Social AI Could Wipe Out the Working Class | Sen. Bernie Sanders

[Loiosh]

We can barely survive in Antarctica and that is by far vastly more habitable than anywhere else in the solar system. These tech people talking about colonizing Mars and all this other bullshit are smoking crack.

They're selling a fantasy.

 

[Loiosh]

I don't know but 100 years is a looonnnggg time and technology is advancing pretty quick. We don't even know what kind of effects quantum computing can have.

People don't seem to appreciate how fragile humans are and how unforgiving space is outside the magnetosphere.

 

[Mr Holmes]

then I'll try to answer : )
Perspective is usually that the ultra-wealthy need the masses to keep consuming in order to stay rich, but that might not actually be their ultimate objective.Instead, I suggest that some of the most powerful and wealthiest might have a long-term vision where:Money is no longer the real goal , they already have more than enough.The true goal is control and exclusivity ,a world optimized for them, not for mass participation.AI and robotics provide all essential services ,from production to maintenance, without relying on human workers.Population reduction of “unnecessary” humans ,intentionally or passively, through lack of opportunity, resources, or societal collapse.A shift from capitalism to post-capitalist elitism ,wealth becomes irrelevant because they control the means of survival outright.In that scenario, the “consumers keep the system alive” logic breaks down, because the system is redesigned for a small elite who don’t need broad consumption to sustain their way of life.

And what about a let them eat cake situation?

 

[plataoplombo]

People don't seem to appreciate how fragile humans are and how unforgiving space is outside the magnetosphere.

True. Just can't think of anything that would give us something to strive for.

 

[Blayt7hh]

Some hundred years ago, knocker-uppers went door to door to wake up workers.

Then the alarm clock was invented, and that profession disappeared.

Throughout history, new technologies have changed the course, but new professions have arisen.

Yeah it’s a little bit different when it’s one job becoming obsolete to whole sectors facing mass layoffs over a short span of time. We’re talking potentially millions of jobs disappearing in the not too distant future. I think it is coming and 10 years from now the work place is going to look very different.

I think job wages are going to go way down for most people and wealth inequality is going to get dramatically worse.

 

[Loiosh]

True. Just can't think of anything that would give us something to strive for.

Oh, don't get me wrong, I definitely think it's something we absolutely have to do.

I just think it's going to take a long time.

 

[Possum Jenkins]

I don't see this happening in the next century.

Too lazy to look this up but I saw a video from legit scientists breaking down how colonizing Mars is VERY hard.

The list of obstacles to overcome is stupid long. Just getting there is one thing but having a permanent base there with people permanently living there isn't happening until like 2300 and beyond.

 

[TeTe]

It’s definitely concerning. And it’s not about “blanket” AI taking jobs. But instead what used to take 1 senior person and 4 newer hires, can now be done by that 1 knowledgeable senior person with AI assisting them.

So then the new hires don’t gain the experience to become proficient enough at that profession and move up and keep the ladder/pyramid going.

Wonder when it's actually coming cause there's some gaslighting going on now

New Yale Study Finds AI Has Had Essentially Zero Impact on Jobs https://futurism.com/artificial-intelligence/yale-study-ai-job-impact

 

[jimjamjammer]

Wonder when it's actually coming cause there's some gaslighting going on now

New Yale Study Finds AI Has Had Essentially Zero Impact on Jobs https://futurism.com/artificial-intelligence/yale-study-ai-job-impact

Won't be too long. All the major financial institutions are working on AI to replace a large number of jobs. Of course they will never say the job losses are due to AI. My wife worked on the initial AI project for her company (Big Bank). The end goal for it is to replace jobs for these companies.

 

[Bwagster]

The left is full of poverty pimps. They’ll be the ones using AI for their financial gain.

 

[TeTe]

Won't be too long. All the major financial institutions are working on AI to replace a large number of jobs. Of course they will never say the job losses are due to AI. My wife worked on the initial AI project for her company (Big Bank). The end goal for it is to replace jobs for these companies.

