I could not be more excited about sharing this announcement and learning with you. Registration opens Tuesday 20 February 2024, 1 PM ET, for “AI Genealogy Seminars: From Basics to Breakthroughs,” one of eleven virtual courses offered this summer by the National Genealogical Society’s GRIP Genealogical Institute (formerly the “Genealogical Research Institute of Pittsburgh”). I will be teaching ten sessions, from basics to breakthroughs in AI Genealogy, and I am humbled to be joined by seven distinguished colleagues who were students (though “fellow pioneers” would be more accurate, as I learned as much from them as they did from me) in my Level 1 and/or Level 2 NGS AI Genealogy courses last fall and this winter. More information is included below, and at the websites noted below.
Course: AI Genealogy Seminars: From Basics to Breakthroughs Coordinator: Steve Little Date: 23-28 June 2024 Venue: GRIP Virtual Session Registration Opens: 1 PM ET, Tue 20 Feb 2024
Description:
As the AI Program Director at the National Genealogical Society (“NGS”) and a pioneer in the field, Steve Little will navigate participants through the foundational concepts to the frontiers of AI Genealogy. His sessions will chart the evolution of AI Genealogy, from its early stages to predictive trends in 2024. Sessions will cover practical skills in prompt engineering, bot building and GPT customization, and the latest in AI Genealogy advancements. Steve’s comprehensive expertise will provide attendees with the tools to not only grasp AI basics but also to apply sophisticated AI strategies to their genealogical research. The AI Genealogy Seminars offer a unique opportunity to learn from the first-hand experiences of industry leaders during the initial year of large language model integration into genealogy. Their insights will shape the course content and provide a diverse perspective on the evolution of this field. Featured experts include Blaine Bettinger, Maureen Taylor, Judy Russell, Dana Leeds, Nicole Dyer, Mary Kircher Roddy, and Mark Thompson.
NGS online course “Empowering Genealogists with Artificial Intelligence – Level One” or commensurate experience (approx. 20+ hours of hands-on AI genealogy experience). The GRIP 2024 course “AI Genealogy Seminars” is NOT for a genealogist’s first experience with large language models or other AI tools; however, if a student has 20+ hands-on hours with ChatGPT Plus (GPT-4) when the course begins, then an updated refresher of the basics and intermediate aspects of AI Genealogy will ensure the student is up-to-speed to take advantage of the advanced topics and special content instructors.
About NGS’s GRIP Genealogy Institute: Formerly the “Genealogical Research Institute of Pittsburgh”, GRIP 2024 is “the” event for genealogists and family historians who want to develop their skills while meeting new friends in a collegial and collaborative community.
Open GeneaGPT (the community-built genealogy AI tool) has been updated from version 2 to version 3 as of Monday 22 January 2024. This is a significant update, transforming Open GeneaGPT into a smarter and more engaging companion for exploring family history, making it easier and more enjoyable for everyone. It brings changes like better conversations, more helpful suggestions for next steps, ensuring a friendly and insightful journey into the past.
OpenAI’s custom GPTs are amazing tools for creating specialized bots that can perform various tasks, such as extracting data; describing documents, images, records; generating reports, stories, images; and much, much more. These GPTs are tools for the way you work; you build the AI tool you need, or find one on the store shelf. I have been exploring genealogy prompt engineering over the past year, building genealogy GPTs since November, and I have learned a lot about how to create and use them effectively. Recently, OpenAI launched their GPT Store, where users can share their custom GPTs with other ChatGPT Plus subscribers. This is a great opportunity to discover new bots and learn from others. I have shared five or six of my custom genealogy GPTs in the store, which are related to family history research (more are being finished in the lab). Custom GPTs are available to ChatGPT Plus subscribers ($20/month) for no additional cost in the ChatGPT Store.
These are the kinds of genealogy AI tools that I teach students to create; no programming skills are necessary. ChatGPT can interview you, to ask you what kind of AI tool you’d like to create. Then I can show you how to fine-tune the tool to suit your exact genealogy workflow. It won’t fetch you a Snickers Bar or promise to solve a 120-year family history mystery, but within the realm of what large language models can do today, this one does okay.
If you’d like hands-on, step-by-step instruction on how to build your own custom GPTs and other specialized genealogy AI tools, your own flock of bots, the National Genealogical Society is now enrolling for Prompt Engineering and Specialized AI Tools for Genealogists, which starts at the end of January 2024; six hours of instruction over four weeks is just the start; also includes a collaborative study group, sharing successes and learning from failures. The first section of 50 seats sold-out in days, so a second section has been opened. Learn more here: https://www.ngsgenealogy.org/ai/
Jump straight the the growing list of Genealogy Bots here or access them at OpenAI Store by searching for bots with the term "genealogy." Custom GPTs are free for ChatGPT Plus subscribers ($20/month). I also teach genealogists and educators how to make their own custom genealogy GPTs, hands-on, step-by-step; enrolling now.
