Showing posts with label AI. Show all posts
Showing posts with label AI. Show all posts

Monday, September 14, 2026

AI, Robots, Jobs and Poverty: Who Will Benefit from the AI Revolution?

 

AI, Robots, Jobs, and Poverty: Who Will Benefit?


I've been thinking a lot about artificial intelligence and what it will eventually do to jobs.

Picture of AI, Robots, Jobs and Poverty. Who will benefit?
Not just next year. I'm thinking ten, twenty, fifty, even a hundred years from now.

I've spent much of my life around technology, and I've seen technology eliminate jobs before. Computers eliminated jobs. Automation eliminated jobs. The Internet destroyed entire businesses.

But they also created new ones.

That's why some people say we shouldn't worry about AI. Workers have always adapted to new technology.

They're right.

But I'm not buying it.

This Time May Be Different

Past technology usually replaced a particular human ability.

A tractor replaced muscle.

A calculator replaced arithmetic.

A word processor replaced a typewriter.

Industrial robots replaced repetitive movements on assembly lines.

AI is different because it is beginning to automate something much broader:

Thinking.

AI can already write, analyze information, translate languages, create computer code, recognize images, answer questions, and solve problems.

Now give AI a body.

I think of AI and robotics somewhat like a computer.

AI is like the operating system and software.

Robotics is like the physical computer.

The comparison isn't technically exact, but the idea is simple.

AI provides the intelligence. Robotics is the hardware.

Combine them and you have something much more powerful.

AI alone can't crawl under someone's house and repair a leaking pipe.

An AI-controlled robot certainly will be able to.

The same principle can be applied to mechanics, electricians, construction workers, farmers, warehouse workers, truck drivers, factory workers, cooks, cleaners, and countless other jobs.

Physical jobs may take longer to automate because the real world is messy and unpredictable.

But longer doesn't mean forever.

AI Doesn't Have to Take Every Job

Here's something else that's easy to miss.

AI doesn't have to completely eliminate an occupation to create massive unemployment.

Suppose a company currently needs ten accountants.

AI makes each accountant twice as productive.

The company still needs accountants.

It just doesn't need ten of them.

The same could eventually happen with plumbers, mechanics, engineers, programmers, nurses, construction workers, and hundreds of other occupations.

The important question isn't:

Will my occupation disappear?

It may be:

How many humans will still be needed to do it?

Poor People Have the Most to Lose

This concerns me most when I think about people who are already poor.

It's easy to tell someone to adapt.

Learn AI.

Go back to school.

Change careers.

Get another certification.

That advice sounds reasonable when you have savings, reliable transportation, a good computer, high-speed Internet, and enough money to survive while you learn something new.

It's different when you're living paycheck to paycheck.

When you're poor, the rent doesn't wait while you learn a new job skill.

Neither does the light bill.

And your kids still need to eat.

I grew up poor, and one thing I learned is that poverty isn't simply having less money.

Poverty means having fewer choices when something goes wrong.

That's what worries me about the AI revolution.

The people with the fewest choices may be the first ones expected to adapt.

The Poor Person Has Always Had Something to Sell

Even someone who owns almost nothing has traditionally possessed one economic asset:

His labor.

The factory owner needed workers.

The farmer needed farmhands.

The trucking company needed drivers.

The construction company needed carpenters, electricians, plumbers, equipment operators, and laborers.

The poor person could sell his labor, his own two hands.

That's how millions of people climbed the economic ladder.

Learn something.

Work.

Earn more.

Save.

Buy a house.

Start a business.

Invest.

Build a future for your children.

But what happens if AI and robotics dramatically reduce the value of human labor?

What does someone with no assets have left to sell? His own two hands become worthless, but does his brain?

I think that's one of the most important economic questions of the AI revolution.

Universal Basic Income Is BASIC

One proposed answer is Universal Basic Income or UBI.

Some form of UBI may eventually become necessary if machines perform a large percentage of the work humans currently do.

But let's be clear about what UBI means.

The important word is:

BASIC.

