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Ethan Choi argues AI will cause a short-term 3-4 year crunch for entry-level…

Brief

Ethan Choi’s essay tackles growing anxiety among students and parents about whether AI will erase the traditional entry-level ladder for college graduates. His conclusion is cautiously optimistic: he expects a meaningful dislocation over the next 3-4 years as AI absorbs some junior white-collar work, but not permanent mass unemployment. He grounds that view in a mix of labor-market indicators and historical comparison, arguing that leading indicators such as JOLTS job openings and job-loss counts have weakened across many sectors, yet the pattern still looks partly like a normalization from the zero-interest-rate hiring boom rather than an unmistakable AI shock. He notes that February 2026 unemployment was 4.4%, below the long-run U.S. average of 6.6%, while recent college-grad unemployment has ticked up to 5.3%.

Choi’s main framework is that AI risk is highest for workers doing simple digital knowledge tasks and lowest for people who combine technical depth with systems-level thinking, leadership, and empathy. He argues that white-collar screen work is vulnerable now, while blue-collar work is temporarily safer until robotics catches up over a possible 5-8 year horizon. He still strongly favors studying computer science, because architecture, infrastructure, and model-level understanding should matter more as coding tools proliferate. On education, he argues universities have moved too slowly despite surging tuition costs and stagnant wage premiums. He wants colleges to assume students will use AI, require AI fluency, replace static assessment with project-based work, and measure success more by entrepreneurial output than by conventional placement pipelines.

Why it matters

Ethan Choi argues AI will cause a short-term 3-4 year crunch for entry-level white-collar work, citing warnings from Anthropic CEO Dario Amodei that 50% of entry-level jobs could be wiped out and ServiceNow CEO Bill McDermott’s warning of 30% unemployment for new college graduates.

Key details

  • The post says broad labor data does not yet show a clear AI-driven collapse: February 2026 U.S. unemployment was 4.4%, still below the roughly 6.6% century-long average, while recent college graduate unemployment had risen to 5.3%, which Choi sees as concerning but still near historical non-recession ranges.
  • Using JOLTS and job-loss data, Choi argues hiring demand has declined across most industries, but much of that may reflect post-ZIRP normalization rather than pure AI substitution; he notes 92,000 job losses in February 2026 and says October 2025 was worse, though attribution to AI remains unclear.
  • Choi identifies digital screen-based knowledge work as the most exposed category, referencing Anthropic labor-market research and Andrej Karpathy’s AI exposure map; he says software development now looks less defensible because tools like Codex and Claude Code push the marginal cost of coding toward zero.
  • Despite that risk, Choi still recommends computer science, arguing that understanding the full application stack, infrastructure, model foundations, and software architecture will remain valuable even as coding is democratized; he also points to data suggesting software-developer job postings have increased in the AI boom.
  • Choi says universities are adapting too slowly and singles out Ohio State, Arizona State, UC Berkeley, and Michigan as more aggressive than Ivy League schools in integrating AI; he recommends requiring AI use in coursework, mandating at least one CS or AI class for all students, and shifting from static tests to longer applied, multidisciplinary projects.
Cleaned source text

title: @EthanChoi7: I'm getting this question constantly from anxious college students / grads and t...

author: EthanChoi7

content_type: twitter_article

published: 2026-03-01T20:10:16+00:00

source_url: https://x.com/EthanChoi7/status/2033360169158238435

word_count: 3956

I'm getting this question constantly from anxious college students / grads and their parents these d

I'm getting this question constantly from anxious college students / grads and their parents these days. As a father of 3 kids myself, I am also filled with anxiety regarding whether my kids will make themselves permanent guests in our guest house forever. 😅

I posted this tweet a couple of weeks ago and it seemed to hit a nerve, given a CS degree from Stanford was seemingly the most secure degree you could obtain!

Of course there might be a little bit of provocative sensationalism in some claims but we have received repeated warnings from prominent leaders that there will be a drastic reduction in entry-level jobs.

@DarioAmodei warned that 50% of entry-level jobs would be wiped out .

@sama hasn't cited a specific % but he has warned that entire categories of jobs will be wiped out .

ServiceNow CEO, Bill McDermott, warned AI could result in 30% unemployment for new college grads.

