Podcast Summary: Today, Explained – "The Price is Rigged" (Dec 16, 2025)

Episode Theme

This episode of Today, Explained dives into the rise of surveillance pricing, where companies harness artificial intelligence and personal data to set individualized prices for goods and services. Through conversations with investigative journalist Derek Kravitz (Consumer Reports) and tech policy reporter Alfred Ng (Politico), the episode investigates how pervasive this practice is, its legality and ethical implications, the lack of effective regulation, and what (if anything) consumers can do about it.

Key Discussion Points & Insights

1. What is Surveillance Pricing?

• Surveillance pricing refers to companies using personal data—like your shopping history, demographics, or even browser habits—to set or change prices for individual consumers, often powered by AI.
  • Memorable Quote:
    “Dynamic pricing, surveillance pricing. Lots of terms that mean companies set prices based on what they know about you, and they know a lot.”
    — Host (00:18)

2. The Instacart Investigation

• Derek Kravitz describes Consumer Reports’ extensive study on Instacart’s pricing mechanisms following its acquisition of the AI firm Eversight.

  • Instacart, with around 300 million orders, uses AI to optimize and individually tailor prices, influencing what customers pay at checkout (02:35).

  • Hundreds of volunteers shopped together for identical items in real-time to expose pricing differences:

    • 75% of tested products had prices algorithmically changed, ranging from a few cents to over two dollars (04:18).
    • Skippy Peanut Butter had a 23% price variance between shoppers (04:18).
    • Only 8% got the lowest available price; 92% paid more (06:34).

  • Quote:
    “Trying to control for as many variables as we could to understand how Instacart is using this tech, this AI to inform their grocery prices.”
    — Derek Kravitz (03:59)

  • Algorithms behave like constant A/B tests, tweaking prices by small margins to see what you’ll tolerate (05:15).

  • Retailers claim negligible differences and say it's about affordability, but data suggests most shoppers pay above the minimum possible (06:34).

3. Surveillance Pricing Beyond Instacart

• Other retailers, like Kroger, use loyalty programs and demographic data to set personalized promotions and prices at scale (08:01).

• Airlines, particularly Delta, are using AI to dynamically price fares, aiming for a sizable fraction of all tickets set this way by year’s end (19:57).

  • Company Line vs. Criticism:
    “They've basically said, we don't use personalized data for people to set these prices. … That’s why people use terms like dynamic pricing or individualized pricing, as opposed to what the FTC called it, which is surveillance pricing.”
    — Alfred Ng (20:01)

4. Is Surveillance Pricing Legal?

• It’s a gray area:
  There is no specific federal law against using shopper data for price discrimination, but some states (e.g., New York) now require disclosure if this is happening (09:16).
• Most state and federal laws bar discrimination based on zip code, income, or proxies for race/ethnicity, but AI pricing can sidestep explicit legal categories (10:59).

5. Ethical and Societal Questions Raised

• Is it fair to charge the rich more and the poor less? Laws generally prohibit pricing directly based on income or locale due to discrimination risks (10:59).

• Regulators and the FTC recognize the issue but are struggling to keep up with rapid tech advances (11:44).

  • Notable Quote:
    “Do we want our own personal data to inform the prices we see? Because if we do, then we’re there. If we don’t, then we need to pass some meaningful laws and regulations that speak to that.”
    — Derek Kravitz, referring to FTC Chair Lina Khan's stance (12:52)

6. Regulatory (In)Action

• The FTC launched a probe in the final days of Biden’s presidency, but the investigation was quickly dropped under a new administration (17:23, 18:13).
• Only one meaningful Congressional bill exists, and it lacks co-sponsors (21:37). Lobbyists successfully diluted state-level legislation, e.g., in New York, from a ban to merely a disclosure requirement (23:19).
• Industry pushes back, arguing bans could kill beneficial discounts (like military/teacher discounts) (22:57).

7. The Consumer Experience: Can You Avoid Surveillance Pricing?

• It's nearly impossible for individual consumers to know, let alone avoid, being targeted for AI-driven price changes. Identifying it requires side-by-side comparisons—which Consumer Reports did with hundreds of coordinated shoppers (25:28).
• If you’re acting alone, you’d need multiple devices/accounts and perfect timing, and you still might not know why you see the price you do (25:28).

Notable Quotes & Memorable Moments

• On the covert nature of pricing:
  “How crazy would it be if brands jacked up prices based on your previous shopping history, had data on you that said you were desperate, and knew that you would spend the money no matter what?”
  — Host (20:36)

• On the state of regulation:
  “So for the moment, it looks like we will not get meaningful regulation. … Is there anything we can do to avoid surveillance pricing?”
  — Host (25:15)

• On legal evasions and consumer confusion:
  “It’s hard to combat that when you don’t know what the causes of it are. And in most cases you don’t even know that it’s happening.”
  — Alfred Ng (26:25)

Key Timestamps

• 00:00 – 02:18: Introduction; the world of dynamic pricing; teaser of AI’s growing role.
• 02:18 – 07:48: Derek Kravitz from Consumer Reports details Instacart investigation and results.
• 07:48 – 12:52: Expansion into other retailers, legal/ethical questions, and broader consequences.
• 16:58 – 23:53: Alfred Ng discusses FTC actions, airline pricing, and the weak state response.
• 23:53 – 26:33: Why disclosure laws replaced actual bans; why surveillance pricing is almost impossible for a consumer to detect or avoid.

Conclusion

"The Price is Rigged" exposes a rapidly advancing frontier in commerce: AI-driven, data-powered individualized pricing schemes that are invisible, barely regulated, and nearly impossible to dodge as a consumer. The key takeaways are the breathtaking scale and subtlety of these systems, the lack of meaningful oversight or action by lawmakers, and the urgent need for public debate on whether we want a future where what you pay is determined by how much a computer thinks you’ll pay—and nothing else.