Friends, you may have heard the announcement that the OpenAI directory of custom GPTs is now being unrolled to ChatGPT Plus users. Custom GPTs represent an advancement in AI usefulness, marking a step towards more customizable and versatile AI tools. According to the OpenAI, these custom GPTs are described as a means to “create for a specific purpose,” highlighting their adaptability and user-centric design. Wharton professor Ethan Mollick in his article “Almost an Agent: What GPTs can do,” emphasizes the current state and future potential of these tools, noting, “GPTs show a near future where AIs can really start to act as agents.” This statement underscores the transitional nature of GPTs as a bridge between current AI capabilities and the more autonomous agents of the future. Simon Willison, in “Exploring GPTs: ChatGPT in a trench coat?” offers a practical perspective, stating, “The combination of features they provide can add up to some very interesting results.” His experience reflects the innovative possibilities that arise when various capabilities of GPTs are combined. Together, these insights from OpenAI, Mollick, and Willison paint a picture of GPTs as transformative tools, offering both a glimpse into the future of AI agents and a practical platform for current applications.
I’ve got four GPTs (now five) that I’m publicly testing (these are genealogy-related GPTs or genealogy-adjacent; another half-dozen others are still in the lab). I think of these GPTs as little AI tools that you can create, save, repeatedly re-use, and share. Custom GPTs, also referred to as bots, assistants, or agents (though these terms aren’t technically synonymous), represent a method to save a bundle of prompts, custom instructions, and abilities (image analysis, image generation, document reading, etc.) in a profile that you can use and share. For us as genealogists, this means that when we find a prompt, series of prompts, or set of custom instructions, to reliably accomplish a genealogically useful task, we can save that process as one of these GPTs; then, when we need to accomplish that task again, that tool, that bot, that GPT, is already in our AI toolbox.
Months ago, professional genealogist Yvette Hoitink created and shared the first genealogy GPT (to my knowledge), Dutch Genealogy Bot, available to ChatGPT Plus users at https://chat.openai.com/g/g-MMm3v0QX3-dutch-genealogy-bot. When asked for a short summary of its abilities, the bot replied: “As the Dutch Genealogy Bot, I specialize in guiding you through the process of researching Dutch ancestry, using resources and insights exclusively from Yvette Hoitink’s Dutch Genealogy website. I can provide detailed information and methodologies for tracing Dutch heritage, and direct you to specific articles on DutchGenealogy.nl for further guidance and authentic information.”
These four five little bots are my initial efforts, for example:
Genealogy Eyes Look at images, photos, and documents through the eyes of a family historian. Try it from your phone! Take a snapshot of a cemetery headstone, document/record, or anything else, and, using the official ChatGPT app, upload the image, say a little about the image and what you want, and click Send. https://chat.openai.com/g/g-gmIAn5mh6-seer-of-roots
Lingua Maven A linguistic expert, I combine dictionary precision, usage panel insights, and style guide expertise. My skills encompass a vast lexicon, dynamic thesaurus, and in-depth knowledge of language evolution, etymology, and dialects. I am a comprehensive resource for analysis and interpretation. https://chat.openai.com/g/g-Rxyt3Xww1-lingua-maven
Genealogy Summarizer Create useful summaries from texts, images, documents, photos, records, and more. This bot looks at what you give it, determines (as best it can) what it is, and suggests several ways to summarize the item. You can then ask follow questions about the item, or collect all the suggested summaries. https://chat.openai.com/g/g-Kg79HuRVD-genealogy-summarizer
Sam the Digital Archivist Kinda like a spicy librarian. Open GeneaGPT’s over-caffeinated genealogy and family history friend. Embark on a journey through your past with our customized genealogist bot, designed to delve into your ancestry and lineage. Discover your roots while having fun and learning genealogical methods. https://chat.openai.com/g/g-v6WgbVnba-sam-the-digital-archivist
PS: Learning how to make these custom GPTs is a significant portion of the focus of the Empowering Genealogists series class, Level 2: Prompt Engineering and Specialized AI Tools for Genealogists, which starts at the end of January 2024: https://www.ngsgenealogy.org/ai/
A common goal when working on family archive projects is to figure out who the people are that are included in photographs or mentioned in letters. Identifying them can be crucial to answering questions about your family history and can lead to new clues to follow up on.
