US Jobs Surprise Defies Inflation Fears; Why Uber and Nvidia are Re-Hiring Humans as AI Budgets Explode
شوک بازار کار آمریکا و بازگشت غولهای فناوری به استخدام انسان؛ چرا تب هوش مصنوعی فروکش کرد؟
The US added 172,000 jobs in May, crushing expectations and signaling a resilient economy despite regional conflicts. Meanwhile, a massive shift is occurring in tech as companies like Uber and Microsoft pivot back to human workers after blowing through their AI budgets.
At time of publishing
USD
174,500
Toman
Gold 18K
18.61M
Toman / gram
Bitcoin
$61,949
US Dollar
Tether
174,511
Toman
US Labor Market Defies Gravity Amid Regional Tensions
The United States labor market delivered a massive surprise today, reporting the addition of 172,000 jobs in May—a figure that more than doubles the 80,000 jobs economists had initially predicted. Despite the persistent economic uncertainty fueled by conflict in the Middle East and rising global inflation, the unemployment rate held steady at 4.3%. This resilience is a double-edged sword; while it proves the American consumer is still spending, it also provides the Federal Reserve with more than enough ammunition to keep interest rates higher for longer, a move that typically strengthens the US dollar against emerging market currencies.
For the Iranian market, this data has immediate consequences. The USD/IRR exchange rate has already reacted, moving from 173,700 to 174,500 (+0.5%) in the last 24 hours. A stronger dollar globally often leads to a retreat in gold prices as investors pivot toward yield-bearing assets. We are seeing this play out in real-time as Gold 18k/gram in Tehran dropped from 18,843,436 to 18,612,585 (-1.2%). The 'higher for longer' narrative in Washington means that liquidity will remain tight, keeping pressure on global commodity prices and regional exchange rates.
The AI Reality Check: Humans Prove Cheaper Than Bots
In a stunning reversal of the 2025 tech narrative, industry leaders like Uber, Microsoft, and Nvidia are reportedly shifting their strategy back toward human hiring. Reports indicate that Uber exhausted its entire 2026 AI budget by April, discovering that the massive compute costs and energy requirements of maintaining large-scale AI models were far more expensive than originally forecasted. This 'busted budget' phenomenon suggests that while AI is efficient at specific tasks, the infrastructure required to replace human workers at scale is currently economically unsustainable for many corporations.
This shift marks a significant 'reality check' for the global tech sector. For the past two years, markets have been driven by the assumption that AI would lead to massive cost savings and staff reductions. However, as companies realize that human intelligence—despite its perceived inefficiencies—is actually more cost-effective in complex roles, we may see a stabilization in the white-collar job market. For investors, this could lead to a 'June swoon' for high-flying tech stocks as profit margins are squeezed by these hidden operational costs. The S&P 500 is already showing signs of pushing its limits, and even positive earnings from companies like Oracle may not be enough to sustain the current rally.
Energy Security and Australia’s 344-Million-Barrel Pivot
As the energy crisis deepens due to ongoing instability in the Middle East and threats to shipping lanes in the Strait of Hormuz, Australia is fast-tracking its largest undeveloped oil project. The Dorado oilfield, containing an estimated 344 million barrels, is finally moving toward a final investment decision. Carnarvon Energy and Santos are looking to capitalize on the global supply vacuum, aiming for a green light by 2027. This move is a direct response to the heightened risk of homegrown resources becoming more valuable than volatile imports from conflict zones.
This development signals a broader geopolitical shift where Western-aligned nations are aggressively seeking energy independence. For Iran and other major regional producers, this represents a long-term threat to market share. While the Dorado field won't provide immediate relief to global prices, the market's anticipation of new supply sources acts as a ceiling on long-term oil futures. Furthermore, the rising costs of traditional retail and charity sectors, such as the British Heart Foundation announcing the closure of 150 shops, highlights how inflation and energy costs are hollowing out the high street, forcing a more digital and decentralized global economy.
Frequently Asked Questions
Why did the US jobs report cause the Dollar to rise in Tehran?
Why are Uber and Microsoft hiring humans instead of using AI?
What does Australia's Dorado oilfield mean for Middle East oil producers?
Human‑in‑the‑Loop AI: Why Companies Like Uber and Nvidia Still Need People
When headlines celebrate the rise of artificial intelligence, it’s easy to assume that machines will soon replace most human workers. In practice, the most successful AI deployments rely on a human‑in‑the‑loop (HITL) architecture, where people and algorithms collaborate on the same task. HITL systems keep a human operator in the decision‑making chain to provide judgment, correct errors, and supply contextual knowledge that current models lack. This approach is especially common in high‑stakes domains such as autonomous driving, content moderation, and large‑scale data labeling – all areas where Uber and Nvidia are currently expanding their AI budgets.
For Uber, the push to automate ride‑matching, route optimization, and even driver‑less vehicle pilots still depends on human supervisors who monitor edge cases, intervene when the system misclassifies a road condition, or resolve disputes with riders. Similarly, Nvidia’s rapid growth in AI hardware has spurred massive data‑center deployments that need human engineers to fine‑tune models, manage GPU workloads, and ensure compliance with safety standards. By hiring more humans, these firms are not back‑tracking on AI; they are building the workforce needed to make AI reliable and trustworthy.
The economic rationale is clear: while AI can process vast amounts of data at low marginal cost, the cost of a catastrophic error—legal liability, brand damage, or safety incidents—can far exceed the savings. HITL reduces that risk by allowing a human to catch anomalies before they cause harm. Moreover, the feedback loop created by human reviewers improves the underlying algorithms, accelerating learning and reducing future reliance on manual oversight. This symbiotic relationship explains why, even as AI budgets explode, job postings for data labelers, safety engineers, and AI ethicists are also on the rise.
Understanding HITL is crucial for anyone watching the labor market. It signals that the future of work will likely be augmented rather than replaced by AI, emphasizing skills such as critical thinking, domain expertise, and the ability to interpret machine output. As AI continues to permeate sectors from transportation to energy, the demand for humans who can supervise, audit, and improve these systems will remain a significant source of employment.
Key take‑aways: - Human‑in‑the‑loop combines machine speed with human judgment. - Companies invest in both AI infrastructure and the people who make it safe. - HITL reduces risk, improves model quality, and creates new job categories. - The trend suggests a hybrid future of work, not mass automation.
Topics
Related Articles
