Planet Money: Is AI Slopifying the Job Market? (Two Indicators)

Episode Date: December 3, 2025
Podcast: Planet Money (NPR)
Hosts: Darian Woods, Waylon Wong, Adrian, Adrienne Ma
Overview:
This episode explores the growing influence of artificial intelligence (AI) on the job market, particularly its impact on white-collar jobs and the hiring process. The episode is divided into two main stories: the macroeconomic parallels between AI adoption and the Industrial Revolution, and the practical effects of AI interviewers on job candidates and hiring outcomes.

Main Theme

As AI becomes integral to many sectors, there’s a debate: is AI eliminating or enhancing jobs? The episode investigates claims that AI will drastically reduce white-collar employment, the historical context for such technological revolutions, and real-world examples of AI changing the recruiting landscape today.

Key Discussion Points & Insights

1. Will AI Replace Half of White-Collar Jobs? (00:20–02:00)

• Ford CEO Jim Farley sparked headlines with this prediction:
  • "Artificial intelligence going to replace literally half of all white collar workers in the U.S." (Jim Farley, 00:51)
• The hosts reflect on similar alarms from business leaders about AI transforming the economy, reminiscent of the societal upheaval witnessed during the Industrial Revolution.

2. The Big Picture: AI, Productivity, and Historical Parallels (03:13–10:23)

a. Is AI Replacing or Complementing Jobs? (03:13–03:37)

• Examples of AI reducing manual labor and enhancing productivity in roles like coding, customer service, and data analysis.
• Listeners have reported using AI to streamline tedious tasks.

b. Economic Research with Professor Laura Veldkamp (03:37–10:23)

• Laura Veldkamp (Columbia Business School) draws historical parallels between today’s AI wave and the Industrial Revolution.
• Knowledge production, not just material goods, is the focus of AI’s impact.
• Historical Ups and Downs:
  • Life expectancy in Britain doubled post-Industrial Revolution but also triggered modern environmental crises.

    "If you look at England...the average life expectancy was less than 40 years. Today it's around 80..." (Josh Freeman, 05:18)

  • Not a smooth road to progress—working conditions for many worsened before getting better through regulation and labor organizing.

    "It took generations of organized labor activity, government regulation, and advancements in healthcare to change these conditions." (Darian Woods, 05:52)

• The concept of labor share of income:
  • Measures how much of economic output goes to workers versus owners/capital.
  • Veldkamp's research shows that in finance (an early AI adopter), AI could shrink labor’s share by 5%, similar to what happened in the Industrial Revolution.

    "We find that a worker who has AI skills in the financial sector is making about $22,000 a year more than somebody who doesn't." (Laura Veldkamp, 08:25)

  • Important nuance: The “pie” (profits/GDP) may be larger, so workers can still earn more in absolute terms even with a smaller share.
• Warnings about monopolization:
  • As in the 19th century, early adopters of AI risk gaining too much market power ("robber barons").

    "There's a risk that we could follow the same path here where...early adopters that become monopolists...squeeze us as consumers and...workers." (Laura Veldkamp, 08:58)

  • Today’s AI landscape already shows high concentration from the start, unlike past industries which took decades to consolidate.

    "We're starting from extreme concentration. That's the way it's beginning...monopolized from the get go." (Josh Freeman, 09:51)

• Open questions remain about how society will share the gains from AI, involving policymakers, regulators, workers—and computers themselves.

3. AI in Recruiting: The Case of "Anna," the AI Interviewer (12:34–20:26)

a. Problem: The "Leaky Funnel" in Recruiting (12:34–14:17)

• David Koch (Chief of Transformation and Innovation at PSG Global Solutions):
  • Describes hiring as a leaky funnel—lots of applicants drop out before placement.
  • Time is critical: If you call an applicant within a minute, 85% connect, but wait 15 minutes and it drops to 35%.

b. Solution: Introducing Anna, the AI Recruiter (14:17–15:59)

• PSG built "Anna," an AI-powered phone recruiter to conduct initial candidate interviews—demonstrated live by host Adrian, who fields typical interview questions from Anna.