Although, as anyone who has tried to do this knows, it can be a painstaking and frustrating process. Letters rarely include the information needed to identify everyone. As letters are usually between people who know everyone they’re writing about, they tend not to include last names, or even worse, first names.
I’ve developed Excel-based approaches over the years for identifying groups of people in these situations. Although, they can be time-consuming to put together, and require specialty skills in Excel to use them.
It occurred to me that I might be able to use artificial intelligence to identify people more easily. This blog post will describe how I tested this idea and what I learned that could help you do the same in your own genealogy research.
Before diving into the fictitious example I used to test this idea, it is helpful to understand how this kind of research is done “manually.”
How to Manually Identify People in a Family Archive
While there are many approaches for identifying people mentioned in a letter, one of the most common techniques used by genealogists is to figure out how the different people mentioned in the letter may be related. They might be friends, co-workers, or family. If you can figure out how they are connected, it is easier to figure out who they are.
After all, it’s easier to find several needles tied together in a haystack than it is to find an individual needle in the haystack.
How to Identify Family Members
For the rest of this article, the names that I use will all be taken from this example, fictitious, family tree.
When I suspect that people mentioned in a letter could be family members, I compare the names of the people to their family tree and try to find close relatives with those names. The assumption is that people tend to write about their immediate family.
For example, let’s say a letter written by “Clara” includes a line that says, “Walter and I went down to the train station to pick up Joe.” While the family tree might include dozens of people named Joe, Walter, and Clara; it will have fewer families (and hopefully, only one) where they are all immediate family members.
While this approach makes intuitive sense, it isn’t easy to use in practice. The problem is that online trees don’t have a button labeled, “Show me all of the families that have a person named Joe, Walter, and Clara in them.” As such, this approach requires repetitive searches of a family tree looking for clues about which family group might be the right one. Alternatively, spreadsheets, or third-party tools designed for this kind of search, can also be used.
Given the challenges in doing these searches the manual way, I decided to see if this problem could be solved more easily using artificial intelligence tools.
Using ChatGPT to Search a Family Tree
Given that ChatGPT is particularly good at finding patterns, it seemed a natural fit for this type of search. Now the big question was how to get ChatGPT to search a family tree? I needed a plan.
Prompt Planning with ChatGPT
Whenever I am working out how to approach a problem using ChatGPT, I think about the following:
How will I provide the AI with the information needed to do the work?
Which role should the AI take on when performing the work?
What is the work that I want the AI to do with the information I provide it?
What is the format that I want the AI to present its findings in?
I’ll walk through my planning process step by step so that you can try this, or something similar, yourself.
How to Give ChatGPT Your Family Tree
The first, and most difficult challenge in this example was to get ChatGPT the information from the family tree. To do the kind of search that I’m interested in, ChatGPT needed to be able to see the people in the tree and understand their relationship to each other.
Thankfully, there is a family tree format that ChatGPT can understand.
The GEDCOM File Format
Image Generated by DALL-E 3
The Genealogical Data Communications format, or GEDCOM for short, was created by the Church of Jesus Christ of Latter-day Saints as a way for exchanging family tree information between computer programs. The information that can be transferred using this format includes information about the people in the tree, (like name, and birth, marriage, and death dates) as well as information about the relationships between the people (like parent, child, and family group).
Of all of the formats for family tree information in use today, you may wonder why GEDCOM is good to use with ChatGPT?
Why GEDCOM Works Well with ChatGPT
Besides the fact that GEDCOM files contain the information needed for this search, there are a few things about the GEDCOM format that make it well-suited to working with ChatGPT.
GEDCOM is a text-based format and ChatGPT excels at working with text.
Even though ChatGPT was trained on information created several years ago, the version of GEDCOM used by the major genealogy companies is several years old. This means that the information that ChatGPT has in its training data is still accurate today.
The GEDCOM format, which has been in use for 40 years, has been the subject of thousands of online articles. In fact, Google found over 4 million web pages that mention GEDCOM! As a result, ChatGPT has been well-trained in how the GEDCOM format works.
Now that we know that the GEDCOM format is a good way to provide information to ChatGPT, how do we get our family tree into the GEDCOM format?
How to Export an Ancestry Family Tree in GEDCOM Format
To generate a GEDCOM file of my family tree at Ancestry, I completed the following steps. Starting within Ancestry’s Tree View:
Select the three dots menu in the left navigation bar.
Select the “Tree Settings” menu.
Click the “Export tree” link.
Click the “Download your GEDCOM file” button.