Well right now they're absolutely saying it's AI. Seems like putting the cart before the horse.

Again, automation is nothing new, but using "AI" as a buzzword is.

 

[HockeyBjj]

Wonder when it's actually coming cause there's some gaslighting going on now

New Yale Study Finds AI Has Had Essentially Zero Impact on Jobs https://futurism.com/artificial-intelligence/yale-study-ai-job-impact

At the moment I think it's industry specifc. And not workers being fired because they've been replaced by AI (yet) it's a hiring slow or freeze as they get the low level productivity from AI rather than new hires now.

And obviously there's jobs being created by the AI boom (holy shit the number of electricians we had working to build a data center) that are currently offsetting the hring freezes. So some industries are getting squeezed and others doing well for a net even at the moment. But I think there's valid concerns of when will the tipping point come.

 

[Loiosh]

Too lazy to look this up but I saw a video from legit scientists breaking down how colonizing Mars is VERY hard.

The list of obstacles to overcome is stupid long. Just getting there is one thing but having a permanent base there with people permanently living there isn't happening until like 2300 and beyond.

Yeah, I've seen lots of people talk about this.

When Elon talks about Mars, he knows he's talking to idiot children who will never look to scientists to verify his claims.

Human beings evolved in a very narrow set of climate conditions.

 

[lowlife]

Cant wait for techno feudalism

It's absolutely coming imo. I don't think it necessarily has to, we can pull ourselves out of this and re-imagine what society/civilization can look like, but I don't hold out much hope. What's crazy to me is how much science fiction has "predicted" in my lifetime, I guess human nature is mostly unchanged so it's not hard to see what path we'll take with emerging technology, as we have proven time and time again.

 

[Beechwood]

The Vermont Senator isn't saying anything new. I think though he is spreading fear.

AI is another disruptive technology that is going to take away some jobs and also will create new ones. How big the change will be is not known.

Economic change due to new technology isn't anything new. And romanticizing past work is something some tend to do also. Famously at one time 90% of the country worked on farms. today about 2% work on farms. That big change came about due to new technology. Most are happy that they do not work on a farm. It is tough boring isolating work that pays little. Some though sing the praises of our past ancestors that worked on farms, believing that was an ideal life.

I suspect similar will happen with AI. AI will make most Americans life easier and better I believe.

 

[Why did you]

Wonder when it's actually coming cause there's some gaslighting going on now

New Yale Study Finds AI Has Had Essentially Zero Impact on Jobs https://futurism.com/artificial-intelligence/yale-study-ai-job-impact

intersting , but when you look into it : ) , at the end of that article, they even have a link for another one,
More on AI and jobs: AI Is Making It Nearly Impossible to Find a Well-Paying Job. Is This the World We Want?

my 2$

Yale’s takeaway (high level)
- aggregate occupational shares and broad labor statistics do not show a glaring, economy-wide disruption since ChatGPT’s release , “no discernible disruption yet.” The Budget Lab at Yale


What more granular evidence shows
- job postings for tech/entry roles are down, layoffs in tech/IT are large and ongoing, entry-level/young workers in AI-exposed occupations show meaningful declines, and employers are increasingly demanding AI skills , all consistent with early displacement and re-shaping of demand. Dice+3Indeed Hiring Lab+3TechCrunch+3

Where Yale’s method is strong and where it’s blind​

-Uses robust, well-known aggregate data (occupational shares, labor force statistics) that are reliable for long-run structural changes. The Budget Lab at Yale

Key blind spots / limitations (that matter)