Almost daily, we are seeing leading companies like @amazon , Baker McKenzie, @blocks , @Meta , and others announce significant layoffs. Sam did warn that some of this might be "AI-washing" but nevertheless, we all know that there is much AI-induced turbulence to come.

Source: http://jobloss.ai

So, in the face of the reduction of these "training" roles, how does a college grad accumulate judgment, domain intuition, and professional taste?

How are we as a society going to train up the next generation of leaders if we don't provide "on-the-job" training?

How should companies and universities evolve in this AI-era in terms of training the next generation?

I definitely don't have all the answers but in case you don't have the time or your ADHD doesn't let you get all the way through this article, what's my conclusion regarding whether college grads are toast and whether they will be completely replaced by AI and robots?

CONCLUSION: While my post above was quite negative, after some work and more contemplation, I'm not a doomer long-term and I'm mostly optimistic that like in job disruptions in the past, humans will adapt and our college grads are smart enough to harness AI to their benefit!

With that said, I do think there will be a short-term crunch in the next 3-4 years where AI subsumes a subset of entry-level white collar jobs and college-grad unemployment will rise temporarily.

However, after this period of dislocation, I expect longer-term job growth due to college grads adjusting to deliver results of more tenured employees and also due to more entrepreneurship in general as expertise and the ability to build is democratized.

I believe we're moving to a world where AI-to-human instruction vs. human-to-human instruction becomes predominant and U.S. colleges should re-constitute themselves to become leaner, potentially replace GEs and drive students to become domain focused much sooner (closer to European / British model), and evolve to having students apply AI via longer duration project-based instruction on real-world problems.

Ultimately, to believe that AI will take most jobs or substantial long-term unemployment will sustain is to believe one or a combination of the following...

We won't need to work or need jobs

A major proportion of the human population will not be able to adapt or re-skill

We will run out of problems to solve in the universe

I certainly don't believe any of the above. 😀

Ok, so let's dive in...

In this article, I'm going to layout the data regarding what's actually happening in the job market, especially at the entry level.

And while some of the things one needs to do survive and thrive are common sense, I'll do my best to provide a high-level framework that I hope you find useful and flexible as you consider what actions you or your child should take.

Below are the main questions I'll answer...

Will we even need to work or have jobs in the future?

How have past major labor market disruptions impacted job openings, unemployment rate, and total number of jobs?

Are entry-level jobs actually disappearing?

Which jobs are at risk and which jobs are safer from AI-disruption?

What should you study and / or what skills do you need to develop to survive and thrive in this AI-era?

Where are universities in their journey to evolve and adapt their pedagogy and curriculum in this AI-era?

Disclaimer: Thoughts are my own and don't necessarily represent that of @khoslaventures or any other organization I work with.

1. Will we even need to work or have jobs in the future?

TLDR: Yes. 😀 As much as I'd love to just watch football or become a leisurely gardener, in the wise words of Stephen Hawking, "Work gives you meaning and purpose, and life is empty without it."

With purpose and fulfillment comes happiness. "It is the working man who is the happy man. It is the idle man who is the miserable man." - Benjamin Franklin

As a Christian, I also believe what God told Adam in the garden of Eden to be true and to apply to all mankind - "By the sweat of your brow you will eat your food until you return to the ground, since from it you were taken; for dust you are and to dust you will return.”

We are veering into the philosophical and even religious, but I believe man's purpose here on earth is to toil and struggle and through hard work, ultimately overcome the natural man who wants to be lazy and eat cheesy nachos in bed all day while playing Super Mario vs. his friends online.

More apt for the male species than our more benevolent female counterparts but we simply do not want a population of men without work, without challenge or purpose. It will not end well. 😂

Prophetic depiction from Wall-E regarding our future without meaningful work...

The founder of @khoslaventures , Vinod, famously believes that in a 15 year timespan, AI will bring massive abundance and a deflationary economy where this abundance that removes the need for work. Many will choose to work but it will become optional. Today's 5 year olds won't need to work.

I don't necessarily disagree with this in principle and he is likely the world's best at predicting the ripple effects and cascading future impact of technology, but I can almost guarantee that he will be working round the clock as he does today =), as will I, and almost all others we know.

Sure, we may not represent the entire U.S. population and there is certainly a large % of Americans who dream of a life with no job. But if you imagine a world where the mundane, rote, and unfulfilling jobs get automated by AI and robots, what does that free up humans to do to fulfill their greater potential?

We will all choose to work because the principles of competition in a free market economy and status attainment via wealth will not change, even in an age of abundance.

Many great thinkers like Thomas Paine with "In Agrarian Justice" or Thomas Spence with "In The Rights of Infants" or Milton Friedman have advocated for something similar to the notion of Universal Basic Income. All these men are much smarter than me but I don't believe a free handout from the government as a baseline protection against poverty will be the prevailing economic philosophy or reality of the average American household and the U.S. economy at-large.

There is no historical precedent where socialism via government-run programs trumps the principles of a free-market economy.

Prove me wrong. 😀

2. How have past major labor market disruptions impacted the unemployment rate, total number of jobs, and job openings rate?

So before I throw a bunch of charts and data at you, let's level set on the different types of data and how to interpret each of the different measures of data.

There is too much fear-mongering by many entities that are conflating leading indicators with lagging indicators and also presenting isolated points of data without full context regarding broader trend lines and also how those data points compare to other industry or historical data points.

This isn't perfect but a rough framework for leading vs. lagging indicators...

Leading indicators: Job openings rate (JOLTs)

and # of Job Losses

counts unfilled positions at the end of the month that meet conditions such as the job could start within ~30 days and the employer is actively recruiting. It’s good for detecting changes in employer appetite and capacity constraints before payroll headcount moves. It’s not the same thing as online job postings, and it doesn’t guarantee a hire will occur.

Job openings will likely go down first before any other indicators if AI is starting to subsume jobs and the number of job losses will increase.

Lagging indicators: “Unemployed” + “Unemployment rate”

(CPS survey) — people-side supply + realized joblessness. It can be “laggy” in slow changes, but in sudden shocks it can jump quickly (COVID), so it’s not always lagging.

In the case of AI, we haven't seen this be a sudden shock yet so will likely be best lagging indicator we have. Will start to increase if AI reduces number of job openings and if unemployment grows due to layoffs occurring + those displaced being unable to find jobs.

Other data points:

Overall number of people employed by industry

probably least helpful in terms of seeing impact of AI in a shorter-to-medium term but gives us a sense of absolute growth or decline.

Leading Indicators - Job Openings Rate (JOLTs) and Job Losses

TLDR: JOLTs data is showing that there is wide-ranging decline across almost all industries in terms of job openings, not just that of white collar jobs. It it appears largely more indicative of a normalization of the increase in hiring in ZIRP era than an AI-induced reduction, although that impact could be starting to take hold - it's just not readily isolated in the data.

There are some tweets pointing at some industry-specific data like this chart below for finance with the conclusion that AI is eating finance jobs.

But if you look at this data for all industries, you'll see this normalization happening across virtually all industries. Some industries like "Information" have already seemingly normalized and started to grow slightly again.

Some point to the 92K in job losses in Feb 2026 as signs of AI's impact on jobs. October 2025 was even works. We are certainly starting to see more losses in general but hard to know if this is from continued normalization from ZIRP and how many of these were specifically AI-induced.

Lagging Indicators - Unemployment Rate + Unemployed

TLDR: Outside of the Great Depression (which brought 15 years of sustained unemployment between 10% to 25%), the U.S. economy has consistently "healed" back down towards 5% or below.

Even after almost 3 years since ChatGPT's launch, February 2026's 4.4% unemployment rate is still well below the 6.6% average over the last century. Yes, while the trend line is important, it's helpful to step back and contextualize that we are still in relative good standing today.

In isolating from pandemic times to now, the trend line of unemployment is certainly concerning.

However, if you take a step back and look at the past century, this pattern plays out over and over again.

The key question is be whether this AI-era results in Covid, GFC, or even Great Depression-level unemployment in terms of % level and also in duration. Today, it is difficult to know but in absolute terms, we're still at healthy levels of unemployment, and therefore employment.

If you look at unemployment rate by industry, you aren't necessarily seeing the white-collar industries getting contributing a greater amount of unemployment than blue-collar industries yet.

Other Data Points: Overall Number of Employed by Industry