Note, that depending on the size of your tree, it can take some time to create the export file before it can be downloaded.
I then saved the GEDCOM file to a known location on my computer, so that I could use it in the next steps.
Now that my family tree was exported to GEDCOM format, it was time to build the ChatGPT prompt.
Assigning a Role to ChatGPT
The process of building a prompt, often referred to as prompt engineering, starts by assigning a role for the AI to adopt when performing the work. The role assignment is important to do first because it sets the context for how additional instructions will be understood by the AI.
To understand why role assignment is important, consider how you ask different people to do work for you. For example, the way that you would ask your 12-year-old child to clean up your yard would be different than the way you would ask a person who works for a professional yard cleaning service. Even though you have very similar goals for them, you would phrase the request for each of them in a very different way because of who they are.
As I was trying to form a complex genealogy search of a GEDCOM file, I wanted ChatGPT to assume a role that specialized in this type of work:
PROMPT: Please act in the role of a professional genealogist who has a deep understanding of the GEDCOM file format.
While the work portion of the prompt seems incomplete by itself, combined with the role assignment in the first step, it had the context to be understood by ChatGPT.
Finally, I needed to tell ChatGPT how I wanted the information it found to be presented to me.
How Should the AI Present Its Findings?
In this example, my goal was to look at the results for clues about family groups. So, I wanted the response to include information about the relationships between the people found. And, because I was going to do these searches frequently, I wanted the results to be easy to interpret at a glance.
PROMPT: Should you find a family group that you believe includes these people, create a table that lists the full name of the people in the family group in one column, and their relationship to Joe in another column.
The Complete Prompt
After testing several different approaches, this is the final prompt. Note, that I’ve shared some of the failed attempts at the end of the article in the “Challenges to be Aware of” section.
PROMPT: Please act in the role of a professional genealogist who has a deep understanding of the GEDCOM file format.
I would like you to analyze the file that I will provide to you next. Please search the file for family groups that include the names Joe, Walter, and Clara.
Should you find a family group that you believe includes these people, create a table that lists the full name of the people in the family group in one column, and their relationship to Joe in another column.
After submitting the prompt, I opened the GEDCOM file in a text editor so that it would be easy to copy the file to provide it to ChatGPT. In my case, I used Notepad++, but you could do this with Notepad, Wordpad, or any other text editor.
Once I had selected and copied all of the text, I pasted the text directly into ChatGPT’s prompt box and then clicked the submit button.
I was very happy to see that it found the correct family group, and displayed them in a way that was easy to confirm and check for additional clues!
Other Complex Searches Tested
I tried several different complex searches that I regularly come up against when doing this kind of project.
Finding More Than One Family Group
In a real-world search, it is likely that I would find more than one family group that included the names that I was looking for.
PROMPT: Please act in the role of a professional genealogist who has a deep understanding of the GEDCOM file format.
Please search for family groups that include the name Terry.
Should you find a family group that you believe includes this person, create a table that lists all of the people in the family group in one column, and their relationship to that person in the other column. Should you find more than one family group, create an additional table for each additional family group.
Focus on People That Were Alive at The Time
One way to zero in on the right family group is to only include people who were alive at the time the letter was written.
PROMPT: Please act in the role of a professional genealogist who has a deep understanding of the GEDCOM file format.
Please search for family groups that include a person named Terry who was alive in 1960.
Should you find a family group that you believe includes this person, create a table that lists all of the people in the family group in one column, and their relationship to that person in the other column. Should you find more than one family group, create an additional table for each additional family group.
This response is particularly interesting as it shows that ChatGPT, acting in the role of a genealogist, knows how to interpret a request for living people.
This is a textbook example of a natural language search.
And many, many more…
I tried several other, increasingly complex searches, and they all worked as long as the information that I was searching for was included in the family tree.
Challenges to Be Aware Of
ChatGPT Plus Can Only Accept 25,000 Characters
The most important limitation to be aware of is that there is a limit on how much text you can ask ChatGPT to process. Because I used ChatGPT Plus in my testing, the limit is about 25,000 characters.
When I tried this test with a sample tree with hundreds of people in hundreds of family groups, ChatGPT said it was “too big.” When I performed my test on a smaller family tree with only a few dozen family groups, it worked successfully. As a result, I consider the approach used in this article a good proof of concept for me, and others, to use as a starting point for searches of larger and more family trees.
There is also a less well-understood limit that is based on the “complexity” of the file being processed. In the context of a GEDCOM, I believe this comes into play when there are more types of facts, and more relationships between people to track. Although, I wasn’t able to find a clear description of this limitation.