1. Lagging and aggregated data: occupational shares and monthly unemployment figures are slow and smooth over micro churn (hires, attrition, entry-level squeezes). Early displacement often appears first in postings, layoff announcements, and hiring practices , not immediately in aggregate employment totals. The Budget Lab at Yale+1
2. No job-posting / vacancy analysis: changes in demand (fewer job ads for certain roles) are early leading indicators but are not used centrally in Yale’s analysis. Job-ad declines are already observable in several markets. The Guardian+1
3. No direct layoff attribution or firm-level AI adoption linking: Yale cannot say whether recent layoffs are caused by AI vs. macro pressures; firm-level disclosures and layoff trackers (and management statements) do point to restructuring often tied to automation strategies. TechCrunch+1
4. No wage/quality-of-job signals: wage compression, reduced entry-level opportunities, or fewer high-pay openings are early signs of “hollowing out” but aren’t captured by headline employment counts. The UK work tracking shows fewer graduate/entry openings. The Guardian
5. Limited task-level resolution: Yale aggregates by occupation; the most consequential shifts occur at the task level within occupations (some tasks automated while others persist). New task-based indices show better early predictive power. arXiv

---

Concrete empirical items Yale missed (or treated weakly)​

1. Job postings fall in AI-vulnerable roles. Several sources show postings for tech/entry roles and high-exposure occupations declining since late-2022 , an early sign of reduced demand. Indeed Hiring Lab+1
2. Sustained tech/IT layoffs and restructuring. Large aggregated layoff tallies (2024 and continuing in 2025) disproportionately hit tech/IT; managements frequently cite “efficiency”/automation as reasons. Layoff trackers and TechCrunch lists document the scale. TechCrunch+1
3. Young / entry-level workers are being hit first. High-frequency payroll and administrative datasets show relative employment declines for ages ~22–25 in highly AI-exposed occupations. That’s a strong micro-signal Yale’s occupational shares can smooth away. Stanford Digital Economy Lab
4. AI skills are shifting hiring requirements. A rising share of tech job postings now list AI skills as required or preferred ,meaning competition and job-match requirements are changing rapidly. Dice
5. Task-based exposure indices predict job-posting declines. New task-based GAISI measures correlate with declines in postings and price premia , they suggest displacement may already outweigh productivity gains in some cohorts/roles. arXiv

​

How the data is skewed and what that does to Yale’s conclusion​

• Survivorship and smoothing bias: aggregate employment hides worker churn (firms replacing junior hires with fewer senior staff, contractors, or AI). Yale’s “no big change” claim is true for headline totals but misses composition changes. The Budget Lab at Yale
• Labeling bias: firms seldom say “AI caused this layoff.” They use euphemisms (“restructuring,” “streamlining”) which dilutes causal attribution in aggregate studies. Layoff trackers + reporting picks up the pattern even if official filings don’t label it “AI.” TechCrunch+1
• Measurement bias toward incumbents: datasets measuring current employment undercount those who never enter a job because entry roles vanished ,which harms young workers disproportionately. Yale’s approach underweights this missing cohort. Stanford Digital Eco

 

[nhbbear]

What has brought you to think that? What jobs will AI not be able to do better than humans in 5, 10, 20 years?

I've been using AI for computer programming, and it's already capable of taking at least 50% of the jobs out there (one programmer with the help of AI can do the work of 2), and I forsee it taking 90% of the jobs in that sector within 5 years. Adoption is the only major hurdle.

Truck driving will be next, 99% of those jobs will be gone in 10 years. Than all white color, non physical jobs... they'll be extinct in 15-20 years.

Robotics is behind, but it will catch up... once it does. Humans will be curiosities, not useful in the private sector at all. Professional sports and other human vs. human competition for entertainment will be about the only thing that won't be affected.

I can tell you one for sure-police work.

