Old vs New: Are all old people technologically challenged?

 

The question in my title reflects a common stereotype in the United States. Having used computers since 1969—from my first Apple II in 1978 through my law career—I’ve seen how technology adoption varies. While I've witnessed how dementia can erode these skills, my experience also shows that the 'digital divide' is often less about age and more about income and education. In my law practice, I saw senior attorneys who refused to use computers; conversely, at the BYU Library Family History Center, I work with retired volunteers who possess advanced technical skills.

I began using computers back in about 1969. Although I spent some time in the U.S. Army and Law school, I bought my first Apple II in about 1978. I have been consistently working on computers since then. I also began doing my own genealogical research in 1982. 

Both my parents were afflicted with dementia in their old age and I have seen the effects of dementia on a person's ability to handle technology. A quick review of a number of online sources reveals  a significant digital divide influenced by age, income, and education levels. While younger generations are often labeled "digital natives," experts argue they are frequently just efficient consumers of social media rather than being proficient in essential workplace software. This is my own experience with my grandchildren. When I retired from my law practice about 12 years ago, there were still senior attorneys working at the law firm who could not and/or would not use computers. Beyond my personal observations, broader data reveals that the 'digital divide' is deeply rooted in systemic literacy gaps.

Socio-economic factors such as education and income act as primary determinants of digital literacy, creating a "digital divide" both within nations and on a global scale. These factors influence not only the ability to access technology but also the capacity to use it for complex problem-solving and economic advancement. I realize I have written on this topic before, but it bears frequent repeating. 

The Role of Education

Educational attainment is one of the most consistent predictors of digital literacy.

• Foundation of Skills: Education provides the foundational literacy and numeracy skills required for "digital problem solving"—defined as the ability to use technology to acquire information, communicate, and perform practical tasks.
• Literacy Gaps: In the United States, digital literacy increases significantly with formal schooling. Approximately 41% of adults without a high school diploma are not digitally literate, compared to only 5% of those with a college degree.
• Quality vs. Degree: Simply graduating does not guarantee literacy. For instance, data from 2024 revealed that nearly 19 million Filipino students who graduated from junior and senior high school were considered functionally illiterate, meaning they could read but struggled to comprehend or apply written instructions—a major barrier to effective digital tool use.
• Global Disparities: Developed nations, which typically have adult literacy rates of 96% or higher, have much lower rates of digital non-literacy than the least developed countries, where literacy rates average only 65%.

The Impact of Income and Wealth

Income shapes digital literacy primarily by dictating access to infrastructure and the affordability of devices.

• Device Adoption and Access: In the U.S., higher-income populations adopt technology at much higher rates. Among seniors, 87% of those earning $75,000 or more have home broadband, compared to just 27% of those earning less than $30,000.
• Infrastructure Barriers: In countries like Mexico, the digital divide is heavily linked to poverty and a lack of proper fiber-optic infrastructure in rural, low-income areas. Similarly, in Sub-Saharan Africa, widespread poverty limits internet use to roughly 7% of inhabitants, even though mobile phone ownership is much higher.
• Service Costs: In regions where telecommunications are monopolized, high costs prevent low-income families from accessing the internet, further stagnating their digital skill development.

The Socio-Economic Feedback Loop

There is a profound cyclical relationship between these factors and economic success:

• Employability: Adults with higher digital literacy have higher rates of labor force participation (84%) compared to those who are not digitally literate (66%).
• Job Quality: Digitally non-literate adults are disproportionately found in unskilled or semi-skilled blue-collar jobs.
• Economic Cost: Low literacy skills are linked to lower earnings and unemployment. In the U.S., low literacy levels are estimated to cost the economy up to $2.2 trillion annually due to reduced productivity and limited employability.

Based on recent data from the National Literacy Institute and the National Center for Education Statistics (NCES), here is a summary of the current state of literacy in the United States:

Current Statistics (2024-2025)

Illiteracy Rate: Approximately 21% of U.S. adults are considered illiterate, which translates to roughly 43 million people who struggle with basic reading tasks.

Low Proficiency: About 54% of adults read at or below a sixth-grade level. Within this group, 20% read below a fifth-grade level.

Global Standing: The U.S. currently ranks 36th in global literacy, significantly behind other developed nations that often report literacy rates of 96% or higher.