I expect that as ChatGPT evolves, these limitations will decrease.
GEDCOM Files Might Contain Personal Information
Be careful when exporting your family tree GEDCOM file format. If your tree contains private information, so will your GEDCOM file.
Ancestry’s GEDCOM export utility exports all the facts in your tree. If you would like to export a portion of your family tree, or only certain facts from your family tree, you will need to use a tool that supports this.
Family Tree Maker, for example, supports the partial export of a family tree.
Exercise Caution with Follow-up Searches
My testing was most successful when I used a fresh chat session in ChatGPT. When I tried follow-up searches in the same chat session, errors in the responses went up dramatically. When I spotted mistakes, I asked ChatGPT to double-check its results and explain how it came to its conclusion. In every case, it found the correct answer on the second try and apologized for its mistake.
Because of this issue, I quickly learned to follow up each response with a “please double check and explain your results” prompt.
Based on my testing, I believe that there are two likely sources for these errors:
The errors might come from answers generated in previous prompts. In other words, ChatGPT mixed its previous responses up with my subsequent requests.
The amount of information in the session grew too long after multiple requests, so information was being “forgotten” because of the space taken up by previous questions.
Final Thoughts
ChatGPT Plus can read and search GEDCOM formatted family trees and correctly interpret the genealogical information in them.
It can also do complex searches of family trees using natural language. These complex queries can include searches for multiple people, family groups, relationships between people, and the time or place that people lived.
False responses were generated by some of the tests, especially when multiple follow up questions were used in the same chat session.
Like all genealogy research, results from ChatGPT need to be treated as clues that require further investigation before they can be relied upon as fact.
At the time of this writing, the approach used in this article is limited to “small” trees. Alternative approaches, or improvements to ChatGPT Plus, will be necessary to search larger trees.
I’d Love To Hear From You
Have you tried any alternative approaches for complex searches of a family tree?
Do you know of a way to search larger family trees with a different approach? If so, please let me know in the comments below.
As genealogists, we find ourselves at the intersection of history and technology. Today’s example comes from the evolving field of AI-generated imagery. Earlier today, Steve Little from AI Genealogy Insights highlighted a resource that addresses a common challenge with DALL-E 3: fine-tuning the generated images to fit our specific needs by using seeds.
As part of a private Facebook group for Steve’s NGS “Empowering Genealogists with Artificial Intelligence” course, a Twitter post by Rowan Cheung was shared which sheds light on the concept of using ‘seeds’ to refine these images. While I had come across the term earlier in the week, it wasn’t until this demonstration that the methodology clicked for me—and it’s a game changer!
What’s the problem?
This and all following images generated using DALL-E 3
Often, when you try to make small changes to a generated image, it instead generates an entirely new image. And that can be frustrating!
For example, above is an image of a black cat with a sign that says “Trick or Treat” (with DALL-E 3’s notorious spelling mistakes).
I liked the cat and the scene, but I wanted to change the sign. So I prompted “Generate another image similar to #1 but have the sign say ‘Boo!’”
The new image changed a lot more than just the sign. It includes a different, younger black cat and different background though it’s similar.
Using seeds can help us to produce additional images that are much similar to the original image.
What is a “Seed”?
To better understand the concept, I turned to ChatGPT for an explanation of what “seeds” mean in the context of AI. Here’s an analogy from the first part of its response:
“Alright, imagine you have a magic book that gives you a random page number every time you ask it. But sometimes, you want to get the same ‘random’ page number every time you ask, so you can show your friend the cool picture on that page. That’s kind of what a seed does in AI.”
So, if we tell DALL-E 3 we want to modify a certain seed or page number, it does a pretty good job of giving back a similar image with the modifications we asked for.
Using Seeds
After reading through the Tweet mentioned earlier, I started playing with seeds (again). This time, I understood the process a lot better. And it worked!
My first success was a baby seal. I will use a series of prompts to get the desired image doing what is called “prompt chaining.”
Prompt #1: Draw an adorable seal with large eyes
Of the two seals DALL-E 3 generated, this was the “adorable baby” seal I chose to work with.
Prompt #2: What’s the seed for image 1?
Since the baby seal I wanted was the first of the two generated images, I asked for the seed for image 1. It responed “1122301494.” Remember, this is like me now knowing what “page” DALL-E 3 has the image on so I can go back and modify that page!