 

[BudKing8806]

intersting , but when you look into it : ) , at the end of that article, they even have a link for another one,
More on AI and jobs: AI Is Making It Nearly Impossible to Find a Well-Paying Job. Is This the World We Want?

my 2$

Yale’s takeaway (high level)
- aggregate occupational shares and broad labor statistics do not show a glaring, economy-wide disruption since ChatGPT’s release , “no discernible disruption yet.” The Budget Lab at Yale


What more granular evidence shows
- job postings for tech/entry roles are down, layoffs in tech/IT are large and ongoing, entry-level/young workers in AI-exposed occupations show meaningful declines, and employers are increasingly demanding AI skills , all consistent with early displacement and re-shaping of demand. Dice+3Indeed Hiring Lab+3TechCrunch+3

Where Yale’s method is strong and where it’s blind​

-Uses robust, well-known aggregate data (occupational shares, labor force statistics) that are reliable for long-run structural changes. The Budget Lab at Yale

Key blind spots / limitations (that matter)

1. Lagging and aggregated data: occupational shares and monthly unemployment figures are slow and smooth over micro churn (hires, attrition, entry-level squeezes). Early displacement often appears first in postings, layoff announcements, and hiring practices , not immediately in aggregate employment totals. The Budget Lab at Yale+1
2. No job-posting / vacancy analysis: changes in demand (fewer job ads for certain roles) are early leading indicators but are not used centrally in Yale’s analysis. Job-ad declines are already observable in several markets. The Guardian+1
3. No direct layoff attribution or firm-level AI adoption linking: Yale cannot say whether recent layoffs are caused by AI vs. macro pressures; firm-level disclosures and layoff trackers (and management statements) do point to restructuring often tied to automation strategies. TechCrunch+1
4. No wage/quality-of-job signals: wage compression, reduced entry-level opportunities, or fewer high-pay openings are early signs of “hollowing out” but aren’t captured by headline employment counts. The UK work tracking shows fewer graduate/entry openings. The Guardian
5. Limited task-level resolution: Yale aggregates by occupation; the most consequential shifts occur at the task level within occupations (some tasks automated while others persist). New task-based indices show better early predictive power. arXiv

---

Concrete empirical items Yale missed (or treated weakly)​

1. Job postings fall in AI-vulnerable roles. Several sources show postings for tech/entry roles and high-exposure occupations declining since late-2022 , an early sign of reduced demand. Indeed Hiring Lab+1
2. Sustained tech/IT layoffs and restructuring. Large aggregated layoff tallies (2024 and continuing in 2025) disproportionately hit tech/IT; managements frequently cite “efficiency”/automation as reasons. Layoff trackers and TechCrunch lists document the scale. TechCrunch+1
3. Young / entry-level workers are being hit first. High-frequency payroll and administrative datasets show relative employment declines for ages ~22–25 in highly AI-exposed occupations. That’s a strong micro-signal Yale’s occupational shares can smooth away. Stanford Digital Economy Lab
4. AI skills are shifting hiring requirements. A rising share of tech job postings now list AI skills as required or preferred ,meaning competition and job-match requirements are changing rapidly. Dice
5. Task-based exposure indices predict job-posting declines. New task-based GAISI measures correlate with declines in postings and price premia , they suggest displacement may already outweigh productivity gains in some cohorts/roles. arXiv

​

How the data is skewed and what that does to Yale’s conclusion​

• Survivorship and smoothing bias: aggregate employment hides worker churn (firms replacing junior hires with fewer senior staff, contractors, or AI). Yale’s “no big change” claim is true for headline totals but misses composition changes. The Budget Lab at Yale
• Labeling bias: firms seldom say “AI caused this layoff.” They use euphemisms (“restructuring,” “streamlining”) which dilutes causal attribution in aggregate studies. Layoff trackers + reporting picks up the pattern even if official filings don’t label it “AI.” TechCrunch+1
• Measurement bias toward incumbents: datasets measuring current employment undercount those who never enter a job because entry roles vanished ,which harms young workers disproportionately. Yale’s approach underweights this missing cohort. Stanford Digital Eco

Did ai generate this for you, lol?

 

[Why did you]

Did ai generate this for you, lol?

with my help, AI was able to generate some of the findings : )

 

[BudKing8806]

with my help, AI was able to generate some of the findings : )

Damn, ai already replacing sherdoggers lol.