It might provide basic food, basic housing, utilities, transportation, and other necessities.

It might keep people from starving or becoming homeless. So does working three jobs at someplace like McDonalds.  Now before McDonald folks get all pissed off at me for using their name, I'm just using them as a fast food example where most folks start a relatively low paying job but who may need to eventually move on to a better paying job.

That's important.

But it doesn't make a poor person wealthy.

It may not even make him comfortable.

The wealthy person might own the AI companies, robots, factories, data centers, land, and investments.

The poor person gets enough money to survive.

Those are not economically equal lives.

UBI can raise the (floor) basic standard of living. It doesn't eliminate the distance between the floor and the penthouse.

In fact, UBI could create a permanent economic class with enough to survive but very little opportunity to accumulate wealth.

That's not eliminating poverty.

That's making poverty more comfortable.

What About All Those Lower Prices?

Another argument is that AI and robotics will make everything much cheaper.

They certainly could make things cheaper to produce.

That's not the same as making them cheaper to buy.

Suppose AI and robotics reduce the cost of producing something by 99 percent.

Will the corporation reduce its selling price by 99 percent?

I doubt it.

Competition could force prices down a little.

But there's no guarantee.

If something costs a company $100 to produce today and automation eventually reduces that cost to $1, the company doesn't automatically have to pass the entire $99 savings to you.

Businesses generally charge what the market will bear or what folks are willing to spend.  Rich folks are willing to spend a LOT while poor folk do without.

If customers are willing to continue paying $150, why would a corporation voluntarily charge $2?

Maybe competition eventually pushes the price down.

Maybe the company lowers the price a little.

Or maybe a handful of enormous corporations control the AI, robots, factories, patents, and distribution systems and keep much of the savings as profit.

That's where corporate greed and concentrated ownership become part of the discussion.

Cheaper to produce doesn't necessarily mean cheaper for you to buy.

Follow the Money

Now combine that with UBI.

The government gives someone enough money each month for basic necessities.

He spends that money on food, housing, electricity, transportation, communication, and other necessities.

Those industries have become increasingly automated.

So where does the money go?

Back to the companies that own the automated systems.

Those companies earn profits.

Their owners invest those profits in more assets.

Those assets produce more profits.

Meanwhile, the poor person receives another basic payment next month and starts over.

The person survives.

The owner accumulates wealth.

That's why UBI by itself doesn't solve the problem.

Income allows you to buy things. Ownership allows you to build wealth.

Who Gets the Benefits?

AI and robotics could create extraordinary wealth.

They could make society more productive beyond anything we can imagine today.

But increased productivity doesn't automatically mean increased prosperity for everyone.

Imagine a factory that once employed 1,000 people.

Eventually robots and AI allow it to produce twice as much with 50 employees.

That's an incredible improvement in productivity.

But what happened to the other 950 workers?

And if the product doesn't become dramatically cheaper, who received most of the financial benefit?

The owners.

That's why whenever someone tells me AI will make everything cheaper, I want to ask:

Cheaper for whom?

Cheaper to manufacture?

Or cheaper for the person buying it?

And when someone tells me AI will create enormous wealth, I have another question:

Who will own that wealth?

The Safety Net Matters. So Does the Ladder.

I believe society needs a basic standard of living or a safety net.  I don't mean or suggest that folks should just stop working and let the government take care of them. I do believe that people need to contribute to society, work, earn a living.  That's today, but what if jobs were no longer available?  What if you once competed for one job in 10,000 but in the future you're likelyhood of finding a job is 1 in 100?

If machines eventually produce more food than we need, people shouldn't starve because a robot replaced their job.

But the safety net isn't enough.

People also need a ladder to climb out of poverty.

They need some realistic way to improve their lives.

To buy a better home.

Travel.

Save money.

Invest.

Help their children.

Build financial security.

And eventually own something themselves.

If AI reduces the value of human labor, we may have to think beyond UBI.

Maybe that means employee ownership.

Profit sharing.

Citizen investment funds.

Retirement accounts invested in automated industries.

Public investment funds that own portions of highly productive AI infrastructure.

Or perhaps something nobody has invented yet.

I don't pretend to know the answer.

But I think I know the question:

If machines eventually produce much of society's wealth, how do ordinary people get an opportunity to own part of that productive economy rather than simply receiving enough money to survive?

What Can Poor People Do Now?

We can't control what the economy will look like fifty years from now.

But we can prepare for what's happening now.

Don't be afraid of AI.

Learn to use it.

You don't need to understand how AI works any more than you need to understand your car's transmission to drive it.

Use AI to learn.

Ask questions.

Improve your writing.

Learn another skill.

Solve problems.

Understand complicated information.

Look at your own job and ask:

Which parts of what I do could AI or a robot eventually do?

Then ask:

How can I use that same technology to make myself more valuable today?

If you can learn another useful skill, learn it.

If you can save something, save it.

If you can avoid unnecessary debt, avoid it.

And teach your children how to use technology instead of simply consuming it.

None of those things guarantees success.

Life isn't fair.

Opportunity matters.

Education matters.

Hard work matters.

Luck matters.

Persistence matters.

But preparation can improve the odds. But the one thing I can't stress enough is when you do use something like chatGPT or other AI tools, use them responsibly and not as a way to try to scam someone.  You'll just end up in a place where the rent and food is free.  Most just call it JAIL.

And sometimes improving the odds is the best we can do.

The Question We Need to Ask Now

For most of human history, our economic problem has been:

How do we produce enough?

AI and robotics may eventually give us an entirely different problem:

We can produce more than enough. How do ordinary people get their share of the prosperity?

AI could dramatically reduce poverty.

It could also create one of the greatest concentrations of wealth in human history.

Both outcomes are possible.

The technology itself won't decide which one we get.

People will.

The AI revolution shouldn't only be about building smarter machines.

It should also be about making sure the people those machines replace still have an opportunity to build better lives.

Because the safety net matters.

But so does the ladder.

Saturday, July 18, 2026

You Don't Need a Computer Science Degree to Land a High-Paying IT Job

You Don't Need a Computer Science Degree to Land a Great Technology Job

Picture of Home Lab

One of the biggest myths in technology is that you need a four-year computer science degree before anyone will hire you.

You don't.

In fact, many technology job postings include a phrase that most people completely overlook:

Bachelor's Degree OR equivalent experience.

That one word—OR—can change your entire career.

Most People Read It Wrong

When they see "Bachelor's Degree or equivalent experience," many people immediately eliminate themselves.

"I don't have a degree."

"I guess I don't qualify."

But that's not what the employer is saying.

They're saying there are two different ways to demonstrate your value.

The first is a college degree.

The second is proving you already know how to do the work.

Many hiring managers will gladly choose the second.

My Degree Isn't Even in Technology

My college degree isn't related to information technology.

I didn't earn a Computer Science degree.

I didn't major in Information Systems.

Yet even after retiring more than a year ago, recruiters still contact me several times every week—and sometimes several times a day.

My LinkedIn profile clearly states that I'm retired.

So why are companies still asking if I'm interested?

Because employers aren't calling about my diploma.

They're calling about decades of experience solving technical problems.

Experience Beats Theory

Over the years I've worked with technologies that businesses depend on every day.

Network engineering.

Enterprise networking.

Linux.

Network security.

Systems architecture.

Infrastructure design.

Automation and scripting.

Technical leadership.

Management.

These aren't just buzzwords on a résumé.

They're years of solving outages, troubleshooting complex problems, designing reliable systems, and helping organizations keep their businesses running.

Companies pay for results.

Experience demonstrates results.

Why Some People Hear Nothing but Crickets

I hear from people all the time who have submitted hundreds of job applications without receiving a single interview.

Many assume the economy is entirely to blame.

Sometimes it is.

But often there's another reason.

They're competing for jobs where thousands of applicants have nearly identical qualifications.

Meanwhile, there are other positions that employers struggle to fill because too few people possess the necessary skills.

That's the Law of Supply and Demand.

When your skills are common, employers have plenty of choices.

When your skills are rare and valuable, employers start searching for you.

How Do You Get "Equivalent Experience?"

This is where people become discouraged.

They think experience only comes from having a full-time job.

It doesn't.

You can build real-world experience by:

  • Building a home lab using inexpensive or retired computers.

  • Installing Linux and using it every day.

  • Learning networking with Cisco Packet Tracer, GNS3, or real Cisco equipment.

  • Learning PowerShell, Python, or Bash by automating repetitive tasks.

  • Building cloud environments using AWS, Azure, or Google Cloud free tiers.

  • Creating virtual machines and enterprise networks at home.

  • Volunteering to support technology for churches, nonprofits, schools, or small businesses.

  • Earning respected industry certifications.

  • Contributing to open-source projects.

  • Publishing your projects on GitHub so employers can see what you've built.

Every one of those demonstrates initiative.

Every one creates experience you can discuss during an interview.

Technology Rewards Curiosity

One of the things I've always loved about technology is that knowledge is available to anyone willing to learn.

You don't need permission.

You don't need a university classroom.

You need curiosity.

The internet contains more high-quality technical training today than existed during my entire career.

Thousands of hours of instruction are available for little or no cost.

The people who continue learning continue growing.

Don't Chase What's Comfortable

If your current skills aren't producing interviews, don't ask yourself:

"What job would I enjoy?"

Instead ask:

"What skills are employers struggling to find?"

Those are two very different questions.

The fastest way to improve your career isn't always finding a job you already know how to do.

Sometimes it's learning a skill that few other people have.

Your Career Is an Investment

A college degree is valuable.

For many professions, it's absolutely necessary.

But in technology, experience often carries just as much weight—and sometimes more.

Don't let the lack of a specific degree convince you that the door is closed.

It isn't.

Build skills.

Build projects.

Build experience.

The next time you see a job posting that says "Bachelor's Degree or Equivalent Experience," don't automatically disqualify yourself.

The employer may be looking for someone exactly like you.

Just make sure you can prove what you know. Are your skills in demand?

10 Technology Skills Employers Will Still Be Hiring For in 2030

No one can predict the future with certainty, but history has shown that businesses will continue investing in technologies that improve security, reduce costs, automate repetitive work, and increase productivity. If you're looking to build a career that remains valuable for years to come, these are the skills I'd be learning today:

  1. AI Automation – Using artificial intelligence to automate business processes and improve decision-making.
  2. Cybersecurity – Protecting organizations from increasingly sophisticated cyber threats.
  3. Cloud Computing – Designing, deploying, and managing services on platforms like AWS, Microsoft Azure, and Google Cloud.
  4. Linux Administration – The operating system that powers much of the world's servers, cloud infrastructure, and embedded devices.
  5. Scripting and Automation – Learning Python, PowerShell, or Bash to automate repetitive tasks and improve efficiency.
  6. Networking – Understanding how data moves across modern enterprise networks, including routing, switching, wireless, and software-defined networking.
  7. Virtualization – Building and managing virtual servers, desktops, and infrastructure that maximize hardware utilization.
  8. DevOps – Combining software development and IT operations to deliver applications faster, more reliably, and with fewer errors.
  9. Data Engineering – Collecting, organizing, and preparing massive amounts of data so businesses can make informed decisions.
  10. Infrastructure Automation – Using tools like Ansible, Terraform, and Infrastructure as Code (IaC) to deploy and manage technology environments at scale.

Notice something? Not one of these skills requires a specific college degree. They require curiosity, persistence, hands-on practice, and a commitment to continuous learning. The technology will continue to evolve, but one thing won't change: employers will always pay well for people who can solve difficult problems. Become one of those people, and you'll spend far less time searching for opportunities—and far more time deciding which ones to accept.

https://www.steviegdavis.com/2026/10/cheap-houses-paying-it-forward-to-help.html

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