’s “Early Settlers of Kings County”, which also credits him with three wives, not realizing that Rachel Detru and Rachel Philips were one and the same person. They were living on Marketfield Street in 1686, according to Dimine Selyn’s Record. We have no record of any children by his first wife.

Children:- 10, 7 sons and 3 daughters. All baptised at New Amsterdam and New York.

By her first husband (Van Bommel).

  1. i. Hieronymus3, bap. Oct 28, 1657. Witnesses: Isaac de Foreest, Sara du Trieux.
  2. ii. Susanna3, bap. Jan. 25, 1660. Witnesses: Jan de la Montagne, Marie Peeck. No further record.
  3. iii. Leurifaes3, bap. Aug. 20, 1662. Witnesse: Abraham du Trieux, Susanna de Foreest. No further record.
  4. iv. Abraham3, bap. March 14, 1666. Witnesses: Jacob Kip, Maria Kip. No further record.
  5. v. Grietie3, bap. July 1, 1668. Witnesses: Jacob du Trieux, Rebecca du Trieux. Probably died young (see No. 51).
  6. vi. Philip3, bap. Feb. 18, 1672. Witnesses: Johannes de Foreest, Rebecca du Trieux. Died in infancy.
  7. vii. Philip3, bap. Aug. 21, 1675. Witnesses: Philip de Foreest, Susanna Verleth. No further record.

By her second husband (de Groot).

  1. viii. Jan3, bap. March 27, 1678. Witnesses: Jacob Pieterszen, Grietie J__. No further record.
  2. ix. Grietie3, bap. Feb. 8, 1679. Witnesses: Johannes Thomaszen, Aech__ Jacobs.
  3. x. Abraham3, bap. April 26, 1682. Witnesses, Pieter de Riemer, Be___ Ariaens. No further record.

Source:

Truax, T. de T., House of Truax. “Bien faire et ne rien craindre.” Historical Genealogy of the Truax-Truex Families of the United States and Canada, descendants of Philippe de Trieux, the first Huguenot-Knickerbocker of that name who settled in New Netherland in 16__ and embracing his posterity to the present date a period of nearly three centuries of Twelve Generations. Manuscript. From New York Public Library, Call No. NYGB Coll-94 Box 1 and Box 2.http://catalog.nypl.org/record=b18209329~S1 . (Accessed 18Jul2015)

[An interesting history of this manuscript can be found at http://freepages.genealogy.rootsweb.ancestry.com/~truax/TheHouseofTruax.html]

IMG_1597 IMG_1598 IMG_1599