  Anna: "Can you describe a situation where you had to manage multiple competing demands while handling a customer call?" (14:50)

c. Evaluating Anna: Does AI Interviewing Work? (15:59–19:39)

• PSG partnered with economist Brian Jabarian (University of Chicago) to test Anna's effectiveness with a randomized study:
  • Three applicant groups: human interviewer; AI interviewer; or choice of either.
  • Human recruiters still reviewed final interview transcripts or audio before hiring.
• Surprising Results:
  • 78% of candidates chose AI over human interviewers.

    "Given a choice, 78% of candidates choose to be interviewed by an AI voice agent." (Brian Jabarian, 17:45)

  • Applicants felt AI was less judgmental; women, in particular, preferred the AI and reported feeling less discrimination.
  • Candidates who used Anna were:
    • 12% more likely to get a job offer.
    • 18% more likely to start and stay in the job for at least a month.
  • Linguistic analysis revealed that Anna’s interviews brought out desirable traits in candidates—more interactivity and vocabulary richness.

    "If you display a lot of interactivity...or you display a high level of vocabulary richness, you increase your chances of getting a job offer." (Brian Jabarian, 19:00)

d. Implications for Recruiters & The Industry (19:39–20:26)

• AI interviewing means fewer human recruiters are needed, but the humans who remain focus more on complex tasks.

  "The role of the recruiter is changing, and I think it's a positive change...it becomes a much more meaningful job, I think." (David Koch, 20:16)

• Dozens of competitors are developing similar tech—AI interviewing may soon be the norm.

Notable Quotes & Memorable Moments

• AI Anxiety:

  "Artificial intelligence going to replace literally half of all white collar workers in the U.S."
  — Jim Farley, Ford CEO (00:51)

• On Long-Term Change:

  "You and I and everyone else is facing a planetary crisis from the Industrial Revolution that may seriously impact the future of our species. So, you know, in the biggest scale, you can see both the upsides and the downsides."
  — Josh Freeman, Historian (05:18)

• Market Power Warning:

  "There’s a risk that we could follow the same path here where...early adopters that become monopolists...have an enormous amount of market power and squeeze us as consumers and...workers."
  — Laura Veldkamp (08:58)

• AI in Practice:

  "Given a choice, 78% of candidates choose to be interviewed by an AI voice agent."
  — Brian Jabarian, Economist (17:45) "Anna allowed people to be better versions of themselves."
  — Waylon Wong (19:28)

• Human + AI Future:

  "The role of the recruiter is changing...it becomes a much more meaningful job, I think."
  — David Koch (20:16)

• Humor on AI "Suck-Ups":

  "There's been all this talk about how AI is too sycophantic. Yeah, it's always sucking up, but I feel like now we have to study up on how to suck up to machines."
  — Adrian and Waylon Wong (20:39)

Timestamps for Major Segments

• 00:20–02:00: Jim Farley’s bold AI job loss forecast
• 03:13–10:23: AI and the labor share—historical and economic analysis
• 12:34–20:26: AI interviews in practice—PSG, Anna the AI recruiter, and the University of Chicago study

Tone & Style

The episode strikes a playful yet thought-provoking tone, with self-deprecating humor, spirited banter, and engaging real-life experiments. The hosts blend rigorous economic research with accessible explanations and witty asides, making complex labor issues relatable.

Conclusion

The episode concludes that while AI is indeed shifting the job market—especially in areas like recruiting—it’s not all doom and gloom. There are historical parallels that suggest both risk and opportunity. AI can, as the study with Anna shows, sometimes make processes fairer and more effective. But the long-term division of economic benefits, and the risk of tech monopolies capturing most gains, remain open—and pressing—questions.

For listeners curious about AI’s immediate effect on the job market and what history can (and can’t) teach us about big tech shifts, this episode is a must-listen.