Prompt #3: Modify the image with seed 1122301494: add a beach scene with a starfish -ar 7:4
When I’m asking DALL-E 3 to modify a seed, I start with the phrase “modify the image with seed [x].” Next, I can ask it to add, remove, or edit something. And finally, I can ask for specific aspect ratios (-ar): 1:1 for square, 7:4 for wide, or 4:7 for tall. (I have also learned I can just use the words square, wide, or tall!) I love changing a square image into “wide” or “tall” which actually expands the scene!
We now have the SAME ADORABLE BABY SEAL with a wider beach scene and a starfish. WOW!!!
And just to try it again…
Prompt #4: Modify the image with seed 1122301494: add his mother -ar 7:4
In hindsite, I don’t think I needed to specifiy the aspect ratio since it was already wide. But I’m still learning!
And once again we have the SAME ADORABLE BABY SEAL with his mom!
Breathing Life Into Family History
And now a bit more from ChatGPT based on my input:
Transforming images with seeds isn’t just about tweaking a picture until it’s perfect; it’s a gateway to visual storytelling that can vividly illustrate our family histories. Whether we aim to elevate a photograph from ‘like’ to ‘love’, or we wish to infuse static images with dynamic action, the possibilities are endless.
Take, for instance, the journey I embarked on with a single image: a photograph of a young Confederate soldier. The original image captured a moment, but I envisioned more. I wanted to broaden the narrative. So, I expanded the image—widening its scope to include additional figures, thereby crafting a richer tableau.
There was also the matter of authenticity. Through prompt chaining, the soldier’s uniform had faded to brown in the “photograph.” With careful editing, I restored the uniform’s gray hue, maintaining historical accuracy while breathing new life into the image.
Join me as I continue to explore the potential of using seeds in AI to create more accurate and personalized visual stories.
If you follow me on Facebook, you’ve probably noticed that I’ve fallen in love with generating Artificial Intelligence (AI) art. I’m also embracing AI in my genealogy work as well as my broader life! This technology really started becoming possible less than a year ago in December 2022. My journey began a short time later.
AI illustration generated by DALL-E 3
So, what have I experimented with so far, how has it been helpful, and what concerns have arisen?
March 2023
I first tried the free version of ChatGPT in March. At that point, I was trying to use it more like Google; I wasn’t impressed. At the time, I didn’t realize that it wasn’t interacting with the live internet so was frustrated that it couldn’t help with more recent events.
May 2023
AI illustration generated by DALL-E 3
By May I had watched a few YouTube videos where they showed how to use it to make plans to learn something. So, besides using it like Google, I also asked for how to learn Spanish at home, learn to be a better artist, and tips for improving my pinball game. Asking for ideas on how to learn something is one of ChatGPT’s strengths! For example, it suggested I do the following (with greater detail) to be a better pinball player:
Practice
Focus on ball control
Study the game
Develop a consistent technique
Stay calm & focused
Watch and learn from other players
Join a pinball league or tournament
Note that even though AI has great tips about how to play pinball better, it doesn’t understand how you physically play pinball! No matter how I changed the prompt, it gets the
I also used it to learn more about a specific group of people I was working with on a project that was beyond what a simple Google search could do.
June 2023
In June I started asking more questions like “Explain X-DNA inheritance” and “If two people share 3505 cM of DNA, how are they related?” It did really well on the X-DNA question, but “failed” on the relatedness question. The Shared cM Project, where most genealogists turn to find genetic relationship probabilities based on a shared amount of DNA, shows that two people who share 3505 cM have a 100% probability of being parent/child. ChatGPT also suggested they could be full siblings, half-siblings, or grandparent/grandchild.
AI illustration generated by DALL-E 3 2023
I also first started using it to help me with my genetic genealogy presentations asking it to help me write titles and descriptions of my talks.
July 2023
In July, I started trying to find an app I could use to create digital art. I was trying to use a program called Journey for free, but it was always closed to new, non-paying members. Since I also do digital art on my iPad using Procreate, I asked it to generate prompts for my art.
AI illustration generated by DALL-E 3
I also used it to help with the probability of two events happening focused on genetic genealogy. I learned that it not only answers your mathematical questions, it shows you HOW to calculate those answers.
(Notice that the AI generated illustration, which I created today, misspells the word “probability.” This is something I’ve noticed on most of my AI illustration generations! I am sure it’ll get better with time.)
August 2023
Why did the genealogist bring a ladder to the family reunion?
He wanted to see if there were any nuts in the tree.
AI illustration generated by DALL-E 3
This is the first joke ChatGPT suggested when I asked, in August, for it to “write a joke about genealogy.” The jokes weren’t very good, and I’m also a terrible joke teller so it was probably a bad idea anyway. It is fun to see what AI can create, though I’m sure this is not an original joke.
