Pinker explains why humans might naturally commit the gambler’s fallacy. Does that mean it’s not really a mistake?
Pinker’s explanation shows why we commit the gambler’s fallacy — our minds evolved to detect patterns in environments where events were often not independent.
However, that doesn’t mean the fallacy isn’t a mistake. In contexts like coin tosses, it’s probabilistically false. So, it’s still an error, even if a natural one.
What is the black box model of vision?
The black box model of vision treats the visual system as a process with known inputs (retinal images) and outputs (percepts) but hidden internal mechanisms.
We infer internal rules by studying how input and output relate.
What is the role of Hoffman’s rules in his model of vision?
Hoffman’s rules are the implicit constraints or heuristics the visual system uses to interpret ambiguous inputs and infer 3D structure.
Are we consciously aware of the visual processes that construct experience?
No — most visual processing occurs unconsciously.
We’re aware only of the result, not the inferential steps that build it.
Our sense of “seeing directly” hides complex, automatic computations.
What is the difference between explaining a belief and justifying it?
Explanation tells us why a belief occurs (causal story).
Justification tells us whether it’s rational or truth-conducive.
They are distinct but related — explanatory accounts can inform, but not replace, justification.
Are we ever justified in committing the gambler’s fallacy? Why or why not?
We are not justified in committing the gambler’s fallacy when we know the events are independent.
Justification depends on epistemic standards, not evolutionary origins.
At best, the fallacy is psychologically understandable, not rationally warranted.
What is the central problem of vision Hoffman wants to explain?
The central problem of vision is that retinal input underdetermines the external world — many 3D scenes can produce the same 2D projection.
Hoffman wants to explain how the brain constructs a single coherent visual world from ambiguous data.
What is the rule of generic views, and why is it important?
The rule of generic views says the visual system assumes we’re not viewing from an accidental or rare angle.
It favors interpretations that remain stable under small changes in viewpoint.
What do change-blindness experiments reveal about our awareness and the limits of perception?
Change blindness shows that we do not store a detailed model of the visual world.
Perception is sparse, attention-limited, and reconstructive — we often miss large changes when attention is diverted.
Can empirical laws of perception function like epistemic norms for vision?
Yes — perceptual “laws” function like epistemic norms: they’re reliable, shared, and empirically grounded.
But they’re descriptive regularities, not prescriptive standards like epistemic justification.
Humans evolved tendencies like inductive inference and social conformity. Does their evolutionary usefulness justify the beliefs they produce?
Evolutionary usefulness does not equal epistemic justification.
A belief-forming tendency can be adaptive yet systematically false (e.g., overconfidence).
Justification requires reliability or rational support — not merely fitness benefits.
Why are optical illusions so important to Hoffman’s project?
Optical illusions reveal the brain’s constructive rules.
When perception diverges from physical reality, we glimpse the interpretive processes that usually operate invisibly.
They’re crucial empirical evidence for vision as inference.
Describe two other rules Hoffman identifies and the evidence he gives for them.
Simplicity Rule – prefer the simplest consistent interpretation (supported by ambiguous figure experiments).
Occlusion Rule – treat T-junctions as occlusion cues, not random line endings (supported by contour and shape-completion studies).
What fair conclusions can we draw from the basketball/moon-walking bear video?
The basketball / moon-walking bear video illustrates inattentional blindness: focused attention filters out unexpected stimuli.
We “see” only what we attend to.
Perception is highly selective, not comprehensive.
If both reasoning and vision evolved for survival rather than truth, how should that affect our concept of justification?
If reasoning and perception evolved for survival, truth may be only an approximate by-product.
This pushes epistemology toward a naturalized view: justification is tied to the reliability of evolved mechanisms, not abstract rational norms.
How does the distinction between explanation and justification help answer whether evolved biases can count as rational?
Explanation describes how a belief arises (psychological or evolutionary cause).
Justification evaluates whether that belief is rational or truth-conducive.
Evolutionary or causal accounts explain biases but don’t necessarily justify them.
What does the wavy-line (cosine function) experiment reveal about how vision works?
The wavy-line or cosine-function experiment shows that identical stimuli can yield different percepts depending on orientation.
This proves that perception depends on context and assumptions, not merely raw input — vision is active and interpretive.
Describe five major differences between retinal input and visual experience. How do these show that vision is constructive?
Five differences between retinal input and visual experience:
2D input → 3D perception
Blind spot filling
Perceived constancy despite eye movements
Illusory contours and surface completion
Stable color constancy despite changing light
→ These show preconscious constructive processing, which we’re not aware of but which shapes experience.
What does it mean to say that vision is both constructive and interpretive?
Vision is constructive because the brain builds percepts from incomplete data.
It’s interpretive because it applies rules and assumptions (like light-from-above or object continuity) to decide among possible interpretations.
Compare the gambler’s fallacy and optical illusions. What do they reveal about evolved heuristics?
The gambler’s fallacy and optical illusions both show that evolved heuristics can mislead us.
They’re adaptive shortcuts that usually serve us well but fail in artificial or novel contexts — highlighting the gap between evolutionary function and epistemic truth.
Can an evolutionary explanation for a belief ever provide epistemic justification? Give an argument for or against.
Evolutionary explanations can sometimes partially support justification if the cognitive process they describe is generally truth-tracking (a reliabilist view).
But mere adaptiveness isn’t enough — we must show that the evolved mechanism tends to produce true beliefs in relevant environments.
If Hoffman is right that perception constructs rather than records reality, does that threaten scientific objectivity? Explain.
If Hoffman is right, perception doesn’t mirror reality but constructs a useful interface for survival.
That challenges naïve realism but not necessarily science: objective inquiry can still work through cross-checking, measurement, and shared methods that transcend individual perception.
Does Hoffman’s empirical evidence give good reason to believe there are laws of human vision? Why or why not?
Yes, the regularity and universality of perceptual phenomena (illusions, constancy, biases) imply laws of vision: systematic, predictable rules governing perception.
They’re empirical generalizations about how all human visual systems construct experience.
How do the phenomena of change blindness and inattentional blindness together challenge our confidence in perceptual awareness?
Both change blindness and inattentional blindness reveal that awareness is narrow and reconstructive.
We don’t continuously perceive the world in detail — instead, we generate coherent “snapshots” guided by attention and expectation.
What do Pinker’s explanation of bias and Hoffman’s theory of vision together suggest about the relationship between naturalized explanation and epistemic normativity?
Pinker and Hoffman together illustrate the core theme of naturalized epistemology:
Human cognition and perception are products of evolution — reliable enough for survival but not designed for perfect truth-tracking.
Explanations of how we think and see must be integrated with normative questions about when such processes yield justified beliefs.
Understanding this boundary is key to reconciling scientific psychology with epistemic philosophy.