Here are some representative sources for the above information:

• Anderson, Monica, and Andrew Perrin. "Tech Adoption Climbs Among Older Adults." Pew Research Center, May 17, 2017. https://www.pewresearch.org/internet/2017/05/17/tech-adoption-climbs-among-older-adults/
• Ankiana. "Millennials assume anyone older than them is technologically illiterate." Reddit, r/GenX, ca. 2023. https://www.reddit.com/r/GenX/comments/11ezz04/millennials_assume_anyone_older_then_them_is/.
• Billau, Christine. "New Study Explores Digitally Native, But Technologically Illiterate Students." UToledo News, May 19, 2021. https://news.utoledo.edu/index.php/05_19_2021/new-study-explores-digitally-native-but-technologically-illiterate-students.
• Friemel, Thomas N. "The digital divide has grown old: Determinants of a digital divide among seniors." New Media & Society 18, no. 2 (2016): 313–331. https://journals.sagepub.com/doi/10.1177/1461444814538648.
• Mamedova, Saida, and Emily Pawlowski. "A Description of U.S. Adults Who Are Not Digitally Literate." National Center for Education Statistics (NCES 2018-161), May 2018. https://nces.ed.gov/pubsearch/pubsinfo.asp?pubid=2018161.
• Moller, Ralph. "45 US Literacy Statistics Exposed." Above and Beyond Therapy, July 16, 2025. https://abtaba.com/blog/us-literacy-statistics.
• OECD. "Adult skills in literacy and numeracy declining or stagnating in most OECD countries." Press release, December 10, 2024. https://www.oecd.org/en/about/news/press-releases/2024/12/adult-skills-in-literacy-and-numeracy-declining-or-stagnating-in-most-oecd-countries.html.
• Wikipedia contributors. "Digital divide by continent, area and country." Wikipedia, The Free Encyclopedia. Last modified October 2023. https://en.wikipedia.org/wiki/Digital_divide_by_continent,_area_and_country.

Analogy for Understanding: Think of socio-economic factors as the foundation and framework of a house. Education provides the blueprint and tools (literacy and logic) needed to build the structure, while income provides the high-quality materials (devices and high-speed internet). Without both, a person might be left standing in an empty lot, unable to build the "home" they need to participate in the modern digital world.

So, what does this "foundation" mean for the world of genealogy?

Genealogy is a rigorous academic pursuit, not just a casual hobby. Just as a house needs a solid base to stand, valid research requires high-level literacy and critical thinking. In my experience, many of the inaccuracies found in the FamilySearch.org Family Tree result from contributors who lack the reading levels necessary to analyze and document complex historical records accurately.

We must also move past the myth that "young people" are naturally better researchers. While they may navigate smartphones with ease, that skill does not translate into the ability to research ancestral lines in Germany or Scandinavia. Success in family history should begin with foundational training in reading and research—not just digital navigation.

The Bottom Line: Are all "old people" technologically challenged? No. But whether you are 18 or 80, the ability to build a reliable family history depends on the same foundation that supports every other digital achievement: literacy.

Enhance your responses from Google Gemini 3 with expanded prompts.

 

I have been talking to computers for about 55 years now and for the first time I am getting helpful answers. The main change is now you can ask the computer how to talk to it for any possible response. Really, if you are working with a Chatbot such as Google's Gemini 3, all you have to do is ask for some suggestions of prompts to use to answer any question or do genealogical research. In fact, Gemini 3 will ask you if you would like a suggested prompt. Here is an example from Gmini 3. The rest of examples will all be from Gemini 3. 

Would you like me to write a specific prompt for you to ensure NotebookLM captures specific details, like URLs or publication dates?

Here is the prompt it wrote:

Role: Act as a professional genealogist and forensic investigator.

Objective: Extend the family line presently on the FamilySearch.org Family Tree beginning with Ludwig Diepolder KHW6-V87 b. 1882, d. 1915, in Ulmerthal, Kreuzthal, Kempton, Schwaben, Bayern, his wife is Matilde Lohner Ferurer KWJD-363 b. 1883 in Öhningen, Amt Konstanz, Deutschland. She died in Öhningen, Amt Konstanz, Deutschland in 1946. 

His father is reported as Johann Diener KZ5G-9CH b. 1858 and has no death information and was also born in Ulmerthal, Buchenberg, Oberallgäu, Schwaben, Bavaria, Germany including spouses and any possible children. His mother is Pauline Diepolder KZYZ-TJY b. 1863 in 

Input Data: I have pasted the vital statistics, timeline, and source lists for these four individuals below. Ulmerthal, Buchenberg, Oberallgäu, Schwaben, Bavaria, Germany

1. Source Analysis: Critique the quality of the sources provided. Are they original or derivative? Do they provide direct evidence of birth/parentage, or only indirect evidence?

