Is Empiricism Innate? Summary Notes

Overview

  • Topic: Do people think knowledge is born or learned? Mostly, they think it's learned, even basic skills.

  • Main Idea: People (adults, kids, scientists, different cultures) guess that core abilities show up later in life than science proves. They credit learning more than innate traits.

  • Meaning: We all seem to have an "intuitive empiricism" – a gut feeling that everything is learned – from a young age, and it sticks around.

Key Concepts

  • Core knowledge: Basic, unlearned mental tools (like knowing objects exist, counting).

  • Innate: Born with it (due to genes).

  • Maturation: Develops with age (not learned).

  • Learning (no instruction): Learn by watching/doing, on your own.

  • Learning (with instruction): Taught directly (school, parents).

  • Intuitive empiricism: Common belief that skills come from experience/learning.

  • Timeline task: Research method to ask participants when an ability first appears.

How They Studied It

  • Question: Do people think it's nature OR nurture, or a mix? Do they lean towards nurture for basic skills?

  • Baseline: They compared people's beliefs to actual scientific findings on when abilities develop.

  • Method: Many experiments with different groups (adults, kids, scientists), using similar tasks to see if results were consistent.

  • Coding Explanations: Sorted reasons into:

    • Innate (genes, born with)

    • Maturation (grows with age)

    • Learning (self-taught)

    • Explicit Teaching (taught by others)

  • Excluded Data: About 15% of unclear answers were left out.

Experiment 1: US Adults

  • Participants: N=101N = 101 US adults online.

  • Task: Read about "Alex" getting abilities (born with, matures, learns alone, taught). Rated 7 core abilities (like color vision, object permanence).

  • Timeline: Marked when abilities appeared on a timeline. y = 0.13 e^{0.78 x}, R^2 > 0.99

  • Results:

    • Onset Age: They guessed core abilities appeared between 0.940.94 and 2.882.88 years (95% CI: [0.66,1.22][0.66, 1.22] lower; [2.60,3.15][2.60, 3.15] upper) — much later than science shows.

    • Explanations: 77%77\% (95% CI [73%,81%][73\%, 81\%]) of explanations were learning-based (t(99) = 11.81, p < 0.001).

    • Exceptions: Seeing/hearing were correctly thought to be early (around 0.320.32 years) and innate (M=3%M = 3\% learning). Reading was correctly thought to be learned (around 4.564.56 years) and taught (100%100\% learning).

  • Replications: Results were consistent in follow-up tests.

Experiment 2: Cross-Cultural (India)

  • Participants: N=99N = 99 Hindu adults in India.

  • Results: Similar to US adults. Core abilities estimated later (between 2.252.25 and 5.115.11 years, 95% CI [1.98,2.53][1.98, 2.53] and [4.84,5.38][4.84, 5.38]), and 80%80\% (95% CI [74%,86%][74\%, 86\%]) of explanations were learning-based.

  • Religiosity: Didn't affect beliefs.

Experiment 3: Humans vs. Animals

  • Participants: N=201N = 201 US adults.

  • Task: Compared core abilities in humans (e.g., face recognition) vs. animals (e.g., chicks' face recognition).

  • Results:

    • Born with: Humans: 37%37\% (95% CI [32%,43%][32\%, 43\%]); Animals: 67%67\% (95% CI [63%,71%][63\%, 71\%]).

    • Learning-based: Humans: 62%62\% (95% CI [56%,68%][56\%, 68\%]); Animals: 31%31\% (95% CI [26%,36%][26\%, 36\%]). Significant difference for most items (\chi^2 > 4.76, ps < .029).

  • Conclusion: People think human abilities are more learned, while animal abilities are more innate.

Experiment 4: Children

  • Participants: N=85N = 85 children (average age 6.686.68 years).

  • Results:

    • Onset Age: Guessed core abilities appeared between 1.271.27 and 2.012.01 years (95% CI [0.99,1.55][0.99, 1.55] lower; [1.74,2.29][1.74, 2.29] upper) — 8x later than actual onset.

    • Learning-based: 92%92\% (95% CI [89%,95%][89\%, 95\%]) of explanations were learning-based (t(84) = 25.52, p < .001) — even stronger than adults.

    • Sensory abilities (seeing) were exceptions (M=24%M = 24\% learning).

Experiment 5: Scientists & Educated Adults

  • Participants: N=400N = 400 from universities (natural scientists, humanities, mind scientists; 36% PhD).

  • Results:

    • Onset Age: Guessed between 0.480.48 and 1.631.63 years (95% CI [0.21,0.74][0.21, 0.74] lower; [1.37,1.89][1.37, 1.89] upper) — still later than actual, but earlier than lay adults.

    • Learning-based: M=64%M = 64\% (95% CI [62%,67%][62\%, 67\%]). Mind scientists gave fewer learning explanations than others (t(399) = 4.32, p < .001).

  • Conclusion: Expertise reduces the bias a bit, but even scientists show this "empiricist" bias.

General Findings

  • People always guess core abilities start later than they actually do.

  • Learning is the top explanation for core abilities across all groups (US, India, kids, scientists).

  • People see human abilities as learned, animal abilities as innate.

  • "Reading" is known as learned; basic senses (seeing/hearing) as innate.

  • Religiosity didn't matter.

  • Scientific training helps a little but doesn't remove the bias.

Why This Matters (Theories)

  • Intuitive Empiricism: It's a strong, widespread cognitive bias, maybe because pedagogy (teaching) is so important in human culture.

  • Re-examine Science: Scientists should be aware of this bias when interpreting research on innate structures.

  • Possible Roots of Bias:

    • Evolved for Teaching: Maybe we're wired to promote social learning.

    • Visible Teaching: We see teaching constantly, shaping our views.

    • Optimism: Believing things are learned can be positive (anyone can learn anything).

Real-World Impact

  • Education: Helps educators understand what students expect about learning.

  • Science Communication: Guides how scientists explain developmental findings to the public.

  • Global: Since it's cross-cultural, it affects how science education happens worldwide.

Summary Takeaways

  • People think core human abilities appear later and are learned, not innate.

  • This "empiricist bias" is strong across cultures and different groups, even if it doesn't match scientific consensus.

  • We need to understand why this bias persists and how it affects scientific learning.