#occupy25 — Public Fediverse posts
Live and recent posts from across the Fediverse tagged #occupy25, aggregated by home.social.
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Fear and Loathing of AI (Part IV): Automation Doesn’t Kill Jobs — It Cheapens People
By Cliff Potts, CSO, and Editor-in-Chief of WPS News
The popular story about automation is that it destroys jobs.
That story is comforting, because it suggests a clean line: a job exists, a machine replaces it, the job disappears. Tragic, but understandable.
What actually happens is worse.
Automation rarely eliminates work outright.
It cheapens the people who do it.The quiet downgrade
Most jobs don’t vanish overnight. They are degraded.
Pay drops.
Expectations rise.
Staffing thins.
Monitoring increases.Workers are told they should be grateful, because “AI makes you more productive now.”
Productivity, however, is not shared.
It is captured.The job remains, but dignity erodes.
From skilled labor to managed output
Before automation, skill carried bargaining power.
After automation, skill becomes assumed.AI-assisted work quickly shifts from:
- expertise → throughput
- judgment → compliance
- craft → metrics
Once the machine is involved, human contribution is reframed as a cost center rather than a value source.
The worker doesn’t disappear.
The status of the worker does.The speed-up without the pay
Historically, when tools made work faster, workers fought for:
- shorter hours,
- higher wages,
- better conditions.
AI flips that script.
Now speed gains are treated as justification for:
- heavier workloads,
- constant availability,
- reduced compensation per unit of work.
You are not paid more for producing more.
You are expected to produce more for the same or less.This is not innovation failure.
It is policy choice.Surveillance masquerading as assistance
AI is often introduced as a “helper.”
In practice, it becomes a manager.It tracks:
- keystrokes,
- output rates,
- response times,
- behavioral patterns.
What begins as assistance quietly becomes supervision.
Automation does not just change what you do.
It changes how closely you are watched while doing it.The moral inversion
When work becomes cheaper, people are treated as more replaceable.
That inversion is always justified with the same language:
- efficiency,
- competitiveness,
- inevitability.
But none of those are natural laws.
They are decisions made by those who benefit.Automation does not have ethics.
Institutions deploying it do.The real danger
The greatest risk of AI-driven automation is not mass unemployment.
It is a world where:
- work still consumes most of your life,
- pay no longer reflects effort,
- and dignity is treated as a luxury benefit.
A world where jobs exist, but people inside them are hollowed out.
A line worth drawing
AI can reduce drudgery.
It can assist judgment.
It can remove unnecessary friction.But if productivity gains are not paired with:
- stronger labor protections,
- shared gains,
- and limits on surveillance,
automation becomes exploitation with better branding.
Automation doesn’t kill jobs.
It kills leverage.
And without leverage, workers don’t disappear.
They endure.
For more social commentary, please see Occupy 2.5 at https://Occupy25.com
#ArtificialIntelligence #automation #economicInequality #futureOfWork #Labor #Occupy25 #platformCapitalism #productivity #technologyCritique #workerRights #workplaceSurveillance #WPSNews -
Fear and Loathing of AI (Part III): “Learn AI” Is the New “Learn to Code”
By Cliff Potts, CSO, and Editor-in-Chief of WPS News
There is a sentence that shows up in every technological cycle right before the disappointment phase begins.
“Just learn the skill.”
It sounds empowering. It sounds reasonable. It sounds like personal agency.
It is also a lie we have been telling people for decades.
The obedience script
“Learn to code” was never about opportunity.
It was about discipline.It trained people to accept that:
- structural failures are personal problems,
- economic insecurity is an individual moral test,
- and survival depends on constant retraining at your own expense.
When the promised jobs didn’t materialize—or paid far less than advertised—the story shifted seamlessly: you didn’t learn the right language, the right framework, the right stack.
Now the phrase has been updated.
“Learn AI.”
Same script. Same pressure. Same outcome.
Skills don’t collapse — markets do
Coding did not fail because people were lazy or incapable. It failed because markets flooded, tools commoditized, and labor lost leverage.
AI will follow the same arc, only faster.
The moment a skill becomes:
- widely accessible,
- easily automated,
- and expected rather than rewarded,
it stops being a path to security and becomes a baseline requirement for staying afloat.
The reward for compliance is not prosperity.
It is continued participation.Training as cost transfer
Here is what “learn AI” really means in practice:
- You pay for the courses.
- You absorb the time cost.
- You shoulder the career risk.
- You adapt repeatedly as tools change.
- You accept lower pay because “AI makes you more efficient.”
None of that is accidental.
It is a system designed to push costs downward while extracting value upward.
The more often you are told to retrain, the clearer it becomes that training itself is the product.
The illusion of agency
People are encouraged to believe that mastery equals control.
But control does not come from skill alone.
It comes from:- ownership,
- bargaining power,
- regulation,
- and collective leverage.
Without those, skill is just labor dressed up as self-improvement.
Learning AI may help you keep your job a little longer.
It will not protect you from the logic of the system deploying it.What learning actually means now
This does not mean you should refuse to learn.
It means you should learn without illusions.
Learn AI the way you learn any tool:
- to reduce friction,
- to save time,
- to extend what you already do.
Do not learn it expecting salvation.
Do not learn it expecting loyalty from platforms.
Do not learn it expecting the market to reward you for effort.Markets reward leverage, not diligence.
The quiet truth
The most dangerous part of “learn AI” is not that it is false.
It is that it is incomplete.
It tells people how to adapt, but never who benefits.
It demands flexibility, but never offers stability.
It promises relevance, but never guarantees dignity.We have seen this cycle before.
And it did not end with freedom.
It ended with exhaustion.
For more social commentary, please see Occupy 2.5 at https://Occupy25.com
#AISkills #ArtificialIntelligence #economicPrecarity #futureOfWork #laborEconomics #learnToCode #Occupy25 #platformCapitalism #technologyHype #workforceRetraining #WPSNews