The Unfolding Story: When AI’s Promise Confronts Labor Economics and the State of Affairs for 2008 Graduates
Grace, Aaron, and Priya huddled in a tiny Brooklyn café as they pondered their uncertain futures, knowing that AI could wipe out half of all entry-level white-collar jobs.
Key Point
- This fictional story scenario is inspired by real-world data and analysis, including recent warnings from figures like Anthropic CEO Dario Amodei regarding the potential for AI to significantly impact white-collar jobs and unemployment rates within the next five years. The narrative highlights what many in the AI community have already been warning about, but which society and the government, in general, view as a distant future or possible consequences.
Urgent Meeting in the Oval Office, White House, January 2025
A report, marked “Secret Restricted Data” and hinting at consequences comparable to a nuclear detonation, landed on the desk of the President’s Chief of Staff. Its subject: the accelerating threat of Artificial Intelligence to the American workforce. The Director of the National Security Council had presented the findings from a recent, private meeting with prominent figures in the AI world.
The Chief of Staff read the stark warning from Dario Amodei, CEO of Anthropic, a leading AI developer:
“AI could wipe out half of all entry-level white-collar jobs — and spike unemployment to 10-20% in the next one to five years.”
Amodei stressed that AI companies and the government must stop “sugar-coating” what’s coming: the potential mass elimination of jobs across technology, finance, law, consulting, and other white-collar professions, particularly at the entry level.
“Why does this matter to him?” the President inquired. The Chief of Staff explained that Amodei felt compelled to speak out, hoping to urge the government and fellow AI companies to prepare and protect the nation. He intended to make his concerns public in a couple of months, framing it as a matter of national security.
The Security Council, the Chief of Staff added, was highly confident in the projection’s timeline. They were also briefed that on this day, Google generates over 25% of its new code with AI, and Microsoft as much as 30%. A trend that is emerging in the field is that fewer coders and engineers are being recruited. The unemployment rate in those fields was 6.1% and 7.5%, respectively, notably higher than the national average of 3.6% for all majors.
“Which jobs will be impacted first overall?” the President pressed. The Chief of Staff informed her that as early as February 2024, reports had detailed which occupations were most susceptible to AI disruption, assessing the likelihood by comparing required tasks and skills with AI capabilities. A graph, she noted, clearly illustrated these findings.
The Scale of the Challenge: The Nuclear Blast
The President then posed two critical questions: How many U.S. jobs are most likely to be affected, and how many graduates enter these fields annually?
Following calls with the Secretary of Labor and the Secretary of Education, the Chief of Staff provided initial estimates. “Mr. President,” she began, “in 2022, 19% of American workers were in jobs most at risk. With a U.S. workforce of approximately 167.8 million in 2023, this translates to roughly 31.9 million potentially impacted jobs.”
The report also highlighted a significant economic disparity: workers in highly exposed jobs earned an average of $33 per hour in 2022, compared to $20 in less vulnerable positions. Adjusted for inflation, that $33 would be approximately $37.66 in 2025. This could result in an estimated $2.34 trillion per year in lost wage earnings, a substantial sum with significant economic repercussions, if all those jobs are eliminated within X time.
Based on simplified assumptions, such lost wages could result in approximately $635.3 billion in lost tax revenue annually, assuming all those jobs are eliminated within X time, which would impact payroll, state, and federal income taxes, as well as other taxes. If we take 50% of the lost jobs, it is likely closer to $374.6 billion under the assumptions of a 30% effective tax rate.
Since you like scenarios Mr. President, let me show you the following graph comparing wage losses:
Regarding graduates, in 2022-2023, approximately 2.1 million bachelor’s degrees were awarded, with roughly 1.6 million in white-collar sectors (business, education, health, STEM). Crucially, about 27% of jobs held by individuals with bachelor’s degrees are highly exposed to AI. “Mr. President, if this 27% estimate holds,” the Chief of Staff concluded, “then 432,000 of those 1.6 million white-collar graduates might face severe AI disruption.”
The President's shock was palpable. “Now I understand,” she said, “why the report was marked as Secret Restricted Data and compared to a nuclear explosion.”
Diverging Opinions and Cautious Responses
“Nevertheless, Mr. President,” the Chief of Staff continued, “remember that, like the COVID-19 origin reports, there is no consensus among our intelligence agencies.” She reminded him that while five agencies believed the virus originated from a spillover, two thought it had laboratory origins, and others remained inconclusive.
Similarly, with potential job losses, disagreements persisted. Some advisors suggested that the timeline for widespread disruption could be much longer—perhaps 45 years or more—allowing ample time for adaptation. Others argued that while AI would indeed disrupt jobs, it would create new kinds of jobs, potentially leading to a shortage of qualified workers to fill these emerging roles. This perspective reflected the Industrial Revolution, where the demand for new skills outstripped the workforce’s supply, and education systems adapted gradually over an extended period. All acknowledged a political “disturbance” in the short and medium term before the job market, education system, and economy stabilized.
“Well,” the President remarked, “this is a serious national security risk if even a quarter of the predicted scenario comes to happen.” She tasked the Secretary of the Treasury with leading discussions to present policy options.
The SCIF Meeting: A Battle of Timelines
At the President’s request, Treasury Secretary Margaret Lin convened high-ranking government officials in a Sensitive Compartmented Information Facility (SCIF) in Washington, D.C. The President had designated it a Special Access Program (SAP) to prevent public alarm and allow they to explore cover disinformation if news of the threat leaked, as the AI community had suggested would happen.
Some strategies could include selective omission, calls for unity or patience, promoting AI's benefits, such as “turbocharging” public services and encouraging innovation, while avoiding mention of the risks of job loss and focusing on AI's ability to “enhance worker productivity” and create “new opportunities.” This approach makes AI appear to be a net positive for the workforce, even though job loss estimates are not directly presented.
The room buzzed as Secretary Lin, a veteran economist, addressed her colleagues: Secretary of Labor David Ramirez, Technology Advisor Dr. Evelyn Carter, and L. Thompson, an AI industry liaison “representing” major AI companies.
“Let's get to it,” Lin stated sharply. “Amodei’s prediction is alarming—mass job losses in tech, finance, law, and consulting, hitting entry-level positions hardest. He says it could happen in five years, but there’s uncertainty. Some of our advisor models suggest ~45 years or more. We need to figure out how seriously to take this and what, if anything, we do now.”
Ramirez, a labor advocate, leaned in. “If even half of this comes true, we’re looking at a crisis. Millions of jobs gone, especially for new graduates. We need to act fast: retraining programs, expanded benefits, something to keep people afloat.”
Dr. Carter, analytical and calm, adjusted her glasses. “I agree it’s serious, but we can’t jump the gun. AI’s trajectory isn’t set. The short-term impact might be overstated, and 45 years gives us breathing room to adapt. Overreacting could disrupt markets unnecessarily.”
Thompson, the industry liaison, nodded smoothly. “AI isn’t just a threat—it’s an opportunity. It’ll kill some jobs, sure, but it’ll create others. The key is responsible development, not panic-driven policies that could choke innovation.”
Lin frowned. “But what if the worst hits sooner? A 10-20% unemployment spike would tank the economy—social unrest, budget deficits, you name it. We’d be scrambling.”
“That’s why we prepare now,” Ramirez insisted. “Invest in education, build a safety net. Even if it’s 45 years out, these steps make sense long-term.”
Carter countered, “Preparation sounds good, but the cost is real. Massive programs based on a five-year guess could drain resources we need elsewhere. If the timeline’s longer, we’d look foolish.”
“And if we regulate too hard,” Thompson added, “we risk losing ground to global competitors. AI’s moving fast—China won’t wait for us to debate.”
The discussion grew heated, with Ramirez pushing for immediate action and Carter and Thompson advocating caution, while emphasizing the benefits of AI. Lin mediated, seeking data and practical steps.
After four hours, Lin raised a hand. “We’ve got two scenarios: a fast collapse in five years or a slow burn over 45. What’s our move?”
Ramirez sighed. “Act now, scale up if needed.”
Carter countered, “Monitor and adjust. We’ve got time.”
Thompson agreed. “Let’s guide AI’s growth, not stifle it.”
Lin took a breath. “Given the 45-year possibility, I say we hold off on big moves. We’ll watch the data—job reports, AI adoption rates, and start small with pilot retraining programs. If things accelerate, we pivot. For now, we wait and see.”
The others nodded reluctantly. “Hope we don’t regret this,” Ramirez muttered, reminding them of Leopold Aschenbrenner's paper, SITUATIONAL AWARENESS: The Decade Ahead, which warned that:
“Hundreds of millions of AGIs could automate AI research, compressing a decade of algorithmic progress (5+ OOMs) into 1 year. We would rapidly go from human-level to vastly superhuman AI systems. The power—and the peril—of superintelligence would be dramatic.”
He also recalled Sergey Brin and Demis Hassabis affirming that AI would match or exceed most human capabilities by around 2030.
After five consecutive four-hour meetings, the officials failed to reach any clear policy recommendations for the President. Despite acknowledging the necessity of considering the future, the President primarily adhered to his directive to prevent public alarm and to manage perception through cover disinformation.
The Chief of Staff later informed him that the Security Council's directive, in compliance with his order, would emphasize AI’s potential to “enhance worker productivity” and create “new opportunities,” framing AI as a net positive despite uncertain job loss estimates.
June 2028: The Consequences Unfold
Four years later, the effects of that cautious approach and the disinformation directive were undeniably clear.
In June 2028, the economy was barely recognizable to Grace, Aaron, and Priya, recent graduates from prestigious universities. Grace (finance), Aaron (law), and Priya (computer science) held degrees that once promised prosperous careers. Now, as they faced the job market, a harsh reality hit.
Grace, who had dreamed of a major investment bank after studying finance at NYU, found those doors slammed shut. AI-driven investment models analyzed vast datasets in seconds, rendering entry-level analysts largely redundant. After six months of fruitless applications, she secured a temporary role overseeing algorithmic compliance—a shadow of her vision. At home, her parents' family restaurant struggled as patrons dwindled due to widespread unemployment and tightened budgets. They worried for Grace and increasingly attended community meetings demanding government intervention.
Aaron, a freshly minted Columbia Law graduate, fared no better. Entry-level paralegal and associate positions had vanished, swallowed by AI systems swiftly reviewing legal documents, contracts, and precedents at superhuman speeds. Law firms, facing shrinking budgets, weren't hiring junior associates when AI delivered faster and cheaper results. Aaron was left hustling in the gig economy, offering freelance legal research at unsustainable rates to repay his massive student debt. His father, a veteran schoolteacher nearing retirement, took part-time jobs to support the family. At the same time, his mother passionately advocated for enhanced unemployment benefits and job retraining programs at local town halls.
Priya, a top student from Stanford, specializing in software engineering and artificial intelligence, paradoxically found that even her skills were disrupted. Companies rapidly adopted advanced generative AI platforms that automated mundane coding and complex algorithm development. Junior developer roles evaporated, and internships were scarce. Priya desperately pivoted, marketing herself as an “AI prompt specialist,” a job that required navigating algorithms instead of building them—the irony was not lost on her. Her parents, both engineers who had proudly anticipated her bright future, now grappled with the threat of automation to their jobs, fueling their activism for policy changes.
Across the nation, communities buzzed with frustration, growing increasingly vocal and organized. Social media groups became digital activist hubs, demanding government action. The government, however, issued lukewarm statements promising future initiatives but remained slow to take decisive action. Critics, echoing earlier warnings from experts like Dario Amodei, accused officials of neglecting clear signs of impending disruption. Economists and labor specialists had advocated for policies promoting lifelong learning, proactive retraining initiatives, universal basic income, and public-private partnerships to manage workforce transitions—recommendations that had been mainly ignored.
In a viral online speech, Dario Amodei, CEO of Anthropic, reiterated his earlier warnings: “We sugar-coated this for too long. Now we are dealing with societal dislocation at a scale we haven’t seen before. Our challenge now isn’t stopping AI; it’s preparing people to survive in the age of AI.”
As Grace, Aaron, and Priya huddled in a tiny Brooklyn café, they pondered their uncertain futures, realizing that resilience and adaptability would be their most valuable skills in a world transformed overnight. Their families’ struggles, coupled with widespread community activism and the delayed governmental response, starkly underscored the urgent need for swift and comprehensive policy changes.
Additional Sources:
Bureau of Labor Statistics, U.S. Department of Labor, The Economics Daily, AI impacts in BLS employment projections at https://www.bls.gov/opub/ted/2025/ai-impacts-in-bls-employment-projections.htm (visited June 03, 2025).
For Some Recent Graduates, the A.I. Job Apocalypse May Already Be Here, By Kevin Roose, Reporting from San Francisco for the New York Times, May 30, 2025.
AI could erase half of all entry-level white-collar jobs within five years, warns Anthropic CEO. Techspot Irony alert: AI firm's CEO issues dire jobs warning. By Rob Thubron, May 29, 2025.
AI may already be shrinking entry-level jobs in tech, new research suggests. By Marina Temkin, May 2025, TechCrunch.
By: Irving A. Jiménez Narváez
Note: This fictional story scenario is inspired by real-world data and analysis that stem from a compilation of references and notes from various authors, media, and academics. I utilized AI platforms, including Gemini, Grok, ChatGPT, and Grammarly, to expedite research while ensuring clarity and logical flow. My aim in using these tools was to verify information across multiple sources and validate it through academic databases and collaborations with equity firm analysts.
.
Comentarios
Publicar un comentario