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12/09/2025

What if Big Thinkers design a dating app: The unique case of Geoffrey Miller

By Gopal Bansal
Tags:
  • building a dating app, 
  • commitment filter, 
  • dating app business model, 
  • dating app industry, 
  • dating app on blockchain, 
  • matchmaking algorithm, 
  • tokenized dating app
What-if-Big-Thinkers-design-a-dating-app-The-unique-case-of-Geoffrey-Miller
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If Geoffrey Miller, evolutionary psychologist and author of “The Mating Mind”, designed a dating app, it would flip the script on Tinder-style swipe culture. His app would be built around sexual selection theory, where mating success depends on displaying costly, hard-to-fake traits like intelligence, creativity, kindness, and mental fitness.

Let’s imagine a serious, Miller-inspired dating app—we might even call it:

“Display” – Where Signals Matter

Here are the core features that reflect Geoffrey Miller’s evolutionary psychology lens:

1. High-Fidelity Signalling Profiles in Dating App

  • Users wouldn’t just upload selfies. Instead, they’d showcase cognitive traits through:
    • Short videos where they tell a funny story or explain a passion project
    • Optional mini podcasts of unscripted personal takes
    • Creative writing samples (poems, opinions, thought essays)
    • Music, digital art, or coded projects as dating “résumés”

Why? Because these are costly, hard-to-fake signals of intelligence and creativity—traits Miller argues evolved via sexual selection.

2. Authenticity Over Appearances

  • No filters, no excessive photos—users are nudged to share:
    • Voice notes (intonation reveals emotional intelligence)
    • Unedited “walk & talk” selfie videos
    • Real-time Q&A rounds with potential matches

Why? Looks matter, but mental fitness signals last longer. Miller would prioritize behaviours that can’t be easily gamed.

3. Mating Fitness Challenges (Optional)

Gamified, opt-in tasks to display your fitness as a mate:

  • Improv rounds (“Your date just spilt wine. Respond!”)
  • Empathy tests (“How would you handle this dilemma?”)
  • Insight expression (“What’s your theory of love?”)
  • Humour challenges (“Tell a joke that reveals your worldview”)

Scoring would be peer-reviewed, not algorithmic. Users rate how impressive, thoughtful, or emotionally aware someone’s signal is.

4. Mental Health & Genetic Disclosure (Optional & Ethical)

  • Instead of superficial bios, users could opt to disclose:
    • Personal growth stories or therapy insights
    • Family health patterns (voluntarily)
    • Lifestyle compatibility factors (sleep, stress, habits)

Why? Because long-term mate selection, in Miller’s view, has always involved evaluating genetic and psychological health.

5. Reputation Ecosystem

What-if-Big-Thinkers-design-a-dating-app

  • Verified endorsements from ex-partners (if amicable)
  • Anonymous third-party reviews (“They were a kind, generous listener”)
  • Blockchains of trust: reputation scores that can’t be faked by bots

Why? Evolution built us to learn about others through indirect signals—what their community says about them.

6. Long-form, Contextual Matching in Dating Apps

  • Instead of left/right swipes, the app surfaces people based on:
    • Shared creative interests
    • Complexity of thought in answers
    • Complementary mating strategies (long-term vs short-term signalling)

Why? Miller’s theory values context-rich assessments over visual heuristics.

7. Cognitive Turn-On Filters

  • Users filter not just by height or age, but by:
    • Curiosity level
    • Philosophical depth
    • Books read recently
    • Political nuance
    • Favourite thought experiments

Why? The app lets people signal niche intelligence, not just generic attractiveness.

8. Anti-Ghosting Contracts

  • Once a conversation is initiated, users commit to:
    • At least one meaningful interaction
    • Timed, respectful disengagement if uninterested
  • Option for “mating etiquette” certification badge

Why? Miller sees mating rituals as cooperative signalling. Ghosting breaks the evolutionary dance.

9. Signal-Matching Algorithm (Not Swipes)

  • Algorithm focuses on signal compatibility:
    • Do your creativity displays align?
    • Are your humour styles mutual attractors?
    • Does your mental health journey resonate with theirs?

Why? Evolution shaped us to recognize complex displays, not Tinder-style snap judgments.

10. Optional Peacocking Arena

A section of the app where users show off in playful, status-aware ways:

  • “Why I’m a great long-term mate” TED-style pitches
  • “Fitness flexes” (without being cringe) like volunteering, teaching, running a startup
  • Satirical self-deprecating monologues

In Short:

If Geoffrey Miller built a dating app, it would feel less like Instagram and more like a cross between an improv night, a philosophy café, and a talent show—but with love as the prize.

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Tags:
  • building a dating app
  • , 
  • commitment filter
  • , 
  • dating app business model
  • , 
  • dating app industry
  • , 
  • dating app on blockchain
  • , 
  • matchmaking algorithm
  • , 
  • tokenized dating app
Tags:
  • building a dating app, 
  • commitment filter, 
  • dating app business model, 
  • dating app industry, 
  • dating app on blockchain, 
  • matchmaking algorithm, 
  • tokenized dating app
Prev:How DropD’s Matchmaking Algorithm Reimagines Compatibility?Next:Imagine If Facebook Had Stayed a Dating Platform — and Evolved as a Tokenized Web3 Network of Love

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