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AI Consultant & Systems Orchestrator, Exit 96 Productions
By Clif Dunn · AI Literacy & Workforce Skills · ~5 min read
If you grew up using a rotary dial phone, you already know one important thing about technology:
Eventually, the weird new thing becomes the thing everybody uses.
Push-button phones seemed fancy.
Answering machines seemed rude.
Email seemed optional.
Smartphones seemed like something NASA misplaced at the mall.
Now we carry tiny supercomputers in our pockets and use them mostly to check the weather, avoid phone calls and look up whether an actor is still alive.
Artificial intelligence feels like the next big leap, because it is.
But here is the good news:
You do not need to become a coder, a data scientist or a 27-year-old hoodie enthusiast to use AI well.
You need to understand what it is, what it is good at, where it gets into trouble and how to use it without handing it the keys to your life.
AARP's annual tech surveys show a clear trend:
Awareness is even higher:
90% of adults over 50 have now heard of generative AI, though many remain cautious about privacy, scams, ease of use and cost.
In other words, plenty of us are curious.
We just do not want to be played for suckers.
Fair enough.
So let's start with the five things you actually need to know.
AI can seem almost human because it writes in complete sentences, answers questions and occasionally sounds like it has read every book in the library plus the owner's manual for your dishwasher.
But AI is not "thinking" the way you and I think.
It is predicting.
Tools like ChatGPT, Claude, Gemini and Microsoft Copilot are trained on enormous amounts of text, code, images and data.
When you ask a question, the tool predicts what kind of answer is most likely to be useful based on patterns it has learned.
That makes it powerful.
It also makes it imperfect.
AI can:
It can also make things up, miss context or sound confident while being wrong.
Anyone who has ever worked with a very bright intern will recognize the pattern.
Think of AI as the world's fastest research assistant.
It can do a lot in seconds.
But you still need to review the work before sending it to your boss, your doctor, your lawyer or your spouse during a disagreement about who said what in 1998.
AI is the world's fastest research assistant. But you still need to review the work.
People like to use the word "prompting," which sounds technical.
It is not.
A prompt is just the instruction you give the AI.
The better the instruction, the better the answer.
This is actually good news for people over 50, because prompting is basically good management.
If you have ever trained an employee, raised a teenager, briefed a contractor or explained to a cable company that no, you do not want a different package, you already understand the basics.
A weak prompt sounds like this:
"Write something about AI."
A better prompt sounds like this:
"Write a 500-word beginner-friendly explanation of AI for adults over 50. Use plain English, a friendly tone and practical examples. Avoid jargon. Include three ways someone could use AI this week."
That second version gives the tool context, audience, tone, format and purpose.
AI loves that.
You can also ask it to improve its own work.
Try phrases like:
The goal is not to ask one perfect question.
The goal is to have a conversation.
You ask.
It answers.
You redirect.
It improves.
You say, "That's close, but make it less corporate and more human."
It tries again.
Which, come to think of it, is already better than most voicemail systems.
Prompting is basically good management. You've been doing this for decades.
One of the biggest fears around AI is that it will replace people.
In some jobs, AI will absolutely change how work gets done.
But for many experienced professionals, the better frame is this:
AI can help you do more of what you are already good at.
AI is especially useful for the kind of work that clogs up the day.
It can:
Research from the Urban Institute points to digital and AI literacy as increasingly important for older workers while also noting that durable human skills like critical thinking, judgment and communication are where experienced professionals hold a real edge.
AI can generate options.
You know which options are nonsense.
AI can draft the email.
You know whether the tone will land.
AI can analyze a spreadsheet.
You know which numbers matter.
AI can suggest a strategy.
You know whether it will survive contact with real customers, real employees and real budgets.
Not man versus machine. Human plus machine — with the human still deciding where to point the thing.
This one matters.
Scams are getting more convincing.
Fake emails look more polished.
Fake texts sound more official.
Voice cloning and deepfake videos are becoming more realistic.
The old warning signs — bad spelling, weird grammar — are no longer enough.
Apparently, even criminals have upgraded their software.
AI can help by acting as a second pair of eyes.
OpenAI and AARP have partnered on training specifically designed to help older adults use ChatGPT to identify possible scams, flagging warning signs like urgent language, requests for secrecy and suspicious links.
For example, you can copy the text of a suspicious email, remove any personal information and ask:
That can be extremely helpful.
But do not let AI make the final decision when money, identity or safety are involved.
Never paste your Social Security number, bank login, passwords, medical records or private client information into an AI tool unless you fully understand the privacy settings.
Never click a link just because an AI tool says the message "seems legitimate."
And if someone says you must act right now, keep it secret and pay with gift cards — that is not an emergency.
That is a scam wearing a cheap mustache.
Pause. Verify. Call the company directly.
Ask AI to help you think it through — but don't outsource your judgment.
AI is useful.
It is not magic.
It can be wrong.
It can be outdated.
It can misunderstand what you meant.
It can invent sources, garble facts or give advice that sounds reasonable until you realize it came from a machine with no life experience, no professional license and no fear of consequences.
So use a simple rule: the more important the decision, the more verification you need.
Asking AI to help write a birthday toast?
Fine.
Asking AI to explain the difference between two Medicare terms?
Useful.
Asking AI whether you should change medication, sign a contract or move your retirement savings?
Stop right there and bring in a qualified human.
You should also be thoughtful about privacy.
Do not treat AI like a diary, lawyer, doctor and banker all rolled into one.
Before you paste sensitive information into any tool, ask yourself:
That does not mean you should be afraid of AI.
It means you should use it like an adult — which is convenient, because you are one.
You do not have to master AI in one weekend.
Start with one useful task.
Then try another task tomorrow.
You learned rotary phones, answering machines, ATMs, email, smartphones, streaming services and at least one television remote that appeared to have been designed by a defense contractor.
You can learn AI too.
This time, the machine talks back. But at least you don't have to untangle the cord.
Clif Dunn runs a practical, no-jargon AI training program built specifically for professionals navigating this shift later in their careers — not a 27-year-old who can't remember a world without Wi-Fi.

[1] Ball, V.E., Schimmelpfennig, D., & Wang, S.L. (2022). The Drivers of U.S. Agricultural Productivity Growth. Federal Reserve Bank of Kansas City. Consumer-to-farmer ratio data: 13:1 in 1900, 159:1 in 2017.
[2] U.S. Bureau of Labor Statistics. Nonfarm Business Sector: Real Output Per Hour of All Persons (OPHNFB). Federal Reserve Bank of St. Louis (FRED). fred.stlouisfed.org/series/OPHNFB
[3] Dell’Acqua, F., McFowland, E., Mollick, E.R., et al. (2023). Navigating the Jagged Technological Frontier: Field Experimental Evidence of the Effects of AI on Knowledge Worker Productivity and Quality. Harvard Business School Working Paper 24-013.
[4] Brynjolfsson, E., Li, D., & Raymond, L.R. (2023). Generative AI at Work. NBER Working Paper 31161. nber.org/papers/w31161
[5] GitHub Research. (2023). Research: Quantifying GitHub Copilot’s Impact on Developer Productivity and Happiness. github.blog
[6] Hao, Q., Xu, F., Li, Y., & Evans, J. (2026). Artificial intelligence tools expand scientists’ impact but contract science’s focus. Nature, 649, 1237–1243. nature.com/articles/s41586-025-09922-y