FTC action against Match and OkCupid for deceiving users, sharing personal data

Original Article ↗ Hacker News Discussion ↗

U.S. regulators have accused Match Group and OkCupid of deceiving users and secretly sharing millions of dating profile photos and related data with facial-recognition firm Clarifai, allegedly in violation of their own privacy policies. Commenters highlight how the proposed FTC settlement appears to impose few concrete penalties beyond promises not to misrepresent privacy practices, raising concerns over weak enforcement and the lack of data deletion or model “untraining” requirements. The case also prompts broader criticism of dating platforms’ business incentives, use of dark patterns, possible fake profiles, and the wider ecosystem of surveillance capitalism and dual‑use AI technologies.

FTC Complaint & Settlement

  • OkCupid allegedly shared nearly 3M user photos plus demographic and location data with a third party without telling users, contradicting its own privacy policy.
  • The proposed settlement mainly prohibits future misrepresentation of privacy policies and data use; several commenters see this as a weak “don’t do it again” response after many years.
  • Some wonder if unlawfully transmitted data and any AI models trained on it must be deleted; the thread finds this unclear from the documents.
  • Others note this is effectively a “first strike” that sets up harsher penalties for repeat offenses.

Third-Party Data Recipient (Clarifai)

  • The FTC complaint identifies the third party as an AI image-recognition company that requested OkCupid data because founders were investors.
  • Commenters highlight the lack of contractual limits on data use.
  • There is debate over whether the core concern is privacy, potential military applications (e.g., targeting), or both.

Legal & Enforcement Questions

  • Some see potential for class actions, including theories around copyright violations.
  • Others counter that typical user agreements grant broad licenses and allow sublicensing, though one comment notes this arrangement did not go through formal sublicensing.
  • A recurring theme is that large corporations are treated leniently by regulators compared to individuals.

Dating App Business Models & Incentives

  • Several comments argue dating apps have misaligned incentives: success means losing paying users, so platforms benefit from keeping people single and engaged.
  • This is framed as a reverse network effect: attractive/relationship-ready users churn out, leaving a progressively worse pool.
  • Alternative incentive structures are debated (matchmaker-style fees, relationship-based payments, government “dating tax,” charity pledges), but practical and abuse issues are raised.

Pricing, Gender Imbalance & User Experience

  • OkCupid’s gender-based pricing (charging different amounts to men vs women) is discussed.
  • Some see it as a rational lever to correct severe gender imbalances; others see it as misleading when most “matches” may be bots or low-quality accounts.
  • Analogies are drawn to nightclubs admitting women for free to attract men.

Data Analytics & Privacy Expectations

  • OkCupid’s historic data analysis and NLP on messages is recalled: ranking reply behavior, studying message patterns, and publishing blog posts/books with findings.
  • Some view this as legitimate, anonymized data science to improve matching and provide evidence-based dating advice.
  • Others find it troubling given later revelations about undisclosed third-party sharing, and question whether “anonymization” meaningfully protects users.

Fake Profiles, Spam & Security Concerns

  • Multiple anecdotes describe account mix-ups, hacked/merged profiles, and spam emerging after account deletion or unique-email registration.
  • There is strong suspicion—supported by one claimed industry insider—that many dating platforms use fake female profiles and dark UX patterns to keep men paying and engaged.
  • Others point to independent scam operations and chatbots (e.g., pig-butchering scams) as another major source of fake activity.

Broader Reflections on Modern Dating

  • Long subthreads explore why online dating feels worse now: hookup vs relationship mismatches, conflicting expectations around first-date spending, social media–driven status signaling, and gendered double standards.
  • Commenters differ on whether problematic behaviors are mostly male, female, or systemic; several stress that adversarial mindsets and unrealistic expectations on both sides erode trust and outcomes.