I also continued to expand how I used ChatGPT for my talks by asking it to brainstorm things to include in a specific talk. This technique helps to save time! Of course, I am not using its suggestions exactly, but it helps to get me started.
I also used ChatGPT during a non-profit meeting to brainstorm fundraising event ideas! This was an amazingly quick way to get a lot of great ideas. And we were able to tweak them to customize them with our theme.
September 2023
AI illustration generated by DALL-E 3
In September, I was struggling with getting the page numbers on a handout in Word as I wanted them. I asked ChatGPT, and it gave me the instructions I needed to quickly fix them! I also asked it to help me come up with an Excel formula to help in a tournament where the calculations were complex. Realizing I could turn to AI for help with Word and Excel was a great help for me!
October 2023
In October 2023, I went to the East Coast Genetic Genealogy Conference where Blaine Bettinger used AI generated illustrations in his presentation. This was a game changer for me!
When I got home from the conference, I discovered Carole McCulloch of “AI and the Genealogist” through a free video she has on YouTube titled “ChatGPT-4 and DALL-E3: an AI Genealogist Tip.” This is how I really got started generating art illustrations with AI! And it was at this point that I switched to a $20/month paid subscription of ChatGPT to access DALL-E 3.
The Future of AI and Genealogy
I have embraced AI’s power to help me solve problems, acquire new skills and knowledge, brainstorm, edit my written words, and generate illustrations. Just as the ability to use our DNA has transformed genealogy, I believe AI will also transform our field by helping us create quick and accurate transcriptions, abstractions, and translations; process and analyze large amounts of data; and much more. Of course we need to educate oursleves on how to use AI ethically and responsibly, especially in this field of genealogy where the accuracy of the information we share is crucial. Missteps in this area could lead to the spreading of errors, inaccurate family histories, and misleading future researchers.
Personally, I look forward to seeing how AI continues to transform our field as we gather, evaluate, and share our family stories. Although some are uncertain about this new technology, I am excited about harnessing this new power to both enhance our existing practices as well as unlock new tools to help us perform tasks more quickly and accurately. Thankfully, our genealogy community is actively discussing, researching, and even educating our members as to how we can use this tool ethically.
Like many others, I believe the world is entering a new era. As we continue to explore and integrate AI into our work, the possibilities for innovation and discovery are limited only by the advancements in these tools and our own imaginations. Let’s embrace the future as we explore how AI can enhance the field of genealogy.
Your Turn
Have you tried AI? If so, what platform have you used? And what successes or failures have you had while using AI? How do you think it will affect your personal and work life in the future?
The Infinity Gauntlet was unlocked Friday night, October 13th, 2023 (Friday the Thirteenth), when the last of the anticipated new beta modes rolled-out to my ChatGPT Plus account when DALL-E 3 access was enabled. In other words, ChatGPT Plus can create images now. ChatGPT Plus users will know you can try this when you see this beta mode enabled:
These are some of my first attempts in the first hours of access to get ChatGPT Plus with DALL-E 3 to create a family tree or something interesting given a bit of an Ahnentafel list.
All were failures in the sense that I had trouble getting DALL-E 3 to render much text correctly. Which makes this a good time to repeat Prof. Mollock’s point: just because one user fails to get ChatGPT to do something, doesn’t mean it can’t be done. Individually, our failed prompts may be revealing our limits at prompt engineering, not the AI’s capability. Today.
So I share these failures because I’m pretty sure one of you will crack this.
Thelma Francis Houck (1921-2017) was my maternal grandmother, my Grandma Lawrence; these experiments were with her in mind, trying to make something nice in honor of her memory.
FAILED PROMPT:
Do something artful with this bit of an Ahnentafel list:
1. Thelma F. Houck (1921-2017)
2. Joseph C. Houck (1888-1983)
3. Pearl E. Houck (1891-1992)
4. James S. Houck (1858-1927)
5. Minerva E. Fox (1862-1957)
6. Thomas M. Houck (1859-1924)
7. Delia T. Parker (1866-1936)
And because some of these “failures” were still pretty cool.
Some interesting failures. I can’t wait to see what you create with this.
By the way, this is what ChatGPT imagines your office looks like:
PROMPT: Show me some images of a genealogist's dream office/library/archive.