2. Data Consistency: Cross-reference the dates and locations. specificially look for:

o Biological impossibility (e.g., mother's age at birth).

o Chronological inconsistencies in location (e.g., being in two states at once).

3. Relationship Logic: Determine if the sources explicitly prove the link between Garrard/Elizabeth and John, or if the link is merely based on assumptions (like similar surnames in the same county).

4. Conclusion: Provide a verdict based on the Genealogical Proof Standard. Classify the relationship as "Proven," "Probable," "Possible," or "Disproven."

Role: Act as a professional genealogist and forensic investigator.

Objective: Evaluate the genealogical proof for the parent-child relationship between Garrard Morgan (L7GZ-YBB) / Elizabeth Milton (22J1-HM4) and their purported son, Doctor John Morgan (GM8Y-L9D) (husband of Mary Woodson GM8B-MS9).

Input Data: I have pasted the vital statistics, timeline, and source lists for these four individuals below.

Instructions:

5. Source Analysis: Critique the quality of the sources provided. Are they original or derivative? Do they provide direct evidence of birth/parentage, or only indirect evidence?

6. Data Consistency: Cross-reference the dates and locations. specificially look for:

o Biological impossibility (e.g., mother's age at birth).

o Chronological inconsistencies in location (e.g., being in two states at once).

7. Relationship Logic: Determine if the sources explicitly prove the link between Garrard/Elizabeth and John, or if the link is merely based on assumptions (like similar surnames in the same county).

8. Conclusion: Provide a verdict based on the Genealogical Proof Standard. Classify the relationship as "Proven," "Probable," "Possible," or "Disproven."

That is all one prompt. The response went on for pages. 

Obviously, you can ask for some things with very simple prompts, for example:

generate an image of a cow

Here is the results of this simple prompt:

The possibilities are endless such as this: 

generate an image of a prize hereford bull in a holding pen at a cattle auction building with bidders in bleachers looking one at an ongoing auction in a ring with a dirt floor. Have all the people wearing traditional us western attire with cowboy hats. Have several additional hold pens with other breeds of cattle. show the auctioneer in the center holding a mic and waving his hand. 

This could have gone on indefinitely but here is the results. By the way, capitalization doesn't seem to matter. 

Now, what do the cows have to do with genealogy? The idea here is that if you think about what you are asking and add details, you will get a more complete and useful answer.  How I really got started with all this was when I wrote a prompt and Google Gemini 3 cam back and told my my prompt was all wrong and asked if I wanted some help drafing prompts. So, you don't need to watch a lot of YouTube videos or buy a book about writing prompts, all you need to do is ask Gemini how to make your prompt better. Ultimately, what I have learned is to just ask. 

An AI Genealogical Source Reliability Scale and Conflict Audit Framework

There is, as yet, no generalized standard that clarifies the levels of trust that can be exercised for validating AI generated information including small organization or individual research. Although, developing a suggested standard would involve an international committee or other effort, I think the following is a good basis for discussion. 

AI Source Reliability Scale and Conflict Audit Framework

Grade 1

Verified Primary

• Human researcher has compared the AI transcription word-for-word against the original image. Zero discrepancies found.
• Word-for-word human audit (comparing AI transcription against original image).
• Zero (Human verified)

Meets the Genealogical Proof Standard (GPS) for accuracy; preferred for final evidence.

Grade 2
High-Confidence AI

• AI confidence score >95%. Document is a clear, printed text (e.g., modern book). Facts align with known historical timelines.
• Verification of metadata and spot-checking alignment with historical timelines.
• Low (High confidence scores and printed format)

High evidential weight but requires citation of AI involvement.

Grade 3
Probable Draft

• AI-transcribed cursive or archaic script. Readable but contains "low-confidence" markers or [?] symbols.
• Full human review required; manual audit if surnames or dates are missed.
• Moderate (Risk of misread archaic script)

Treatment as a draft; requires human collation to meet GPS.

Grade 4
Unverified Lead

• Summary or extraction provided by AI without a direct link to a specific line in the image.
• Finding direct links to specific lines in images; manual disentanglement of FAN (Friends, Acquaintances, Neighbors) club.
• High (Risk of name-merging or date-shifting)

AI suggestions are clues, not evidence; requires manual verification.

Grade 5
Suspected Fiction

• AI-generated "fact" that contradicts established records or lacks a verifiable citation (Hallucination).
• Re-verification of physical files; do not enter data into tree.
• Extreme (Hallucination/Fabrication)

Violates the Genealogical Proof Standard (GPS) requirements for complete and accurate source citations.

In this case, the levels of trust are set out in a descending manner. Genealogical organizations might be relied upon to provide such guidance. I am open to discussion. 

Now on YouTube; An Update of the Now Seventeen Rules of Genealogy

https://youtu.be/mDIGO80_xCM?si=84NLGrTGlJNnKEQr

The recent BYU Library Family History Center webinar "An Update of the Now Seventeen Rules of Genealogy" is not available on YouTube. Here is a summary of the YouTube video. 

This presentation, delivered by James Tanner at the BYU Library Family History Center, provides a vital "reality check" for genealogists. Tanner, drawing on over 43 years of experience and a background in law, outlines 17 fundamental rules designed to act as "guardrails" against the common pitfalls of genealogical research [02:29].

Below is a summary of these rules, categorized by their underlying principles:

The Physical Reality of Life

These rules focus on the biological and logical constraints that must govern your research.

• Rule 1: The Mother was There: A mother cannot give birth in two places at once or after her death. If a record suggests otherwise, the record is wrong [04:13].

• Rule 2: Absence of Evidence is Not Evidence of Absence: The lack of a death record or obituary does not mean a person is still alive. Many deaths simply went unrecorded [05:57].

• Rule 3: Unique Identity: Every person has a unique birth order and biological parents. Differentiate between people with the same name by looking at their "FAN" club—family, associates, and neighbors [07:49].

• Rule 14: You're Not Responsible for Your Ancestors: You are a recorder of history. You will find ancestors who were criminals or slave owners; your job is to observe and record, not to hide the truth [53:25].

The Nature of Historical Records

Understanding how records were created and where they are kept is half the battle.

• Rule 4: There are Always More Records: Most researchers stop at birth, marriage, death, and census records. Tanner emphasizes that land, tax, court, and church records often hold the answers [10:06].

• Rule 6: Records Migrate: Records rarely stay where the event happened. They move to county seats, state archives, or digital servers. Boundary changes (like those in Pennsylvania) often mean your ancestor’s records "moved" even if they never did [14:26].

• Rule 17: Where Life Happened, Records Remained: If people lived in an area, they left a trail. To find it, you must identify who had the authority to record events at that specific time and place [18:24].

• Rule 16: Gravity Always Wins: Physical deterioration from fire, flood, mold, and pests is a reality. Some records are simply lost forever [54:05].

The Logic of Genealogical Information

• Rule 7: Information Flows Downhill (Entropy): It is significantly easier to trace descendants forward in time than to trace ancestors backward. Records become scarcer and more fragile the further back you go [20:50].

• Rule 8: Everything is Connected: Unexpected sources, like cattle brands or property marks, can provide proof of identity or inheritance because they were legal assets [25:44].

• Rule 9: Patterns Everywhere: Use naming patterns (e.g., naming the eldest son after the paternal grandfather) and migration patterns to predict where an ancestor might have gone [28:10].

• Rule 10: Read the Fine Print: Don't just look for names. Witnesses on deeds and marginal notes in church registers often hold the key to a "brick wall" [34:38].

Verification and Truth

• Rule 11: Match is Not Identity: Just because a name, date, and place match your expectation doesn't mean it's your ancestor. Coincidences are frequent in history [37:32].

• Rule 15: It's Not a Fact Without a Record: Do not trust unsourced online trees or compiled books. Without a contemporaneous record, a lineage is just a theory [41:17].

• Rule 12: The End is Always There: Every lineage eventually ends where records cease to exist. Tanner warns against fabricating lines back to Adam or ancient royalty [46:02].

• Rule 13: Don't Just Fill Blank Spaces: Genealogists are "collectors" by nature, but you should never add a name just to complete a fan chart or pedigree [49:29].

Conclusion:

Tanner concludes that while technology like DNA and AI has changed the field, these core principles remain the same [55:47]. He recommends resources like his blog, Genealogy Star, and The Family History Guide for further study.

Video Link: https://youtu.be/mDIGO80_xCM