ChatGPT with Vision (GPT-4V) analyzes a handwritten WWII draft card, and not only reads handwriting correctly but also accurately identifies text fields (name, address, next of kin, date of birth, occupation, etc.). This draft card, from my maternal grandfather Dean Lawrence (1921-2003) was chosen for the average block print handwriting; testing will continue to determine how good GPT-4V is with recognizing cursive handwriting, but it appears to handle average print well. Again, though, the innovation is that the AI will correctly label the data; that is, earlier OCR can process simple block handwriting, but it couldn’t tell you whether the text was name, address, or occupation. ChatGPT with Vision (GPT-4V) correctly labels the data. Now, imagine a simple Python script that processes a folder of 20 or 200 or 2000 images like this for you; that will be a trivial task once OpenAI makes API access available for GPT-4V, which is expected (more simply, that is, with middle-school programming skills, tasks such as these will be quickly and easily automated).
PROMPT: You are a professional genealogist; your area of expertise is documents and records; you are adept at extracting every piece of information from a document or record. You are also a skilled writer and image analyst. Think now about a World War II Draft Registration Card, also called DDS Form 1: list every conceivable piece of information that might be found on a draft card (focus especially on names, relationships, dates, places, events, and facts).
Then, find attached a draft card. Extract every piece of information from the image of the draft card.
Finally, create a biographical narrative report from the text on the draft card; dry recitation, no editorializing.
A couple of points to highlight:
you can assign multiple roles simultaneously to the AI: you can prompt the AI to act not only as an expert genealogist, but at the same time to act as a skilled writer and image analysist.
you can ask for several tasks, essentially stepping ChatGPT through a process.
you can ask for a narrative summary of the text in the image, e.g., “create a biographical narrative report from the text on the draft card; dry recitation, no editorializing.”
Here was the response:
RESPONSE:
Information Extracted from the Attached Draft Card: 1. Serial Number: 234 2. Full name of the registrant: Warren Dean Lawrence 3. Place of residence: West Jefferson, Ashe, NC 4. Mailing address: Same as residence 5. Telephone number: Not provided on this card 6. Age in years: 20 7. Date of Birth: May 21, 1921 8. Place of Birth: West Jefferson, USA 9. Name and address of someone who will always know the registrant's address: Mrs. Warren Dean Lawrence, West Jefferson, NC 10. Employer's name and address: Partially illegible but appears to reference a mining company 11. Place of employment or business: West Jefferson, Ashe, NC 12. Signature of the registrant: Appears to be "Dean Lawrence" or a similar variant 13. Date of registration: Not clearly visible on this card
Biographical Narrative Report: Warren Dean Lawrence, residing in West Jefferson, located in Ashe County, North Carolina, registered for the World War II draft. Born on May 21, 1921, in West Jefferson, USA, he was 20 years old at the time of registration. His mailing address was the same as his place of residence. The individual who would always be aware of Warren's address was Mrs. Warren Dean Lawrence, also of West Jefferson. Warren's employment details reference what appears to be a mining company located in West Jefferson, Ashe, North Carolina. The draft card carries what seems to be his signature, "Dean Lawrence" or a similar variant.
Prompt Chain to process data further
Once we have the “Information Extracted from the Attached Draft Card,” that information can be standardized, so that if you have many sources of this type (in this example, a draft card), the data can be collected, compiled, compared, and analyzed. For example, if you had 20 of these cards, you may wish to move that extracted data into a spreadsheet or database. Saving the data for each record as a CSV (Comma Separated File, a widely-used file format) file allows us to do this simple task. In the instance, I followed-up the first prompt with a second prompt; using the results of one task as the input for a subsequent task is called prompt chaining. Here was my second prompt:
PROMPT: Create a CSV file from the Information Extracted from the Attached Draft Card. Use the format: "FIELD NAME","VALUE", where FIELD NAME is the field label used in the original image and VALUE is the value extracted from the image, such as "NAME","Warren Dean Lawrence". Display the response in a code window for easy copy-and-paste.
ChatGPT responds with the data in the format of a CSV file, and places that information in a code window, which makes copying-and-pasting easy (just click the “📋 Copy code” icon). One beta mode of ChatGPT, called “Advanced Data Analysis” (formerly “Code Interpreter”), will create an actual CSV file and present you with a download link, but for now we can only use one beta feature at a time; expect that to get better in time.
Up Next: Clean, simple cursive handwriting on a draft card
There remain many document types to test. I’ve been testing more challenging samples to discover where the limit of ChatGPT’s handwriting recognition. Up next is a clean, simple cursive script on a form such as this draft card. Ultimately, however, we will test handwritten documents such as letters, diaries, journals, court orders, and probate files. Handwriting recognition is hard, so I expect the limit might be discovered sooner than anticipated, for the time being.
For the record, here is a screenshot of the beginning of this ChatGPT conversation:
